	<rdf:RDF xmlns:admin="http://webns.net/mvcb/" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:prism="http://purl.org/rss/1.0/modules/prism/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/">
	<channel rdf:about="https://biorxiv.org">
	<admin:errorReportsTo rdf:resource="mailto:biorxiv@cshlpress.edu"/>
	<title>bioRxiv Channel: European Molecular Biology Laboratory (EMBL)</title>
	<link>https://biorxiv.org</link>
	<description>
	This feed contains articles for bioRxiv Channel "European Molecular Biology Laboratory (EMBL)"
	</description>

		<items>
	<rdf:Seq>
		</rdf:Seq>
	</items>
	<prism:eIssn/>
	<prism:publicationName>bioRxiv</prism:publicationName>
	<prism:issn/>

	<image rdf:resource=""/>
	</channel>
	<image rdf:about="">
	<title>bioRxiv</title>
	<url/>
	<link>https://biorxiv.org</link>
	</image>
	<item rdf:about="https://biorxiv.org/cgi/content/short/067876v1?rss=1">
<title>
<![CDATA[
An RNA-binding tropomyosin recruits kinesin-1 dynamically to oskar mRNPs 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/067876v1?rss=1"
</link>
<description><![CDATA[
Localization and local translation of oskar mRNA at the posterior pole of the Drosophila oocyte directs abdominal patterning and germline formation in the embryo. The process requires recruitment and precise regulation of motor proteins to form transport-competent mRNPs. We show that the posterior-targeting kinesin-1 is loaded upon nuclear export of oskar mRNPs, prior to their dynein-dependent transport from the nurse cells into the oocyte. We demonstrate that kinesin-1 recruitment requires the DmTropomyosin1-I/C isoform, an atypical RNA-binding tropomyosin that binds directly to dimerizing oskar 3UTRs. Finally, we show that a small but dynamically changing subset of oskar mRNPs gets loaded with inactive kinesin-1 and that the motor is activated during mid-oogenesis by the functionalized spliced oskar RNA localization element. This inefficient, dynamic recruitment of Khc decoupled from cargo-dependent motor activation constitutes an optmized, coordinated mechanism of mRNP transport, by minimizing interference with other cargo-transport processes and between the cargo associated dynein and kinesin-1.
]]></description>
<dc:creator>Imre Gaspar</dc:creator>
<dc:creator>Vasily Sysoev</dc:creator>
<dc:creator>Artem Komissarov</dc:creator>
<dc:creator>Anne Ephrussi</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-08-04</dc:date>
<dc:identifier>doi:10.1101/067876</dc:identifier>
<dc:title><![CDATA[An RNA-binding tropomyosin recruits kinesin-1 dynamically to oskar mRNPs]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-08-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/107599v1?rss=1">
<title>
<![CDATA[
Enzymatic production of single molecule FISH and RNA capture probes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/107599v1?rss=1"
</link>
<description><![CDATA[
Arrays of singly-labelled short oligonucleotides that hybridize to a specific target revolutionized RNA biology, enabling quantitative, single molecule microscopy analysis and high efficiency RNA/RNP capture. Here, we describe a simple and efficient method that allows flexible functionalization of inexpensive DNA oligonucleotides by different fluorescent dyes or biotin using terminal deoxynucleotidyl transferase and custom-made functional group conjugated dideoxy-UTP. We show that 1) all steps of the oligonucleotide labelling - including conjugation, enzymatic synthesis and product purification - can be performed in a standard biology laboratory, 2) the process yields >90 %, often >95 % labeled product with minimal carry-over of impurities and 3) the oligonucleotides can be labeled with different dyes or biotin, allowing single molecule FISH or RNA affinity purification to be performed.nnGraphical abstractnnO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=66 SRC="FIGDIR/small/107599_ufig1.gif" ALT="Figure 1">nView larger version (20K):norg.highwire.dtl.DTLVardef@a26162org.highwire.dtl.DTLVardef@a780d9org.highwire.dtl.DTLVardef@fc3a62org.highwire.dtl.DTLVardef@15d183c_HPS_FORMAT_FIGEXP  M_FIG C_FIG
]]></description>
<dc:creator>Gaspar, I.</dc:creator>
<dc:creator>Wippich, F.</dc:creator>
<dc:creator>Ephrussi, A.</dc:creator>
<dc:date>2017-02-10</dc:date>
<dc:identifier>doi:10.1101/107599</dc:identifier>
<dc:title><![CDATA[Enzymatic production of single molecule FISH and RNA capture probes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-02-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/363028v1?rss=1">
<title>
<![CDATA[
Transposon silencing in the Drosophila female germline ensures genome stability in progeny embryos 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/363028v1?rss=1"
</link>
<description><![CDATA[
The piRNA pathway functions in transposon control in the germ line of metazoans. The conserved RNA helicase Vasa is an essential piRNA pathway component, but has additional important developmental functions. Here we address the importance of Vasa-dependent transposon control in the Drosophila female germline and early embryos. We find that transient loss of vasa expression during early oogenesis leads to transposon up-regulation in supporting nurse cells of the fly egg-chamber. We show that elevated transposon levels have dramatic consequences, as de-repressed transposons accumulate in the oocyte where they cause DNA damage. We find that suppression of Chk2-mediated DNA damage signaling in vasa mutant females restores oogenesis and egg production. Damaged DNA and up-regulated transposons are transmitted from the mother to the embryos, which sustain severe nuclear defects and arrest development. Our findings reveal that the Vasa-dependent protection against selfish genetic elements in the nuage of nurse cell is essential to prevent DNA damage-induced arrest of embryonic development.
]]></description>
<dc:creator>Ephrussi, A.</dc:creator>
<dc:creator>Durdevic, Z.</dc:creator>
<dc:creator>Pillai, R. S.</dc:creator>
<dc:date>2018-07-05</dc:date>
<dc:identifier>doi:10.1101/363028</dc:identifier>
<dc:title><![CDATA[Transposon silencing in the Drosophila female germline ensures genome stability in progeny embryos]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/396994v1?rss=1">
<title>
<![CDATA[
All four double-stranded RNA binding domains of Staufen2 contribute to efficient mRNA recognition and transcript localization 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/396994v1?rss=1"
</link>
<description><![CDATA[
Throughout metazoans, Staufen (Stau) proteins are core factors of mRNA localization particles. They consist of three to four double-stranded RNA binding domains (dsRBDs) and a C-terminal dsRBD-like domain. Mouse Staufen2 (mStau2) like Drosophila Stau (dmStau) contains four dsRBDs. Existing data suggest that only dsRBDs 3-4 are necessary and sufficient for mRNA binding. Here, we show that dsRBDs 1 and 2 of mStau2 bind RNA with similar affinities and kinetics as dsRBDs 3 and 4. While RNA binding by these tandem domains is transient, all four dsRBDs recognize their target RNAs with high stability. Rescue experiments in Drosophila oocytes demonstrate that mStau2 partially rescues dmStau-dependent mRNA localization. In contrast, a rescue with mStau2 bearing RNA-binding mutations in dsRBD1-2 fails, confirming the physiological relevance of our findings. In summary, our data show that the dsRBDs 1-2 play essential roles in the mRNA recognition and function of Stau- family proteins of different species.
]]></description>
<dc:creator>Heber, S.</dc:creator>
<dc:creator>Gaspar, I.</dc:creator>
<dc:creator>Tants, J.-N.</dc:creator>
<dc:creator>Günther, J.</dc:creator>
<dc:creator>Fernandez Moya, S. M.</dc:creator>
<dc:creator>Janowski, R.</dc:creator>
<dc:creator>Ephrussi, A.</dc:creator>
<dc:creator>Sattler, M.</dc:creator>
<dc:creator>Niessing, D.</dc:creator>
<dc:date>2018-08-21</dc:date>
<dc:identifier>doi:10.1101/396994</dc:identifier>
<dc:title><![CDATA[All four double-stranded RNA binding domains of Staufen2 contribute to efficient mRNA recognition and transcript localization]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/121913v1?rss=1">
<title>
<![CDATA[
Iterative model-based density improvement yields better atomic structures from cryo-EM maps 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/121913v1?rss=1"
</link>
<description><![CDATA[
Atomic models based on high-resolution density maps are the ultimate result of the cryo-EM structure determination process. Current cryo-EM model refinement procedures work with the experimental density map that remains constant throughout the process. Here, we introduce a general procedure that iteratively improves cryo-EM density maps based on prior knowledge of an atomic reference structure. The procedure optimizes contrast of cryo-EM densities by local amplitude scaling (LocScale) based on an atomic model without introducing model bias. We alternate the procedure with consecutive rounds of model refinement and tested it on four cryo-EM structures of TRPV1, {beta}-galactosidase, {gamma}-secretase and RNA polymerase III. We demonstrate that LocScale density improvement reveals previously undiscovered map features and improves the quality of atomic models. The presented approach enhances the interpretability of cryo-EM density maps and provides an implementation reminiscent of iterative density improvement as it is routinely employed in the refinement of X-ray crystallographic models.
]]></description>
<dc:creator>Jakobi, A. J.</dc:creator>
<dc:creator>Wilmanns, M.</dc:creator>
<dc:creator>Sachse, C.</dc:creator>
<dc:date>2017-03-29</dc:date>
<dc:identifier>doi:10.1101/121913</dc:identifier>
<dc:title><![CDATA[Iterative model-based density improvement yields better atomic structures from cryo-EM maps]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-03-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/367755v1?rss=1">
<title>
<![CDATA[
NG-meta-profiler: fast processing of metagenomes using NGLess, a domain-specific language 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/367755v1?rss=1"
</link>
<description><![CDATA[
NGLess is a domain specific language for describing next-generation sequence processing pipelines. It was developed with the goal of enabling user-friendly computational reproducibility.nnUsing this framework, we developed NG-meta-profiler, a fast profiler for metagenomes which performs sequence preprocessing, mapping to bundled databases, filtering of the mapping results, and profiling (taxonomic and functional). It is significantly faster than either MOCAT2 or htseq-count and (as it builds on NGLess) its results are perfectly reproducible. These pipelines can easily be customized and extended with other tools.nnNGLess and NG-meta-profiler are open source software (under the liberal MIT licence) and can be downloaded from http://ngless.embl.de or installed through bioconda.
]]></description>
<dc:creator>Coelho, L. P.</dc:creator>
<dc:creator>Alves, R.</dc:creator>
<dc:creator>Monteiro, P.</dc:creator>
<dc:creator>Huerta-Cepas, J.</dc:creator>
<dc:creator>Freitas, A. T.</dc:creator>
<dc:creator>Bork, P.</dc:creator>
<dc:date>2018-07-13</dc:date>
<dc:identifier>doi:10.1101/367755</dc:identifier>
<dc:title><![CDATA[NG-meta-profiler: fast processing of metagenomes using NGLess, a domain-specific language]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/389502v1?rss=1">
<title>
<![CDATA[
Software tools for automated transmission electron microscopy 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/389502v1?rss=1"
</link>
<description><![CDATA[
In the recent years, electron microscopy in the life sciences has witnessed increasing demand for high-throughput data collection in both structural and cellular biology. We present a combination of software tools that enable automated acquisition guided by image analysis for a wide variety of Transmission Electron Microscopy applications. Using these tools, we demonstrate dose-reduction in single particle cryo-EM experiments, fully automated acquisition of every single cell in a plastic section and automated targeting of features on serial sections for 3D volume imaging even across multiple grids.
]]></description>
<dc:creator>Schorb, M.</dc:creator>
<dc:creator>Haberbosch, I.</dc:creator>
<dc:creator>Hagen, W.</dc:creator>
<dc:creator>Schwab, Y.</dc:creator>
<dc:creator>Mastronarde, D.</dc:creator>
<dc:date>2018-08-10</dc:date>
<dc:identifier>doi:10.1101/389502</dc:identifier>
<dc:title><![CDATA[Software tools for automated transmission electron microscopy]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/170571v1?rss=1">
<title>
<![CDATA[
Curatr: a web application for creating, curating, and sharing a mass spectral library 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/170571v1?rss=1"
</link>
<description><![CDATA[
MotivationIdentification from metabolomics mass spectrometry experiments requires comparison of fragmentation spectra from experimental samples to spectra from analytical standards. As the quality of identification depends directly on the quality of the reference spectra, manual curation is routine during the selection of reference spectra to include in a spectral library. Whilst building our own in-house spectral library we realised that there is currently no vendor neutral open access tool for for facilitating manual curation of spectra from raw LC-MS data into a custom spectral library.nnResultsWe developed a web application curatr for the rapid generation of high quality mass spectral fragmentation libraries for liquid-chromatography mass spectrometry analysis. Curatr handles datasets from single or multiplexed standards, automatically extracting chromatographic profiles and potential fragmentation spectra for multiple adducts. These are presented through an intuitive interface for manual curation before being documented in a custom spectral library. Searchable molecular information and the providence of each standard is stored along with metadata on the experimental protocol. Curatr support the export of spectral libraries in several standard formats for easy use with third party software or submission to community databases, maximising the return on investment for these costly measurements. We demonstrate the use of curatr to generate the EMBL Metabolomics Core Facility spectral library which is publicly available at http://curatr.mcf.embl.de.nnAvailabilityThe source code is freely available at http://github.com/alexandrovteam/curatr/ along with example data.nnSupplementary informationA step-by step user manual is available in the supplementary information
]]></description>
<dc:creator>Palmer, A.</dc:creator>
<dc:creator>Phapale, P.</dc:creator>
<dc:creator>Fay, D.</dc:creator>
<dc:creator>Alexandrov, T.</dc:creator>
<dc:date>2017-08-15</dc:date>
<dc:identifier>doi:10.1101/170571</dc:identifier>
<dc:title><![CDATA[Curatr: a web application for creating, curating, and sharing a mass spectral library]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/364117v1?rss=1">
<title>
<![CDATA[
Conserved SQ and QS motifs in bacterial effectors suggest pathogen interplay with the ATM kinase family during infection 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/364117v1?rss=1"
</link>
<description><![CDATA[
Understanding how bacteria hijack eukaryotic cells during infection is vital to develop better strategies to counter the pathologies that they cause. ATM kinase family members phosphorylate eukaryotic protein substrates on Ser or Thr residues followed by Gln. The kinases are active under oxidative stress conditions and/or the presence of ds-DNA breaks. While examining the protein sequences of well-known bacterial effector proteins such as CagA and Tir, we noticed that they often show conserved (S/TQ) motifs, even though the evidence for effector phosphorylation by ATM has not been reported. We undertook a bioinformatics analysis to examine effectors for their potential to mimic the eukaryotic substrates of the ATM kinase. The candidates we found could interfere with the hosts intracellular signaling network upon interaction, which might give an advantage to the pathogen inside the host. Further, the putative phosphorylation sites should be accessible, conserved across species and, in the vicinity to the phosphorylation sites, positively charged residues should be depleted. We also noticed that the reverse motif (QT/S) is often also conserved and located close to (S/TQ) sites, indicating its potential biological role in ATM kinase function. Our findings could suggest a mechanism of infection whereby many pathogens inactivate/modulate the host ATM signaling pathway.
]]></description>
<dc:creator>Sampietro, D.</dc:creator>
<dc:creator>Samano-Sanchez, H.</dc:creator>
<dc:creator>Davey, N. E.</dc:creator>
<dc:creator>Sharan, M.</dc:creator>
<dc:creator>Meszaros, B.</dc:creator>
<dc:creator>Gibson, T. J.</dc:creator>
<dc:creator>Kumar, M.</dc:creator>
<dc:date>2018-07-09</dc:date>
<dc:identifier>doi:10.1101/364117</dc:identifier>
<dc:title><![CDATA[Conserved SQ and QS motifs in bacterial effectors suggest pathogen interplay with the ATM kinase family during infection]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/227751v1?rss=1">
<title>
<![CDATA[
An experimental and computational framework to build a dynamic protein atlas of human cell division 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/227751v1?rss=1"
</link>
<description><![CDATA[
Essential biological functions, such as mitosis, require tight coordination of hundreds of proteins in space and time. Localization, timing of interactions and changes in cellular structure are all crucial to ensure correct assembly, function and regulation of protein complexes1-4. Live cell imaging can reveal protein distributions and dynamics but experimental and theoretical challenges prevented its use to produce quantitative data and a model of mitosis that comprehensively integrates information and enables analysis of the dynamic interactions between the molecular parts of the mitotic machinery within changing cellular boundaries.nnTo address this, we generated a 4D image data-driven, canonical model of the morphological changes during mitotic progression of human cells. We used this model to integrate dynamic 3D concentration data of many fluorescently knocked-in mitotic proteins, imaged by fluorescence correlation spectroscopy-calibrated microscopy5. The approach taken here in the context of the MitoSys consortium to generate a dynamic protein atlas of human cell division is generic. It can be applied to systematically map and mine dynamic protein localization networks that drive cell division in different cell types and can be conceptually transferred to other cellular functions.
]]></description>
<dc:creator>Cai, Y.</dc:creator>
<dc:creator>Hossain, M. J.</dc:creator>
<dc:creator>Heriche, J.-K.</dc:creator>
<dc:creator>Politi, A. Z.</dc:creator>
<dc:creator>Walther, N.</dc:creator>
<dc:creator>Koch, B.</dc:creator>
<dc:creator>Wachsmuth, M.</dc:creator>
<dc:creator>Nijmeijer, B.</dc:creator>
<dc:creator>Kueblbeck, M.</dc:creator>
<dc:creator>Martinic, M.</dc:creator>
<dc:creator>Ladurner, R.</dc:creator>
<dc:creator>Peters, J.-M.</dc:creator>
<dc:creator>Ellenberg, J.</dc:creator>
<dc:date>2017-12-01</dc:date>
<dc:identifier>doi:10.1101/227751</dc:identifier>
<dc:title><![CDATA[An experimental and computational framework to build a dynamic protein atlas of human cell division]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/198275v1?rss=1">
<title>
<![CDATA[
Disruption of dual zygotic spindle assembly shows epigenetic asymmetry to be chromosome intrinsic 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/198275v1?rss=1"
</link>
<description><![CDATA[
At the beginning of mammalian life the genetic material from each parent meets when the fertilized egg divides. It was previously thought that a single microtubule spindle is responsible to spatially combine the two genomes and then segregate them to create the two-cell embryo. Utilizing light-sheet microscopy, we showed that two bipolar spindles form in the zygote, that independently congress the maternal and paternal genomes. These two spindles aligned their poles prior to anaphase but kept the parental genomes apart during the first cleavage. This spindle assembly mechanism provides a rationale for erroneous divisions into more than two blastomeric nuclei observed in mammalian zygotes and reveals the mechanism behind the observation that parental genomes occupy separate nuclear compartments in the two-cell embryo.nnOne Sentence Summary: After fertilization, two spindles form around pro-nuclei in mammalian zygotes and keep the parental genomes apart during the first division.
]]></description>
<dc:creator>Reichmann, J.</dc:creator>
<dc:creator>Nijmeijer, B.</dc:creator>
<dc:creator>Hossain, M. J.</dc:creator>
<dc:creator>Eguren, M.</dc:creator>
<dc:creator>Schneider, I.</dc:creator>
<dc:creator>Politi, A. Z.</dc:creator>
<dc:creator>Roberti, M. J.</dc:creator>
<dc:creator>Hufnagel, L.</dc:creator>
<dc:creator>Hiiragi, T.</dc:creator>
<dc:creator>Ellenberg, J.</dc:creator>
<dc:date>2017-10-04</dc:date>
<dc:identifier>doi:10.1101/198275</dc:identifier>
<dc:title><![CDATA[Disruption of dual zygotic spindle assembly shows epigenetic asymmetry to be chromosome intrinsic]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/309054v1?rss=1">
<title>
<![CDATA[
Discovery of a new path for red blood cell generation in the mouse embryo 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/309054v1?rss=1"
</link>
<description><![CDATA[
Erythropoiesis occurs through several waves during embryonic development. Although the source of the primitive wave is well characterized, the origin of erythrocytes later in embryogenesis is less clear due to overlaps between the different erythroid waves. Using the miR144/451-GFP mouse model to track cells expressing the erythroid microRNAs miR144/451, we identified cells co-expressing VE-Cadherin and GFP in the yolk sac between E9.5 and E12. This suggested the existence of hemogenic endothelial cells committed to erythropoiesis (Ery-HEC). We showed that these cells were capable of generating erythrocytes ex vivo and we demonstrated that the formation of Ery-HEC was independent of the Runx1 gene expression. Using transcriptome analysis, we demonstrated that these cells coexpressed endothelial and erythroid genes such as Hbb-bh1 and Gata1 but we were surprised to detect the primitive erythroid genes Aqp3 and Aqp8 suggesting the formation of primitive erythrocytes at a much later time point than initially thought. Finally, we showed that enforced expression of Gata1 in endothelial cells was enough to initiate the erythroid transcriptional program.
]]></description>
<dc:creator>Pinheiro, I.</dc:creator>
<dc:creator>Vargel Bolukbasi, O.</dc:creator>
<dc:creator>Ganter, K.</dc:creator>
<dc:creator>Sabou, L. A.</dc:creator>
<dc:creator>Tew, V. K.</dc:creator>
<dc:creator>Bolasco, G.</dc:creator>
<dc:creator>Shvartsman, M.</dc:creator>
<dc:creator>Pavlovich, P. V.</dc:creator>
<dc:creator>Buness, A.</dc:creator>
<dc:creator>Nikolakopoulou, C.</dc:creator>
<dc:creator>Bergiers, I.</dc:creator>
<dc:creator>Kouskoff, V.</dc:creator>
<dc:creator>Lacaud, G.</dc:creator>
<dc:creator>Lancrin, C.</dc:creator>
<dc:date>2018-04-28</dc:date>
<dc:identifier>doi:10.1101/309054</dc:identifier>
<dc:title><![CDATA[Discovery of a new path for red blood cell generation in the mouse embryo]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/413377v1?rss=1">
<title>
<![CDATA[
Cytoskeleton mechanics determine resting size and activation dynamics of platelets. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/413377v1?rss=1"
</link>
<description><![CDATA[
Platelets are cell fragments of various size that help maintain hemostasis. The way platelets respond during a clotting process is known to depend on their size, with important physiological consequences. We characterized the cytoskeleton of platelets as a function of their size. In resting Human and Mice platelets, we find a quadradic law between the size of a platelet and the amount of microtubule polymer it contains. We further estimate the length and number of microtubules in the marginal band using Electron and Super-resolution microscopy. In platelets activated with ADP, the marginal band coils as a consequence of cortical contraction driven by actin. We observe that this elastic coiling response is accompanied by a reversible shortening of the marginal band. Moreover, larger platelets have a higher propensity to coil. These results establish the dynamic equilibrium that is responsible for platelet size and differential response on a more quantitative level.nnHighlightsO_LIPlatelet size scales consistently with amount of polymerized tubulin in both mouse and human.nC_LIO_LIPolymerized actin is required for ADP-induced marginal band coiling.nC_LIO_LIUpon activation, the marginal band exhibits a reversible visco-elastic response involving shortening.nC_LIO_LILarger marginal bands have a higher propensity to coil than shorter ones.nC_LInnIn briefThe cytoskeleton is adapted to platelet size and its mechanical properties determine propensity of a platelet to undergo morphological changes in response to agonists.
]]></description>
<dc:creator>Mathur, A.</dc:creator>
<dc:creator>Correia, S. R.</dc:creator>
<dc:creator>Dmitrieff, S.</dc:creator>
<dc:creator>Gibeaux, R.</dc:creator>
<dc:creator>Kalinina, I.</dc:creator>
<dc:creator>Quidwai, T.</dc:creator>
<dc:creator>Ries, J.</dc:creator>
<dc:creator>Nedelec, F.</dc:creator>
<dc:date>2018-09-10</dc:date>
<dc:identifier>doi:10.1101/413377</dc:identifier>
<dc:title><![CDATA[Cytoskeleton mechanics determine resting size and activation dynamics of platelets.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/373845v1?rss=1">
<title>
<![CDATA[
Non-Parametric Analysis of Thermal Proteome Profiles Reveals Novel Drug-Binding Proteins 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/373845v1?rss=1"
</link>
<description><![CDATA[
Detecting the targets of drugs and other molecules in intact cellular contexts is a major objective in drug discovery and in biology more broadly. Thermal proteome profiling (TPP) pursues this aim at proteome-wide scale by inferring target engagement from its effects on temperature-dependent protein denaturation. However, a key challenge of TPP is the statistical analysis of the measured melting curves with controlled false discovery rates at high proteome coverage and detection power. We present non-parametric analysis of response curves (NPARC), a statistical method for TPP based on functional data analysis and nonlinear regression. We evaluate NPARC on five independent TPP datasets and observe that it is able to detect subtle changes in any region of the melting curves, reliably detects the known targets, and outperforms a melting point-centric, single-parameter fitting approach in terms of specificity and sensitivity. NPARC can be combined with established analysis of variance (ANOVA) statistics and enables flexible, factorial experimental designs and replication levels. To facilitate access to a wide range of users, a freely available software implementation of NPARC is provided.
]]></description>
<dc:creator>Childs, D.</dc:creator>
<dc:creator>Bach, K.</dc:creator>
<dc:creator>Franken, H.</dc:creator>
<dc:creator>Anders, S.</dc:creator>
<dc:creator>Kurzawa, N.</dc:creator>
<dc:creator>Bantscheff, M.</dc:creator>
<dc:creator>Mikhail, S.</dc:creator>
<dc:creator>Huber, W.</dc:creator>
<dc:date>2018-07-22</dc:date>
<dc:identifier>doi:10.1101/373845</dc:identifier>
<dc:title><![CDATA[Non-Parametric Analysis of Thermal Proteome Profiles Reveals Novel Drug-Binding Proteins]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/385773v1?rss=1">
<title>
<![CDATA[
CausalTab: PSI-MITAB 2.8 updated format for signaling data representation and dissemination 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/385773v1?rss=1"
</link>
<description><![CDATA[
Combining multiple layers of information underlying biological complexity into a structured framework, and in particular deciphering the molecular mechanisms behind cellular phenotypes, represent two challenges in systems biology. A key task is the formalisation of such information in models describing how biological entities interact to mediate the response to external and internal signals. Several databases with signaling information, such as SIGNOR, SignaLink and IntAct, focus on capturing, organising and displaying signaling interactions by representing them as binary, causal relationships between biological entities. The curation efforts that build these individual databases demand a concerted effort to ensure interoperability among resources, through the development of a standardized exchange format, ontologies and controlled vocabularies supporting the domain of causal interactions. Aware of the enormous benefits of standardization efforts in the molecular interaction research field, representatives of the signalling network community agreed to extend the PSI-MI controlled vocabulary to include additional terms representing aspects of causal interactions. Here, we present a common standard for the representation and dissemination of signaling information: the PSI Causal Interaction tabular format (CausalTAB) which is an extension of the existing PSI-MI tab-delimited format, now designated MITAB2.8. We define the new term "causal interaction", and related child terms, which are children of the PSI-MI "molecular interaction" term. The new vocabulary terms in this extended PSI-MI format will enable systems biologists to model large-scale signaling networks more precisely and with higher coverage than before.
]]></description>
<dc:creator>Perfetto, L.</dc:creator>
<dc:creator>Acencio, M. L.</dc:creator>
<dc:creator>Bradley, G.</dc:creator>
<dc:creator>Cesareni, G.</dc:creator>
<dc:creator>del Toro, N.</dc:creator>
<dc:creator>Fazekas, D.</dc:creator>
<dc:creator>Hermjakob, H.</dc:creator>
<dc:creator>Korcsmaros, T.</dc:creator>
<dc:creator>Kuiper, M.</dc:creator>
<dc:creator>laegreid, A.</dc:creator>
<dc:creator>Lo Surdo, P.</dc:creator>
<dc:creator>Lovering, R. C.</dc:creator>
<dc:creator>Orchard, S.</dc:creator>
<dc:creator>Porras, P.</dc:creator>
<dc:creator>Thomas, P. D.</dc:creator>
<dc:creator>Toure, V.</dc:creator>
<dc:creator>Zobolas, J.</dc:creator>
<dc:creator>Licata, L.</dc:creator>
<dc:date>2018-08-06</dc:date>
<dc:identifier>doi:10.1101/385773</dc:identifier>
<dc:title><![CDATA[CausalTab: PSI-MITAB 2.8 updated format for signaling data representation and dissemination]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/389619v1?rss=1">
<title>
<![CDATA[
Hydraulic control of embryo size, tissue shape and cell fate 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/389619v1?rss=1"
</link>
<description><![CDATA[
Size control is fundamental in tissue development and homeostasis1,2. While the role of cell proliferation in this process has been widely studied3, the mechanisms of organ size control and how it impacts cell fates remain elusive. Here, we use mouse blastocyst development as a model to unravel a key role of fluid-filled lumen in embryonic size control and cell fate specification. We find that during blastocyst expansion, there is a two-fold increase in the pressure of the lumen that translates into a concomitant increase in the cortical tension of trophectoderm (TE) cells lining the lumen. Increased cortical tension leads to vinculin mechanosensing and maturation of the functional tight junctions, thereby establishing a positive feedback loop to accommodate lumenal growth. However, when the cortical tension reaches a critical threshold, cell-cell adhesion cannot be sustained, and mitotic entry leads to a rupture of TE epithelium, fluid leakage and collapse of the blastocyst cavity. A simple theory of hydraulically-gated oscillations that integrates these feedback interactions recapitulates the evolution of cavity size and predicts the scaling of embryonic size with the tissue volume. Our theory further predicts that reduced cortical tension or disrupted tight junctions, and increased tissue stiffness lead to smaller embryonic size. These predictions are verified experimentally by embryological, pharmacological and genetic manipulations of the embryos. Remarkably, these changes to lumenal size, without a change in the tissue volume, lead to alteration of tissue architecture and cell fate. Overall, our study reveals how lumenal pressure and tissue mechanics control embryonic size at the tissue scale, that in turn couples to cell position and fate at the cellular scale.
]]></description>
<dc:creator>Chan, C. J.</dc:creator>
<dc:creator>Costanzo, M.</dc:creator>
<dc:creator>Ruiz-Herrero, T.</dc:creator>
<dc:creator>Monke, G.</dc:creator>
<dc:creator>Petrie, R.</dc:creator>
<dc:creator>Mahadevan, L.</dc:creator>
<dc:creator>Hiiragi, T.</dc:creator>
<dc:date>2018-08-10</dc:date>
<dc:identifier>doi:10.1101/389619</dc:identifier>
<dc:title><![CDATA[Hydraulic control of embryo size, tissue shape and cell fate]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/422998v1?rss=1">
<title>
<![CDATA[
Patient-specific logic models of signaling pathways from screenings on cancer biopsies to prioritize personalized combination therapies 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/422998v1?rss=1"
</link>
<description><![CDATA[
Mechanistic modeling of signaling pathways mediating patient-specific response to therapy can help to unveil resistance mechanisms and improve therapeutic strategies. Yet, creating such models for patients, in particular for solid malignancies, is challenging. A major hurdle to build these models is the limited material available, that precludes the generation of large-scale perturbation data. Here, we present an approach that couples ex vivo high-throughput screenings of cancer biopsies using microfluidics with logic-based modeling to generate patient-specific dynamic models of extrinsic and intrinsic apoptosis signaling pathways. We used the resulting models to investigate heterogeneity in pancreatic cancer patients, showing dissimilarities especially in the PI3K-Akt pathway. Variation in model parameters reflected well the different tumor stages. Finally, we used our dynamic models to efficaciously predict new personalized combinatorial treatments. Our results suggest our combination of microfluidic experiments and mathematical model can be a novel tool toward cancer precision medicine.
]]></description>
<dc:creator>Eduati, F.</dc:creator>
<dc:creator>Jaaks, P.</dc:creator>
<dc:creator>Merten, C. A.</dc:creator>
<dc:creator>Garnett, M. J.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:date>2018-09-21</dc:date>
<dc:identifier>doi:10.1101/422998</dc:identifier>
<dc:title><![CDATA[Patient-specific logic models of signaling pathways from screenings on cancer biopsies to prioritize personalized combination therapies]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/188862v1?rss=1">
<title>
<![CDATA[
Quantitative mapping of fluorescently tagged cellular proteins using FCS-calibrated four dimensional imaging 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/188862v1?rss=1"
</link>
<description><![CDATA[
EDITORIAL SUMMARYThis protocol describes how to estimate and spatially resolve the concentration and copy number of fluorescently tagged proteins in live cells using fluorescence imaging and fluorescence correlation spectroscopy (FCS).nnTWEETDetermining protein concentrations and copy numbers in live cells using fluorescence correlation spectroscopy (FCS)-calibrated imaging.nnCOVER TEASER Map protein concentrations with FCS-calibrated imagingUp to four primary research articles where the protocol has been used and/or developed:nnO_LIWalther, N., Hossain, M. J., Politi, A. Z., Koch, B., Kueblbeck, M., Oedegaard-Fougner, O., Lampe, M. and J. Ellenberg (2018). A quantitative map of human Condensins provides new insights into mitotic chromosome architecture. bioRxiv, 237834. https://doi.org/10.1101/2378342.nC_LIO_LICai, Y., Hossain, M. J., Heriche, J.-K., Politi, A. Z., Walther, N., Koch, B., Wachsmuth, M., Nijmeijer, B., Kueblbeck, M., Martinic, M., Ladurner, R., Peters, J.M. and J. Ellenberg (2017). An experimental and computational framework to build a dynamic protein atlas of human cell division. bioRxiv, 227751 https://doi.org/10.1101/227751nC_LIO_LIGermier, T., Kocanova, S., Walther, N., Bancaud, A., Shaban, H.A., Sellou, H., Politi, A.Z., Ellenberg, J., Gallardo, F. and K. Bystricky (2017). Real-Time Imaging of a Single Gene Reveals Transcription-Initiated Local Confinement. Biophysical Journal, 113(7), 1383-1394, https://doi.org/10.1016/j.bpj.2017.08.014.nC_LIO_LICuylen, S., Blaukopf, C., Politi, A. Z., Muller-Reichert, T., Neumann, B., Poser, I., Ellenberg, J., Hyman, A.A., and D.W. Gerlich (2016). Ki-67 acts as a biological surfactant to disperse mitotic chromosomes. Nature, 535(7611), 308-312. http://doi.org/10.1038/nature18610.nC_LInnAbstractThe ability to tag a protein at its endogenous locus with a fluorescent protein (FP) enables the quantitative understanding of protein dynamics at the physiological level. Genome editing technology has now made this powerful approach routinely applicable to mammalian cells and many other model systems, opening up the possibility to systematically and quantitatively map the cellular proteome in four dimensions. 3D time-lapse confocal microscopy (4D imaging) is an essential tool to investigate spatial and temporal protein dynamics, however it lacks the required quantitative power to make absolute and comparable measurements required for systems analysis. Fluorescence correlation spectroscopy (FCS) on the other hand provides quantitative proteomic and biophysical parameters such as protein concentration, hydrodynamic radius and oligomerization but lacks the ability for high-throughput application in 4D spatial and temporal imaging. Here, we present an automated experimental and computational workflow that integrates both methods and delivers quantitative 4D imaging data in high-throughput. These data is processed to yield a calibration curve relating the fluorescence intensities of image voxels to absolute protein abundance. The calibration curve allows the conversion of the arbitrary fluorescence intensities to protein amounts for all voxels of 4D imaging stacks. With our workflow the users can acquire and analyze hundreds of FCS-calibrated image series to map their proteins of interest in four dimensions. Compared to other protocols, the current protocol does not require additional calibration standards and provides an automated acquisition pipeline for FCS and imaging data. The protocol can be completed in 1 day.
]]></description>
<dc:creator>Politi, A. Z.</dc:creator>
<dc:creator>Cai, Y.</dc:creator>
<dc:creator>Walther, N.</dc:creator>
<dc:creator>Hossain, M. J.</dc:creator>
<dc:creator>Koch, B.</dc:creator>
<dc:creator>Wachsmuth, M.</dc:creator>
<dc:creator>Ellenberg, J.</dc:creator>
<dc:date>2017-09-14</dc:date>
<dc:identifier>doi:10.1101/188862</dc:identifier>
<dc:title><![CDATA[Quantitative mapping of fluorescently tagged cellular proteins using FCS-calibrated four dimensional imaging]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/185736v1?rss=1">
<title>
<![CDATA[
Enabling rapid cloud-based analysis of thousands of human genomes via Butler 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/185736v1?rss=1"
</link>
<description><![CDATA[
We present Butler, a computational framework developed in the context of the international Pan-cancer Analysis of Whole Genomes (PCAWG)1 project to overcome the challenges of orchestrating analyses of thousands of human genomes on the cloud. Butler operates equally well on public and academic clouds. This highly flexible framework facilitates management of virtual cloud infrastructure, software configuration, genomics workflow development, and provides unique capabilities in workflow execution management. By comprehensively collecting and analysing metrics and logs, performing anomaly detection as well as notification and cluster self-healing, Butler enables large-scale analytical processing of human genomes with 43% increased throughput compared to prior setups. Butler was key for delivering the germline genetic variant call-sets in 2,834 cancer genomes analysed by PCAWG1.
]]></description>
<dc:creator>Yakneen, S.</dc:creator>
<dc:creator>Waszak, S.</dc:creator>
<dc:creator>Gertz, M.</dc:creator>
<dc:creator>Korbel, J. O.</dc:creator>
<dc:date>2017-09-07</dc:date>
<dc:identifier>doi:10.1101/185736</dc:identifier>
<dc:title><![CDATA[Enabling rapid cloud-based analysis of thousands of human genomes via Butler]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/351015v1?rss=1">
<title>
<![CDATA[
Xist lncRNA forms silencing granules that induce heterochromatin formation and repressive complexes recruitment by phase separation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/351015v1?rss=1"
</link>
<description><![CDATA[
Main text Main text Microscopy RNA Structure Protein-RNA interactions Granule propensity Material and methods in... References Long non-coding RNAs (lncRNAs) are RNA molecules longer than 200 bases that lack coding potential1,2. They represent a significant portion of the cell transcriptome3 and work as activators or repressors of gene transcription acting on different regulatory mechanisms4-6. Indeed, lncRNAs can act as macro-scaffolds for protein recruitment7-14 and behave as guides and sponges for titrating RNA and proteins, influencing transcription at regulatory regions or triggering transcriptional interfere ...
]]></description>
<dc:creator>Cerase, A.</dc:creator>
<dc:creator>Armaos, A.</dc:creator>
<dc:creator>Cid-Samper, F.</dc:creator>
<dc:creator>Avner, P.</dc:creator>
<dc:creator>Tartaglia, G. G.</dc:creator>
<dc:date>2018-06-20</dc:date>
<dc:identifier>doi:10.1101/351015</dc:identifier>
<dc:title><![CDATA[Xist lncRNA forms silencing granules that induce heterochromatin formation and repressive complexes recruitment by phase separation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/338178v1?rss=1">
<title>
<![CDATA[
Single-cell transcriptomics identifies CD44 as a new marker and regulator of haematopoietic stem cells development 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/338178v1?rss=1"
</link>
<description><![CDATA[
The endothelial to haematopoietic transition (EHT) is the process whereby haemogenic endothelium differentiates into haematopoietic stem and progenitor cells (HSPCs). The intermediary steps of this process are unclear, in particular the identity of endothelial cells that give rise to HSPCs is unknown. Using single-cell transcriptome analysis and antibody screening we identified CD44 as a new marker of EHT enabling us to isolate robustly the different stages of EHT in the aorta gonad mesonephros (AGM) region. This allowed us to provide a very detailed phenotypical and transcriptional profile for haemogenic endothelial cells, characterising them with high expression of genes related to Notch signalling, TGFbeta/BMP antagonists (Smad6, Smad7 and Bmper) and a downregulation of genes related to glycolysis and the TCA cycle. Moreover, we demonstrated that by inhibiting the interaction between CD44 and its ligand hyaluronan we could block EHT, identifying a new regulator of HSPC development.
]]></description>
<dc:creator>Oatley, M.</dc:creator>
<dc:creator>Vargel Bolukbasi, O.</dc:creator>
<dc:creator>Svensson, V.</dc:creator>
<dc:creator>Shvartsman, M.</dc:creator>
<dc:creator>Ganter, K.</dc:creator>
<dc:creator>Zirngibl, K.</dc:creator>
<dc:creator>Pavlovich, P. V.</dc:creator>
<dc:creator>Milchevskaya, V.</dc:creator>
<dc:creator>Foteva, V.</dc:creator>
<dc:creator>Natarajan, K. N.</dc:creator>
<dc:creator>Baying, B.</dc:creator>
<dc:creator>Benes, V.</dc:creator>
<dc:creator>Patil, K. R.</dc:creator>
<dc:creator>Teichmann, S. A.</dc:creator>
<dc:creator>Lancrin, C.</dc:creator>
<dc:date>2018-06-06</dc:date>
<dc:identifier>doi:10.1101/338178</dc:identifier>
<dc:title><![CDATA[Single-cell transcriptomics identifies CD44 as a new marker and regulator of haematopoietic stem cells development]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/164624v1?rss=1">
<title>
<![CDATA[
A real-time compression library for microscopy images 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/164624v1?rss=1"
</link>
<description><![CDATA[
Fluorescence imaging techniques such as single molecule localization microscopy, high-content screening and light-sheet microscopy are producing ever-larger datasets, which poses increasing challenges in data handling and data sharing. Here, we introduce a real-time compression library that allows for very fast (beyond 1 GB/s) compression and de-compression of microscopy datasets during acquisition. In addition to an efficient lossless mode, our algorithm also includes a lossy option, which limits pixel deviations to the intrinsic noise level of the image and yields compression ratio of up to 100-fold. We present a detailed performance analysis of the different compression modes for various biological samples and imaging modalities.
]]></description>
<dc:creator>Balazs, B.</dc:creator>
<dc:creator>Deschamps, J.</dc:creator>
<dc:creator>Albert, M.</dc:creator>
<dc:creator>Ries, J.</dc:creator>
<dc:creator>Hufnagel, L.</dc:creator>
<dc:date>2017-07-21</dc:date>
<dc:identifier>doi:10.1101/164624</dc:identifier>
<dc:title><![CDATA[A real-time compression library for microscopy images]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/265009v1?rss=1">
<title>
<![CDATA[
F-actin patches nucleated on chromosomes coordinate capture by microtubules in oocyte meiosis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/265009v1?rss=1"
</link>
<description><![CDATA[
Capture of each and every chromosome by spindle microtubules is essential to prevent chromosome loss and aneuploidy. In somatic cells, astral microtubules search and capture chromosomes forming lateral attachments to kinetochores. However, this mechanism alone is insufficient in large oocytes. We have previously shown that a contractile F-actin network is additionally required to collect chromosomes scattered in the 70-m starfish oocyte nucleus. How this F-actin-driven mechanism is coordinated with microtubule capture remained unknown. Here, we show that after nuclear envelope breakdown Arp2/3-nucleated F-actin patches form around chromosomes in a Ran-GTP-dependent manner, and we propose that these structures sterically block kinetochore-microtubule attachments. Once F-actin-driven chromosome transport is complete, coordinated disassembly of these F-actin patches allows synchronous capture by microtubules. Our observations indicate that this coordination is necessary, as early capture of chromosomes by microtubules would interfere with F-actin-driven transport leading to chromosome loss and formation of aneuploid eggs.
]]></description>
<dc:creator>Burdyniuk, M.</dc:creator>
<dc:creator>Callegari, A.</dc:creator>
<dc:creator>Mori, M.</dc:creator>
<dc:creator>Nedelec, F.</dc:creator>
<dc:creator>Lenart, P.</dc:creator>
<dc:date>2018-02-13</dc:date>
<dc:identifier>doi:10.1101/265009</dc:identifier>
<dc:title><![CDATA[F-actin patches nucleated on chromosomes coordinate capture by microtubules in oocyte meiosis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/291443v1?rss=1">
<title>
<![CDATA[
PDX Finder: A Portal for Patient-Derived tumor Xenograft Model Discovery 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/291443v1?rss=1"
</link>
<description><![CDATA[
Patient-derived tumor xenograft (PDX) mouse models are a versatile oncology research platform for studying tumor biology and for testing chemotherapeutic approaches tailored to genomic characteristics of individual patients tumors. PDX models are generated and distributed by a diverse group of academic labs, research organizations, multi-institution consortia, and contract research organizations. The distributed nature of PDX repositories and the use of different standards in the associated metadata presents a significant challenge to finding PDX models relevant to specific cancer research questions. The Jackson Laboratory and EMBL-EBI are addressing these challenges by co-developing PDX Finder, a comprehensive open global catalog of PDX models and their associated datasets. Within PDX Finder, model attributes are harmonized and integrated using a previously developed community minimal information standard to support consistent searching across the originating resources. Links to repositories are provided from the PDX Finder search results to facilitate model acquisition and/or collaboration. The PDX Finder resource currently contains information for more than 1900 PDX models of diverse cancers including those from large resources such as the Patient-Derived Models Repository, PDXNet, and EurOPDX. Individuals or organizations that generate and distribute PDXs are invited to increase the "findability" of their models by participating in the PDX Finder initiative at www.pdxfinder.org.
]]></description>
<dc:creator>Conte, N.</dc:creator>
<dc:creator>Mason, J.</dc:creator>
<dc:creator>Halmagyi, C.</dc:creator>
<dc:creator>Neuhauser, S.</dc:creator>
<dc:creator>Mosaku, A.</dc:creator>
<dc:creator>Begley, D. A.</dc:creator>
<dc:creator>Kupkre, D. M.</dc:creator>
<dc:creator>Parkinson, H.</dc:creator>
<dc:creator>Meehan, T.</dc:creator>
<dc:creator>Bult, C. J.</dc:creator>
<dc:date>2018-04-03</dc:date>
<dc:identifier>doi:10.1101/291443</dc:identifier>
<dc:title><![CDATA[PDX Finder: A Portal for Patient-Derived tumor Xenograft Model Discovery]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/375097v1?rss=1">
<title>
<![CDATA[
PathwayMatcher: multi-omics pathway mapping and proteoform network generation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/375097v1?rss=1"
</link>
<description><![CDATA[
BackgroundMapping biomedical data to functional knowledge is an essential task in bioinformatics and can be achieved by querying identifiers, e.g. gene sets, in pathway knowledgebases. However, the isoform and post-translational modification states of proteins are lost when converting input and pathways into gene-centric lists.nnFindingsBased on the Reactome knowledgebase, we built a network of protein-protein interactions accounting for the documented isoform and modification statuses of proteins. We then implemented a command line application called PathwayMatcher (github.com/PathwayAnalysisPlatform/PathwayMatcher) to query this network. PathwayMatcher supports multiple types of omics data as input, and outputs the possibly affected biochemical reactions, subnetworks, and pathways.nnConclusionsPathwayMatcher enables refining the network-representation of pathways by including isoform and post-translational modifications. The specificity of pathway analyses is hence adapted to different levels of granularity and it becomes possible to distinguish interactions between different forms of the same protein.
]]></description>
<dc:creator>Hernandez Sanchez, L. F.</dc:creator>
<dc:creator>Burger, B.</dc:creator>
<dc:creator>Horro, C.</dc:creator>
<dc:creator>Fabregat, A.</dc:creator>
<dc:creator>Johansson, S.</dc:creator>
<dc:creator>Njolstad, P. R.</dc:creator>
<dc:creator>Barsnes, H.</dc:creator>
<dc:creator>Hermjakob, H.</dc:creator>
<dc:creator>Vaudel, M.</dc:creator>
<dc:date>2018-07-23</dc:date>
<dc:identifier>doi:10.1101/375097</dc:identifier>
<dc:title><![CDATA[PathwayMatcher: multi-omics pathway mapping and proteoform network generation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/372995v1?rss=1">
<title>
<![CDATA[
Identifying alternative splicing isoforms in the human proteome with small proteotranscriptomic databases 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/372995v1?rss=1"
</link>
<description><![CDATA[
RNA sequencing has led to the discovery of many transcript isoforms created by alternative splicing, but the translational status and functional significance of most alternative splicing events remain unknown. Here we applied a splice junction-centric approach to survey the landscape of protein alternative isoform expression in the human proteome. We focused on alternative splice events where pairs of splice junctions corresponding to included and excluded exons with appreciable read counts are translated together into selective protein sequence databases. Using this approach, we constructed tissue-specific FASTA databases from ENCODE RNA sequencing data, then reanalyzed splice junction peptides in existing mass spectrometry datasets across 10 human tissues (heart, lung, liver, pancreas, ovary, testis, colon, prostate, adrenal gland, and esophagus). Our analysis reidentified 1,108 non-canonical isoforms annotated in SwissProt. We further found 253 novel splice junction peptides in 212 genes that are not documented in the comprehensive Uniprot TrEMBL or Ensembl RefSeq databases. On a proteome scale, non-canonical isoforms differ from canonical sequences preferentially at sequences with heightened protein disorder, suggesting a functional consequence of alternative splicing on the proteome is the regulation of intrinsically disordered regions. We further observed examples where isoform-specific regions intersect with important cardiac protein phosphorylation sites. Our results reveal previously unidentified protein isoforms and may avail efforts to elucidate the functions of splicing events and expand the pool of observable biomarkers in profiling studies.

Acronyms and Abbreviations
]]></description>
<dc:creator>Lau, E.</dc:creator>
<dc:creator>Lam, M. P. Y.</dc:creator>
<dc:date>2018-07-27</dc:date>
<dc:identifier>doi:10.1101/372995</dc:identifier>
<dc:title><![CDATA[Identifying alternative splicing isoforms in the human proteome with small proteotranscriptomic databases]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/374546v1?rss=1">
<title>
<![CDATA[
Thresholding of cryo-EM density maps by false discovery rate control 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/374546v1?rss=1"
</link>
<description><![CDATA[
Cryo-EM now commonly generates close-to-atomic resolution as well as intermediate resolution maps from macromolecules observed in isolation and in situ. Interpreting these maps remains a challenging task due to poor signal in the highest resolution shells and the necessity to select a threshold for density analysis. In order to facilitate this process, we developed a statistical framework for the generation of confidence maps by multiple hypothesis testing and false discovery rate (FDR) control. In this way, 3D confidence maps contain separated signal from background noise in the form of local detection rates of EM density values. We demonstrate that confidence maps and FDR-based thresholding can be used for the interpretation of near-atomic resolution single-particle structures as well as lower resolution maps determined by subtomogram averaging. Confidence maps represent a conservative way of interpreting molecular structures due to minimized noise. At the same time they provide a detection error with respect to background noise, which is associated with the density and particularly beneficial for the interpretation of weaker cryo-EM densities in cases of conformational flexibility and lower occupancy of bound molecules and ions to the structure.
]]></description>
<dc:creator>Beckers, M.</dc:creator>
<dc:creator>Jakobi, A.</dc:creator>
<dc:creator>Sachse, C.</dc:creator>
<dc:date>2018-07-23</dc:date>
<dc:identifier>doi:10.1101/374546</dc:identifier>
<dc:title><![CDATA[Thresholding of cryo-EM density maps by false discovery rate control]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/188920v1?rss=1">
<title>
<![CDATA[
PlasmidTron: assembling the cause of phenotypes from NGS data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/188920v1?rss=1"
</link>
<description><![CDATA[
When defining bacterial populations through whole genome sequencing (WGS) the samples often have detailed associated metadata that relate to disease severity, antimicrobial resistance, or even rare biochemical traits. When comparing these bacterial populations, it is apparent that some of these phenotypes do not follow the phylogeny of the host i.e. they are genetically unlinked to the evolutionary history of the host bacterium. One possible explanation for this phenomenon is that the genes are moving independently between hosts and are likely associated with mobile genetic elements (MGE). However, identifying the element that is associated with these traits can be complex if the starting point is short read WGS data. With the increased use of next generation WGS in routine diagnostics, surveillance and epidemiology a vast amount of short read data is available and these types of associations are relatively unexplored. One way to address this would be to perform assembly de novo of the whole genome read data, including its MGEs. However, MGEs are often full of repeats and can lead to fragmented consensus sequences. Deciding which sequence is part of the chromosome, and which is part of a MGE can be ambiguous. We present PlasmidTron, which utilises the phenotypic data normally available in bacterial population studies, such as antibiograms, virulence factors, or geographic information, to identify sequences that are likely to represent MGEs linked to the phenotype. Given a set of reads, categorised into cases (showing the phenotype) and controls (phylogenetically related but phenotypically negative), PlasmidTron can be used to assemble de novo reads from each sample linked by a phenotype. A k-mer based analysis is performed to identify reads associated with a phylogenetically unlinked phenotype. These reads are then assembled de novo to produce contigs. By utilising k-mers and only assembling a fraction of the raw reads, the method is fast and scalable to large datasets. This approach has been tested on plasmids, because of their contribution to important pathogen associated traits, such as AMR, hence the name, but there is no reason why this approach cannot be utilized for any MGE that can move independently through a bacterial population. PlasmidTron is written in Python 3 and available under the open source licence GNU GPL3 from https://github.com/sanger-pathogens/plasmidtron.nnDATA SUMMARYO_LISource code for PlasmidTron is available from Github under the open source licence GNU GPL 3; (url - https://goo.gl/ot6rT5)nC_LIO_LISimulated raw reads files have been deposited in Figshare; (url - https://doi.org/10.6084/m9.figshare.5406355.vl)nC_LIO_LISalmonella enterica serovar Weltevreden strain VNS10259 is available from GenBank; accession number GCA_001409135.nC_LIO_LISalmonella enterica serovar Typhi strain BL60006 is available from GenBank; accession number GCA_900185485.nC_LIO_LIAccession numbers for all of the Illumina datasets used in this paper are listed in the supplementary tables.nC_LInnI/We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. {boxtimes}nnIMPACT STATEMENTPlasmidTron utilises the phenotypic data normally available in bacterial population studies, such as antibiograms, virulence factors, or geographic information, to identify sequences that are likely to represent MGEs linked to the phenotype.
]]></description>
<dc:creator>Page, A. J.</dc:creator>
<dc:creator>Wailan, A.</dc:creator>
<dc:creator>Shao, Y.</dc:creator>
<dc:creator>Judge, K.</dc:creator>
<dc:creator>Dougan, G.</dc:creator>
<dc:creator>Klemm, E. J.</dc:creator>
<dc:creator>Thomson, N. R.</dc:creator>
<dc:creator>Keane, J. A.</dc:creator>
<dc:date>2017-09-15</dc:date>
<dc:identifier>doi:10.1101/188920</dc:identifier>
<dc:title><![CDATA[PlasmidTron: assembling the cause of phenotypes from NGS data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/280834v1?rss=1">
<title>
<![CDATA[
Bicoid gradient formation mechanism and dynamics revealed by protein lifetime analysis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/280834v1?rss=1"
</link>
<description><![CDATA[
Embryogenesis relies on instructions provided by spatially organized signaling molecules known as morphogens. Understanding the principles behind morphogen distribution and how cells interpret locally this information remains a major challenge in developmental biology. Here we introduce morphogen-age measurements as a novel approach to retrieve key parameters in morphogen dynamics. Using a tandem fluorescent timer (tFT) as a protein-age sensor we find a gradient of increasing age of Bicoid (Bcd) along the anterior-posterior (AP) axis in the early Drosophila embryo. Quantitative analysis retrieves parameter that are most consistent with the synthesis-diffusion-degradation (SDD) model underlying Bcd-gradient formation, and rule out some other hypotheses for gradient formation. Moreover, we show that the timer can detect transitions in the dynamics associated with syncytial cellularization. Our results provide new insight into Bcd gradient formation, and demonstrate how morphogen age-information can complement knowledge about movement, abundance and distribution, which should be widely applicable for other systems.
]]></description>
<dc:creator>Durrieu, L.</dc:creator>
<dc:creator>Kirrmaier, D.</dc:creator>
<dc:creator>Schneidt, T.</dc:creator>
<dc:creator>Kats, I.</dc:creator>
<dc:creator>Raghavan, S.</dc:creator>
<dc:creator>Knop, M.</dc:creator>
<dc:creator>Saunders, T. E.</dc:creator>
<dc:creator>Hufnagel, L.</dc:creator>
<dc:date>2018-03-13</dc:date>
<dc:identifier>doi:10.1101/280834</dc:identifier>
<dc:title><![CDATA[Bicoid gradient formation mechanism and dynamics revealed by protein lifetime analysis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/177048v1?rss=1">
<title>
<![CDATA[
Detection and removal of barcode swapping in single-cell RNA-seq data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/177048v1?rss=1"
</link>
<description><![CDATA[
Barcode swapping results in the mislabeling of sequencing reads between multiplexed samples on the new patterned flow cell Illumina sequencing machines. This may compromise the validity of numerous genomic assays, especially for single-cell studies where many samples are routinely multiplexed together. The severity and consequences of barcode swapping for single-cell transcriptomic studies remain poorly understood. We have used two statistical approaches to robustly quantify the fraction of swapped reads in each of two plate-based single-cell RNA sequencing datasets. We found that approximately 2.5% of reads were mislabeled between samples on the HiSeq 4000 machine, which is lower than previous reports. We observed no correlation between the swapped fraction of reads and the concentration of free barcode across plates. Furthermore, we have demonstrated that barcode swapping may generate complex but artefactual cell libraries in droplet-based single-cell RNA sequencing studies. To eliminate these artefacts, we have developed an algorithm to exclude individual molecules that have swapped between samples in 10X Genomics experiments, exploiting the combinatorial complexity present in the data. This permits the continued use of cutting-edge sequencing machines for droplet-based experiments while avoiding the confounding effects of barcode swapping.
]]></description>
<dc:creator>Griffiths, J. A.</dc:creator>
<dc:creator>Lun, A. T. L.</dc:creator>
<dc:creator>Richard, A. C.</dc:creator>
<dc:creator>Bach, K.</dc:creator>
<dc:creator>Marioni, J. C.</dc:creator>
<dc:date>2017-08-16</dc:date>
<dc:identifier>doi:10.1101/177048</dc:identifier>
<dc:title><![CDATA[Detection and removal of barcode swapping in single-cell RNA-seq data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/409151v1?rss=1">
<title>
<![CDATA[
PhenoMeNal: Processing and analysis of Metabolomics data in the Cloud 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/409151v1?rss=1"
</link>
<description><![CDATA[
BackgroundMetabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organisms metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological and many other applied biological domains. Its computationally-intensive nature has driven requirements for open data formats, data repositories and data analysis tools. However, the rapid progress has resulted in a mosaic of independent - and sometimes incompatible - analysis methods that are difficult to connect into a useful and complete data analysis solution.nnFindingsThe PhenoMeNal (Phenome and Metabolome aNalysis) e-infrastructure provides a complete, workflow-oriented, interoperable metabolomics data analysis solution for a modern infrastructure-as-a-service (IaaS) cloud platform. PhenoMeNal seamlessly integrates a wide array of existing open source tools which are tested and packaged as Docker containers through the projects continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardized, automated and published analysis workflows in the user interfaces Galaxy, Jupyter, Luigi and Pachyderm.nnConclusionsPhenoMeNal constitutes a keystone solution in cloud infrastructures available for metabolomics. It provides scientists with a ready-to-use, workflow-driven, reproducible and shareable data analysis platform harmonizing the software installation and configuration through user-friendly web interfaces. The deployed cloud environments can be dynamically scaled to enable large-scale analyses which are interfaced through standard data formats, versioned, and have been tested for reproducibility and interoperability. The flexible implementation of PhenoMeNal allows easy adaptation of the infrastructure to other application areas and  omics research domains.
]]></description>
<dc:creator>Peters, K.</dc:creator>
<dc:creator>Bradbury, J.</dc:creator>
<dc:creator>Bergmann, S.</dc:creator>
<dc:creator>Capuccini, M.</dc:creator>
<dc:creator>Cascante, M.</dc:creator>
<dc:creator>de Atauri, P.</dc:creator>
<dc:creator>Ebbels, T.</dc:creator>
<dc:creator>Foguet, C.</dc:creator>
<dc:creator>Glen, R.</dc:creator>
<dc:creator>Gonzalez-Beltran, A.</dc:creator>
<dc:creator>Handakas, E.</dc:creator>
<dc:creator>Hankemeier, T.</dc:creator>
<dc:creator>Herman, S.</dc:creator>
<dc:creator>Haug, K.</dc:creator>
<dc:creator>Holub, P.</dc:creator>
<dc:creator>Izzo, M.</dc:creator>
<dc:creator>Jacob, D.</dc:creator>
<dc:creator>Johnson, D.</dc:creator>
<dc:creator>Jourdan, F.</dc:creator>
<dc:creator>Kale, N.</dc:creator>
<dc:creator>Karaman, I.</dc:creator>
<dc:creator>Khalili, B.</dc:creator>
<dc:creator>Emami Khoonsari, P.</dc:creator>
<dc:creator>Kultima, K.</dc:creator>
<dc:creator>Lampa, S.</dc:creator>
<dc:creator>Larsson, A.</dc:creator>
<dc:creator>Moreno, P.</dc:creator>
<dc:creator>Neumann, S.</dc:creator>
<dc:creator>Novella, J. A.</dc:creator>
<dc:creator>O'Donovan, C.</dc:creator>
<dc:creator>Pearce, J. T.</dc:creator>
<dc:creator>Peluso, A.</dc:creator>
<dc:creator>Pireddu, L.</dc:creator>
<dc:creator>Piras, M. E.</dc:creator>
<dc:creator>Reed, M. A.</dc:creator>
<dc:creator>Rocca-Serra, P.</dc:creator>
<dc:creator>Roger, P.</dc:creator>
<dc:creator>Rosato, A.</dc:creator>
<dc:creator>Rueedi, R.</dc:creator>
<dc:creator>Ruttkies, C.</dc:creator>
<dc:creator>Sadawi, N.</dc:creator>
<dc:creator>Salek, R.</dc:creator>
<dc:creator>Sansone, S.-A.</dc:creator>
<dc:creator>Selivanov, V.</dc:creator>
<dc:creator>Spjuth, O.</dc:creator>
<dc:creator></dc:creator>
<dc:date>2018-09-06</dc:date>
<dc:identifier>doi:10.1101/409151</dc:identifier>
<dc:title><![CDATA[PhenoMeNal: Processing and analysis of Metabolomics data in the Cloud]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/223198v1?rss=1">
<title>
<![CDATA[
Fast automated reconstruction of genome-scale metabolic models for microbial species and communities 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/223198v1?rss=1"
</link>
<description><![CDATA[
Genome-scale metabolic models are instrumental in uncovering operating principles of cellular metabolism and model-guided re-engineering. Recent applications of metabolic models have also demonstrated their usefulness in unraveling cross-feeding within microbial communities. Yet, the application of genome-scale models, especially to microbial communities, is lagging far behind the availability of sequenced genomes. This is largely due to the time-consuming steps of manual cura-tion required to obtain good quality models and thus physiologically meaningful simulation results. Here, we present an automated tool - CarveMe - for reconstruction of species and community level metabolic models. We introduce the concept of a universal model, which is manually curated and simulation-ready. Starting with this universal model and annotated genome sequences, CarveMe uses a top-down approach to build single-species and community models in a fast and scalable manner. We build reconstructions for two model organisms, Escherichia coli and Bacillus subtillis, as well as a collection of human gut bacteria, and show that CarveMe models perform similarly to manually curated models in reproducing experimental phenotypes. Finally, we demonstrate the scalability of CarveMe through reconstructing 5587 bacterial models. Overall, CarveMe provides an open-source and user-friendly tool towards broadening the use of metabolic modeling in studying microbial species and communities.
]]></description>
<dc:creator>Machado, D.</dc:creator>
<dc:creator>Andrejev, S.</dc:creator>
<dc:creator>Tramontano, M.</dc:creator>
<dc:creator>Patil, K. R.</dc:creator>
<dc:date>2018-01-12</dc:date>
<dc:identifier>doi:10.1101/223198</dc:identifier>
<dc:title><![CDATA[Fast automated reconstruction of genome-scale metabolic models for microbial species and communities]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/331587v1?rss=1">
<title>
<![CDATA[
A congenital pain insensitivity mutation in the nerve growth factor gene uncouples nociception from affective pain in heterozygous humans and mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/331587v1?rss=1"
</link>
<description><![CDATA[
Pain is an unpleasant but necessary sensory experience, which facilitates adaptive behaviours, such as fear. Despite recent advances, the question of how the pain experience influences learning of the fear response is still debated1,2. Genetic disorders rendering patients congenitally unable to feel pain have been described, and are usually explained by defects in peripheral nociceptors3-5. It is not known how growing up without pain affects central emotional and motivational responses to aversive stimuli. The rare autosomal recessive Hereditary Sensory and Autonomic Neuropathy type V (HSAN V) is caused by a mutation in the nerve growth factor (NGF) gene (R100W). HSAN V homozygous patients display a congenital indifference to painful events, with deficits in peripheral nociceptors but without overt cognitive impairment6. In contrast, heterozygous carriers do not present with pain-related deficits and have been identified only through pedigree and genetic screening7,8. We exploited this clinically silent population to dissociate nociceptive from affective features of pain. To address this we investigated both heterozygous knock-in mice bearing the R100W mutation (NGFR100W/m mice) and a cohort of HSAN V heterozygous human carriers. Surprisingly, we found that NGFR100W/m mice, despite normal responses to a noxious conditioning stimulus, show a deficit in learned fear while their social and innate fear responses are normal. The lack of pain-related fear response was linked to a reduced activation of anterior cingulate and motor cortices and of striatum, but not in primary somatosensory cortex. Likewise, human heterozygous R100W carriers, despite perceiving noxious stimuli and reporting subjective pain thresholds, show increased reaction latencies in response to painful stimulation, alongside a decreased subjective urgency to react. Functional magnetic resonance imaging (fMRI) revealed, comparably to the mouse data, an altered processing of painful stimuli in rostral anterior cingulate, medial premotor cortical regions and striatum. These findings from both human and mouse HSAN V carriers uncover behavioural and motivational consequences of a mild genetic pain insensitivity on the establishment of pain-dependent affective responses and memories.
]]></description>
<dc:creator>Testa, G.</dc:creator>
<dc:creator>Perini, I.</dc:creator>
<dc:creator>Mainardi, M.</dc:creator>
<dc:creator>Morelli, C.</dc:creator>
<dc:creator>Olimpico, F.</dc:creator>
<dc:creator>Pancrazi, L.</dc:creator>
<dc:creator>Petrella, C.</dc:creator>
<dc:creator>Severini, C.</dc:creator>
<dc:creator>Florio, R.</dc:creator>
<dc:creator>Malerba, F.</dc:creator>
<dc:creator>Heppenstall, P.</dc:creator>
<dc:creator>Costa, M.</dc:creator>
<dc:creator>Morrison, I.</dc:creator>
<dc:creator>Capsoni, S.</dc:creator>
<dc:creator>Cattaneo, A.</dc:creator>
<dc:date>2018-05-25</dc:date>
<dc:identifier>doi:10.1101/331587</dc:identifier>
<dc:title><![CDATA[A congenital pain insensitivity mutation in the nerve growth factor gene uncouples nociception from affective pain in heterozygous humans and mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/411173v1?rss=1">
<title>
<![CDATA[
Effect of Sec61 interaction with Mpd1 on Endoplasmic Reticulum-Associated Degradation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/411173v1?rss=1"
</link>
<description><![CDATA[
Proteins that misfold in the endoplasmic reticulum (ER) are transported back to the cytosol for ER-associated degradation (ERAD). The Sec61 channel is one of the candidates for the retrograde transport conduit. Channel opening from the ER lumen must be triggered by ERAD factors and substrates. Here we identified new lumenal interaction partners of Sec61 by chemical crosslinking and mass spectrometry. In addition to known Sec61 interactors we detected ERAD factors including Cue1, Ubc6, Ubc7, Asi3, and Mpd1. We show that the CPY* ERAD factor Mpd1 binds to the lumenal Sec61 hinge region. Deletion of the Mpd1 binding site reduced the interaction between both proteins and caused an ERAD defect specific for CPY* without affecting protein import into the ER or ERAD of other substrates. Our data suggest that Mpd1 binding to Sec61 is a prerequisite for CPY* ERAD and confirm a role of Sec61 in ERAD of misfolded secretory proteins.
]]></description>
<dc:creator>Pereira, F.</dc:creator>
<dc:creator>Rettel, M.</dc:creator>
<dc:creator>Stein, F.</dc:creator>
<dc:creator>Savitski, M. M.</dc:creator>
<dc:creator>Collinson, I.</dc:creator>
<dc:creator>Romisch, K.</dc:creator>
<dc:date>2018-09-07</dc:date>
<dc:identifier>doi:10.1101/411173</dc:identifier>
<dc:title><![CDATA[Effect of Sec61 interaction with Mpd1 on Endoplasmic Reticulum-Associated Degradation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/188847v1?rss=1">
<title>
<![CDATA[
Generation and validation of homozygous fluorescent knock-in cells using genome editing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/188847v1?rss=1"
</link>
<description><![CDATA[
Gene tagging with fluorescent proteins is essential to investigate the dynamic properties of cellular proteins. CRISPR/Cas9 technology is a powerful tool for inserting fluorescent markers into all alleles of the gene of interest (GOI) and permits functionality and physiological expression of the fusion protein. It is essential to evaluate such genome-edited cell lines carefully in order to preclude off-target effects caused by either (i) incorrect insertion of the fluorescent protein, (ii) perturbation of the fusion protein by the fluorescent proteins or (iii) non-specific genomic DNA damage by CRISPR/Cas9. In this protocol1, we provide a step-by-step description of our systematic pipeline to generate and validate homozygous fluorescent knock-in cell lines.nnWe have used the paired Cas9D10A nickase approach to efficiently insert tags into specific genomic loci via homology-directed repair with minimal off-target effects. It is time- and cost-consuming to perform whole genome sequencing of each cell clone. Therefore, we have developed an efficient validation pipeline of the generated cell lines consisting of junction PCR, Southern Blot analysis, Sanger sequencing, microscopy, Western blot analysis and live cell imaging for cell cycle dynamics. This protocol takes between 6-9 weeks. Using this protocol, up to 70% of the targeted genes can be tagged homozygously with fluorescent proteins and result in physiological levels and phenotypically functional expression of the fusion proteins.nnEditorial SummaryThis protocol provides a detailed workflow describing how to insert fluorescent markers into all alleles of a gene of interest using CRISPR/Cas 9 technology and how to generate and validate homozygous fluorescent knock-in cell lines.
]]></description>
<dc:creator>Koch, B.</dc:creator>
<dc:creator>Nijmeijer, B.</dc:creator>
<dc:creator>Kueblbeck, M.</dc:creator>
<dc:creator>Cai, Y.</dc:creator>
<dc:creator>Walther, N.</dc:creator>
<dc:creator>Ellenberg, J.</dc:creator>
<dc:date>2017-09-14</dc:date>
<dc:identifier>doi:10.1101/188847</dc:identifier>
<dc:title><![CDATA[Generation and validation of homozygous fluorescent knock-in cells using genome editing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/346957v1?rss=1">
<title>
<![CDATA[
A combinatorial extracellular code tunes the intracellular signaling network activity to distinct cellular responses 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/346957v1?rss=1"
</link>
<description><![CDATA[
Cells constantly survey a complex set of inputs that is processed by the intracellular signaling network, but little is known of how cells integrate input information from more than one cue. We employed a FRET biosensor-based imaging platform to study the effect of combinatorial growth factor levels on the signaling network in human cells. We found that pairwise stimuli caused distinct concentration- and ratio-dependent signaling states through signaling signatures such as antagonism, additivity and synergy. The unique signaling states correlated with differential gene expression and non-additive transcription patterns. We further elucidated how a signal-rich environment can fine-tune the signaling network and adjust physiological outcomes, by kinase and phosphatase activity profiling. We describe how complex extracellular conditions affect phospho-turnover and the basal phosphorylation status. Thus, we provide mechanistic insights into cellular processing of multiple cues and explain part of the complexity of cellular adaptation to changes in the extracellular environment.
]]></description>
<dc:creator>Kuchenov, D.</dc:creator>
<dc:creator>Ziebell, F.</dc:creator>
<dc:creator>Salopiata, F.</dc:creator>
<dc:creator>Citir, M.</dc:creator>
<dc:creator>Klingmueller, U.</dc:creator>
<dc:creator>Huber, W.</dc:creator>
<dc:creator>Schultz, C.</dc:creator>
<dc:date>2018-06-14</dc:date>
<dc:identifier>doi:10.1101/346957</dc:identifier>
<dc:title><![CDATA[A combinatorial extracellular code tunes the intracellular signaling network activity to distinct cellular responses]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/192914v1?rss=1">
<title>
<![CDATA[
UniProt Genomic Mapping for Deciphering Functional Effects of Missense Variants 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/192914v1?rss=1"
</link>
<description><![CDATA[
Understanding the association of genetic variation with its functional consequences in proteins is essential for the interpretation of genomic data and identifying causal variants in diseases. Integration of protein function knowledge with genome annotation can assist in rapidly comprehending genetic variation within complex biological processes. Here, we describe mapping UniProtKB human sequences and positional annotations such as active sites, binding sites, and variants to the human genome (GRCh38) and the release of a public genome track hub for genome browsers. To demonstrate the power of combining protein annotations with genome annotations for functional interpretation of variants, we present specific biological examples in disease-related genes and proteins. Computational comparisons of UniProtKB annotations and protein variants with ClinVar clinically annotated SNP data show that 32% of UniProtKB variants co-locate with 8% of ClinVar SNPs. The majority of co-located UniProtKB disease-associated variants (86%) map to  pathogenic ClinVar SNPs. UniProt and ClinVar are collaborating to provide a unified clinical variant annotation for genomic, protein and clinical researchers. The genome track hubs, and related UniProtKB files, are downloadable from the UniProt FTP site and discoverable as public track hubs at the UCSC and Ensembl genome browsers.
]]></description>
<dc:creator>McGarvey, P.</dc:creator>
<dc:creator>Nightingale, A.</dc:creator>
<dc:creator>Luo, J.</dc:creator>
<dc:creator>Huang, H.</dc:creator>
<dc:creator>Martin, M.-J.</dc:creator>
<dc:creator>Wu, C.</dc:creator>
<dc:creator>UniProt Consortium,</dc:creator>
<dc:date>2017-09-22</dc:date>
<dc:identifier>doi:10.1101/192914</dc:identifier>
<dc:title><![CDATA[UniProt Genomic Mapping for Deciphering Functional Effects of Missense Variants]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/217554v1?rss=1">
<title>
<![CDATA[
Multi-Omics factor analysis disentangles heterogeneity in blood cancer 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/217554v1?rss=1"
</link>
<description><![CDATA[
Multi-omic studies promise the improved characterization of biological processes across molecular layers. However, methods for the unsupervised integration of the resulting heterogeneous datasets are lacking. We present Multi-Omics Factor Analysis (MOFA), a computational method for discovering the principal sources of variation in multi-omic datasets. MOFA infers a set of (hidden) factors that capture biological and technical sources of variability. It disentangles axes of heterogeneity that are shared across multiple modalities and those specific to individual data modalities. The learnt factors enable a variety of downstream analyses, including identification of sample subgroups, data imputation, and the detection of outlier samples. We applied MOFA to a cohort of 200 patient samples of chronic lymphocytic leukaemia, profiled for somatic mutations, RNA expression, DNA methylation and ex-vivo drug responses. MOFA identified major dimensions of disease heterogeneity, including immunoglobulin heavy chain variable region status, trisomy of chromosome 12 and previously underappreciated drivers, such as response to oxidative stress. In a second application, we used MOFA to analyse single-cell multiomics data, identifying coordinated transcriptional and epigenetic changes along cell differentiation.
]]></description>
<dc:creator>Argelaguet, R.</dc:creator>
<dc:creator>Velten, B.</dc:creator>
<dc:creator>Arnol, D.</dc:creator>
<dc:creator>Dietrich, S.</dc:creator>
<dc:creator>Zenz, T.</dc:creator>
<dc:creator>Marioni, J. C.</dc:creator>
<dc:creator>Buettner, F.</dc:creator>
<dc:creator>Huber, W.</dc:creator>
<dc:creator>Stegle, O.</dc:creator>
<dc:date>2017-11-10</dc:date>
<dc:identifier>doi:10.1101/217554</dc:identifier>
<dc:title><![CDATA[Multi-Omics factor analysis disentangles heterogeneity in blood cancer]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/403543v1?rss=1">
<title>
<![CDATA[
Chromatin-dependent cryptic promoters encode alternative protein isoforms in yeast. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/403543v1?rss=1"
</link>
<description><![CDATA[
Cryptic transcription is widespread and generates a heterogeneous group of RNA molecules of unknown function. To improve our understanding of cryptic transcription, we investigated their transcription start site usage, chromatin organization and post-transcriptional consequences in Saccharomyces cerevisiae. We show that transcription start sites (TSSs) of chromatin-sensitive internal cryptic transcripts retain comparable features of canonical TSSs in terms of DNA sequence, directionality and chromatin accessibility. We degine the 5 and 3 boundaries of cryptic transcripts and show that, contrary to RNA degradation-sensitive ones, they often overlap with the end of the gene thereby using the canonical polyadenylation site and associate to polyribosomes. We show that chromatin-sensitive cryptic transcripts can be recognized by ribosomes and may produce truncated polypeptides from downstream, in-frame start codons. Finally, we congirm the presence of the predicted polypeptides by reanalyzing N-terminal proteomic datasets. Our work suggests that a fraction of chromatin-sensitive internal cryptic promoters are in fact alternative truncated mRNA isoforms. The expression of these chromatin-sensitive isoforms is conserved from yeast to human expanding the functional consequences of cryptic transcription and proteome complexity.
]]></description>
<dc:creator>Wei, W.</dc:creator>
<dc:creator>Hennig, B.</dc:creator>
<dc:creator>Wang, J.</dc:creator>
<dc:creator>Zhang, Y.</dc:creator>
<dc:creator>Chabbert, C. D.</dc:creator>
<dc:creator>Adjalley, S. H.</dc:creator>
<dc:creator>Steinmetz, L. M.</dc:creator>
<dc:creator>Pelechano, V.</dc:creator>
<dc:date>2018-08-29</dc:date>
<dc:identifier>doi:10.1101/403543</dc:identifier>
<dc:title><![CDATA[Chromatin-dependent cryptic promoters encode alternative protein isoforms in yeast.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/217836v1?rss=1">
<title>
<![CDATA[
Systematic analysis of the molecular architecture of endocytosis reveals a nanoscale actin nucleation template that drives efficient vesicle formation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/217836v1?rss=1"
</link>
<description><![CDATA[
Clathrin-mediated endocytosis is an essential cellular function in all eukaryotes that is driven by a self-assembled macromolecular machine of over 50 different proteins in tens to hundreds of copies. How these proteins are organized to produce endocytic vesicles with high precision and efficiency is not understood. Here, we developed high-throughput superresolution microscopy to reconstruct the nanoscale structural organization of 23 endocytic proteins from over 100,000 endocytic sites in yeast. We found that proteins assemble by radially-ordered recruitment according to function. WASP family proteins form a circular nano-scale template on the membrane to spatially control actin nucleation during vesicle formation. Mathematical modeling of actin polymerization showed that this WASP nano-template creates sufficient force for membrane invagination and substantially increases the efficiency of endocytosis. Such nanoscale pre-patterning of actin nucleation may represent a general design principle for directional force generation in membrane remodeling processes such as during cell migration and division.
]]></description>
<dc:creator>Mund, M.</dc:creator>
<dc:creator>van der Beek, J. A.</dc:creator>
<dc:creator>Deschamps, J.</dc:creator>
<dc:creator>Dmitrieff, S.</dc:creator>
<dc:creator>Monster, J. L.</dc:creator>
<dc:creator>Picco, A.</dc:creator>
<dc:creator>Nedelec, F.</dc:creator>
<dc:creator>Kaksonen, M.</dc:creator>
<dc:creator>Ries, J.</dc:creator>
<dc:date>2017-11-15</dc:date>
<dc:identifier>doi:10.1101/217836</dc:identifier>
<dc:title><![CDATA[Systematic analysis of the molecular architecture of endocytosis reveals a nanoscale actin nucleation template that drives efficient vesicle formation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/282517v1?rss=1">
<title>
<![CDATA[
Quantifying the impact of public omics data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/282517v1?rss=1"
</link>
<description><![CDATA[
The amount of omics data in the public domain is increasing every year [1, 2]. Public availability of datasets is growing in all disciplines, because it is considered to be a good scientific practice (e.g. to enable reproducibility), and/or it is mandated by funding agencies, scientific journals, etc. Science is now a data intensive discipline and therefore, new and innovative ways for data management, data sharing, and for discovering novel datasets are increasingly required [3, 4]. However, as data volumes grow, quantifying its impact becomes more and more important. In this context, the FAIR (Findable, Accessible, Interoperable, Reusable) principles have been developed to promote good scientific practises for scientific data and data resources [5]. In fact, recently, several resources [1, 2, 6] have been created to facilitate the Findability (F) and Accessibility (A) of biomedical datasets. These principles put a specific emphasis on enhancing the ability of both individuals and software to discover and re-use digital objects in an automated fashion throughout their entire life cycle [5]. While data resources typically assign an equal relevance to all datasets (e.g. as results of a query), the usage patterns of the data can vary enormously, similarly to other "research products" such as publications. How do we know which datasets are getting more attention? More generally, how can we quantify the scientific impact of datasets?
]]></description>
<dc:creator>Perez-Riverol, Y.</dc:creator>
<dc:creator>Zorin, A.</dc:creator>
<dc:creator>Dass, G.</dc:creator>
<dc:creator>Glont, M.</dc:creator>
<dc:creator>Vizcaino, J. A.</dc:creator>
<dc:creator>Jarnuczak, A.</dc:creator>
<dc:creator>Petryszak, R.</dc:creator>
<dc:creator>Ping, P.</dc:creator>
<dc:creator>Hermjakob, H.</dc:creator>
<dc:date>2018-03-14</dc:date>
<dc:identifier>doi:10.1101/282517</dc:identifier>
<dc:title><![CDATA[Quantifying the impact of public omics data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/167742v1?rss=1">
<title>
<![CDATA[
Whole-body single-cell sequencing of the Platynereis larva reveals a subdivision into apical versus non-apical tissues 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/167742v1?rss=1"
</link>
<description><![CDATA[
Animal bodies comprise a diverse array of tissues and cells. To characterise cellular identities across an entire body, we have compared the transcriptomes of single cells randomly picked from dissociated whole larvae of the marine annelid Platynereis dumerilii1-4. We identify five transcriptionally distinct groups of differentiated cells that are spatially coherent, as revealed by spatial mapping5. Besides somatic musculature, ciliary bands and midgut, we find a group of cells located at the apical tip of the animal, comprising sensory-peptidergic neurons, and another group composed of non-apical neural and epidermal cells covering the rest of the body. These data establish a basic subdivision of the larval body surface into molecularly defined apical versus non-apical tissues, and support the evolutionary conservation of the apical nervous system as a distinct part of the bilaterian brain6.
]]></description>
<dc:creator>Achim, K.</dc:creator>
<dc:creator>Eling, N.</dc:creator>
<dc:creator>Martinez Vergara, H.</dc:creator>
<dc:creator>Bertucci, P. Y.</dc:creator>
<dc:creator>Brunet, T.</dc:creator>
<dc:creator>Collier, P.</dc:creator>
<dc:creator>Benes, V.</dc:creator>
<dc:creator>Marioni, J. C.</dc:creator>
<dc:creator>Arendt, D.</dc:creator>
<dc:date>2017-07-24</dc:date>
<dc:identifier>doi:10.1101/167742</dc:identifier>
<dc:title><![CDATA[Whole-body single-cell sequencing of the Platynereis larva reveals a subdivision into apical versus non-apical tissues]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/010926v1?rss=1">
<title>
<![CDATA[
Genome-wide comparative analysis reveals human- mouse regulatory landscape and evolution 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/010926v1?rss=1"
</link>
<description><![CDATA[
BackgroundBecause species-specific gene expression is driven by species-specific regulation, understanding the relationship between sequence and function of the regulatory regions in different species will help elucidate how differences among species arise. Despite active experimental and computational research, the relationships among sequence, conservation, and function are still poorly understood.nnResultsWe compared transcription factor occupied segments (TFos) for 116 human and 35 mouse TFs in 546 human and 125 mouse cell types and tissues from the Human and the Mouse ENCODE projects. We based the map between human and mouse TFos on a one-to-one nucleotide cross-species mapper, bnMapper, that utilizes whole genome alignments (WGA).nnOur analysis shows that TFos are under evolutionary constraint, but a substantial portion (25.1% of mouse and 25.85% of human on average) of the TFos does not have a homologous sequence on the other species; this portion varies among cell types and TFs. Furthermore, 47.67% and 57.01% of the homologous TFos sequence shows binding activity on the other species for human and mouse respectively. However, 79.87% and 69.22% is repurposed such that it binds the same TF in different cells or different TFs in the same cells. Remarkably, within the set of TFos not showing conservation of occupancy, the corresponding genome regions in the other species are preferred locations of novel TFos. These events suggest that a substantial amount of functional regulatory sequences is exapted from other biochemically active genomic material.nnDespite substantial repurposing of TFos, we did not find substantial changes in their predicted target genes, suggesting that CRMs buffer evolutionary events allowing little or no change in the TF - target gene associations. Thus, the small portion of TFos with strictly conserved occupancy underestimates the degree of conservation of regulatory interactions.nnConclusionWe mapped regulatory sequences from an extensive number of TFs and cell types between human and mouse. A comparative analysis of this correspondence unveiled the extent of the shared regulatory sequence across TFs and cell types under study. Importantly, a large part of the shared regulatory sequence repurposed on the other species. This sequence, fueled by turnover events, provides a strong case for exaptation in regulatory elements.
]]></description>
<dc:creator>Olgert Denas</dc:creator>
<dc:creator>Richard Sandstrom</dc:creator>
<dc:creator>Yong Cheng</dc:creator>
<dc:creator>Kathryn Beal</dc:creator>
<dc:creator>Javier Herrero</dc:creator>
<dc:creator>Ross Hardison</dc:creator>
<dc:creator>James Taylor</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-10-30</dc:date>
<dc:identifier>doi:10.1101/010926</dc:identifier>
<dc:title><![CDATA[Genome-wide comparative analysis reveals human- mouse regulatory landscape and evolution]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-10-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/010504v1?rss=1">
<title>
<![CDATA[
Cooperative development of logical modelling standards and tools with CoLoMoTo 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/010504v1?rss=1"
</link>
<description><![CDATA[
The identification of large regulatory and signalling networks involved in the control of crucial cellular processes calls for proper modelling approaches. Indeed, models can help elucidate properties of these networks, understand their behaviour, and provide (testable) predictions by performing in silico experiments. In this context, qualitative, logical frameworks have emerged as relevant approaches as demonstrated by a growing number of published models, along with new methodologies and software tools. This productive activity now requires a concerted effort to ensure model reusability and interoperability between tools. Here, we outline the logical modelling framework and present the most important achievements of the Consortium for Logical Models and Tools, along with future objectives. This open community welcomes contributions from all researchers interested in logical modelling or in related mathematical and computational developments.
]]></description>
<dc:creator>Aurélien Naldi</dc:creator>
<dc:creator>Pedro T Monteiro</dc:creator>
<dc:creator>Christoph Müssel</dc:creator>
<dc:creator>the Consortium for Logical Models and Tools</dc:creator>
<dc:creator>Hans A Kestler</dc:creator>
<dc:creator>Denis Thieffry</dc:creator>
<dc:creator>Ioannis Xenarios</dc:creator>
<dc:creator>Julio Saez-Rodriguez</dc:creator>
<dc:creator>Tomas Helikar</dc:creator>
<dc:creator>Claudine Chaouiya</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-10-19</dc:date>
<dc:identifier>doi:10.1101/010504</dc:identifier>
<dc:title><![CDATA[Cooperative development of logical modelling standards and tools with CoLoMoTo]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-10-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/009100v1?rss=1">
<title>
<![CDATA[
Conservation and structural analysis of the Xenopus laevis phospho-proteome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/009100v1?rss=1"
</link>
<description><![CDATA[
The African clawed frog Xenopus laevis is an important model organism for studies in developmental and cell biology, including cell-signaling. However, our knowledge of X. laevis protein post-translational modifications remains scarce. Here, we used a mass spectrometry-based approach to survey the phosphoproteome of this species, compiling a list of 3225 phosphosites. We used this resource to study the conservation between the phosphoproteomes of X. laevis and 13 other species. We found that the degree of conservation of phosphorylation across species is predictive of sites with known molecular function, kinase interactions and functionally relevant phospho-regulatory interactions. In addition, using comparative protein structure models, we find that phosphosites within structured domains tend to be located at positions with high conformational flexibility. A fraction of sites appear to occur in inaccessible positions and have the potential to regulate protein conformation.
]]></description>
<dc:creator>Jeffrey R Johnson</dc:creator>
<dc:creator>Silvia D Santos</dc:creator>
<dc:creator>Tasha Johnson</dc:creator>
<dc:creator>Ursula Pieper</dc:creator>
<dc:creator>Andrej Sali</dc:creator>
<dc:creator>Nevan J Krogan</dc:creator>
<dc:creator>Pedro Beltrao</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-09-14</dc:date>
<dc:identifier>doi:10.1101/009100</dc:identifier>
<dc:title><![CDATA[Conservation and structural analysis of the Xenopus laevis phospho-proteome]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-09-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/008425v1?rss=1">
<title>
<![CDATA[
DISEASES: Text mining and data integration of disease–gene associations 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/008425v1?rss=1"
</link>
<description><![CDATA[
Text mining is a flexible technology that can be applied to numerous different tasks in biology and medicine. We present a system for extracting disease-gene associations from biomedical abstracts. The system consists of a highly efficient dictionary-based tagger for named entity recognition of human genes and diseases, which we combine with a scoring scheme that takes into account co-occurrences both within and between sentences. We show that this approach is able to extract half of all manually curated associations with a false positive rate of only 0.16%. Nonetheless, text mining should not stand alone, but be combined with other types of evidence. For this reason, we have developed the DISEASES resource, which integrates the results from text mining with manually curated disease-gene associations, cancer mutation data, and genome-wide association studies from existing databases. The DISEASES resource is accessible through a user-friendly web interface at http://diseases.jensenlab.org/, where the text-mining software and all associations are also freely available for download.
]]></description>
<dc:creator>Sune Pletscher-Frankild</dc:creator>
<dc:creator>Albert Pallejà</dc:creator>
<dc:creator>Kalliopi Tsafou</dc:creator>
<dc:creator>Janos X Binder</dc:creator>
<dc:creator>Lars Juhl Jensen</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-08-25</dc:date>
<dc:identifier>doi:10.1101/008425</dc:identifier>
<dc:title><![CDATA[DISEASES: Text mining and data integration of disease–gene associations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-08-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/002824v1?rss=1">
<title>
<![CDATA[
HTSeq - A Python framework to work with high-throughput sequencing data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/002824v1?rss=1"
</link>
<description><![CDATA[
MotivationA large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard work flows, custom scripts are needed.nnResultsWe present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data such as genomic coordinates, sequences, sequencing reads, alignments, gene model information, variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes.nnAvailabilityHTSeq is released as open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index https://pypi.python.org/pypi/HTSeq.nnContactsanders@fs.tum.de
]]></description>
<dc:creator>Simon Anders</dc:creator>
<dc:creator>Paul Theodor Pyl</dc:creator>
<dc:creator>Wolfgang Huber</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-02-20</dc:date>
<dc:identifier>doi:10.1101/002824</dc:identifier>
<dc:title><![CDATA[HTSeq - A Python framework to work with high-throughput sequencing data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-02-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/007963v1?rss=1">
<title>
<![CDATA[
RNA-Rocket: An RNA-Seq Analysis Resource for Infectious Disease Research 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/007963v1?rss=1"
</link>
<description><![CDATA[
MotivationRNA-Seq is a method for profiling transcription using high-throughput sequencing and is an important component of many research projects that wish to study transcript isoforms, condition specific expression, and transcriptional structure. The methods, tools, and technologies employed to perform RNA-Seq analysis continue to change, creating a bioinformatics challenge for researchers who wish to exploit these data. Resources that bring together genomic data, analysis tools, educational material, and computational infrastructure can minimize the overhead required of life science researchers.nnResultsRNA-Rocket is a free service that provides access to RNA-Seq and ChIP-Seq analysis tools for studying infectious diseases. The site makes available thousands of pre-indexed genomes, their annotations, and the ability to stream results to the bioinformatics resources VectorBase, EuPathDB, and PATRIC. The site also provides a combination of experimental data and metadata, examples of pre-computed analysis, step-by-step guides, and a user interface designed to enable both novice and experienced users of RNA-Seq data.nnAvailability: RNA-Rocket can be found at rnaseq.pathogenportal.org Source code for this project can be found at github.com/cidvbi/PathogenPortal
]]></description>
<dc:creator>Andrew S. Warren</dc:creator>
<dc:creator>Cristina Aurrecoechea</dc:creator>
<dc:creator>Brian Brunk</dc:creator>
<dc:creator>Prerak Desai</dc:creator>
<dc:creator>Scott Emrich</dc:creator>
<dc:creator>Gloria I. Giraldo-Calderón</dc:creator>
<dc:creator>Omar Harb</dc:creator>
<dc:creator>Deborah Hix</dc:creator>
<dc:creator>Daniel Lawson</dc:creator>
<dc:creator>Dustin Machi</dc:creator>
<dc:creator>Chunhong Mao</dc:creator>
<dc:creator>Michael McClelland</dc:creator>
<dc:creator>Eric Nordberg</dc:creator>
<dc:creator>Maulik Shukla</dc:creator>
<dc:creator>Leslie B. Vosshall</dc:creator>
<dc:creator>Alice R. Wattam</dc:creator>
<dc:creator>Rebecca Will</dc:creator>
<dc:creator>Hyun Seung Yoo</dc:creator>
<dc:creator>Bruno Sobral</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-08-14</dc:date>
<dc:identifier>doi:10.1101/007963</dc:identifier>
<dc:title><![CDATA[RNA-Rocket: An RNA-Seq Analysis Resource for Infectious Disease Research]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-08-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/005207v1?rss=1">
<title>
<![CDATA[
RNA-seq gene profiling - a systematic empirical comparison 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/005207v1?rss=1"
</link>
<description><![CDATA[
Accurately quantifying gene expression levels is a key goal of experiments using RNA-sequencing to assay the transcriptome. This typically requires aligning the short reads generated to the genome or transcriptome before quantifying expression of pre-defined sets of genes. Differences in the alignment/quantification tools can have a major effect upon the expression levels found with important consequences for biological interpretation. Here we address two main issues: do different analysis pipelines affect the gene expression levels inferred from RNA-seq data? And, how close are the expression levels inferred to the "true" expression levels?nnWe evaluate fifty gene profiling pipelines in experimental and simulated data sets with different characteristics (e.g, read length and sequencing depth). In the absence of knowledge of the  ground truth in real RNAseq data sets, we used simulated data to assess the differences between the "true" expression and those reconstructed by the analysis pipelines. Even though this approach does not take into account all known biases present in RNAseq data, it still allows to estimate the accuracy of the gene expression values inferred by different analysis pipelines. The results show that i) overall there is a high correlation between the expression levels inferred by the best pipelines and the true quantification values; ii) the error in the estimated gene expression values can vary considerably across genes; and iii) a small set of genes have expression estimates with consistently high error (across data sets and methods). Finally, although the mapping software is important, the quantification method makes a greater difference to the results.
]]></description>
<dc:creator>Nuno A Fonseca</dc:creator>
<dc:creator>John A Marioni</dc:creator>
<dc:creator>Alvis Brazma</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-05-14</dc:date>
<dc:identifier>doi:10.1101/005207</dc:identifier>
<dc:title><![CDATA[RNA-seq gene profiling - a systematic empirical comparison]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-05-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/000992v1?rss=1">
<title>
<![CDATA[
Mutated SF3B1 is associated with transcript isoform changes of the genes UQCC and RPL31 both in CLLs and uveal melanomas 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/000992v1?rss=1"
</link>
<description><![CDATA[
BackgroundGenome sequencing studies of chronic lympoid leukemia (CLL) have provided a comprehensive overview of recurrent somatic mutations in coding genes. One of the most intriguing discoveries has been the prevalence of mutations in the HEAT-repeat domain of the splicing factor SF3B1. A frequently observed variant is predicted to cause the substitution of a lysine with a glutamic acid at position 700 of the protein (K700E). However, the molecular consequences of the mutations are largely unknown.nnResultsTo start exploring this question, we sequenced the transcriptomes of six samples: four samples of CLL tumour cells, of which two contained the K700E mutation in SF3B1, and CD19 positive cells from two healthy donors. We identified 41 genes that showed differential usage of exons statistically associated with the mutated status of SF3B1 (false discovery rate of 10%). These genes were enriched in pathways related to interferon signaling and mRNA splicing.nnAmong these genes, we found UQCC and RPL31; notably, a similar effect on these genes was described in a previously published study of uveal melanoma. In addition, while this manuscript was under revision, another study independently reported the common splicing signature of the gene UQCC in different tumour types with mutations in SF3B1.nnConclusionsOur results suggest common effects of isoform deregulation in the genes UQCC and RPL31 upon mutations in SF3B1. Additionally, our data provide a candidate list of potential isoform consequences of the SF3B1 (K700E) mutation in CLL, some of which might contribute to the tumourigenesis.nnValidation studies on larger cohorts and model systems are required to extend these findings.
]]></description>
<dc:creator>Alejandro Reyes</dc:creator>
<dc:creator>Carolin Blume</dc:creator>
<dc:creator>Vicent Pelechano</dc:creator>
<dc:creator>Petra Jakob</dc:creator>
<dc:creator>Lars M Steinmetz</dc:creator>
<dc:creator>Thorsten Zenz</dc:creator>
<dc:creator>Wolfgang Huber</dc:creator>
<dc:creator></dc:creator>
<dc:date>2013-12-02</dc:date>
<dc:identifier>doi:10.1101/000992</dc:identifier>
<dc:title><![CDATA[Mutated SF3B1 is associated with transcript isoform changes of the genes UQCC and RPL31 both in CLLs and uveal melanomas]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2013-12-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/005967v1?rss=1">
<title>
<![CDATA[
Identification, annotation and visualisation of extreme changes in splicing from RNA-seq experiments with SwitchSeq 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/005967v1?rss=1"
</link>
<description><![CDATA[
In the past years, RNA sequencing has become the method of choice for the study of transcriptome composition. When working with this type of data, several tools exist to quantify differences in splicing across conditions and to address the significance of those changes. However, the number of genes predicted to undergo differential splicing is often high, and further interpretation of the results becomes a challenging task. Here we present SwitchSeq, a novel set of tools designed to help the users in the interpretation of differential splicing events that affect protein coding genes. More specifically, we provide a framework to identify switch events, i.e., cases where, for a given gene, the identity of the most abundant transcript changes across conditions. The identified events are then annotated by incorporating information from several public databases and third-party tools, and are further visualised in an intuitive manner with the independent R package tviz. All the results are displayed in a self-contained HTML document, and are also stored in txt and json format to facilitate the integration with any further downstream analysis tools. Such analysis approach can be used complementarily to Gene Ontology and pathway enrichment analysis, and can also serve as an aid in the validation of predicted changes in mRNA and protein abundance. The latest version of SwitchSeq, including installation instructions and use cases, can be found at https://github.com/mgonzalezporta/SwitchSeq. Additionally, the plot capabilities are provided as an independent R package at https://github.com/mgonzalezporta/tviz.
]]></description>
<dc:creator>Mar Gonzàlez-Porta</dc:creator>
<dc:creator>Alvis Brazma</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-06-06</dc:date>
<dc:identifier>doi:10.1101/005967</dc:identifier>
<dc:title><![CDATA[Identification, annotation and visualisation of extreme changes in splicing from RNA-seq experiments with SwitchSeq]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-06-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/005991v1?rss=1">
<title>
<![CDATA[
iRAP - an integrated RNA-seq Analysis Pipeline 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/005991v1?rss=1"
</link>
<description><![CDATA[
RNA-sequencing (RNA-Seq) has become the technology of choice for whole-transcriptome profiling. However, processing the millions of sequence reads generated requires considerable bioinformatics skills and computational resources. At each step of the processing pipeline many tools are available, each with specific advantages and disadvantages. While using a specific combination of tools might be desirable, integrating the different tools can be time consuming, often due to specificities in the formats of input/output files required by the different programs. Here we present iRAP, an integrated RNA-seq analysis pipeline that allows the user to select and apply their preferred combination of existing tools for mapping reads, quantifying expression, testing for differential expression. iRAP also includes multiple tools for gene set enrichment analysis and generates web browsable reports of the results obtained in the different stages of the pipeline. Depending upon the application, iRAP can be used to quantify expression at the gene, exon or transcript level. iRAP is aimed at a broad group of users with basic bioinformatics training and requires little experience with the command line. Despite this, it also provides more advanced users with the ability to customise the options used by their chosen tools.
]]></description>
<dc:creator>Nuno A. Fonseca</dc:creator>
<dc:creator>Robert Petryszak</dc:creator>
<dc:creator>John Marioni</dc:creator>
<dc:creator>Alvis Brazma</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-06-06</dc:date>
<dc:identifier>doi:10.1101/005991</dc:identifier>
<dc:title><![CDATA[iRAP - an integrated RNA-seq Analysis Pipeline]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-06-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/003905v1?rss=1">
<title>
<![CDATA[
LIMIX: genetic analysis of multiple traits 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/003905v1?rss=1"
</link>
<description><![CDATA[
Multi-trait mixed models have emerged as a promising approach for joint analyses of multiple traits. In principle, the mixed model framework is remarkably general. However, current methods implement only a very specific range of tasks to optimize the necessary computations. Here, we present a multi-trait modeling framework that is versatile and fast: LIMIX enables to flexibly adapt mixed models for a broad range of applications with different observed and hidden covariates, and variable study designs. To highlight the novel modeling aspects of LIMIX we performed three vastly different genetic studies: joint GWAS of correlated blood lipid phenotypes, joint analysis of the expression levels of the multiple transcript-isoforms of a gene, and pathway-based modeling of molecular traits across environments. In these applications we show that LIMIX increases GWAS power and phenotype prediction accuracy, in particular when integrating stepwise multi-locus regression into multi-trait models, and when analyzing large numbers of traits. An open source implementation of LIMIX is freely available at: https://github.com/PMBio/limix.
]]></description>
<dc:creator>Christoph Lippert</dc:creator>
<dc:creator>Francesco Paolo Casale</dc:creator>
<dc:creator>Barbara Rakitsch</dc:creator>
<dc:creator>Oliver Stegle</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-05-21</dc:date>
<dc:identifier>doi:10.1101/003905</dc:identifier>
<dc:title><![CDATA[LIMIX: genetic analysis of multiple traits]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-05-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/004168v1?rss=1">
<title>
<![CDATA[
Neural lineage induction reveals multi-scale dynamics of 3D chromatin organization 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/004168v1?rss=1"
</link>
<description><![CDATA[
Regulation of gene expression underlies cell identity. Chromatin structure and gene activity are linked at multiple levels, via positioning of genomic loci to transcriptionally permissive or repressive environments and by connecting cis-regulatory elements such as promoters and enhancers. However, the genome-wide dynamics of these processes during cell differentiation has not been characterized. Using tethered chromatin conformation capture (TCC) sequencing we determined global three-dimensional chromatin structures in mouse embryonic stem (ES) and neural stem (NS) cell derivatives. We found that changes in the propensity of genomic regions to form inter-chromosomal contacts are pervasive in neural induction and are associated with the regulation of gene expression. Moreover, we found a pronounced contribution of euchromatic domains to the intra-chromosomal interaction network of pluripotent cells, indicating the existence of an ES cell-specific mode of chromatin organization. Mapping of promoter-enhancer interactions in pluripotent and differentiated cells revealed that spatial proximity without enhancer element activity is a common architectural feature in cells undergoing early developmental changes. Activity-independent formation of higher-order contacts between cis-regulatory elements, predominant at complex loci, may thus provide an additional layer of transcriptional control.
]]></description>
<dc:creator>Aleksandra Pekowska</dc:creator>
<dc:creator>Bernd Klaus</dc:creator>
<dc:creator>Felix Alexander Klein</dc:creator>
<dc:creator>Simon Anders</dc:creator>
<dc:creator>Malgorzata Oles</dc:creator>
<dc:creator>Lars Michael Steinmetz</dc:creator>
<dc:creator>Paul Bertone</dc:creator>
<dc:creator>Wolfgang Huber</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-04-11</dc:date>
<dc:identifier>doi:10.1101/004168</dc:identifier>
<dc:title><![CDATA[Neural lineage induction reveals multi-scale dynamics of 3D chromatin organization]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-04-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/003285v1?rss=1">
<title>
<![CDATA[
Alignathon: A competitive assessment of whole genome alignment methods. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/003285v1?rss=1"
</link>
<description><![CDATA[
BackgroundMultiple sequence alignments (MSAs) are a prerequisite for a wide variety of evolutionary analyses. Published assessments and benchmark datasets for protein and, to a lesser extent, global nucleotide MSAs are available, but less effort has been made to establish benchmarks in the more general problem of whole genome alignment (WGA).nnResultsUsing the same model as the successful Assemblathon competitions, we organized a competitive evaluation in which teams submitted their alignments, and assessments were performed collectively after all the submissions were received. Three datasets were used: two of simulated primate and mammalian phylogenies, and one of 20 real fly genomes. In total 35 submissions were assessed, submitted by ten teams using 12 different alignment pipelines.nnConclusionsWe found agreement between independent simulation-based and statistical assessments, indicating that there are substantial accuracy differences between contemporary alignment tools. We saw considerable difference in the alignment quality of differently annotated regions, and found few tools aligned the duplications analysed. We found many tools worked well at shorter evolutionary distances, but fewer performed competitively at longer distances. We provide all datasets, submissions and assessment programs for further study, and provide, as a resource for future benchmarking, a convenient repository of code and data for reproducing the simulation assessments.
]]></description>
<dc:creator>Dent Earl</dc:creator>
<dc:creator>Ngan K Nguyen</dc:creator>
<dc:creator>Glenn Hickey</dc:creator>
<dc:creator>Robert S. Harris</dc:creator>
<dc:creator>Stephen Fitzgerald</dc:creator>
<dc:creator>Kathryn Beal</dc:creator>
<dc:creator>Igor Seledtsov</dc:creator>
<dc:creator>Vladimir Molodtsov</dc:creator>
<dc:creator>Brian Raney</dc:creator>
<dc:creator>Hiram Clawson</dc:creator>
<dc:creator>Jaebum Kim</dc:creator>
<dc:creator>Carsten Kemena</dc:creator>
<dc:creator>Jia-Ming Chang</dc:creator>
<dc:creator>Ionas Erb</dc:creator>
<dc:creator>Alexander Poliakov</dc:creator>
<dc:creator>Minmei Hou</dc:creator>
<dc:creator>Javier Herrero</dc:creator>
<dc:creator>Victor Solovyev</dc:creator>
<dc:creator>Aaron E. Darling</dc:creator>
<dc:creator>Jian Ma</dc:creator>
<dc:creator>Cedric Notredame</dc:creator>
<dc:creator>Michael Brudno</dc:creator>
<dc:creator>Inna Dubchak</dc:creator>
<dc:creator>David Haussler</dc:creator>
<dc:creator>Benedict Paten</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-03-10</dc:date>
<dc:identifier>doi:10.1101/003285</dc:identifier>
<dc:title><![CDATA[Alignathon: A competitive assessment of whole genome alignment methods.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-03-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/009548v1?rss=1">
<title>
<![CDATA[
FourCSeq: Analysis of 4C sequencing data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/009548v1?rss=1"
</link>
<description><![CDATA[
1 Abstract 1.1 MotivationCircularized Chromosome Conformation Capture (4C) is a powerful technique for studying the spatial interactions of a specific genomic region called the "viewpoint" with the rest of the genome, both in a single condition or comparing different experimental conditions or cell types. Observed ligation frequencies show a strong, regular dependence on genomic distance from the viewpoint, on top of which specific interaction peaks are superimposed. Here, we address the computational task to find these specific interactions and to detect changes between interaction profiles of different conditions.nn1.2 ResultsWe model the overall trend of decreasing interaction frequency with genomic distance by fitting a smooth monotonously decreasing function to suitably transformed count data. Based on the fit, z-scores are calculated from the residuals, with high z scores being interpreted as peaks providing evidence for specific interactions. To compare different conditions, we normalize fragment counts between samples, and call for differential contact frequencies using the statistical method DESeq2 adapted from RNA-Seq analysis.nn1.3 Availability and ImplementationA full end-to-end analysis pipeline is implemented in the R package FourCSeq available at www.bioconductor.org.nn1.4 Contactfelix.klein@embl.de, whuber@embl.de
]]></description>
<dc:creator>Felix A. Klein</dc:creator>
<dc:creator>Tibor Pakozdi</dc:creator>
<dc:creator>Simon Anders</dc:creator>
<dc:creator>Yad Ghavi-Helm</dc:creator>
<dc:creator>Eileen E. M. Furlong</dc:creator>
<dc:creator>Wolfgang Huber</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-09-23</dc:date>
<dc:identifier>doi:10.1101/009548</dc:identifier>
<dc:title><![CDATA[FourCSeq: Analysis of 4C sequencing data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-09-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/019117v1?rss=1">
<title>
<![CDATA[
Open science resources for the discovery and analysis of Tara Oceans Data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/019117v1?rss=1"
</link>
<description><![CDATA[
The Tara Oceans expedition (2009-2013) sampled contrasting ecosystems of the world oceans, collecting environmental data and plankton, from viruses to metazoans, for later analysis using modern sequencing and state-of-the-art imaging technologies. It surveyed 210 ecosystems in 20 biogeographic provinces, collecting over 35000 samples of seawater and plankton. The interpretation of such an extensive collection of samples in their ecological context requires means to explore, assess and access raw and validated data sets. To address this challenge, the Tara Oceans Consortium offers open science resources, including the use of open access archives for nucleotides (ENA) and for environmental, biogeochemical, taxonomic and morphological data (PANGAEA), and the development of on line discovery tools and collaborative annotation tools for sequences and images. Here, we present an overview of Tara Oceans Data, and we provide detailed registries (data sets) of all campaigns (from port-to-port), stations and sampling events.
]]></description>
<dc:creator>Stéphane Pesant</dc:creator>
<dc:creator>Fabrice Not</dc:creator>
<dc:creator>Marc Picheral</dc:creator>
<dc:creator>Stefanie Kandels-Lewis</dc:creator>
<dc:creator>Noan Le Bescot</dc:creator>
<dc:creator>Gabriel Gorsky</dc:creator>
<dc:creator>Daniele Iudicone</dc:creator>
<dc:creator>Eric Karsenti</dc:creator>
<dc:creator>Sabrina Speich</dc:creator>
<dc:creator>Romain Troublé</dc:creator>
<dc:creator>Celine Dimier</dc:creator>
<dc:creator>Sarah Searson</dc:creator>
<dc:creator>Tara Oceans Consortium Coordinators</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-05-08</dc:date>
<dc:identifier>doi:10.1101/019117</dc:identifier>
<dc:title><![CDATA[Open science resources for the discovery and analysis of Tara Oceans Data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-05-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/010686v1?rss=1">
<title>
<![CDATA[
SomaticSignatures: Inferring Mutational Signatures from Single Nucleotide Variants 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/010686v1?rss=1"
</link>
<description><![CDATA[
Mutational signatures are patterns in the occurrence of somatic single nucleotide variants (SNVs) that can reflect underlying mutational processes. The SomaticSignatures package provides flexible, interoperable, and easy-to-use tools that identify such signatures in cancer sequencing studies. It facilitates large-scale, cross-dataset estimation of mutational signatures, implements existing methods for pattern decomposition, supports extension through user-defined methods and integrates with Bioconductor workflows.nnThe R package SomaticSignatures is available as part of the Bioconductor project (R Core Team, 2014; Gentleman et al., 2004). Its documentation provides additional details on the methodology and demonstrates applications to biological datasets.
]]></description>
<dc:creator>Julian S. Gehring</dc:creator>
<dc:creator>Bernd Fischer</dc:creator>
<dc:creator>Michael Lawrence</dc:creator>
<dc:creator>Wolfgang Huber</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-10-24</dc:date>
<dc:identifier>doi:10.1101/010686</dc:identifier>
<dc:title><![CDATA[SomaticSignatures: Inferring Mutational Signatures from Single Nucleotide Variants]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-10-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/016204v1?rss=1">
<title>
<![CDATA[
Mutational oncogenic signatures on structurally resolved protein interacting interfaces 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/016204v1?rss=1"
</link>
<description><![CDATA[
The importance of the context of interactions in the proteins mutated in cancer is long known. However, our knowledge on how mutations affecting to protein-protein interactions (PPIs) are related to cancer occurrence and progression is still poor. Here, we extracted the missense somatic mutations from 5920 cancer patients of 33 different cancer types, taken from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), and mapped them onto a structurally resolved interactome, which integrates three-dimensional atomic-level models of domain-domain interactions with experimentally determined PPIs, involving a total of 7580 unique interacting domains that participate in 13160 interactions connecting 4996 proteins. We observed that somatic nonsynonymous mutations tend to concentrate in ordered regions of the affected proteins and, within these, they have a clear preference for the interacting interfaces. Also, we have identified more than 250 interacting interfaces candidate to drive cancer. Examples demonstrate how mutations in the interacting interfaces are strongly associated with patient survival time, while similar mutations in other areas of the same proteins lack this association. Our results suggest that the perturbation caused by cancer mutations in protein interactions is an important factor in explaining the heterogeneity between cancer patients.
]]></description>
<dc:creator>Luz Garcia-Alonso</dc:creator>
<dc:creator>Joaquin Dopazo</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-03-07</dc:date>
<dc:identifier>doi:10.1101/016204</dc:identifier>
<dc:title><![CDATA[Mutational oncogenic signatures on structurally resolved protein interacting interfaces]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-03-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/013045v1?rss=1">
<title>
<![CDATA[
FORGE : A tool to discover cell specific enrichments of GWAS associated SNPs in regulatory regions. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/013045v1?rss=1"
</link>
<description><![CDATA[
Genome wide association studies provide an unbiased discovery mechanism for numerous human diseases. However, a frustration in the analysis of GWAS is that the majority of variants discovered do not directly alter protein-coding genes. We have developed a simple analysis approach that detects the tissue-specific regulatory component of a set of GWAS SNPs by identifying enrichment of overlap with DNase I hotspots from diverse tissue samples. Functional element Overlap analysis of the Results of GWAS Experiments (FORGE) is available as a web tool and as standalone software and provides tabular and graphical summaries of the enrichments. Conducting FORGE analysis on SNP sets for 260 phenotypes available from the GWAS catalogue reveals numerous overlap enrichments with tissue-specific components reflecting the known aetiology of the phenotypes as well as revealing other unforeseen tissue involvements that may lead to mechanistic insights for disease.
]]></description>
<dc:creator>Ian Dunham</dc:creator>
<dc:creator>Eugene Kulesha</dc:creator>
<dc:creator>Valentina Iotchkova</dc:creator>
<dc:creator>Sandro Morganella</dc:creator>
<dc:creator>Ewan Birney</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-12-20</dc:date>
<dc:identifier>doi:10.1101/013045</dc:identifier>
<dc:title><![CDATA[FORGE : A tool to discover cell specific enrichments of GWAS associated SNPs in regulatory regions.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-12-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/011700v1?rss=1">
<title>
<![CDATA[
Cell-Line Annotation on Europe PubMed Central 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/011700v1?rss=1"
</link>
<description><![CDATA[
A cell line is a cell culture developed from a single cell and therefore consisting of cells with a uniform genetic make-up. A cell line has an important role as a research resource such as organisms, antibodies, constructs, knockdown reagents, etc. Unique identification of cell lines in the biomedical literature is important for the reproducibility of science. As data citation, resource citation is also important for resource re-use.nnIn this paper, we mention the challenges of identifying cell lines and describe a system for cell line annotation with perluminary results.
]]></description>
<dc:creator>Jee-Hyub Kim</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-11-20</dc:date>
<dc:identifier>doi:10.1101/011700</dc:identifier>
<dc:title><![CDATA[Cell-Line Annotation on Europe PubMed Central]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-11-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/011585v1?rss=1">
<title>
<![CDATA[
Triticeae resources in Ensembl Plants 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/011585v1?rss=1"
</link>
<description><![CDATA[
Recent developments in DNA sequencing have enabled the large and complex genomes of many crop species to be determined for the first time, even those previously intractable due to their polyploid nature. Indeed, over the course of the last two years, the genome sequences of several commercially important cereals, notably barley and bread wheat, have become available, as well as those of related wild species. While still incomplete, comparison to other, more completely assembled species suggests that coverage of genic regions is likely to be high.nnEnsembl Plants (http://plants.ensembl.org) is an integrative resource organising, analysing and visualising genome-scale information for important crop and model plants. Available data includes reference genome sequence, variant loci, gene models and functional annotation. For variant loci, individual and population genotypes, linkage information and, where available, phenotypic information, are shown. Comparative analyses are performed on DNA and protein sequence alignments. The resulting genome alignments and gene trees, representing the implied evolutionary history the gene family, are made available for visualisation and analysis. Driven by the use case of bread wheat, specific extensions to the analysis pipelines and web interface have recently been developed to support polyploid genomes.nnData in Ensembl Plants is accessible through a genome browser incorporating various specialist interfaces for different data types, and through a variety of additional methods for programmatic access and data mining. These interfaces are consistent with those offered through the Ensembl interface for the genomes of non-plant species, including those of plant pathogens, pests and pollinators, facilitating the study of the plant in its environment.
]]></description>
<dc:creator>Dan M Bolser</dc:creator>
<dc:creator>Arnaud Kerhornou</dc:creator>
<dc:creator>Brandon Walts</dc:creator>
<dc:creator>Paul Kersey</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-11-18</dc:date>
<dc:identifier>doi:10.1101/011585</dc:identifier>
<dc:title><![CDATA[Triticeae resources in Ensembl Plants]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-11-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/002832v1?rss=1">
<title>
<![CDATA[
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/002832v1?rss=1"
</link>
<description><![CDATA[
In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html.
]]></description>
<dc:creator>Michael I Love</dc:creator>
<dc:creator>Wolfgang Huber</dc:creator>
<dc:creator>Simon Anders</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-02-19</dc:date>
<dc:identifier>doi:10.1101/002832</dc:identifier>
<dc:title><![CDATA[Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-02-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/043687v1?rss=1">
<title>
<![CDATA[
The evolutionary fates of a large segmental duplication in mouse 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/043687v1?rss=1"
</link>
<description><![CDATA[
Gene duplication and loss are major sources of genetic polymorphism in populations, and are important forces shaping the evolution of genome content and organization. We have reconstructed the origin and history of a 127 kbp segmental duplication, R2d, in the house mouse (Mus musculus). R2d contains a single protein-coding gene, Cwc22. De novo assembly of both the ancestral (R2d1) and the derived (R2d2) copies reveals that they have been subject to non-allelic gene conversion events spanning tens of kilobases. R2d2 is also a hotspot for structural variation: its diploid copy number ranges from zero in the mouse reference genome to more than 80 in wild mice sampled from around the globe. Hemizgyosity for high-copy-number alleles of R2d2 is associated in cis with meiotic drive, suppression of meiotic crossovers, and copy-number instability, with a mutation rate in excess of 1 per 100 transmissions in laboratory populations. We identify an additional 57 loci covering 0.8% of the mouse genome with patterns of sequence variation similar to those at R2d1 and R2d2. Our results provide a striking example of allelic diversity generated by duplication and demonstrate the value of de novo assembly in a phylogenetic context for understanding the mutational processes affecting duplicate genes.
]]></description>
<dc:creator>Andrew Parker Morgan</dc:creator>
<dc:creator>James Matthew Holt</dc:creator>
<dc:creator>Rachel Clara McMullan</dc:creator>
<dc:creator>Timothy A Bell</dc:creator>
<dc:creator>Amelia Mary-Frances Clayshulte</dc:creator>
<dc:creator>John Paul Didion</dc:creator>
<dc:creator>Liran Yadgary</dc:creator>
<dc:creator>David Thybert</dc:creator>
<dc:creator>Duncan T Odom</dc:creator>
<dc:creator>Paul Flicek</dc:creator>
<dc:creator>Leonard McMillan</dc:creator>
<dc:creator>Fernando Pardo-Manuel de Villena</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-03-15</dc:date>
<dc:identifier>doi:10.1101/043687</dc:identifier>
<dc:title><![CDATA[The evolutionary fates of a large segmental duplication in mouse]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-03-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/057968v1?rss=1">
<title>
<![CDATA[
Centrosome centering and decentering by microtubule network rearrangement 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/057968v1?rss=1"
</link>
<description><![CDATA[
The centrosome is positioned at the cell center by pushing and pulling forces transmitted by microtubules (MTs). Centrosome decentering is often considered to result from asymmetric, cortical pulling forces exerted in particular by molecular motors on MTs, and controlled by external cues affecting the cell cortex locally. Here we used numerical simulations to investigate the possibility that it could equally result from the redistribution of pushing forces due to a reorientation of MTs. We first showed that MT gliding along cell edges and pivoting around the centrosome regulate MT rearrangement and thereby direct the spatial distribution of pushing forces, while the number, dynamics and stiffness of MTs determine the magnitude of these forces. By modulating these parameters, we identified different regimes, involving both pushing and pulling forces, characterized either by robust centrosome centering, robust off-centering or "reactive" positioning. In those latter conditions weak asymmetric cues can induce a misbalance of pushing and pulling forces resulting in an abrupt transition from a centered to an off-centered position. Altogether these results point at the central role played by the configuration of the MTs on the distribution of pushing forces that position the centrosome. We suggest that asymmetric external cues should not be seen as direct driver of centrosome decentering and cell polarization, but rather as inducers of an effective reorganization of the MT network, fostering centrosome motion to the cell periphery.
]]></description>
<dc:creator>Gaelle Letort</dc:creator>
<dc:creator>Francois Nedelec</dc:creator>
<dc:creator>Laurent Blanchoin</dc:creator>
<dc:creator>Manuel Thery</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-06-09</dc:date>
<dc:identifier>doi:10.1101/057968</dc:identifier>
<dc:title><![CDATA[Centrosome centering and decentering by microtubule network rearrangement]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-06-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/051938v1?rss=1">
<title>
<![CDATA[
AtRTD2: A Reference Transcript Dataset for accurate quantification of alternative splicing and expression changes in Arabidopsis thaliana RNA-seq data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/051938v1?rss=1"
</link>
<description><![CDATA[
BackgroundAlternative splicing is the major post-transcriptional mechanism by which gene expression is regulated and affects a wide range of processes and responses in most eukaryotic organisms. RNA-sequencing (RNA-seq) can generate genome-wide quantification of individual transcript isoforms to identify changes in expression and alternative splicing. RNA-seq is an essential modern tool but its ability to accurately quantify transcript isoforms depends on the diversity, completeness and quality of the transcript information.nnResultsWe have developed a new Reference Transcript Dataset for Arabidopsis (AtRTD2) for RNA-seq analysis containing over 82k non-redundant transcripts, whereby 74,194 transcripts originate from 27,667 protein-coding genes. A total of 13,524 protein-coding genes have at least one alternatively spliced transcript in AtRTD2 such that about 60% of the 22,453 protein-coding, intron-containing genes in Arabidopsis undergo alternative splicing. More than 600 putative U12 introns were identified in more than 2,000 transcripts. AtRTD2 was generated from transcript assemblies of ca. 8.5 billion pairs of reads from 285 RNA-seq data sets obtained from 129 RNA-seq libraries and merged along with the previous version, AtRTD, and Araport11 transcript assemblies. AtRTD2 increases the diversity of transcripts and through application of stringent filters represents the most extensive and accurate transcript collection for Arabidopsis to date. We have demonstrated a generally good correlation of alternative splicing ratios from RNA-seq data analysed by Salmon and experimental data from high resolution RT-PCR. However, we have observed inaccurate quantification of transcript isoforms for genes with multiple transcripts which have variation in the lengths of their UTRs. This variation is not effectively corrected in RNA-seq analysis programmes and will therefore impact RNA-seq analyses generally. To address this, we have tested different genome-wide modifications of AtRTD2 to improve transcript quantification and alternative splicing analysis. As a result, we release AtRTD2-QUASI specifically for use in Quantification of Alternatively Spliced Isoforms and demonstrate that it out-performs other available transcriptomes for RNA-seq analysis.nnConclusionsWe have generated a new transcriptome resource for RNA-seq analyses in Arabidopsis (AtRTD2) designed to address quantification of different isoforms and alternative splicing in gene expression studies. Experimental validation of alternative splicing changes identified inaccuracies in transcript quantification due to UTR length variation. To solve this problem, we also release a modified reference transcriptome, AtRTD2-QUASI for quantification of transcript isoforms, which shows high correlation with experimental data.
]]></description>
<dc:creator>Runxuan Zhang</dc:creator>
<dc:creator>Cristiane P G Calixto</dc:creator>
<dc:creator>Yamile Marquez</dc:creator>
<dc:creator>Peter Venhuizen</dc:creator>
<dc:creator>Nikoleta A Tzioutziou</dc:creator>
<dc:creator>Wenbin Guo</dc:creator>
<dc:creator>Mark Spensley</dc:creator>
<dc:creator>Nicolas Frei dit Frey</dc:creator>
<dc:creator>Heribert Hirt</dc:creator>
<dc:creator>Allan B James</dc:creator>
<dc:creator>Hugh G Nimmo</dc:creator>
<dc:creator>Andrea Barta</dc:creator>
<dc:creator>Maria Kalyna</dc:creator>
<dc:creator>John W S Brown</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-05-06</dc:date>
<dc:identifier>doi:10.1101/051938</dc:identifier>
<dc:title><![CDATA[AtRTD2: A Reference Transcript Dataset for accurate quantification of alternative splicing and expression changes in Arabidopsis thaliana RNA-seq data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-05-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/095943v1?rss=1">
<title>
<![CDATA[
Molecular and functional variation in iPSC-derived sensory neurons 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/095943v1?rss=1"
</link>
<description><![CDATA[
Induced pluripotent stem cells (iPSCs), and cells derived from them, have become key tools to model biological processes and disease mechanisms, particularly in cell types such as neurons that are difficult to access from living donors. Here, we present the first map of regulatory variants in an iPSC-derived cell type. To investigate genetic contributions to human sensory function, we performed 123 differentiations of iPSCs from 103 unique donors to a sensory neuronal fate, and measured gene expression, chromatin accessibility, and neuronal excitability. Compared with primary dorsal root ganglion, where sensory nerves collect near the spinal cord, gene expression was more variable across iPSC-derived neuronal cultures, particularly in genes related to differentiation and nervous system development. Single cell RNA-sequencing revealed that although the majority of cells are neuronal and express the expected marker genes, a substantial fraction have a fibroblast-like expression profile. By applying an allele-specific method we identify 3,778 quantitative trait loci influencing gene expression, 6,318 for chromatin accessibility, and 2,097 for RNA splicing at FDR 10%. A number of these overlap with common disease associations, and suggest candidate causal variants and target genes. These include known causal variants at SNCA for Parkinsons disease and TNFRSF1A for multiple sclerosis, as well as new candidates for migraine, Parkinsons disease, and schizophrenia.
]]></description>
<dc:creator>Schwartzentruber, J.</dc:creator>
<dc:creator>Foskolou, S.</dc:creator>
<dc:creator>Kilpinen, H.</dc:creator>
<dc:creator>Rodrigues, J.</dc:creator>
<dc:creator>Alasoo, K.</dc:creator>
<dc:creator>Knights, A. J.</dc:creator>
<dc:creator>Patel, M.</dc:creator>
<dc:creator>Goncalves, A.</dc:creator>
<dc:creator>Ferreira, R.</dc:creator>
<dc:creator>Benn, C. L.</dc:creator>
<dc:creator>Wilbrey, A.</dc:creator>
<dc:creator>Bictash, M.</dc:creator>
<dc:creator>Impey, E.</dc:creator>
<dc:creator>Cao, L.</dc:creator>
<dc:creator>Lainez, S.</dc:creator>
<dc:creator>Loucif, A. J.</dc:creator>
<dc:creator>Whiting, P. J.</dc:creator>
<dc:creator>HIPSCI Consortium,</dc:creator>
<dc:creator>Gutteridge, A.</dc:creator>
<dc:creator>Gaffney, D. J.</dc:creator>
<dc:date>2017-01-06</dc:date>
<dc:identifier>doi:10.1101/095943</dc:identifier>
<dc:title><![CDATA[Molecular and functional variation in iPSC-derived sensory neurons]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-01-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/097477v1?rss=1">
<title>
<![CDATA[
Joint genetic analysis using variant sets reveals polygenic gene-context interactions 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/097477v1?rss=1"
</link>
<description><![CDATA[
Joint genetic models for multiple traits have helped to enhance association analyses. Most existing multi-trait models have been designed to increase power for detecting associations, whereas the analysis of interactions has received considerably less attention. Here, we propose iSet, a method based on linear mixed models to test for interactions between sets of variants and environmental states or other contexts. Our model generalizes previous interaction tests and in particular provides a test for local differences in the genetic architecture between contexts. We first use simulations to validate iSet before applying the model to the analysis of genotype-environment interactions in an eQTL study. Our model retrieves a larger number of interactions than alternative methods and reveals that up to 20% of cases show context-specific configurations of causal variants. Finally, we apply iSet to test for sub-group specific genetic effects in human lipid levels in a large human cohort, where we identify a gene-sex interaction for C-reactive protein that is missed by alternative methods.nnAuthor summaryGenetic effects on phenotypes can depend on external contexts, including environment. Statistical tests for identifying such interactions are important to understand how individual genetic variants may act in different contexts. Interaction effects can either be studied using measurements of a given phenotype in different contexts, under the same genetic backgrounds, or by stratifying a population into subgroups. Here, we derive a method based on linear mixed models that can be applied to both of these designs. iSet enables testing for interactions between context and sets of variants, and accounts for polygenic effects. We validate our model using simulations, before applying it to the genetic analysis of gene expression studies and genome-wide association studies of human blood lipid levels. We find that modeling interactions with variant sets offers increased power, thereby uncovering interactions that cannot be detected by alternative methods.
]]></description>
<dc:creator>Casale, F. P.</dc:creator>
<dc:creator>Horta, D.</dc:creator>
<dc:creator>Rakitsch, B.</dc:creator>
<dc:creator>Stegle, O.</dc:creator>
<dc:date>2016-12-31</dc:date>
<dc:identifier>doi:10.1101/097477</dc:identifier>
<dc:title><![CDATA[Joint genetic analysis using variant sets reveals polygenic gene-context interactions]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-12-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/077057v1?rss=1">
<title>
<![CDATA[
Global changes in patterning, splicing and primate specific lncRNAs in autism brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/077057v1?rss=1"
</link>
<description><![CDATA[
We apply transcriptome-wide RNA sequencing in postmortem autism spectrum disorder (ASD) brain and controls and identify convergent alterations in the noncoding transcriptome, including primate specific lncRNA, and transcript splicing in ASD cerebral cortex, but not cerebellum. We characterize an attenuation of patterning between frontal and temporal cortex in ASD and identify SOX5, a transcription factor involved in cortical neuron fate specification, as a likely driver of this pattern. We further show that a genetically defined subtype of ASD, Duplication 15q Syndrome, shares the core transcriptomic signature of idiopathic ASD, indicating that observed molecular convergence in autism brain is the likely consequence of manifold genetic alterations. Using co-expression network analysis, we show that diverse forms of genetic risk for ASD affect convergent, independently replicated, biological pathways and provide an unprecedented resource for understanding the molecular alterations associated with ASD in humans.
]]></description>
<dc:creator>Neelroop N Parikshak</dc:creator>
<dc:creator>Vivek Swarup</dc:creator>
<dc:creator>T Grant Belgard</dc:creator>
<dc:creator>Michael J Gandal</dc:creator>
<dc:creator>Manuel Irimia</dc:creator>
<dc:creator>Virpi Leppa</dc:creator>
<dc:creator>Jennifer K Lowe</dc:creator>
<dc:creator>Robert Johnson</dc:creator>
<dc:creator>Benjamin J. Blencowe</dc:creator>
<dc:creator>Steve Horvath</dc:creator>
<dc:creator>Daniel H. Geschwind</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-09-23</dc:date>
<dc:identifier>doi:10.1101/077057</dc:identifier>
<dc:title><![CDATA[Global changes in patterning, splicing and primate specific lncRNAs in autism brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-09-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/022061v1?rss=1">
<title>
<![CDATA[
Structure and evolutionary history of a large family of NLR proteins in the zebrafish 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/022061v1?rss=1"
</link>
<description><![CDATA[
NACHT- and Leucine-Rich-Repeat-containing domain (NLR) proteins act as cytoplasmic sensors for pathogen- and danger-associated molecular patterns and are found throughout the plant and animal kingdoms. In addition to having a small set of conserved NLRs, the genomes in some animal lineages contain massive expansions of this gene family. One of these arose in fishes, after the creation of a gene fusion that combined the core NLR domains with another domain used for immune recognition, the PRY/SPRY or B30.2 domain. We have analysed the expanded NLR gene family in zebrafish, which contains 368 genes, and studied its evolutionary history. The encoded proteins share a defining overall structure, but individual domains show different evolutionary trajectories. Our results suggest gene conversion homogenizes NACHT and B30.2 domain sequences among different gene subfamilies, however, the functional implications of its action remains unclear. The majority of the genes are located on the long arm of chromosome 4, interspersed with several other large multi-gene families, including a new family encoding proteins with multiple tandem arrays of Zinc fingers. This suggests that chromosome 4 may be a hotspot for rapid evolutionary change in zebrafish.
]]></description>
<dc:creator>Kerstin Howe</dc:creator>
<dc:creator>Philipp H Schiffer</dc:creator>
<dc:creator>Julia Zielinski</dc:creator>
<dc:creator>Thomas Wiehe</dc:creator>
<dc:creator>Gavin K Laird</dc:creator>
<dc:creator>John Marioni</dc:creator>
<dc:creator>Onuralp Soylemez</dc:creator>
<dc:creator>Fyodor Kondrashov</dc:creator>
<dc:creator>Maria Leptin</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-07-07</dc:date>
<dc:identifier>doi:10.1101/022061</dc:identifier>
<dc:title><![CDATA[Structure and evolutionary history of a large family of NLR proteins in the zebrafish]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-07-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/129478v1?rss=1">
<title>
<![CDATA[
Transcription factor activities enhance markers of drug response in cancer 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/129478v1?rss=1"
</link>
<description><![CDATA[
Transcriptional dysregulation is a key feature of cancer. Transcription factors (TFs) are the main link between signalling pathways and the transcriptional regulatory machinery of the cell, positioning them as key oncogenic inductors and therefore potential targets of therapeutic intervention. We implemented a computational pipeline to infer TF regulatory activities from basal gene expression and applied it to publicly available and newly generated RNA-seq data from a collection of 1,010 cancer cell lines and 9,250 primary tumors. We show that the predicted TF activities recapitulate known mechanisms of transcriptional dysregulation in cancer and dissect mutant-specific effects in driver genes. Importantly, we show the potential for predicted TF activities to be used as markers of sensitivity to the inhibition of their upstream regulators. Furthermore, combining these inferred activities with existing pharmacogenomic markers significantly improves the stratification of sensitive and resistant cell lines for several compounds. Our approach provides a framework to link driver genomic alterations with transcriptional dysregulation that helps to predict drug sensitivity in cancer and to dissect its mechanistic determinants.
]]></description>
<dc:creator>Garcia-Alonso, L.</dc:creator>
<dc:creator>Iorio, F.</dc:creator>
<dc:creator>Matchan, A.</dc:creator>
<dc:creator>Fonseca, N.</dc:creator>
<dc:creator>Jaaks, P.</dc:creator>
<dc:creator>Falcone, F.</dc:creator>
<dc:creator>Bignell, G.</dc:creator>
<dc:creator>McDade, S. S.</dc:creator>
<dc:creator>Garnett, M. J.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:date>2017-04-21</dc:date>
<dc:identifier>doi:10.1101/129478</dc:identifier>
<dc:title><![CDATA[Transcription factor activities enhance markers of drug response in cancer]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/033167v1?rss=1">
<title>
<![CDATA[
Meiotic interactors of a mitotic gene TAO3 revealed by functional analysis of its rare variant 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/033167v1?rss=1"
</link>
<description><![CDATA[
Studying the molecular consequences of rare genetic variants has the potential of identifying novel and hereto uncharacterized pathways causally contributing to phenotypic variation. Here we characterize the functional consequences of a rare coding variant of TAO3, previously reported to significantly contribute to sporulation efficiency variation in Saccharomyces cerevisiae. During mitosis TAO3 interacts with CBK1, a conserved NDR kinase and a component of RAM network. The RAM network genes are involved in regulation cell separation and polarization. We demonstrate that the role of the rare allele TAO3(4477C) in meiosis is distinct from its role in mitosis by being independent of ACE2, which is a RAM network target gene. By quantitatively measuring cell morphological dynamics and conditionally expressing TAO3(4477C) allele during sporulation, we show that TAO3 has an early role in meiosis. This early role of TAO3 coincides with entry of cells into meiotic division. Time-resolved transcriptome analyses during early sporulation phase identified regulators of carbon and lipid metabolic pathways as candidate mediators. We experimentally show that during sporulation the TAO3 allele genetically interacts with ERT1 and PIP2, the regulators of tricarboxylic acid cycle and gluconeogenic enzymes, respectively. We thus uncover meiotic functions of TAO3, a mitotic gene and propose ERT1 and PIP2 as novel regulators of sporulation efficiency. Our results demonstrate that study of causal effects of genetic variation on the underlying molecular network has the potential to provide more extensive comprehension of the pathways driving a complex trait. This can help identify prospective personalized targets for intervention in complex diseases.
]]></description>
<dc:creator>Saumya Gupta</dc:creator>
<dc:creator>Aparna Radhakrishnan</dc:creator>
<dc:creator>Rachana Nitin</dc:creator>
<dc:creator>Pandu Raharja-Liu</dc:creator>
<dc:creator>Gen Lin</dc:creator>
<dc:creator>Lars M Steinmetz</dc:creator>
<dc:creator>Julien Gagneur</dc:creator>
<dc:creator>Himanshu Sinha</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-11-27</dc:date>
<dc:identifier>doi:10.1101/033167</dc:identifier>
<dc:title><![CDATA[Meiotic interactors of a mitotic gene TAO3 revealed by functional analysis of its rare variant]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-11-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/065672v1?rss=1">
<title>
<![CDATA[
Perturbation-response genes reveal signaling footprints in cancer gene expression 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/065672v1?rss=1"
</link>
<description><![CDATA[
Aberrant cell signaling is known to cause cancer and many other diseases, as well as a focus of treatment. A common approach is to infer its activity on the level of pathways using gene expression. However, mapping gene expression to pathway components disregards the effect of post-translational modifications, and downstream signatures represent very specific experimental conditions. Here we present PROGENy, a method that overcomes both limitations by leveraging a large compendium of publicly available perturbation experiments to yield a common core of Pathway RespOnsive GENes. Unlike existing methods, PROGENy can (i) recover the effect of known driver mutations, (ii) provide or improve strong markers for drug indications, and (iii) distinguish between oncogenic and tumor suppressor pathways for patient survival. Collectively, these results show that PROGENy more accurately infers pathway activity from gene expression than other methods.
]]></description>
<dc:creator>Michael Schubert</dc:creator>
<dc:creator>Bertram Klinger</dc:creator>
<dc:creator>Martina Klünemann</dc:creator>
<dc:creator>Mathew J Garnett</dc:creator>
<dc:creator>Nils Blüthgen</dc:creator>
<dc:creator>Julio Saez-Rodriguez</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-07-25</dc:date>
<dc:identifier>doi:10.1101/065672</dc:identifier>
<dc:title><![CDATA[Perturbation-response genes reveal signaling footprints in cancer gene expression]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-07-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/146811v1?rss=1">
<title>
<![CDATA[
An integrated genomic analysis of anaplastic meningioma identifies prognostic molecular signatures 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/146811v1?rss=1"
</link>
<description><![CDATA[
Anaplastic meningioma is a rare and aggressive brain tumor characterised by intractable recurrences and dismal outcomes. Here, we present an integrated analysis of the whole genome, transcriptome and methylation profiles of primary and recurrent anaplastic meningioma. A key finding was the delineation of two distinct molecular subgroups that were associated with diametrically opposed survival outcomes. Relative to lower grade meningiomas, anaplastic tumors harbored frequent driver mutations in SWI/SNF complex genes, which were confined to the poor prognosis subgroup. Our analyses discern two biologically distinct variants of anaplastic meningioma with potential prognostic and therapeutic significance.
]]></description>
<dc:creator>Collord, G.</dc:creator>
<dc:creator>Tarpey, P.</dc:creator>
<dc:creator>Kurbatova, N.</dc:creator>
<dc:creator>Martincorena, I.</dc:creator>
<dc:creator>Moran, S.</dc:creator>
<dc:creator>Castro, M.</dc:creator>
<dc:creator>Nagy, T.</dc:creator>
<dc:creator>Bignell, G.</dc:creator>
<dc:creator>Maura, F.</dc:creator>
<dc:creator>Berna, J.</dc:creator>
<dc:creator>Tubio, J. M.</dc:creator>
<dc:creator>McMurran, C. E.</dc:creator>
<dc:creator>Young, A. M. H.</dc:creator>
<dc:creator>Young, M. D.</dc:creator>
<dc:creator>Noorani, I.</dc:creator>
<dc:creator>Price, S. J.</dc:creator>
<dc:creator>Watts, C.</dc:creator>
<dc:creator>Leipnitz, E.</dc:creator>
<dc:creator>Kirsch, M.</dc:creator>
<dc:creator>Schackert, G.</dc:creator>
<dc:creator>Pearson, D.</dc:creator>
<dc:creator>Devadass, A.</dc:creator>
<dc:creator>Ram, Z.</dc:creator>
<dc:creator>Collins, V. P.</dc:creator>
<dc:creator>Allinson, K.</dc:creator>
<dc:creator>Jenkinson, M.</dc:creator>
<dc:creator>Zakaria, R.</dc:creator>
<dc:creator>Syed, K.</dc:creator>
<dc:creator>Hanemann, C. O.</dc:creator>
<dc:creator>Dunn, J.</dc:creator>
<dc:creator>McDermott, M.</dc:creator>
<dc:creator>Kirollos, R.</dc:creator>
<dc:creator>Vassiliou, G. S.</dc:creator>
<dc:creator>Esteller, M.</dc:creator>
<dc:creator>Behjati, S.</dc:creator>
<dc:creator>Brazma, A.</dc:creator>
<dc:creator>Santarius, T.</dc:creator>
<dc:creator>McDermott, U.</dc:creator>
<dc:date>2017-06-06</dc:date>
<dc:identifier>doi:10.1101/146811</dc:identifier>
<dc:title><![CDATA[An integrated genomic analysis of anaplastic meningioma identifies prognostic molecular signatures]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/037721v1?rss=1">
<title>
<![CDATA[
The wiring diagram of a glomerular olfactory system 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/037721v1?rss=1"
</link>
<description><![CDATA[
The sense of smell enables animals to react to long-distance cues according to learned and innate valences. Here, we have mapped with electron microscopy the complete wiring diagram of the Drosophila larval antennal lobe, an olfactory neuropil similar to the vertebrate olfactory bulb. We found a canonical circuit with uniglomerular projection neurons (uPNs) relaying gain-controlled ORN activity to the mushroom body and the lateral horn. A second, parallel circuit with multiglomerular projection neurons (mPNs) and hierarchically connected local neurons (LNs) selectively integrates multiple ORN signals already at the first synapse. LN-LN synaptic connections putatively implement a bistable gain control mechanism that either computes odor saliency through panglomerular inhibition, or allows some glomeruli to respond to faint aversive odors in the presence of strong appetitive odors. This complete wiring diagram will support experimental and theoretical studies towards bridging the gap between circuits and behavior.
]]></description>
<dc:creator>Matthew E. Berck</dc:creator>
<dc:creator>Avinash Khandelwal</dc:creator>
<dc:creator>Lindsey Claus</dc:creator>
<dc:creator>Luis Hernandez-Nunez</dc:creator>
<dc:creator>Guangwei Si</dc:creator>
<dc:creator>Christopher J. Tabone</dc:creator>
<dc:creator>Feng Li</dc:creator>
<dc:creator>James W. Truman</dc:creator>
<dc:creator>Richard D. Fetter</dc:creator>
<dc:creator>Matthieu Louis</dc:creator>
<dc:creator>Aravinthan D. T. Samuel</dc:creator>
<dc:creator>Albert Cardona</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-01-22</dc:date>
<dc:identifier>doi:10.1101/037721</dc:identifier>
<dc:title><![CDATA[The wiring diagram of a glomerular olfactory system]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-01-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/040733v1?rss=1">
<title>
<![CDATA[
Bayesian analysis of normal mouse cell lineage trees allowing intra-individual, cell population specific mutation rates 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/040733v1?rss=1"
</link>
<description><![CDATA[
Individual cell lineage trees are of biological and clinical importance. The Sanger Mouse Pilot Study used clonal organoid lines of endodermal origin to extract somatic base substitutions from single cells of two healthy mice. Here we applied Bayesian phylogenetics analysis using the Pilots 35 somatic base substitutions in order to reconstruct the two cell trees and apply relaxed clock methods allowing intra-individual, cell lineage specific mutation rates. Detailed analysis provided support for the strict clock for mouse_1 and relaxed clock for mouse_2. Interestingly, a clade of two prostate organoid lines in mouse_2 presented one outlier branch mutation rate compared to the mean rates calculated. Based on this study unbiased clock analysis has the potential to add a new, useful layer to our understanding of normal and disturbed cell lineage trees. This study is the first to apply the popular Bayesian BEAST package to individual single cell resolution data.
]]></description>
<dc:creator>Attila Csordas</dc:creator>
<dc:creator>Remco Bouckaert</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-02-22</dc:date>
<dc:identifier>doi:10.1101/040733</dc:identifier>
<dc:title><![CDATA[Bayesian analysis of normal mouse cell lineage trees allowing intra-individual, cell population specific mutation rates]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-02-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/051052v1?rss=1">
<title>
<![CDATA[
Genomic positional conservation identifies topological anchor point (tap)RNAs linked to developmental loci 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/051052v1?rss=1"
</link>
<description><![CDATA[
The mammalian genome is transcribed into large numbers of long noncoding RNAs (lncRNAs), but the definition of functional lncRNA groups has proven difficult, partly due to their low sequence conservation and lack of identified shared properties. Here we consider positional conservation across mammalian genomes as an indicator of functional commonality. We identify 665 conserved lncRNA promoters in mouse and human genomes that are preserved in genomic position relative to orthologous coding genes. The identified  positionally conserved lncRNA genes are primarily associated with developmental transcription factor loci with which they are co-expressed in a tissue-specific manner. Strikingly, over half of all positionally conserved RNAs in this set are linked to distinct chromatin organization structures, overlapping the binding sites for the CTCF chromatin organizer and located at chromatin loop anchor points and borders of topologically associating domains (TADs). These topological anchor point (tap)RNAs possess conserved sequence domains that are enriched in potential recognition motifs for Zinc Finger proteins. Characterization of these noncoding RNAs and their associated coding genes shows that they are functionally connected: they regulate each others expression and influence the metastatic phenotype of cancer cells in vitro in a similar fashion. Thus, interrogation of positionally conserved lncRNAs identifies a new subset of tapRNAs with shared functional properties. These results provide a large dataset of lncRNAs that conform to the "extended gene" model, in which conserved developmental genes are genomically and functionally linked to regulatory lncRNA loci across mammalian evolution.
]]></description>
<dc:creator>Paulo P Amaral</dc:creator>
<dc:creator>Tommaso Leonardi</dc:creator>
<dc:creator>Namshik Han</dc:creator>
<dc:creator>Emmanuelle Vire</dc:creator>
<dc:creator>Dennis K Gascoigne</dc:creator>
<dc:creator>Raul Arias-Carrasco</dc:creator>
<dc:creator>Magdalena Buscher</dc:creator>
<dc:creator>Anda Zhang</dc:creator>
<dc:creator>Stefano Pluchino</dc:creator>
<dc:creator>Vinicius Maracaja-Coutinho</dc:creator>
<dc:creator>Helder I Nakaya</dc:creator>
<dc:creator>Martin Hemberg</dc:creator>
<dc:creator>Ramin Shiekhattar</dc:creator>
<dc:creator>Anton J Enright</dc:creator>
<dc:creator>Tony Kouzarides</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-04-29</dc:date>
<dc:identifier>doi:10.1101/051052</dc:identifier>
<dc:title><![CDATA[Genomic positional conservation identifies topological anchor point (tap)RNAs linked to developmental loci]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-04-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/068064v1?rss=1">
<title>
<![CDATA[
Dynamic Maternal Gradients Control Timing and Shift-Rates for Gap Gene Expression 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/068064v1?rss=1"
</link>
<description><![CDATA[
Pattern formation during development is a highly dynamic process. In spite of this, few experimental and modelling approaches take into account the explicit time-dependence of the rules governing regulatory systems. We address this problem by studying dynamic morphogen interpretation by the gap gene network in Drosophila melanogaster. Gap genes are involved in segment determination during early embryogenesis. They are activated by maternal morphogen gradients encoded by bicoid (bcd) and caudal (cad). These gradients decay at the same time-scale as the establishment of the antero-posterior gap gene pattern. We use a reverse-engineering approach, based on data-driven regulatory models called gene circuits, to isolate and characterise the explicitly time-dependent effects of changing morphogen concentrations on gap gene regulation. To achieve this, we simulate the system in the presence and absence of dynamic gradient decay. Comparison between these simulations reveals that maternal morphogen decay controls the timing and limits the rate of gap gene expression. In the anterior of the embyro, it affects peak expression and leads to the establishment of smooth spatial boundaries between gap domains. In the posterior of the embryo, it causes a progressive slow-down in the rate of gap domain shifts, which is necessary to correctly position domain boundaries and to stabilise the spatial gap gene expression pattern. We use a newly developed method for the analysis of transient dynamics in non-autonomous (time-variable) systems to understand the regulatory causes of these effects. By providing a rigorous mechanistic explanation for the role of maternal gradient decay in gap gene regulation, our study demonstrates that such analyses are feasible and reveal important aspects of dynamic gene regulation which would have been missed by a traditional steady-state approach. More generally, it highlights the importance of transient dynamics for understanding complex regulatory processes in development.nnAuthor SummaryAnimal development is a highly dynamic process. Biochemical or environmental signals can cause the rules that shape it to change over time. We know little about the effects of such changes. For the sake of simplicity, we usually leave them out of our models and experimental assays. Here, we do exactly the opposite. We characterise precisely those aspects of pattern formation caused by changing signalling inputs to a gene regulatory network, the gap gene system of Drosophila melanogaster. Gap genes are involved in determining the body segments of flies and other insects during early development. Gradients of maternal morphogens activate the expression of the gap genes. These gradients are highly dynamic themselves, as they decay while being read out. We show that this decay controls the peak concentration of gap gene products, produces smooth boundaries of gene expression, and slows down the observed positional shifts of gap domains in the posterior of the embryo, thereby stabilising the spatial pattern. Our analysis demonstrates that the dynamics of gene regulation not only affect the timing, but also the positioning of gene expression. This suggests that we must pay closer attention to transient dynamic aspects of development than is currently the case.
]]></description>
<dc:creator>Berta Verd</dc:creator>
<dc:creator>Anton Crombach</dc:creator>
<dc:creator>Johannes Jaeger</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-08-05</dc:date>
<dc:identifier>doi:10.1101/068064</dc:identifier>
<dc:title><![CDATA[Dynamic Maternal Gradients Control Timing and Shift-Rates for Gap Gene Expression]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-08-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/162982v1?rss=1">
<title>
<![CDATA[
A comprehensive map of genetic variation in the world’s largest ethnic group - Han Chinese 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/162982v1?rss=1"
</link>
<description><![CDATA[
As are most non-European populations around the globe, the Han Chinese are relatively understudied in population and medical genetics studies. From low-coverage whole-genome sequencing of 11,670 Han Chinese women we present a catalog of 25,057,223 variants, including 548,401 novel variants that are seen at least 10 times in our dataset. Individuals from our study come from 19 out of 22 provinces across China, allowing us to study population structure, genetic ancestry, and local adaptation in Han Chinese. We identify previously unrecognized population structure along the East-West axis of China and report unique signals of admixture across geographical space, such as European influences among the Northwestern provinces of China. Finally, we identified a number of highly differentiated loci, indicative of local adaptation in the Han Chinese. In particular, we detected extreme differentiation among the Han Chinese at MTHFR, ADH7, and FADS loci, suggesting that these loci may not be specifically selected in Tibetan and Inuit populations as previously suggested. On the other hand, we find that Neandertal ancestry does not vary significantly across the provinces, consistent with admixture prior to the dispersal of modern Han Chinese. Furthermore, contrary to a previous report, Neandertal ancestry does not explain a significant amount of heritability in depression. Our findings provide the largest genetic data set so far made available for Han Chinese and provide insights into the history and population structure of the worlds largest ethnic group.
]]></description>
<dc:creator>Chiang, C. W. K.</dc:creator>
<dc:creator>Mangul, S.</dc:creator>
<dc:creator>Robles, C. R.</dc:creator>
<dc:creator>Kretzschmar, W. W.</dc:creator>
<dc:creator>Cai, N.</dc:creator>
<dc:creator>Kendler, K. S.</dc:creator>
<dc:creator>Sankararam, S.</dc:creator>
<dc:creator>Flint, J.</dc:creator>
<dc:date>2017-07-13</dc:date>
<dc:identifier>doi:10.1101/162982</dc:identifier>
<dc:title><![CDATA[A comprehensive map of genetic variation in the world’s largest ethnic group - Han Chinese]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/028142v1?rss=1">
<title>
<![CDATA[
Characterising Complex Enzyme Reaction Data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/028142v1?rss=1"
</link>
<description><![CDATA[
The relationship between enzyme-catalysed reactions and the Enzyme Commission (EC) number, the widely accepted classification scheme used to characterise enzyme activity, is complex and with the rapid increase in our knowledge of the reactions catalysed by enzymes needs revisiting. We present a manual and computational analysis to investigate this complexity and found that almost one-third of all known EC numbers are linked to more than one reaction in the secondary reaction databases (e.g. KEGG). Although this complexity is often resolved by defining generic, alternative and partial reactions, we have also found individual EC numbers with more than one reaction catalysing different types of bond changes. This analysis adds a new dimension to our understanding of enzyme function and might be useful for the accurate annotation of the function of enzymes and to study the changes in enzyme function during evolution.
]]></description>
<dc:creator>Handan Melike Dönertaş</dc:creator>
<dc:creator>Sergio Martínez Cuesta</dc:creator>
<dc:creator>Syed Asad Rahman</dc:creator>
<dc:creator>Janet M. Thornton</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-10-03</dc:date>
<dc:identifier>doi:10.1101/028142</dc:identifier>
<dc:title><![CDATA[Characterising Complex Enzyme Reaction Data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-10-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/055731v1?rss=1">
<title>
<![CDATA[
Principles for RNA metabolism and alternative transcription initiation within closely spaced promoters 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/055731v1?rss=1"
</link>
<description><![CDATA[
Mammalian transcriptomes are complex and formed by extensive promoter activity. In addition, gene promoters are largely divergent and initiate transcription of reverse-oriented promoter upstream transcripts (PROMPTs). Although PROMPTs are commonly terminated early, influenced by polyadenylation sites, promoters often cluster so that the divergent activity of one might impact another. Here, we find that the distance between promoters strongly correlates with the expression, stability and length of their associated PROMPTs. Adjacent promoters driving divergent mRNA transcription support PROMPT formation, but due to polyadenylation site constraints, these transcripts tend to spread into the neighboring mRNA on the same strand. This mechanism to derive new alternative mRNA transcription start sites (TSSs) is also evident at closely spaced promoters supporting convergent mRNA transcription. We suggest that basic building blocks of divergently transcribed core promoter pairs, in combination with the wealth of TSSs in mammalian genomes, provides a framework with which evolution shapes transcriptomes.
]]></description>
<dc:creator>Yun Chen</dc:creator>
<dc:creator>Athma A Pai</dc:creator>
<dc:creator>Jan Herudek</dc:creator>
<dc:creator>Michal Lubas</dc:creator>
<dc:creator>Nicola Meola</dc:creator>
<dc:creator>Aino I Jarvelin</dc:creator>
<dc:creator>Robin Andersson</dc:creator>
<dc:creator>Vicent Pelechano</dc:creator>
<dc:creator>Lars M Steinmetz</dc:creator>
<dc:creator>Torben Heick Jensen</dc:creator>
<dc:creator>Albin Sandelin</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-05-27</dc:date>
<dc:identifier>doi:10.1101/055731</dc:identifier>
<dc:title><![CDATA[Principles for RNA metabolism and alternative transcription initiation within closely spaced promoters]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-05-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/155325v1?rss=1">
<title>
<![CDATA[
PARP mediated chromatin unfolding is coupled to long-range enhancer activation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/155325v1?rss=1"
</link>
<description><![CDATA[
Enhancers are critical regulators of gene expression and can be located far from their target gene. It is widely assumed that mechanisms of enhancer action involve reorganization of three-dimensional chromatin architecture, but this is poorly understood. Here we identify a novel mechanism of long-range enhancer associated chromatin reorganization. At the Sonic hedgehog (Shh) locus we observe large-scale decompaction of chromatin between Shh and its brain enhancers in neural progenitor cells. We show that the chromatin unfolding is dependent on activation of the enhancers, not the promoter, is impeded by chromatin-bound proteins located between the enhancer and promoter, and is mediated by the recruitment of Poly (ADP-Ribose) Polymerase 1. We suggest that large-scale chromatin decompaction, analogous to the inducible puffs in Drosophila polytene chromosomes, represents a new mechanism of chromatin reorganization coupled to long-range gene activation from mammalian enhancers and that seems incompatible with a chromatin-looping model of enhancer-promoter communication
]]></description>
<dc:creator>Benabdallah, N. S.</dc:creator>
<dc:creator>Williamson, I.</dc:creator>
<dc:creator>Illingworth, R. S.</dc:creator>
<dc:creator>Boyle, S.</dc:creator>
<dc:creator>Grimes, G. R.</dc:creator>
<dc:creator>Therizols, P.</dc:creator>
<dc:creator>Bickmore, W.</dc:creator>
<dc:date>2017-06-25</dc:date>
<dc:identifier>doi:10.1101/155325</dc:identifier>
<dc:title><![CDATA[PARP mediated chromatin unfolding is coupled to long-range enhancer activation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/187609v1?rss=1">
<title>
<![CDATA[
Selective and mechanistic sources of recurrent rearrangements across the cancer genome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/187609v1?rss=1"
</link>
<description><![CDATA[
Cancer cells can acquire profound alterations to the structure of their genomes, including rearrangements that fuse distant DNA breakpoints. We analyze the distribution of somatic rearrangements across the cancer genome, using whole-genome sequencing data from 2,693 tumor-normal pairs. We observe substantial variation in the density of rearrangement breakpoints, with enrichment in open chromatin and sites with high densities of repetitive elements. After accounting for these patterns, we identify significantly recurrent breakpoints (SRBs) at 52 loci, including novel SRBs near BRD4 and AKR1C3. Taking into account both loci fused by a rearrangement, we observe different signatures resembling either single breaks followed by strand invasion or two separate breaks that become joined. Accounting for these signatures, we identify 90 pairs of loci that are significantly recurrently juxtaposed (SRJs). SRJs are primarily tumor-type specific and tend to involve genes with tissue-specific expression. SRJs were frequently associated with disruption of topology-associated domains, juxtaposition of enhancer elements, and increased expression of neighboring genes. Lastly, we find that the power to detect SRJs decreases for short rearrangements, and that reliable detection of all driver SRJs will require whole-genome sequencing data from an order of magnitude more cancer samples than currently available.
]]></description>
<dc:creator>Wala, J. A.</dc:creator>
<dc:creator>Shapira, O.</dc:creator>
<dc:creator>Li, Y.</dc:creator>
<dc:creator>Craft, D.</dc:creator>
<dc:creator>Schumacher, S. E.</dc:creator>
<dc:creator>Imielinski, M.</dc:creator>
<dc:creator>Haber, J. E.</dc:creator>
<dc:creator>Roberts, N.</dc:creator>
<dc:creator>Yao, X.</dc:creator>
<dc:creator>Stewart, C.</dc:creator>
<dc:creator>Zhang, C.-Z.</dc:creator>
<dc:creator>Tubio, J.</dc:creator>
<dc:creator>Ju, Y. S.</dc:creator>
<dc:creator>Campbell, P.</dc:creator>
<dc:creator>Weischenfeldt, J.</dc:creator>
<dc:creator>Beroukhim, R.</dc:creator>
<dc:creator>PCAWG-Structural Variation Working Group,</dc:creator>
<dc:creator>the PCAWG Network,</dc:creator>
<dc:date>2017-09-14</dc:date>
<dc:identifier>doi:10.1101/187609</dc:identifier>
<dc:title><![CDATA[Selective and mechanistic sources of recurrent rearrangements across the cancer genome]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/183889v1?rss=1">
<title>
<![CDATA[
Pan-cancer study of heterogeneous RNA aberrations 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/183889v1?rss=1"
</link>
<description><![CDATA[
We present the most comprehensive catalogue of cancer-associated gene alterations through characterization of tumor transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes project. Using matched whole-genome sequencing data, we attributed RNA alterations to germline and somatic DNA alterations, revealing likely genetic mechanisms. We identified 444 associations of gene expression with somatic non-coding single-nucleotide variants. We found 1,872 splicing alterations associated with somatic mutation in intronic regions, including novel exonization events associated with Alu elements. Somatic copy number alterations were the major driver of total gene and allele-specific expression (ASE) variation. Additionally, 82% of gene fusions had structural variant support, including 75 of a novel class called "bridged" fusions, in which a third genomic location bridged two different genes. Globally, we observe transcriptomic alteration signatures that differ between cancer types and have associations with DNA mutational signatures. Given this unique dataset of RNA alterations, we also identified 1,012 genes significantly altered through both DNA and RNA mechanisms. Our study represents an extensive catalog of RNA alterations and reveals new insights into the heterogeneous molecular mechanisms of cancer gene alterations.
]]></description>
<dc:creator>Fonseca, N. A.</dc:creator>
<dc:creator>Kahles, A.</dc:creator>
<dc:creator>Lehmann, K.-V.</dc:creator>
<dc:creator>Calabrese, C.</dc:creator>
<dc:creator>Chateigner, A.</dc:creator>
<dc:creator>Davidson, N. R.</dc:creator>
<dc:creator>Demircioglu, D.</dc:creator>
<dc:creator>He, Y.</dc:creator>
<dc:creator>Lamaze, F. C.</dc:creator>
<dc:creator>Li, S.</dc:creator>
<dc:creator>Liu, D.</dc:creator>
<dc:creator>Liu, F.</dc:creator>
<dc:creator>Perry, M. D.</dc:creator>
<dc:creator>Su, H.</dc:creator>
<dc:creator>Xiang, L.</dc:creator>
<dc:creator>Zhang, J.</dc:creator>
<dc:creator>Amin, S. B.</dc:creator>
<dc:creator>Bailey, P.</dc:creator>
<dc:creator>Craft, B.</dc:creator>
<dc:creator>Frenkel-Morgenstern, M.</dc:creator>
<dc:creator>Goldman, M.</dc:creator>
<dc:creator>Greger, L.</dc:creator>
<dc:creator>Hoadley, K. A.</dc:creator>
<dc:creator>Hou, Y.</dc:creator>
<dc:creator>Khurana, E.</dc:creator>
<dc:creator>Korbel, J. O.</dc:creator>
<dc:creator>Li, C.</dc:creator>
<dc:creator>Li, X.</dc:creator>
<dc:creator>Li, X.</dc:creator>
<dc:creator>Liu, X.</dc:creator>
<dc:creator>Lu, Y.</dc:creator>
<dc:creator>Marin, M. G.</dc:creator>
<dc:creator>Meyerson, M.</dc:creator>
<dc:creator>Nandi, T.</dc:creator>
<dc:creator>Nielsen, M. M.</dc:creator>
<dc:creator>Ojesina, A. I.</dc:creator>
<dc:creator>Ouellette, B. F. F.</dc:creator>
<dc:creator>Pan-Hammarström, Q.</dc:creator>
<dc:creator>Pedamallu, C. S.</dc:creator>
<dc:creator>Pedersen, J. S.</dc:creator>
<dc:creator>Shiraishi, Y.</dc:creator>
<dc:creator>Siebert, R.</dc:creator>
<dc:creator>Soulette, C. M.</dc:creator>
<dc:creator>Stark, S. G.</dc:creator>
<dc:creator>Tan</dc:creator>
<dc:date>2017-09-03</dc:date>
<dc:identifier>doi:10.1101/183889</dc:identifier>
<dc:title><![CDATA[Pan-cancer study of heterogeneous RNA aberrations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/055715v1?rss=1">
<title>
<![CDATA[
Accurate prediction of single-cell DNA methylation states using deep learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/055715v1?rss=1"
</link>
<description><![CDATA[
Recent technological advances have enabled assaying DNA methylation at single-cell resolution. Current protocols are limited by incomplete CpG coverage and hence methods to predict missing methylation states are critical to enable genome-wide analyses. Here, we report DeepCpG, a computational approach based on deep neural networks to predict DNA methylation states from DNA sequence and incomplete methylation profiles in single cells. We evaluated DeepCpG on single-cell methylation data from five cell types generated using alternative sequencing protocols, finding that DeepCpG yields substantially more accurate predictions than previous methods. Additionally, we show that the parameters of our model can be interpreted, thereby providing insights into the effect of sequence composition on methylation variability.
]]></description>
<dc:creator>Christof Angermueller</dc:creator>
<dc:creator>Heather Lee</dc:creator>
<dc:creator>Wolf Reik</dc:creator>
<dc:creator>Oliver Stegle</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-05-27</dc:date>
<dc:identifier>doi:10.1101/055715</dc:identifier>
<dc:title><![CDATA[Accurate prediction of single-cell DNA methylation states using deep learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-05-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/168948v1?rss=1">
<title>
<![CDATA[
A compartmentalized, self-extinguishing signaling network mediates crossover control in meiosis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/168948v1?rss=1"
</link>
<description><![CDATA[
Meiotic recombination between homologous chromosomes is tightly regulated to ensure proper chromosome segregation. Each chromosome pair typically undergoes at least one crossover event (crossover assurance) but these exchanges are also strictly limited in number and widely spaced along chromosomes (crossover interference). This has implied the existence of chromosome-wide signals that regulate crossovers, but their molecular basis remains mysterious. Here we characterize a family of four related RING finger proteins in C. elegans. These proteins are recruited to the synaptonemal complex between paired homologs, where they act as two heterodimeric complexes, likely as E3 ubiquitin ligases. Genetic and cytological analysis reveals that they act with additional components to create a self-extinguishing circuit that controls crossover designation and maturation. These proteins also act at the top of a hierarchical chromosome remodeling process that enables crossovers to direct stepwise segregation. Work in diverse phyla indicates that related mechanisms mediate crossover control across eukaryotes.
]]></description>
<dc:creator>Zhang, L.</dc:creator>
<dc:creator>Koehler, S.</dc:creator>
<dc:creator>Rillo-Bohn, R.</dc:creator>
<dc:creator>Dernburg, A. F.</dc:creator>
<dc:date>2017-07-26</dc:date>
<dc:identifier>doi:10.1101/168948</dc:identifier>
<dc:title><![CDATA[A compartmentalized, self-extinguishing signaling network mediates crossover control in meiosis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/008821v1?rss=1">
<title>
<![CDATA[
Epigenomic co-localization and co-evolution reveal a key role for 5hmC as a communication hub in the chromatin network of ESCs 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/008821v1?rss=1"
</link>
<description><![CDATA[
Epigenetic communication through histone and cytosine modifications is essential for gene regulation and cell identity. Here, we propose a framework that is based on a chromatin communication model to get insight on the function of epigenetic modifications in ESCs. The epigenetic communication network was inferred from genome-wide location data plus extensive manual annotation. Notably, we found that 5-hydroxymethylcytosine (5hmC) is the most influential hub of this network, connecting DNA demethylation to nucleosome remodeling complexes and to key transcription factors of pluripotency. Moreover, an evolutionary analysis revealed a central role of 5hmC in the co-evolution of chromatin-related proteins. Further analysis of regions where 5hmC colocalizes with specific interactors shows that each interaction points to chromatin remodelling, stemness, differentiation or metabolism. Our results highlight the importance of cytosine modifications in the epigenetic communication of ESCs.
]]></description>
<dc:creator>David Juan</dc:creator>
<dc:creator>Juliane Perner</dc:creator>
<dc:creator>Enrique Carrillo de Santa Pau</dc:creator>
<dc:creator>Simone Marsili</dc:creator>
<dc:creator>David Ochoa</dc:creator>
<dc:creator>Ho-Ryun Chung</dc:creator>
<dc:creator>Martin Vingron</dc:creator>
<dc:creator>Daniel Rico</dc:creator>
<dc:creator>Alfonso Valencia</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-09-06</dc:date>
<dc:identifier>doi:10.1101/008821</dc:identifier>
<dc:title><![CDATA[Epigenomic co-localization and co-evolution reveal a key role for 5hmC as a communication hub in the chromatin network of ESCs]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-09-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/048744v1?rss=1">
<title>
<![CDATA[
Ten Simple Rules for Taking Advantage of git and GitHub 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/048744v1?rss=1"
</link>
<description><![CDATA[
A  Ten Simple Rules guide to git and GitHub. We describe and provide examples on how to use these software to track projects, as users, teams and organizations. We document collaborative development using branching and forking, interaction between collaborators using issues and continuous integration and automation using, for example, Travis CI and codevoc. We also describe dissemination and social aspects of GitHub such as GitHub pages, following and watching repositories, and give advice on how to make code citable.
]]></description>
<dc:creator>Yasset Perez-Riverol</dc:creator>
<dc:creator>Laurent Gatto</dc:creator>
<dc:creator>Rui Wang</dc:creator>
<dc:creator>Timo Sachsenberg</dc:creator>
<dc:creator>Julian Uszkoreit</dc:creator>
<dc:creator>Felipe Leprevost</dc:creator>
<dc:creator>Christian Fufezan</dc:creator>
<dc:creator>Tobias Ternent</dc:creator>
<dc:creator>Stephen J Eglen</dc:creator>
<dc:creator>Daniel S. S Katz</dc:creator>
<dc:creator>Tom J Pollard</dc:creator>
<dc:creator>Alexander Konovalov</dc:creator>
<dc:creator>Robert M Flight</dc:creator>
<dc:creator>Kai Blin</dc:creator>
<dc:creator>Juan Antonio Vizcaino</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-04-15</dc:date>
<dc:identifier>doi:10.1101/048744</dc:identifier>
<dc:title><![CDATA[Ten Simple Rules for Taking Advantage of git and GitHub]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-04-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/125435v1?rss=1">
<title>
<![CDATA[
Complexity and conservation of regulatory landscapes underlie evolutionary resilience of mammalian gene expression 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/125435v1?rss=1"
</link>
<description><![CDATA[
To gain insight into how mammalian gene expression is controlled by rapidly evolving regulatory elements, we jointly analysed promoter and enhancer activity with downstream transcription levels in liver samples from twenty species. Genes associated with complex regulatory landscapes generally exhibit high expression levels that remain evolutionarily stable. While the number of regulatory elements is the key driver of transcriptional output and resilience, regulatory conservation matters: elements active across mammals most effectively stabilise gene expression. In contrast, recently-evolved enhancers typically contribute weakly, consistent with their high evolutionary plasticity. These effects are observed across the entire mammalian clade and robust to potential confounders, such as gene expression level. Overall, our results illuminate how the evolutionary stability of gene expression is profoundly entwined with both the number and conservation of surrounding promoters and enhancers.nnHighlightsO_LIGene expression levels and stability are linked to the number of elements in the regulatory landscape.nC_LIO_LIConserved regulatory elements associate with tightly controlled, highly expressed genes.nC_LIO_LIRecently evolved enhancers weakly influence gene expression, but promoters are similarly active regardless of conservation.nC_LIO_LIThe interplay between complexity of the regulatory landscape and conservation of individual promoters and enhancers shapes gene expression in mammals.nC_LI
]]></description>
<dc:creator>Berthelot, C.</dc:creator>
<dc:creator>Villar, D.</dc:creator>
<dc:creator>Horvath, J. E.</dc:creator>
<dc:creator>Odom, D. T.</dc:creator>
<dc:creator>Flicek, P.</dc:creator>
<dc:date>2017-04-07</dc:date>
<dc:identifier>doi:10.1101/125435</dc:identifier>
<dc:title><![CDATA[Complexity and conservation of regulatory landscapes underlie evolutionary resilience of mammalian gene expression]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/074971v1?rss=1">
<title>
<![CDATA[
Temporal mixture modelling of single-cell RNA-seq data resolves a CD4+ T cell fate bifurcation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/074971v1?rss=1"
</link>
<description><![CDATA[
Differentiation of naive CD4+ T cells into functionally distinct T helper subsets is crucial for the orchestration of immune responses. Due to multiple levels of heterogeneity and multiple overlapping transcriptional programs in differentiating T cell populations, this process has remained a challenge for systematic dissection in vivo. By using single-cell RNA transcriptomics and computational modelling of temporal mixtures, we reconstructed the developmental trajectories of Th1 and Tfh cell populations during Plasmodium infection in mice at single-cell resolution. These cell fates emerged from a common, highly proliferative and metabolically active precursor. Moreover, by tracking clonality from T cell receptor sequences, we infer that ancestors derived from the same naive CD4+ T cell can concurrently populate both Th1 and Tfh subsets. We further found that precursor T cells were coached towards a Th1 but not a Tfh fate by monocytes/macrophages. The integrated genomic and computational approach we describe is applicable for analysis of any cellular system characterized by differentiation towards multiple fates.nnOne Sentence SummaryUsing single-cell RNA sequencing and a novel unsupervised computational approach, we resolve the developmental trajectories of two CD4+ T cell fates in vivo, and show that uncommitted T cells are externally influenced towards one fate by inflammatory monocytes.
]]></description>
<dc:creator>Tapio Lönnberg</dc:creator>
<dc:creator>Valentine Svensson</dc:creator>
<dc:creator>Kylie R James</dc:creator>
<dc:creator>Daniel Fernandez-Ruiz</dc:creator>
<dc:creator>Ismail Sebina</dc:creator>
<dc:creator>Ruddy Montandon</dc:creator>
<dc:creator>Megan S F Soon</dc:creator>
<dc:creator>Lily G Fogg</dc:creator>
<dc:creator>Michael J T Stubbington</dc:creator>
<dc:creator>Frederik Otzen Bagger</dc:creator>
<dc:creator>Max Zwiessele</dc:creator>
<dc:creator>Neil Lawrence</dc:creator>
<dc:creator>Fernando Souza-Fonseca- Guimaraes</dc:creator>
<dc:creator>William R Heath</dc:creator>
<dc:creator>Oliver Billker</dc:creator>
<dc:creator>Oliver Stegle</dc:creator>
<dc:creator>Ashraful Haque</dc:creator>
<dc:creator>Sarah A Teichmann</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-09-13</dc:date>
<dc:identifier>doi:10.1101/074971</dc:identifier>
<dc:title><![CDATA[Temporal mixture modelling of single-cell RNA-seq data resolves a CD4+ T cell fate bifurcation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-09-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/170142v1?rss=1">
<title>
<![CDATA[
Flipping the odds of drug development success through human genomics 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/170142v1?rss=1"
</link>
<description><![CDATA[
Drug development depends on accurately identifying molecular targets that both play a causal role in a disease and are amenable to pharmacological action by small molecule drugs or bio-therapeutics, such as monoclonal antibodies.nnErrors in drug target specification contribute to the extremely high rates of drug development failure.nnIntegrating knowledge of genes that encode druggable targets with those that influence susceptibility to common disease has the potential to radically improve the probability of drug development success.
]]></description>
<dc:creator>Hingorani, A. D.</dc:creator>
<dc:creator>Kuan, V.</dc:creator>
<dc:creator>Finan, C.</dc:creator>
<dc:creator>Kruger, F. A.</dc:creator>
<dc:creator>Gaulton, A.</dc:creator>
<dc:creator>Chopade, S.</dc:creator>
<dc:creator>Sofat, R.</dc:creator>
<dc:creator>MacAllister, R. J.</dc:creator>
<dc:creator>Overington, J.</dc:creator>
<dc:creator>Hemingway, H.</dc:creator>
<dc:creator>Denaxas, S.</dc:creator>
<dc:creator>Prieto-Merino, D.</dc:creator>
<dc:creator>Casas, J. P.</dc:creator>
<dc:date>2017-07-30</dc:date>
<dc:identifier>doi:10.1101/170142</dc:identifier>
<dc:title><![CDATA[Flipping the odds of drug development success through human genomics]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/149989v1?rss=1">
<title>
<![CDATA[
Inferring synteny between genome assemblies: a systematic evaluation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/149989v1?rss=1"
</link>
<description><![CDATA[
Identification of synteny between genomes of closely related species is an important aspect of comparative genomics. However, it is unknown to what extent draft assemblies lead to errors in such analysis. To investigate this, we fragmented genome assemblies of model nematodes to various extents and conducted synteny identification and downstream analysis. We first show that synteny between species can be underestimated up to 40% and find disagreements between popular tools that infer synteny blocks. This inconsistency and further demonstration of erroneous gene ontology enrichment tests throws into question the robustness of previous synteny analysis when gold standard genome sequences remain limited. In addition, determining the true evolutionary relationship is compromised by assembly improvement using a reference guided approach with a closely related species. Annotation quality, however, has minimal effect on synteny if the assembled genome is highly contiguous. Our results highlight the need for gold standard genome assemblies for synteny identification and accurate downstream analysis.nnAuthor summaryGenome assemblies across all domains of life are currently produced routinely. Initial analysis of any new genome usually includes annotation and comparative genomics. Synteny provides a framework in which conservation of homologous genes and gene order is identified between genomes of different species. The availability of human and mouse genomes paved the way for algorithm development in large-scale synteny mapping, which eventually became an integral part of comparative genomics. Synteny analysis is regularly performed on assembled sequences that are fragmented, neglecting the fact that most methods were developed using complete genomes. Here, we systematically evaluate this interplay by inferring synteny in genome assemblies with different degrees of contiguation. As expected, our investigation reveals that assembly quality can drastically affect synteny analysis, from the initial synteny identification to downstream analysis. Importantly, we found that improving a fragmented assembly using synteny with the genome of a related species can be dangerous, as this a priori assumes a potentially false evolutionary relationship between the species. The results presented here re-emphasize the importance of gold standard genomes to the science community, and should be achieved given the current progress in sequencing technology.
]]></description>
<dc:creator>Liu, D.</dc:creator>
<dc:creator>Hunt, M.</dc:creator>
<dc:creator>Tsai, I. J.</dc:creator>
<dc:date>2017-06-14</dc:date>
<dc:identifier>doi:10.1101/149989</dc:identifier>
<dc:title><![CDATA[Inferring synteny between genome assemblies: a systematic evaluation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/057497v1?rss=1">
<title>
<![CDATA[
Personally tailored cancer management based on knowledge banks of genomic and clinical data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/057497v1?rss=1"
</link>
<description><![CDATA[
Sequencing of cancer genomes, or parts thereof, has become widespread and will soon be implemented as part of routine clinical diagnostics. However the clinical ramifications of this have not been fully assessed. Here we assess the utility of sequencing large and clinically well-annotated cancer cohorts to derive personalized predictions about treatment outcome. To this end we study a cohort of 1,540 patients with AML (acute myeloid leukemia) with genetic profiles from 111 cancer genes, cytogenetic data and diagnostic blood counts. We test existing and develop new models to compute the probability of six different clinical outcomes based on more than 100 genetic and clinical variables. The predictions derived from our knowledge bank are more detailed and outperform strata currently used in clinical practice (concordance C=72% v C=64%), and are validated on three cohorts and data from TCGA (C=70%). Our prognostic algorithm is available as an online tool (http://cancer.sanger.ac.uk/aml-multistage). A simulation of different treatment scenarios indicates that a refined risk stratification could reduce the number of bonemarrow transplants by up to 25%, while achieving the same survival. Power calculation show that the inclusion of further genes most likely has small effects on the prognostic accuracy; increasing the number of cases will further reduce the error of personalized predictions.
]]></description>
<dc:creator>Moritz Gerstung</dc:creator>
<dc:creator>Elli Papaemmanuil</dc:creator>
<dc:creator>Inigo Martincorena</dc:creator>
<dc:creator>Lars Bullinger</dc:creator>
<dc:creator>Verena I Gaidzik</dc:creator>
<dc:creator>Peter Paschka</dc:creator>
<dc:creator>Michael Heuser</dc:creator>
<dc:creator>Felicitas Thol</dc:creator>
<dc:creator>Niccolo Bolli</dc:creator>
<dc:creator>Peter Ganly</dc:creator>
<dc:creator>Arnold Ganser</dc:creator>
<dc:creator>Ultan McDermott</dc:creator>
<dc:creator>Konstanze Dohner</dc:creator>
<dc:creator>Richard F Schlenk</dc:creator>
<dc:creator>Hartmut Dohner</dc:creator>
<dc:creator>Peter J Campbell</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-06-07</dc:date>
<dc:identifier>doi:10.1101/057497</dc:identifier>
<dc:title><![CDATA[Personally tailored cancer management based on knowledge banks of genomic and clinical data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-06-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/087239v1?rss=1">
<title>
<![CDATA[
Ensembl Core Software Resources: storage and programmatic access for DNA sequence and genome annotation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/087239v1?rss=1"
</link>
<description><![CDATA[
The Ensembl software resources are a stable infrastructure to store, access and manipulate genome assemblies and their functional annotations. The Ensembl "Core" database and Application Programming Interface (API) was our first major piece of software infrastructure and remains at the centre of all of our genome resources. Since its initial design more than fifteen years ago, the number of publicly available genomic, transcriptomic and proteomic datasets has grown enormously, accelerated by continuous advances in DNA sequencing technology. Initially intended to provide annotation for the reference human genome, we have extended our framework to support the genomes of all species as well as richer assembly models. Cross-referenced links to other informatics resources facilitate searching our database with a variety of popular identifiers such as UniProt and RefSeq. Our comprehensive and robust framework storing a large diversity of genome annotations in one location serves as a platform for other groups to generate and maintain their own tailored annotation. Our databases and APIs are publicly available and all of our source code is released with a permissive Apache v2.0 licence at http://github.com/Ensembl.
]]></description>
<dc:creator>Ruffier, M.</dc:creator>
<dc:creator>Kahari, A.</dc:creator>
<dc:creator>Komorowska, M.</dc:creator>
<dc:creator>Keenan, S.</dc:creator>
<dc:creator>Laird, M. R.</dc:creator>
<dc:creator>Longden, I.</dc:creator>
<dc:creator>Proctor, G.</dc:creator>
<dc:creator>Searle, S.</dc:creator>
<dc:creator>Staines, D.</dc:creator>
<dc:creator>Taylor, K.</dc:creator>
<dc:creator>Vullo, A.</dc:creator>
<dc:creator>Yates, A.</dc:creator>
<dc:creator>Zerbino, D.</dc:creator>
<dc:creator>Flicek, P.</dc:creator>
<dc:date>2016-11-11</dc:date>
<dc:identifier>doi:10.1101/087239</dc:identifier>
<dc:title><![CDATA[Ensembl Core Software Resources: storage and programmatic access for DNA sequence and genome annotation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-11-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/196022v1?rss=1">
<title>
<![CDATA[
An unbiased reconstruction of the T helper cell type 2 differentiation network 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/196022v1?rss=1"
</link>
<description><![CDATA[
T helper type 2 (Th2) cells are important regulators of our adaptive immune response, particularly the response against parasites, and have relevance for auto-immunity as well as tumour progression. This classic T helper type has been studied intensively, but not systematically. Using newly developed, genome-wide retroviral CRISPR knock-out (KO) technology, combined with RNA-seq, ATAC-seq and ChIP-seq, we have dissected the regulatory circuitry governing differentiation in these cells. During Th2 activation/differentiation approximately 4000 genes are perturbed, with at least 200 genes specifically associated with the Th2 program in mouse and human. We confirm previously known Th2 driver genes and have discovered several novel genes, including transcription factors, metabolic genes and potential receptors/cytokines, critical for Th2 function. Our study provides an atlas for, but not limited to, the Th2 regulatory network, pinpointing the key players of Th2 differentiation.
]]></description>
<dc:creator>Henriksson, J.</dc:creator>
<dc:creator>Chen, X.</dc:creator>
<dc:creator>Gomes, T.</dc:creator>
<dc:creator>Miragaia, R.</dc:creator>
<dc:creator>Ullah, U.</dc:creator>
<dc:creator>Pramanik, J.</dc:creator>
<dc:creator>Meyer, K.</dc:creator>
<dc:creator>Yusa, K.</dc:creator>
<dc:creator>Lahesmaa, R.</dc:creator>
<dc:creator>Teichmann, S. A.</dc:creator>
<dc:date>2017-10-04</dc:date>
<dc:identifier>doi:10.1101/196022</dc:identifier>
<dc:title><![CDATA[An unbiased reconstruction of the T helper cell type 2 differentiation network]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/163295v1?rss=1">
<title>
<![CDATA[
Immature HIV-1 Lattice Assembly Dynamics are Regulated by Scaffolding from Nucleic Acid and the Plasma Membrane 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/163295v1?rss=1"
</link>
<description><![CDATA[
The packaging and budding of Gag polyprotein and viral ribonucleic acid (RNA) is a critical step in the human immunodeficiency virus-1 (HIV-1) lifecycle. High-resolution structures of the Gag polyprotein have revealed that the capsid (CA) and spacer peptide 1 (SP1) domains contain important interfaces for Gag self-assembly. However, the molecular details of the multimerization process, especially in the presence of RNA and the cell membrane, have remained unclear. In this work, we investigate the mechanisms that work in concert between the polyproteins, RNA, and membrane to promote immature lattice growth. We develop a coarse-grained (CG) computational model that is derived from sub-nanometer resolution structural data. Our simulations recapitulate contiguous and hexameric lattice assembly driven only by weak anisotropic attractions at the helical CA-SP1 junction. Importantly, analysis from CG and single-particle tracking photoactivated localization (spt-PALM) trajectories indicates that viral RNA and the membrane are critical constituents that actively promote Gag multimerization through scaffolding, while over-expression of short competitor RNA can suppress assembly. We also find that the CA amino-terminal domain imparts intrinsic curvature to the Gag lattice. As a consequence, immature lattice growth appears to be coupled to the dynamics of spontaneous membrane deformation. Our findings elucidate a simple network of interactions that regulate the early stages of HIV-1 assembly and budding.nnSIGNIFICANCE STATEMENTIn order for human immunodeficiency virus to proliferate, viral proteins and genomic dimers are assembled at host cell membranes and released as immature virions. Disrupting this key intermediate step in viral replication is a potential target for treatment. However, a detailed molecular view of this process remains lacking. Here, we elucidate a network of constitutive interactions that regulate viral assembly dynamics through a combined computational and experimental approach. Specifically, our analysis reveals the active roles of nucleic acid and the membrane as scaffolds that promote the multimerization of Gag polyprotein which proceeds through multi-step and self-correcting nucleation. Our findings also illustrate the functional importance of the N-terminal, C-terminal, and spacer peptide 1 protein domains.
]]></description>
<dc:creator>Pak, A. J.</dc:creator>
<dc:creator>Grime, J. M. A.</dc:creator>
<dc:creator>Sengupta, P.</dc:creator>
<dc:creator>Chen, A. K.</dc:creator>
<dc:creator>Durumeric, A. E. P.</dc:creator>
<dc:creator>Srivastava, A.</dc:creator>
<dc:creator>Yeager, M.</dc:creator>
<dc:creator>Briggs, J. A. G.</dc:creator>
<dc:creator>Lippincott-Schwartz, J.</dc:creator>
<dc:creator>Voth, G. A.</dc:creator>
<dc:date>2017-07-13</dc:date>
<dc:identifier>doi:10.1101/163295</dc:identifier>
<dc:title><![CDATA[Immature HIV-1 Lattice Assembly Dynamics are Regulated by Scaffolding from Nucleic Acid and the Plasma Membrane]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/237784v1?rss=1">
<title>
<![CDATA[
Comparative analysis of neutrophil and monocyte epigenomes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/237784v1?rss=1"
</link>
<description><![CDATA[
Neutrophils and monocytes provide a first line of defense against infections as part of the innate immune system. Here we report the integrated analysis of transcriptomic and epigenetic landscapes for circulating monocytes and neutrophils with the aim to enable downstream interpretation and functional validation of key regulatory elements in health and disease. We collected RNA-seq data, ChIP-seq of six histone modifications and of DNA methylation by bisulfite sequencing at base pair resolution from up to 6 individuals per cell type. Chromatin segmentation analyses suggested that monocytes have a higher number of cell-specific enhancer regions (4-fold) compared to neutrophils. This highly plastic epigenome is likely indicative of the greater differentiation potential of monocytes into macrophages, dendritic cells and osteoclasts. In contrast, most of the neutrophil-specific features tend to be characterized by repressed chromatin, reflective of their status as terminally differentiated cells. Enhancers were the regions where most of differences in DNA methylation between cells were observed, with monocyte-specific enhancers being generally hypomethylated. Monocytes show a substantially higher gene expression levels than neutrophils, in line with epigenomic analysis revealing that gene more active elements in monocytes. Our analyses suggest that the overexpression of c-Myc in monocytes and its binding to monocyte-specific enhancers could be an important contributor to these differences. Altogether, our study provides a comprehensive epigenetic chart of chromatin states in primary human neutrophils and monocytes, thus providing a valuable resource for studying the regulation of the human innate immune system.
]]></description>
<dc:creator>Rico, D.</dc:creator>
<dc:creator>Martens, J. H.</dc:creator>
<dc:creator>Downes, K.</dc:creator>
<dc:creator>Carrillo-de-Santa-Pau, E.</dc:creator>
<dc:creator>Pancaldi, V.</dc:creator>
<dc:creator>Breschi, A.</dc:creator>
<dc:creator>Richardson, D.</dc:creator>
<dc:creator>Heath, S.</dc:creator>
<dc:creator>Saeed, S.</dc:creator>
<dc:creator>Frontini, M.</dc:creator>
<dc:creator>Chen, L.</dc:creator>
<dc:creator>Watt, S.</dc:creator>
<dc:creator>Muller, F.</dc:creator>
<dc:creator>Clarke, L.</dc:creator>
<dc:creator>Kerstens, H. H.</dc:creator>
<dc:creator>Wilder, S. P.</dc:creator>
<dc:creator>Palumbo, E.</dc:creator>
<dc:creator>Djebali, S.</dc:creator>
<dc:creator>Rainieri, E.</dc:creator>
<dc:creator>Merkel, A.</dc:creator>
<dc:creator>Esteve-Codina, A.</dc:creator>
<dc:creator>Sultan, M.</dc:creator>
<dc:creator>van Bommel, A.</dc:creator>
<dc:creator>Gut, M.</dc:creator>
<dc:creator>Yaspo, M.-L.</dc:creator>
<dc:creator>Rubio, M.</dc:creator>
<dc:creator>Fernandez, J. M.</dc:creator>
<dc:creator>Attwood, A.</dc:creator>
<dc:creator>de la Torre, V.</dc:creator>
<dc:creator>Royo, R.</dc:creator>
<dc:creator>Fragkogianni, S.</dc:creator>
<dc:creator>Gelpi, J. L.</dc:creator>
<dc:creator>Torrents, D.</dc:creator>
<dc:creator>Iotchkova, V.</dc:creator>
<dc:creator>Logie, C.</dc:creator>
<dc:creator>Aghajanirefah, A.</dc:creator>
<dc:creator>Singh, A. A.</dc:creator>
<dc:creator>Janssen-Megens, E. M.</dc:creator>
<dc:creator>Berentsen, K.</dc:creator>
<dc:creator>Erber, W.</dc:creator>
<dc:creator>Rendon, A.</dc:creator>
<dc:creator>Kostadima, M.</dc:creator>
<dc:creator>Loos, R.</dc:creator>
<dc:date>2017-12-22</dc:date>
<dc:identifier>doi:10.1101/237784</dc:identifier>
<dc:title><![CDATA[Comparative analysis of neutrophil and monocyte epigenomes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/151225v1?rss=1">
<title>
<![CDATA[
High Frequency Actionable Pathogenic Exome Mutations in an Average-Risk Cohort 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/151225v1?rss=1"
</link>
<description><![CDATA[
Whole exome sequencing (WES) is increasingly utilized in both clinical and non-clinical settings, but little is known about the utility of WES in healthy individuals. In order to determine the frequency of both medically actionable and non-actionable but medically relevant exome findings in the general population we assessed the exomes of 70 participants who have been extensively characterized over the past several years as part of a longitudinal integrated multi-omics profiling study at Stanford University. We assessed exomes for rare likely pathogenic and pathogenic variants in genes associated with Mendelian disease in the Online Mendelian Inheritance in Man (OMIM) database. We used American College of Medical Genetics (ACMG) guidelines were used for the classification of rare sequence variants, and additionally we assessed pharmacogenetic variants. Twelve out of 70 (17%) participants had medically actionable findings in Mendelian disease genes, including 6 (9%) with mutations in genes not currently included in the ACMGs list of 59 actionable genes. This number is higher than that reported in previous studies and suggests added benefit from utilizing expanded gene lists and manual curation to assess actionable findings. A total of 60 participants (89%) had non-actionable findings identified including 57 who were found to be mutation carriers for recessive diseases and 21 who have increased Alzheimers disease risk due to heterozyg ous or homozygous APOE e4 alleles (18 participants had both). These results suggest that exome sequencing may have considerably more utility for health management in the general population than previously thought.
]]></description>
<dc:creator>Rego, S.</dc:creator>
<dc:creator>Dagan-Rosenfeld, O.</dc:creator>
<dc:creator>Zhou, W.</dc:creator>
<dc:creator>Sailani, M. R.</dc:creator>
<dc:creator>Limcaoco, P.</dc:creator>
<dc:creator>Colbert, E.</dc:creator>
<dc:creator>Avina, M.</dc:creator>
<dc:creator>Wheeler, J.</dc:creator>
<dc:creator>Craig, C.</dc:creator>
<dc:creator>Salins, D.</dc:creator>
<dc:creator>Rost, H. L.</dc:creator>
<dc:creator>Dunn, J.</dc:creator>
<dc:creator>McLaughlin, T.</dc:creator>
<dc:creator>Steinmetz, L. M.</dc:creator>
<dc:creator>Bernstein, J. A.</dc:creator>
<dc:creator>Snyder, M. P.</dc:creator>
<dc:date>2017-06-18</dc:date>
<dc:identifier>doi:10.1101/151225</dc:identifier>
<dc:title><![CDATA[High Frequency Actionable Pathogenic Exome Mutations in an Average-Risk Cohort]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/229492v1?rss=1">
<title>
<![CDATA[
Two consecutive microtubule-based epithelial seaming events mediate dorsal closure in the scuttle fly Megaselia abdita 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/229492v1?rss=1"
</link>
<description><![CDATA[
Evolution of morphogenesis is generally associated with changes in genetic regulation. Here we report evidence indicating that dorsal closure, a conserved morphogenetic process in dipterans, evolved as the consequence of rearrangements in epithelial organization rather than signaling regulation. In Drosophila melanogaster, dorsal closure consists of a two-tissue system where the contraction of extraembryonic amnioserosa and a JNK/Dpp-dependent epidermal actomyosin cable result in microtubule-dependent seaming of the epidermis. We find that dorsal closure in Megaselia abdita, a three-tissue system comprising serosa, amnion and epidermis, differs in morphogenetic rearrangements despite conservation of JNK/Dpp signaling. In addition to an actomyosin cable, M. abdita dorsal closure is driven by the rupture and contraction of the serosa and the consecutive microtubule-dependent seaming of amnion and epidermis. Our study indicates that the evolutionary transition to a reduced system of dorsal closure involves simplification of the seaming process without changing the signaling pathways of closure progression.nnImpact StatementEvolutionary reduction in tissue number involves the simplification of the seaming process but not signaling during epithelial fusion.
]]></description>
<dc:creator>Fraire-Zamora, J. J.</dc:creator>
<dc:creator>Jaeger, J.</dc:creator>
<dc:creator>Solon, J.</dc:creator>
<dc:date>2017-12-05</dc:date>
<dc:identifier>doi:10.1101/229492</dc:identifier>
<dc:title><![CDATA[Two consecutive microtubule-based epithelial seaming events mediate dorsal closure in the scuttle fly Megaselia abdita]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/053090v1?rss=1">
<title>
<![CDATA[
Ecogenomics and biogeochemical impacts of uncultivated globally abundant ocean viruses 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/053090v1?rss=1"
</link>
<description><![CDATA[
Ocean microbes drive global-scale biogeochemical cycling1, but do so under constraints imposed by viruses on host community composition, metabolism, and evolutionary trajectories2-5. Due to sampling and cultivation challenges, genome-level viral diversity remains poorly described and grossly understudied in nature such that <1% of observed surface ocean viruses, even those that are abundant and ubiquitous, are  known5. Here we analyze a global map of abundant, double stranded DNA (dsDNA) viruses and viral-encoded auxiliary metabolic genes (AMGs) with genomic and ecological contexts through the Global Ocean Viromes (GOV) dataset, which includes complete genomes and large genomic fragments from both surface and deep ocean viruses sampled during the Tara Oceans and Malaspina research expeditions6,7. A total of 15,222 epi- and mesopelagic viral populations were identified that comprised 867 viral clusters (VCs, approximately genus-level groups8,9). This roughly triples known ocean viral populations10, doubles known candidate bacterial and archaeal virus genera9, and near-completely samples epipelagic communities at both the population and VC level. Thirty-eight of the 867 VCs were identified as the most impactful dsDNA viral groups in the oceans, as these were locally or globally abundant and accounted together for nearly half of the viral populations in any GOV sample. Most of these were predicted in silico to infect dominant, ecologically relevant microbes, while two thirds of them represent newly described viruses that lacked any cultivated representative. Beyond these taxon-specific ecological observations, we identified 243 viral-encoded AMGs in GOV, only 95 of which were known. Deeper analyses of 4 of these AMGs revealed that abundant viruses directly manipulate sulfur and nitrogen cycling, and do so throughout the epipelagic ocean. Together these data provide a critically-needed organismal catalog and functional context to begin meaningfully integrating viruses into ecosystem models as key players in nutrient cycling and trophic networks.
]]></description>
<dc:creator>Simon Roux</dc:creator>
<dc:creator>Jennifer R Brum</dc:creator>
<dc:creator>Bas E. Dutilh</dc:creator>
<dc:creator>Shinichi Sunagawa</dc:creator>
<dc:creator>Melissa B Duhaime</dc:creator>
<dc:creator>Alexander Loy</dc:creator>
<dc:creator>Bonnie T Poulos</dc:creator>
<dc:creator>Natalie Solonenko</dc:creator>
<dc:creator>Elena Lara</dc:creator>
<dc:creator>Julie Poulain</dc:creator>
<dc:creator>Stephane PESANT</dc:creator>
<dc:creator>Stefanie Kandels-Lewis</dc:creator>
<dc:creator>Céline Dimier</dc:creator>
<dc:creator>Marc Picheral</dc:creator>
<dc:creator>Sarah Searson</dc:creator>
<dc:creator>Corinne Cruaud</dc:creator>
<dc:creator>Adriana Alberti</dc:creator>
<dc:creator>Carlos M. M Duarte</dc:creator>
<dc:creator>Josep M M Gasol</dc:creator>
<dc:creator>Dolors Vaqué</dc:creator>
<dc:creator>Tara Oceans Coordinators</dc:creator>
<dc:creator>Peer Bork</dc:creator>
<dc:creator>Silvia G Acinas</dc:creator>
<dc:creator>Patrick Wincker</dc:creator>
<dc:creator>Matthew B Sullivan</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-05-12</dc:date>
<dc:identifier>doi:10.1101/053090</dc:identifier>
<dc:title><![CDATA[Ecogenomics and biogeochemical impacts of uncultivated globally abundant ocean viruses]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-05-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/255497v1?rss=1">
<title>
<![CDATA[
LiMMBo: a simple, scalable approach for linear mixed models in high-dimensional genetic association studies 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/255497v1?rss=1"
</link>
<description><![CDATA[
Genome-wide association studies have helped to shed light on the genetic architecture of complex traits and diseases. Deep phenotyping of population cohorts is increasingly applied, where multi-to high-dimensional phenotypes are recorded in the individuals. Whilst these rich datasets provide important opportunities to analyse complex trait structures and pleiotropic effects at a genome-wide scale, existing statistical methods for joint genetic analyses are hampered by computational limitations posed by high-dimensional phenotypes. Consequently, such multivariate analyses are currently limited to a moderate number of traits. Here, we introduce a method that combines linear mixed models with bootstrapping (LiMMBo) to enable computationally efficient joint genetic analysis of high-dimensional phenotypes. Our method builds on linear mixed models, thereby providing robust control for population structure and other confounding factors, and the model scales to larger datasets with up to hundreds of phenotypes. We first validate LiMMBo using simulations, demonstrating consistent covariance estimates at greatly reduced computational cost compared to existing methods. We also find LiMMBo yields consistent power advantages compared to univariate modelling strategies, where the advantages of multivariate mapping increases substantially with the phenotype dimensionality. Finally, we applied LiMMBo to 41 yeast growth traits to map their genetic determinants, finding previously known and novel pleiotropic relationships in this high-dimensional phenotype space. LiMMBo is accessible as open source software (https://github.com/HannahVMeyer/limmbo).nnAuthor summaryIn multi-trait genetic association studies one is interested in detecting genetic variants that are associated with one or multiple traits. Genetic variants that influence two or more traits are referred to as pleiotropic. Multivariate linear mixed models have been successfully applied to detect pleiotropic effects, by jointly modelling association signals across traits. However, these models are currently limited to a moderate number of phenotypes as the number of model parameters grows steeply with the number of phenotypes, raising a computational burden. We developed LiMMBo, a new approach for the joint analysis of high-dimensional phenotypes. Our method reduces the number of effective model parameters by introducing an intermediate subsampling step. We validate this strategy using simulations, where we apply LiMMBo for the genetic analysis of hundreds of phenotypes, detecting pleiotropic effects for a wide range of simulated genetic architectures. Finally, to illustrate LiMMBo in practice, we apply the model to a study of growth traits in yeast, where we identify pleiotropic effects for traits with formerly known genetic effects as well as revealing previously unconnected traits.
]]></description>
<dc:creator>Hannah, M. V.</dc:creator>
<dc:creator>Casale, F. P.</dc:creator>
<dc:creator>Stegle, O.</dc:creator>
<dc:creator>Birney, E.</dc:creator>
<dc:date>2018-01-30</dc:date>
<dc:identifier>doi:10.1101/255497</dc:identifier>
<dc:title><![CDATA[LiMMBo: a simple, scalable approach for linear mixed models in high-dimensional genetic association studies]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/038380v1?rss=1">
<title>
<![CDATA[
Short template switch events explain mutation clusters in the human genome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/038380v1?rss=1"
</link>
<description><![CDATA[
Resequencing efforts are uncovering the extent of genetic variation in humans and provide data to study the evolutionary processes shaping our genome. One recurring puzzle in both intra- and inter-species studies is the high frequency of complex mutations comprising multiple nearby base substitutions or insertion-deletions. We devised a generalized mutation model of template switching during replication that extends existing models of genome rearrangement, and used this to study the role of template switch events in the origin of such mutation clusters. Applied to the human genome, our model detects thousands of template switch events during the evolution of human and chimp from their common ancestor, and hundreds of events between two independently sequenced human genomes. While many of these are consistent with the template switch mechanism previously proposed for bacteria but not thought significant in higher organisms, our model also identifies new types of mutations that create short inversions, some flanked by paired inverted repeats. The local template switch process can create numerous complex mutation patterns, including hairpin loop structures, and explains multi-nucleotide mutations and compensatory substitutions without invoking positive selection, complicated and speculative mechanisms, or implausible coincidence. Clustered sequence differences are challenging for mapping and variant calling methods, and we show that detection of mutation clusters with current resequencing methodologies is difficult and many erroneous variant annotations exist in human reference data. Template switch events such as those we have uncovered may have been neglected as an explanation for complex mutations because of biases in commonly used analyses. Incorporation of our model into reference-based analysis pipelines and comparisons of de novo-assembled genomes will lead to improved understanding of genome variation and evolution.
]]></description>
<dc:creator>Ari Löytynoja</dc:creator>
<dc:creator>Nick Goldman</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-02-01</dc:date>
<dc:identifier>doi:10.1101/038380</dc:identifier>
<dc:title><![CDATA[Short template switch events explain mutation clusters in the human genome]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-02-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/075556v1?rss=1">
<title>
<![CDATA[
Lipid metabolic perturbation is an early-onset phenotype in adult spin mutants: a Drosophila model for lysosomal storage disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/075556v1?rss=1"
</link>
<description><![CDATA[
Intracellular accumulation of lipids and swollen dysfunctional lysosomes are linked to several neurodegenerative diseases including lysosomal storage disorders (LSD). A detailed characterization of lipid metabolic changes in relation to the onset and progression of neurodegeneration is currently missing. In this study, we systematically analyzed lipid perturbations in spinster (spin) mutants, a Drosophila model of neurodegeneration associated with LSD. Our results highlight an imbalance in brain ceramide and sphingosine as a crucial phenotype in the early stages of neurodegeneration. This perturbation in ceramide metabolism precedes the accumulation of endomembranous structures, manifestation of altered behavior and buildup of lipofuscin (the ageing pigment). Manipulating levels of ceramidase, and, consequently further altering these lipids in spin mutants have allowed us to conclude that ceramide/sphingosine homeostasis is the driving force in disease progression and is integral to spin function in the adult nervous system. Furthermore, we have identified 29 novel and direct interaction partners of Spin. We specifically focused on the lipid carrier protein, Lipophorin (Lpp), and demonstrate its localization with Spin in the adult nervous system and in organs specialized for lipid metabolism including fat bodies and oenocytes. Our observations in spin mutants of altered Lpp immunostaining, and of increased levels of lipid metabolites produced by oenocytes, allude to a functional relevance of the Spin-Lpp interaction.nnOverall, these results detailing the kinetics of ceramide perturbations in the context of lipofuscin accumulation, as well as the proteomics experiment, represent a valuable resource to further unravel the mechanistic link between systemic changes in lipid metabolism and lysosomal storage disorders.nnSummary StatementElevations in specific brain lipids and connections to relevant metabolic genes are identified in a fly model for lysosomal storage disorders. This enables a better understanding of disease progression.
]]></description>
<dc:creator>sarita hebbar</dc:creator>
<dc:creator>Avinash Khandelwal</dc:creator>
<dc:creator>Jayashree R</dc:creator>
<dc:creator>Samantha J Hindle</dc:creator>
<dc:creator>Yin Ning Chiang</dc:creator>
<dc:creator>Joanne Yew</dc:creator>
<dc:creator>Sean Sweeney</dc:creator>
<dc:creator>Dominik Schwudke</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-09-16</dc:date>
<dc:identifier>doi:10.1101/075556</dc:identifier>
<dc:title><![CDATA[Lipid metabolic perturbation is an early-onset phenotype in adult spin mutants: a Drosophila model for lysosomal storage disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-09-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/073692v1?rss=1">
<title>
<![CDATA[
Power Analysis of Single Cell RNA‐Sequencing Experiments 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/073692v1?rss=1"
</link>
<description><![CDATA[
High-throughput single cell RNA sequencing (scRNA-seq) has become an established and powerful method to investigate transcriptomic cell-to-cell variation, and has revealed new cell types, and new insights into developmental process and stochasticity in gene expression. There are now several published scRNA-seq protocols, which all sequence transcriptomes from a minute amount of starting material. Therefore, a key question is how these methods compare in terms of sensitivity of detection of mRNA molecules, and accuracy of quantification of gene expression. Here, we assessed the sensitivity and accuracy of many published data sets based on standardized spike-ins with a uniform raw data processing pipeline. We developed a flexible and fast UMI counting tool (https://github.com/vals/umis) which is compatible with all UMI based protocols. This allowed us to relate these parameters to sequencing depth, and discuss the trade offs between the different methods. To confirm our results, we performed experiments on cells from the same population using three different protocols. We also investigated the effect of RNA degradation on spike-in molecules, and the average efficiency of scRNA-seq on spike-in molecules versus endogenous RNAs.
]]></description>
<dc:creator>Valentine Svensson</dc:creator>
<dc:creator>Kedar N Natarajan</dc:creator>
<dc:creator>Lam-Ha Ly</dc:creator>
<dc:creator>Ricardo J Miragaia</dc:creator>
<dc:creator>Charlotte Labalette</dc:creator>
<dc:creator>Iain C Macaulay</dc:creator>
<dc:creator>Ana Cvejic</dc:creator>
<dc:creator>Sarah A Teichmann</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-09-08</dc:date>
<dc:identifier>doi:10.1101/073692</dc:identifier>
<dc:title><![CDATA[Power Analysis of Single Cell RNA‐Sequencing Experiments]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-09-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/036558v1?rss=1">
<title>
<![CDATA[
SC3 - consensus clustering of single-cell RNA-Seq data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/036558v1?rss=1"
</link>
<description><![CDATA[
Using single-cell RNA-seq (scRNA-seq), the full transcriptome of individual cells can be acquired, enabling a quantitative cell-type characterisation based on expression profiles. However, due to the large variability in gene expression, identifying cell types based on the transcriptome remains challenging. We present Single-Cell Consensus Clustering (SC3), a tool for unsupervised clustering of scRNA-seq data. SC3 achieves high accuracy and robustness by consistently integrating different clustering solutions through a consensus approach. Tests on twelve published datasets show that SC3 outperforms five existing methods while remaining scalable, as shown by the analysis of a large dataset containing 44,808 cells. Moreover, an interactive graphical implementation makes SC3 accessible to a wide audience of users, and SC3 aids biological interpretation by identifying marker genes, differentially expressed genes and outlier cells. We illustrate the capabilities of SC3 by characterising newly obtained transcriptomes from subclones of neoplastic cells collected from patients.
]]></description>
<dc:creator>Vladimir Yu. Kiselev</dc:creator>
<dc:creator>Kristina Kirschner</dc:creator>
<dc:creator>Michael T. Schaub</dc:creator>
<dc:creator>Tallulah Andrews</dc:creator>
<dc:creator>Andrew Yiu</dc:creator>
<dc:creator>Tamir Chandra</dc:creator>
<dc:creator>Kedar N Natarajan</dc:creator>
<dc:creator>Wolf Reik</dc:creator>
<dc:creator>Mauricio Barahona</dc:creator>
<dc:creator>Anthony R Green</dc:creator>
<dc:creator>Martin Hemberg</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-01-13</dc:date>
<dc:identifier>doi:10.1101/036558</dc:identifier>
<dc:title><![CDATA[SC3 - consensus clustering of single-cell RNA-Seq data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-01-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/169748v1?rss=1">
<title>
<![CDATA[
Genome variation and conserved regulation identify genomic regions responsible for strain specific phenotypes in rat 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/169748v1?rss=1"
</link>
<description><![CDATA[
The genomes of laboratory rat strains are characterised by a mosaic haplotype structure caused by their unique breeding history. These mosaic haplotypes have been recently mapped by extensive sequencing of key strains. Comparison of genomic variation between two closely related rat strains with different phenotypes has been proposed as an effective strategy for the discovery of candidate strain-specific regions involved in phenotypic differences.nnWe developed a method to prioritise strain-specific haplotypes by integrating genomic variation and genomic regulatory data predicted to be involved in specific phenotypes. To identify genomic regions associated with metabolic syndrome, a disorder of energy utilization and storage affecting several organ systems, we compared two Lyon rat strains, LH/Mav which is susceptible to MetS, and LL/Mav, which is susceptible to obesity as an intermediate MetS phenotype, with a third strain (LN/Mav) that is resistant to both MetS and obesity. Applying a novel metric, we ranked the identified strain-specific haplotypes using evolutionary conservation of the occupancy three liver-specific transcription factors (HNF4A, CEBPA, and FOXA1) in five rodents including rat.nnConsideration of regulatory information effectively identified regions with liver-associated genes and rat orthologues of human GWAS variants related to obesity and metabolic traits. We attempted to find possible causative variants and compared them with the candidate genes proposed by previous studies. In strain-specific regions with conserved regulation, we found a significant enrichment for published evidence to obesity--one of the metabolic symptoms shown by the Lyon strains--amongst the genes assigned to promoters with strain-specific variation.nnOur results show that the use of functional regulatory conservation is a potentially effective approach to select strain-specific genomic regions associated with phenotypic differences among Lyon rats and could be extended to other systems.
]]></description>
<dc:creator>Martin-Galvez, D.</dc:creator>
<dc:creator>Dunoyer-de-Segonzac, D.</dc:creator>
<dc:creator>Ma, M. C. J.</dc:creator>
<dc:creator>Kwitek, A. E.</dc:creator>
<dc:creator>Thybert, D.</dc:creator>
<dc:creator>Flicek, P.</dc:creator>
<dc:date>2017-07-28</dc:date>
<dc:identifier>doi:10.1101/169748</dc:identifier>
<dc:title><![CDATA[Genome variation and conserved regulation identify genomic regions responsible for strain specific phenotypes in rat]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/059873v1?rss=1">
<title>
<![CDATA[
Interplay of cis and trans mechanisms driving transcription factor binding, chromatin, and gene expression evolution 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/059873v1?rss=1"
</link>
<description><![CDATA[
Noncoding regulatory variants play a central role in the genetics of human diseases and in evolution. Here we measure allele-specific transcription factor binding occupancy of three liver-specific transcription factors between crosses of two inbred mouse strains to elucidate the regulatory mechanisms underlying transcription factor binding variations in mammals. Our results highlight the pre-eminence of cis-acting variants on transcription factor occupancy divergence. Transcription factor binding differences linked to cis-acting variants generally exhibit additive inheritance, while those linked to trans-acting variants are most often dominantly inherited. Cis-acting variants lead to local coordination of transcription factor occupancies that decay with distance; distal coordination is also observed and may be modulated by long-range chromatin contacts. Our results reveal the regulatory mechanisms that interplay to drive transcription factor occupancy, chromatin state, and gene expression in complex mammalian cell states.
]]></description>
<dc:creator>Emily S Wong</dc:creator>
<dc:creator>Bianca M Schmitt</dc:creator>
<dc:creator>Anastasiya Kazachenka</dc:creator>
<dc:creator>David Thybert</dc:creator>
<dc:creator>Aisling Redmond</dc:creator>
<dc:creator>Frances Connor</dc:creator>
<dc:creator>Tim F Rayner</dc:creator>
<dc:creator>Christine Feig</dc:creator>
<dc:creator>Anne C Ferguson-Smith</dc:creator>
<dc:creator>John C Marioni</dc:creator>
<dc:creator>Paul Flicek</dc:creator>
<dc:creator>Duncan T Odom</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-06-19</dc:date>
<dc:identifier>doi:10.1101/059873</dc:identifier>
<dc:title><![CDATA[Interplay of cis and trans mechanisms driving transcription factor binding, chromatin, and gene expression evolution]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-06-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/074963v1?rss=1">
<title>
<![CDATA[
Cotranslational assembly imposes evolutionary constraints on homomeric proteins 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/074963v1?rss=1"
</link>
<description><![CDATA[
There is increasing evidence that some proteins fold during translation, i.e. cotranslationally, which implies that partial protein function, including interactions with other molecules, could potentially be unleashed early on during translation. Although little is known about cotranslational assembly mechanisms, for homomeric protein complexes, translation by the ribosome, folding and assembly, should be well-coordinated to avoid misassembly in the context of polysomes. We analysed 3D structures of homomers and identified a statistically significant trend conserved across evolution that supports this hypothesis: namely that homomeric contacts tend to be localized towards the C-terminus rather than N-terminus of homomeric polypeptide chains. To probe this in more detail, we expressed a GFP-based library of 611 homomeric E. coli genes, and analyzing their folding and assembly in vivo. Consistent with our hypothesis, interface residues tend to be located near the N-terminus in cotranslationally aggregating homomers. In order to dissect the mechanisms of folding and assembly under controlled conditions, we engineered a protein library with three variable components: (i) the position and type homomerization domain, (ii) the reporter domain and (iii) the linker length that connects the two. By analyzing the misassembly rates of these engineered constructs in vivo, in vitro and in silico, we confirmed our hypothesis that C-terminal homomerization is favorable to N-terminal homomerization. More generally, these results provide a set of spatiotemporal constraints within polypeptide chains that favor efficient assembly, with implications for protein evolution and design.
]]></description>
<dc:creator>Eviatar Natan</dc:creator>
<dc:creator>Tamaki Endoh</dc:creator>
<dc:creator>Liora Haim-Vilmovsky</dc:creator>
<dc:creator>Guilhem Chalancon</dc:creator>
<dc:creator>Tilman Flock</dc:creator>
<dc:creator>Jonathan TS Hopper</dc:creator>
<dc:creator>Balint Kintses</dc:creator>
<dc:creator>Lejla Daruka</dc:creator>
<dc:creator>Gergely Fekete</dc:creator>
<dc:creator>Csaba Pal</dc:creator>
<dc:creator>Balazs Papp</dc:creator>
<dc:creator>Peter Horvath</dc:creator>
<dc:creator>Joseph A Marsh</dc:creator>
<dc:creator>Adrian H Elcock</dc:creator>
<dc:creator>M Madan Babu</dc:creator>
<dc:creator>Carol V Robinson</dc:creator>
<dc:creator>Naoki Sugimoto</dc:creator>
<dc:creator>Sarah A Teichmann</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-09-13</dc:date>
<dc:identifier>doi:10.1101/074963</dc:identifier>
<dc:title><![CDATA[Cotranslational assembly imposes evolutionary constraints on homomeric proteins]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-09-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/069633v1?rss=1">
<title>
<![CDATA[
scater: pre-processing, quality control, normalisation and visualisation of single-cell RNA-seq data in R 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/069633v1?rss=1"
</link>
<description><![CDATA[
MotivationSingle-cell RNA sequencing (scRNA-seq) is increasingly used to study gene expression at the level of individual cells. However, preparing raw sequence data for further analysis is not a straightforward process. Biases, artifacts, and other sources of unwanted variation are present in the data, requiring substantial time and effort to be spent on pre-processing, quality control (QC) and normalisation.nnResultsWe have developed the R/Bioconductor package scater to facilitate rigorous pre-processing, quality control, normalisation and visualisation of scRNA-seq data. The package provides a convenient, flexible workflow to process raw sequencing reads into a high-quality expression dataset ready for downstream analysis. scater provides a rich suite of plotting tools for single-cell data and a flexible data structure that is compatible with existing tools and can be used as infrastructure for future software development.nnAvailabilityThe open-source code, along with installation instructions, vignettes and case studies, is available through Bioconductor at http://bioconductor.org/packages/scater.nnSupplementary informationSupplementary material is available online at bioRxiv accompanying this manuscript, and all materials required to reproduce the results presented in this paper are available at dx.doi.org/10.5281/zenodo.60139.
]]></description>
<dc:creator>Davis J McCarthy</dc:creator>
<dc:creator>Kieran R Campbell</dc:creator>
<dc:creator>Aaron T L Lun</dc:creator>
<dc:creator>Quin F Wills</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-08-15</dc:date>
<dc:identifier>doi:10.1101/069633</dc:identifier>
<dc:title><![CDATA[scater: pre-processing, quality control, normalisation and visualisation of single-cell RNA-seq data in R]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-08-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/068668v1?rss=1">
<title>
<![CDATA[
Excitability in the p53 network mediates robust signaling with tunable activation thresholds in single cells 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/068668v1?rss=1"
</link>
<description><![CDATA[
Cellular signaling systems precisely transmit information in the presence of molecular noise while retaining flexibility to accommodate the needs of individual cells. To understand design principles underlying such versatile signaling, we analyzed the response of the tumor suppressor p53 to varying levels of DNA damage in hundreds of individual cells and observed a switch between distinct signaling modes characterized by isolated pulses and sustained oscillations of p53 accumulation. Guided by dynamic systems theory we show that this requires an excitable network structure comprising positive feedback and provide experimental evidence for its molecular identity. The resulting data-driven model reproduced all features of measured signaling responses and is sufficient to explain their heterogeneity in individual cells. We present evidence that heterogeneity in the levels of the feedback regulator Wip1 sets cell-specific thresholds for p53 activation, providing means to modulate its response through interacting signaling pathways. Our results demonstrate how excitable signaling networks can provide high specificity, sensitivity and robustness while retaining unique possibilities to adjust their function to the physiology of individual cells.
]]></description>
<dc:creator>Gregor Moenke</dc:creator>
<dc:creator>Elena Christiano</dc:creator>
<dc:creator>Ana Finzel</dc:creator>
<dc:creator>Dhana Friedrich</dc:creator>
<dc:creator>Hanspeter Herzel</dc:creator>
<dc:creator>Martin Falcke</dc:creator>
<dc:creator>Alexander Loewer</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-08-09</dc:date>
<dc:identifier>doi:10.1101/068668</dc:identifier>
<dc:title><![CDATA[Excitability in the p53 network mediates robust signaling with tunable activation thresholds in single cells]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-08-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/089581v1?rss=1">
<title>
<![CDATA[
Structural reorganization of the chromatin remodeling enzyme Chd1 upon engagement with nucleosomes. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/089581v1?rss=1"
</link>
<description><![CDATA[
The yeast Chd1 protein acts to position nucleosomes across genomes. Here we model the structure of the Chd1 protein in solution and when bound to nucleosomes. In the apo state the DNA binding domain contacts the edge of the nucleosome while in the presence of the non-hydrolyzable ATP analog, ADP-beryllium fluoride, we observe additional interactions between the ATPase domain and the adjacent DNA gyre 1.5 helical turns from the dyad axis of symmetry. Binding in this conformation involves unravelling the outer turn of nucleosomal DNA and requires substantial reorientation of the DNA binding domain with respect to the ATPase domains. The orientation of the DNA-binding domain is mediated by sequences in the N-terminus and mutations to this part of the protein have positive and negative effects on Chd1 activity. These observations indicate that the unfavourable alignment of C-terminal DNA binding region in solution contributes to an auto-inhibited state.
]]></description>
<dc:creator>Sundaramoorthy, R.</dc:creator>
<dc:creator>Hughes, A. L.</dc:creator>
<dc:creator>Singh, V.</dc:creator>
<dc:creator>Wiechens, N.</dc:creator>
<dc:creator>Ryan, D. P.</dc:creator>
<dc:creator>El-Mkami, H.</dc:creator>
<dc:creator>Petoukhov, M.</dc:creator>
<dc:creator>Svergun, D. I.</dc:creator>
<dc:creator>Treuutlein, B.</dc:creator>
<dc:creator>Fischer, M.</dc:creator>
<dc:creator>Michaelis, J.</dc:creator>
<dc:creator>Bottcher, B.</dc:creator>
<dc:creator>Norman, D. G.</dc:creator>
<dc:creator>Owen-Hughes, T.</dc:creator>
<dc:date>2016-11-26</dc:date>
<dc:identifier>doi:10.1101/089581</dc:identifier>
<dc:title><![CDATA[Structural reorganization of the chromatin remodeling enzyme Chd1 upon engagement with nucleosomes.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-11-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/024471v1?rss=1">
<title>
<![CDATA[
Gap gene regulatory dynamics evolve along a genotype network 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/024471v1?rss=1"
</link>
<description><![CDATA[
Developmental gene networks implement the dynamic regulatory mechanisms that pattern and shape the organism. Over evolutionary time, the wiring of these networks changes, yet the patterning outcome is often preserved, a phenomenon known as "system drift". System drift is illustrated by the gap gene network--involved in segmental patterning--in dipteran insects. In the classic model organism Drosophila melanogaster and the non-model scuttle fly Megaselia abdita, early activation and placement of gap gene expression domains show significant quantitative differences, yet the final patterning output of the system is essentially identical in both species. In this detailed modeling analysis of system drift, we use gene circuits which are fit to quantitative gap gene expression data in M. abdita and compare them to an equivalent set of models from D. melanogaster. The results of this comparative analysis show precisely how compensatory regulatory mechanisms achieve equivalent final patterns in both species. We discuss the larger implications of the work in terms of "genotype networks" and the ways in which the structure of regulatory networks can influence patterns of evolutionary change (evolvability).
]]></description>
<dc:creator>Anton Crombach</dc:creator>
<dc:creator>Karl R Wotton</dc:creator>
<dc:creator>Eva Jimenez-Guri</dc:creator>
<dc:creator>Johannes Jaeger</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-08-12</dc:date>
<dc:identifier>doi:10.1101/024471</dc:identifier>
<dc:title><![CDATA[Gap gene regulatory dynamics evolve along a genotype network]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-08-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/189704v1?rss=1">
<title>
<![CDATA[
A survey of DNA methylation polymorphism identifies environmentally responsive co-regulated networks of epigenetic variation in the human genome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/189704v1?rss=1"
</link>
<description><![CDATA[
While studies such as the 1000 Genomes Projects have resulted in detailed maps of genetic variation in humans, to date there are few robust maps of epigenetic variation. We defined sites of common epigenetic variation, termed Variably Methylated Regions (VMRs) in five purified cell types. We observed that VMRs occur preferentially at enhancers and 3 UTRs. While the majority of VMRs have high heritability, a subset of VMRs within the genome show highly correlated variation in trans, forming co-regulated networks that have low heritability, differ between cell types and are enriched for specific transcription factor binding sites and biological pathways of functional relevance to each tissue. For example, in T cells we defined a network of 72 co-regulated VMRs enriched for genes with roles in T-cell activation; in fibroblasts a network of 21 coregulated VMRs comprising all four HOX gene clusters enriched for control of tissue growth; and in neurons a network of 112 VMRs enriched for roles in learning and memory. By culturing genetically-identical fibroblasts under varying conditions of nutrient deprivation and cell density, we experimentally demonstrate that some VMR networks are responsive to environmental conditions, with methylation levels at these loci changing in a coordinated fashion in trans dependent on cellular growth. Intriguingly these environmentally-responsive VMRs showed a strong enrichment for imprinted loci (p<10-94), suggesting that these are particularly sensitive to environmental conditions. Our study provides a detailed map of common epigenetic variation in the human genome, showing that both genetic and environmental causes underlie this variation.
]]></description>
<dc:creator>Garg, P.</dc:creator>
<dc:creator>Joshi, R. S.</dc:creator>
<dc:creator>Watson, C.</dc:creator>
<dc:creator>Sharp, A. J.</dc:creator>
<dc:date>2017-09-15</dc:date>
<dc:identifier>doi:10.1101/189704</dc:identifier>
<dc:title><![CDATA[A survey of DNA methylation polymorphism identifies environmentally responsive co-regulated networks of epigenetic variation in the human genome]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/085738v1?rss=1">
<title>
<![CDATA[
GARFIELD - GWAS Analysis of Regulatory or Functional Information Enrichment with LD correction 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/085738v1?rss=1"
</link>
<description><![CDATA[
Loci discovered by genome-wide association studies (GWAS) predominantly map outside protein-coding genes. The interpretation of functional consequences of non-coding variants can be greatly enhanced by catalogs of regulatory genomic regions in cell lines and primary tissues. However, robust and readily applicable methods are still lacking to systematically evaluate the contribution of these regions to genetic variation implicated in diseases or quantitative traits. Here we propose a novel approach that leverages GWAS findings with regulatory or functional annotations to classify features relevant to a phenotype of interest. Within our framework, we account for major sources of confounding that current methods do not offer. We further assess enrichment statistics for 27 GWAS traits within regulatory regions from the ENCODE and Roadmap projects. We characterise unique enrichment patterns for traits and annotations, driving novel biological insights. The method is implemented in standalone software and R package to facilitate its application by the research community.
]]></description>
<dc:creator>Iotchkova, V.</dc:creator>
<dc:creator>Ritchie, G. R. S.</dc:creator>
<dc:creator>Geihs, M.</dc:creator>
<dc:creator>Morganella, S.</dc:creator>
<dc:creator>Min, J. L.</dc:creator>
<dc:creator>Walter, K.</dc:creator>
<dc:creator>Timpson, N. J.</dc:creator>
<dc:creator>UK10K Consortium,</dc:creator>
<dc:creator>Dunham, I.</dc:creator>
<dc:creator>Birney, E.</dc:creator>
<dc:creator>Soranzo, N.</dc:creator>
<dc:date>2016-11-07</dc:date>
<dc:identifier>doi:10.1101/085738</dc:identifier>
<dc:title><![CDATA[GARFIELD - GWAS Analysis of Regulatory or Functional Information Enrichment with LD correction]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-11-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/043430v1?rss=1">
<title>
<![CDATA[
Computational Pan-Genomics: Status, Promises and Challenges 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/043430v1?rss=1"
</link>
<description><![CDATA[
Many disciplines, from human genetics and oncology to plant breeding, microbiology and virology, commonly face the challenge of analyzing rapidly increasing numbers of genomes. In case of Homo sapiens, the number of sequenced genomes will approach hundreds of thousands in the next few years. Simply scaling up established bioinformatics pipelines will not be sufficient for leveraging the full potential of such rich genomic datasets. Instead, novel, qualitatively different computational methods and paradigms are needed. We will witness the rapid extension of computational pan-genomics, a new sub-area of research in computational biology. In this paper, we generalize existing definitions and understand a pan-genome as any collection of genomic sequences to be analyzed jointly or to be used as a reference. We examine already available approaches to construct and use pan-genomes, discuss the potential benefits of future technologies and methodologies, and review open challenges from the vantage point of the above-mentioned biological disciplines. As a prominent example for a computational paradigm shift, we particularly highlight the transition from the representation of reference genomes as strings to representations as graphs. We outline how this and other challenges from different application domains translate into common computational problems, point out relevant bioinformatics techniques and identify open problems in computer science. With this review, we aim to increase awareness that a joint approach to computational pan-genomics can help address many of the problems currently faced in various domains.
]]></description>
<dc:creator>Tobias Marschall</dc:creator>
<dc:creator>Manja Marz</dc:creator>
<dc:creator>Thomas Abeel</dc:creator>
<dc:creator>Louis Dijkstra</dc:creator>
<dc:creator>Bas E Dutilh</dc:creator>
<dc:creator>Ali Ghaffaari</dc:creator>
<dc:creator>Paul Kersey</dc:creator>
<dc:creator>Wigard Kloosterman</dc:creator>
<dc:creator>Veli Makinen</dc:creator>
<dc:creator>Adam Novak</dc:creator>
<dc:creator>Benedict Paten</dc:creator>
<dc:creator>David Porubsky</dc:creator>
<dc:creator>Eric RIVALS</dc:creator>
<dc:creator>Can Alkan</dc:creator>
<dc:creator>Jasmijn Baaijens</dc:creator>
<dc:creator>Paul I. W. de Bakker</dc:creator>
<dc:creator>Valentina Boeva</dc:creator>
<dc:creator>Raoul J.P. Bonnal</dc:creator>
<dc:creator>Francesca Chiaromonte</dc:creator>
<dc:creator>Rayan Chikhi</dc:creator>
<dc:creator>Francesca D. Ciccarelli</dc:creator>
<dc:creator>Robin Cijvat</dc:creator>
<dc:creator>Erwin Datema</dc:creator>
<dc:creator>Cornelia M. Van Duijn</dc:creator>
<dc:creator>Evan E. Eichler</dc:creator>
<dc:creator>Corinna Ernst</dc:creator>
<dc:creator>Eleazar Eskin</dc:creator>
<dc:creator>Erik Garrison</dc:creator>
<dc:creator>Mohammed El-Kebir</dc:creator>
<dc:creator>Gunnar W. Klau</dc:creator>
<dc:creator>Jan O Korbel</dc:creator>
<dc:creator>Eric-Wubbo Lameijer</dc:creator>
<dc:creator>Ben Langmead</dc:creator>
<dc:creator>Marcel Martin</dc:creator>
<dc:creator>Paul Medvedev</dc:creator>
<dc:creator>John C. Mu</dc:creator>
<dc:creator>Pieter Neerincx</dc:creator>
<dc:creator>Klaasjan Ouwens</dc:creator>
<dc:creator>Pierre Peterlongo</dc:creator>
<dc:creator>Pisan</dc:creator>
<dc:date>2016-03-12</dc:date>
<dc:identifier>doi:10.1101/043430</dc:identifier>
<dc:title><![CDATA[Computational Pan-Genomics: Status, Promises and Challenges]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-03-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/195297v1?rss=1">
<title>
<![CDATA[
Fibril branching dominates self-assembly of mutant huntingtin exon-1 aggregates in vitro 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/195297v1?rss=1"
</link>
<description><![CDATA[
Huntingtin (HTT) fragments with extended polyglutamine (polyQ) tracts self-assemble into amyloid-like fibrillar aggregates. Elucidating the fibril formation mechanism is critical for understanding Huntingtons disease pathology and for developing novel therapeutic strategies. Here, we performed systematic experimental and theoretical studies to examine the self-assembly of an aggregation-prone N-terminal HTT exon-1 fragment with 49 glutamines (Ex1Q49). Using high resolution imaging techniques such as electron microscopy and atomic force microscopy, we show that Ex1Q49 fragments in cell-free assays spontaneously convert into large, highly complex bundles of amyloid fibrils with multiple ends and fibril branching points. Furthermore, we present experimental evidence that two nucleation mechanisms control spontaneous Ex1Q49 fibrillogenesis: (1) a relatively slow primary fibril-independent nucleation process, which involves the spontaneous formation of aggregation-competent fibrillary structures, and (2) a fast secondary fibril-dependent nucleation process, which involves nucleated branching and promotes the rapid assembly of highly complex fibril bundles with multiple ends. The proposed aggregation mechanism is supported by studies with the small molecule O4, which perturbs early events in the aggregation cascade and delays Ex1Q49 fibril assembly, comprehensive mathematical and computational modelling studies, and seeding experiments with small, preformed fibrillar Ex1Q49 aggregates that promote the assembly of amyloid fibrils. Together, our results suggest that nucleated branching in vitro plays a critical role in the formation of complex fibrillar HTT exon-1 aggregates with multiple ends.
]]></description>
<dc:creator>Wagner, A. S.</dc:creator>
<dc:creator>Politi, A. Z.</dc:creator>
<dc:creator>Steinhof, A.</dc:creator>
<dc:creator>Bravo-Rodriguez, K.</dc:creator>
<dc:creator>Buntru, A.</dc:creator>
<dc:creator>Strempel, N. U.</dc:creator>
<dc:creator>Brusendorf, L.</dc:creator>
<dc:creator>Haenig, C.</dc:creator>
<dc:creator>Boeddrich, A.</dc:creator>
<dc:creator>Plassmann, S.</dc:creator>
<dc:creator>Ramirez-Anguita, J. M.</dc:creator>
<dc:creator>Baum, K.</dc:creator>
<dc:creator>Sanchez-Garcia, E.</dc:creator>
<dc:creator>Wolf, J.</dc:creator>
<dc:creator>Wanker, E. E.</dc:creator>
<dc:date>2017-10-19</dc:date>
<dc:identifier>doi:10.1101/195297</dc:identifier>
<dc:title><![CDATA[Fibril branching dominates self-assembly of mutant huntingtin exon-1 aggregates in vitro]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/203497v1?rss=1">
<title>
<![CDATA[
Csde1 binds transcripts involved in protein homeostasis and controls their expression in erythropoiesis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/203497v1?rss=1"
</link>
<description><![CDATA[
Expression of the RNA-binding protein Csde1 (Cold shock domain protein e1) is strongly upregulated during erythropoiesis compared to other hematopoietic lineages. In the severe congenital anemia Diamond Blackfan Anemia (DBA), however, Csde1 expression is impaired. Reduced expression of Csde1 in healthy erythroblasts impaired their proliferation and differentiation, which suggests an important role for Csde1 in erythropoiesis. To investigate the cellular pathways controlled by Csde1 in erythropoiesis, we identified the transcripts that physically associate with Csde1 in erythroid cells. These mainly encoded proteins involved in ribogenesis, mRNA translation and protein degradation, but also proteins associated with the mitochondrial respiratory chain and mitosis. Crispr/Cas9-mediated deletion of the first cold shock domain of Csde1 affected RNA expression and/or protein expression of Csde1-bound transcripts. For instance, protein expression of Pabpc1 was enhanced while Pabpc1 mRNA expression was reduced indicating more efficient translation of Pabpc1 followed by negative feedback on mRNA stability. Overall, the effect of reduced Csde1 function on mRNA stability and translation of Csde1-bound transcripts was modest. Clones with complete loss of Csde1, however, could not be generated. We suggest that Csde1 is involved in feed-back control in protein homeostasis and that it dampens stochastic changes in mRNA expression.
]]></description>
<dc:creator>Moore, K. S.</dc:creator>
<dc:creator>Yagci, N.</dc:creator>
<dc:creator>van Alphen, F.</dc:creator>
<dc:creator>Paolini, N. A.</dc:creator>
<dc:creator>horos, R.</dc:creator>
<dc:creator>Held, N. M.</dc:creator>
<dc:creator>Houtkooper, R. H.</dc:creator>
<dc:creator>van den Akker, E.</dc:creator>
<dc:creator>Meijer, A. B.</dc:creator>
<dc:creator>'t Hoen, P. A. C.</dc:creator>
<dc:creator>von Lindern, M.</dc:creator>
<dc:date>2017-10-15</dc:date>
<dc:identifier>doi:10.1101/203497</dc:identifier>
<dc:title><![CDATA[Csde1 binds transcripts involved in protein homeostasis and controls their expression in erythropoiesis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/092874v1?rss=1">
<title>
<![CDATA[
Genetic variation and gene expression across multiple tissues and developmental stages in a non-human primate 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/092874v1?rss=1"
</link>
<description><![CDATA[
By analyzing multi-tissue gene expression and genome-wide genetic variation data in samples from a vervet monkey pedigree, we generated a transcriptome resource and produced the first catalogue of expression quantitative trait loci (eQTLs) in a non-human primate model. This catalogue contains more genome-wide significant eQTLs, per sample, than comparable human resources, and reveals sex and age-related expression patterns. Findings include a master regulatory locus that likely plays a role in immune function, and a locus regulating hippocampal long non-coding RNAs (lncRNAs), whose expression correlates with hippocampal volume. This resource will facilitate genetic investigation of quantitative traits, including brain and behavioral phenotypes relevant to neuropsychiatric disorders.
]]></description>
<dc:creator>Jasinska, A. J.</dc:creator>
<dc:creator>Zelaya, I.</dc:creator>
<dc:creator>Service, S. K.</dc:creator>
<dc:creator>Peterson, C.</dc:creator>
<dc:creator>Cantor, R. M.</dc:creator>
<dc:creator>Choi, O.-W.</dc:creator>
<dc:creator>DeYoung, J.</dc:creator>
<dc:creator>Eskin, E.</dc:creator>
<dc:creator>Fairbanks, L. A.</dc:creator>
<dc:creator>Fears, S.</dc:creator>
<dc:creator>Furterer, A.</dc:creator>
<dc:creator>Huang, Y. S.</dc:creator>
<dc:creator>Ramensky, V.</dc:creator>
<dc:creator>Schmitt, C. A.</dc:creator>
<dc:creator>Svardal, H.</dc:creator>
<dc:creator>Jorgensen, M. J.</dc:creator>
<dc:creator>Kaplan, J. R.</dc:creator>
<dc:creator>Villar, D.</dc:creator>
<dc:creator>Aken, B. L.</dc:creator>
<dc:creator>Flicek, P.</dc:creator>
<dc:creator>Nag, R.</dc:creator>
<dc:creator>Wong, E. S.</dc:creator>
<dc:creator>Blangero, J.</dc:creator>
<dc:creator>Dyer, T. D.</dc:creator>
<dc:creator>Bogomolov, M.</dc:creator>
<dc:creator>Benjamini, Y.</dc:creator>
<dc:creator>Weinstock, G. M.</dc:creator>
<dc:creator>Dewar, K.</dc:creator>
<dc:creator>Sabatti, C.</dc:creator>
<dc:creator>Wilson, R. K.</dc:creator>
<dc:creator>Jentsch, J. D.</dc:creator>
<dc:creator>Warren, W.</dc:creator>
<dc:creator>Coppola, G.</dc:creator>
<dc:creator>Woods, R. P.</dc:creator>
<dc:creator>Freimer, N. B.</dc:creator>
<dc:date>2016-12-09</dc:date>
<dc:identifier>doi:10.1101/092874</dc:identifier>
<dc:title><![CDATA[Genetic variation and gene expression across multiple tissues and developmental stages in a non-human primate]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-12-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/277335v1?rss=1">
<title>
<![CDATA[
The human leukemia virus HTLV-1 alters the structure and transcription of host chromatin in cis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/277335v1?rss=1"
</link>
<description><![CDATA[
Chromatin looping controls gene expression by regulating promoter-enhancer contacts, the spread of epigenetic modifications, and the segregation of the genome into transcriptionally active and inactive compartments. We studied the impact on the structure and expression of host chromatin by the human retrovirus HTLV-1. We show that HTLV-1 disrupts host chromatin structure by forming loops between the provirus and the host genome; certain loops depend on the critical chromatin architectural protein CTCF, which we recently showed binds to the HTLV-1 provirus. Finally, we show that the provirus causes two distinct patterns of abnormal transcription of the host genome in cis: bidirectional transcription in the host genome immediately flanking the provirus, and clone-specific transcription in cis at non-contiguous loci up to >300 kb from the integration site. We conclude that HTLV-1 causes insertional mutagenesis up to the megabase range in the host genome in >104 persistently-maintained HTLV-1+ T-cell clones in vivo.
]]></description>
<dc:creator>Melamed, A.</dc:creator>
<dc:creator>Yaguchi, H.</dc:creator>
<dc:creator>Miura, M.</dc:creator>
<dc:creator>Witkover, A.</dc:creator>
<dc:creator>Fitzgerald, T. W.</dc:creator>
<dc:creator>Birney, E.</dc:creator>
<dc:creator>Bangham, C. R. M.</dc:creator>
<dc:date>2018-03-07</dc:date>
<dc:identifier>doi:10.1101/277335</dc:identifier>
<dc:title><![CDATA[The human leukemia virus HTLV-1 alters the structure and transcription of host chromatin in cis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/093369v1?rss=1">
<title>
<![CDATA[
Chromosomal rearrangements are commonly post-transcriptionally attenuated in cancer 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/093369v1?rss=1"
</link>
<description><![CDATA[
Chromosomal rearrangements, despite being detrimental, are ubiquitous in cancer and often act as driver events. The effect of copy number variations (CNVs) on the cellular proteome of tumours is poorly understood. Therefore, we have analysed recently generated proteogenomic data-sets on 282 tumour samples to investigate the impact of CNVs in the proteome of these cells. We found that CNVs are post-transcriptionally attenuated in 23-33% of proteins with an enrichment for protein complexes. Complex subunits are highly co-regulated and some act as rate-limiting steps of complex assembly, indirectly controlling the abundance of other complex members. We identified 48 such regulatory interactions and experimentally validated AP3B1 and GTF2E2 as controlling subunits. Lastly, we found that a gene-signature of protein attenuation is associated with increased resistance to chaperone and proteasome inhibitors. This study highlights the importance of post-transcriptional mechanisms in cancer which allow cells to cope with their altered genomes.
]]></description>
<dc:creator>Goncalves, E.</dc:creator>
<dc:creator>Fraguais, A.</dc:creator>
<dc:creator>Garcia-Alonso, L.</dc:creator>
<dc:creator>Cramer, T.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:creator>Beltrao, P.</dc:creator>
<dc:date>2016-12-12</dc:date>
<dc:identifier>doi:10.1101/093369</dc:identifier>
<dc:title><![CDATA[Chromosomal rearrangements are commonly post-transcriptionally attenuated in cancer]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-12-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/107631v1?rss=1">
<title>
<![CDATA[
A high-resolution mRNA expression time course of embryonic development in zebrafish 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/107631v1?rss=1"
</link>
<description><![CDATA[
We have produced an mRNA expression time course of zebrafish development across 18 time points from 1-cell to 5 days post-fertilisation sampling individual and pools of embryos. Using poly(A) pulldown stranded RNA-seq and a 3' end transcript counting method we characterise the temporal expression profiles of 23,642 genes. We identify temporal and functional transcript co-variance that associates 5,024 unnamed genes with distinct developmental time points. Specifically, a class of over 100 previously uncharacterised zinc finger domain containing genes, located on the long arm of chromosome 4, is expressed in a sharp peak during zygotic genome activation. The data reveal complex and widespread differential use of exons and previously unidentified 3' ends across development, new primary microRNA transcripts and temporal divergence of gene paralogues generated in the teleost genome duplication. To make this dataset a useful baseline reference, the data are accessible to browse and download at Expression Atlas and Ensembl.
]]></description>
<dc:creator>White, R. J.</dc:creator>
<dc:creator>Collins, J. E.</dc:creator>
<dc:creator>Sealy, I. M.</dc:creator>
<dc:creator>Wali, N.</dc:creator>
<dc:creator>Dooley, C. M.</dc:creator>
<dc:creator>Digby, Z.</dc:creator>
<dc:creator>Murphy, D. N.</dc:creator>
<dc:creator>Hourlier, T.</dc:creator>
<dc:creator>Fullgrabe, A.</dc:creator>
<dc:creator>Davis, M. P.</dc:creator>
<dc:creator>Enright, A. J.</dc:creator>
<dc:creator>Busch-Nentwich, E. M.</dc:creator>
<dc:date>2017-02-10</dc:date>
<dc:identifier>doi:10.1101/107631</dc:identifier>
<dc:title><![CDATA[A high-resolution mRNA expression time course of embryonic development in zebrafish]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-02-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/176024v1?rss=1">
<title>
<![CDATA[
Integrative analysis of large scale transcriptome data draws a comprehensive landscape of Phaeodactylum tricornutum functional genome and evolutionary origin of diatoms 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/176024v1?rss=1"
</link>
<description><![CDATA[
Diatoms are one of the most successful and ecologically important groups of eukaryotic phytoplankton in the modern ocean. Deciphering their genomes is a key step towards better understanding of their biological innovations, evolutionary origins, and ecological underpinnings. Here, we have used 90 RNA-Seq datasets from different growth conditions combined with published expressed sequence tags and protein sequences from multiple taxa to explore the genome of the model diatom Phaeodactylum tricornutum, and introduce 1,489 novel genes. The new annotation additionally permitted the discovery for the first time of extensive alternative splicing (AS) in diatoms, including intron retention and exon skipping which increases the diversity of transcripts to regulate gene expression in response to nutrient limitations. In addition, we have used up-to-date reference sequence libraries to dissect the taxonomic origins of diatom genomes. We show that the P. tricornutum genome is replete in lineage-specific genes, with up to 47% of the gene models present only possessing orthologues in other stramenopile groups. Finally, we have performed a comprehensive de novo annotation of repetitive elements showing novel classes of TEs such as SINE, MITE, LINE and TRIM/LARD. This work provides a solid foundation for future studies of diatom gene function, evolution and ecology.
]]></description>
<dc:creator>Rastogi, A.</dc:creator>
<dc:creator>Maheswari, U.</dc:creator>
<dc:creator>Dorrell, R. G.</dc:creator>
<dc:creator>Maumus, F.</dc:creator>
<dc:creator>Rocha Jimenez Vieira, F.</dc:creator>
<dc:creator>Kustka, A.</dc:creator>
<dc:creator>McCarthy, J.</dc:creator>
<dc:creator>Allen, A. E.</dc:creator>
<dc:creator>Kersey, P.</dc:creator>
<dc:creator>Bowler, C.</dc:creator>
<dc:creator>Tirichine, L.</dc:creator>
<dc:date>2017-08-14</dc:date>
<dc:identifier>doi:10.1101/176024</dc:identifier>
<dc:title><![CDATA[Integrative analysis of large scale transcriptome data draws a comprehensive landscape of Phaeodactylum tricornutum functional genome and evolutionary origin of diatoms]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/102285v1?rss=1">
<title>
<![CDATA[
Tex19.1 Regulates Acetylated SMC3 Cohesin and Prevents Aneuploidy in Mouse Oocytes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/102285v1?rss=1"
</link>
<description><![CDATA[
Age-dependent oocyte aneuploidy, a major cause of Down syndrome, is associated with declining sister chromatid cohesion in postnatal oocytes. Here we show that cohesion in postnatal mouse oocytes is regulated by Tex19.1. We show that Tex19.1-/- oocytes have defects in the maintenance of chiasmata, mis-segregate their chromosomes during meiosis, and transmit aneuploidies to the next generation. By reconstituting aspects of this pathway in mitotic somatic cells, we show that Tex19.1 regulates an acetylated SMC3-marked subpopulation of cohesin by inhibiting the activity of the E3 ubiquitin ligase UBR2 towards specific substrates, and that UBR2 itself has a previously undescribed role in negatively regulating acetylated SMC3. Lastly, we show that acetylated SMC3 is associated with meiotic chromosome axes in oocytes, but that this is reduced in the absence of Tex19.1. These findings indicate that Tex19.1 maintains acetylated SMC3 and sister chromatid cohesion in postnatal oocytes, and prevents aneuploidy in the female germline.
]]></description>
<dc:creator>Reichmann, J.</dc:creator>
<dc:creator>Dobie, K.</dc:creator>
<dc:creator>Lister, L. M.</dc:creator>
<dc:creator>Best, D.</dc:creator>
<dc:creator>Crichton, J. H.</dc:creator>
<dc:creator>MacLennan, M.</dc:creator>
<dc:creator>Read, D.</dc:creator>
<dc:creator>Raymond, E. S.</dc:creator>
<dc:creator>Hung, C.-C.</dc:creator>
<dc:creator>Boyle, S.</dc:creator>
<dc:creator>Shirahige, K.</dc:creator>
<dc:creator>Cooke, H. J.</dc:creator>
<dc:creator>Bickmore, W. A.</dc:creator>
<dc:creator>Herbert, M.</dc:creator>
<dc:creator>Adams, I. R.</dc:creator>
<dc:date>2017-02-07</dc:date>
<dc:identifier>doi:10.1101/102285</dc:identifier>
<dc:title><![CDATA[Tex19.1 Regulates Acetylated SMC3 Cohesin and Prevents Aneuploidy in Mouse Oocytes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-02-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/216630v1?rss=1">
<title>
<![CDATA[
Condensin’s ATPase Machinery Drives and Dampens Mitotic Chromosome Condensation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/216630v1?rss=1"
</link>
<description><![CDATA[
Chromosome condensation by condensin is essential for faithful chromosome segregation. Metazoans have two complexes, named condensin I and II. Both are thought to act by creating looped structures in DNA, but how they do so is unknown. Condensins SMC subunits together form a composite ATPase with two pseudo-symmetric ATPase sites. We reveal that these sites have opposite functions in the condensation process. One site drives condensation, while the other site rather has a dampening function. Mutation of this dampener site hyperactivates both condensin I and II complexes. We find that hyperactive condensin I efficiently shortens chromosomes in the total absence of condensin II. The two complexes form loops with different lengths, and specifically condensin II is key to the decatenation of sister chromatids and the formation of a straight chromosomal axis.
]]></description>
<dc:creator>Elbatsh, A. M. O.</dc:creator>
<dc:creator>Raaijmakers, J. A.</dc:creator>
<dc:creator>van der Weide, R. H.</dc:creator>
<dc:creator>uit de Bos, J.</dc:creator>
<dc:creator>Teunissen, H.</dc:creator>
<dc:creator>Bravo, S.</dc:creator>
<dc:creator>Medema, R. H.</dc:creator>
<dc:creator>de Wit, E.</dc:creator>
<dc:creator>Haering, C. H.</dc:creator>
<dc:creator>Rowland, B. D.</dc:creator>
<dc:date>2017-11-08</dc:date>
<dc:identifier>doi:10.1101/216630</dc:identifier>
<dc:title><![CDATA[Condensin’s ATPase Machinery Drives and Dampens Mitotic Chromosome Condensation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/074310v1?rss=1">
<title>
<![CDATA[
Re-evaluation of SNP heritability in complex human traits 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/074310v1?rss=1"
</link>
<description><![CDATA[
SNP heritability, the proportion of phenotypic variance explained by SNPs, has been reported for many hundreds of traits. Its estimation requires strong prior assumptions about the distribution of heritability across the genome, but the assumptions in current use have not been thoroughly tested. By analyzing imputed data for a large number of human traits, we empirically derive a model that more accurately describes how heritability varies with minor allele frequency, linkage disequilibrium and genotype certainty. Across 19 traits, our improved model leads to estimates of common SNP heritability on average 43% (SD 3) higher than those obtained from the widely-used software GCTA, and 25% (SD 2) higher than those from the recently-proposed extension GCTA-LDMS. Previously, DNaseI hypersensitivity sites were reported to explain 79% of SNP heritability; using our improved heritability model their estimated contribution is only 24%.
]]></description>
<dc:creator>Doug Speed</dc:creator>
<dc:creator>Na Cai</dc:creator>
<dc:creator>The UCLEB Consortium</dc:creator>
<dc:creator>Michael Johnson</dc:creator>
<dc:creator>Sergey Nejentsev</dc:creator>
<dc:creator>David Balding</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-09-09</dc:date>
<dc:identifier>doi:10.1101/074310</dc:identifier>
<dc:title><![CDATA[Re-evaluation of SNP heritability in complex human traits]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-09-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/101311v1?rss=1">
<title>
<![CDATA[
Functional regulatory evolution outside of the minimal even-skipped stripe 2 enhancer 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/101311v1?rss=1"
</link>
<description><![CDATA[
Transcriptional enhancers are regions of DNA that drive gene expression at precise times, levels, and locations. While many studies have elucidated how individual enhancers can evolve, most of this work has focused on what are called "minimal" enhancers, the smallest DNA regions that drive expression that approximates an aspect of native gene expression. Here we explore how the Drosophila erecta even-skipped (eve) locus has evolved by testing its activity in the divergent D. melanogaster genome. We found, as has been reported previously, that the minimal D. erecta eve stripe 2 enhancer (eveS2) fails to drive appreciable expression in D. melanogaster [1]. However, we found that a large transgene carrying the entire D. erecta eve locus drives normal eve expression, including in stripe 2. We performed a functional dissection of the region upstream of the D. erecta eveS2 region and found that regulatory information outside of the minimal D. erecta eveS2 contains multiple Zelda motifs that are required for normal expression. Our results illustrate how sequences outside of minimal enhancer regions can evolve functionally through mechanisms other than changes in transcription factor binding sites that drive patterning.
]]></description>
<dc:creator>Crocker, J.</dc:creator>
<dc:creator>Stern, D. L.</dc:creator>
<dc:date>2017-01-18</dc:date>
<dc:identifier>doi:10.1101/101311</dc:identifier>
<dc:title><![CDATA[Functional regulatory evolution outside of the minimal even-skipped stripe 2 enhancer]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-01-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/170811v1?rss=1">
<title>
<![CDATA[
A synthetic biology approach to probing nucleosome symmetry 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/170811v1?rss=1"
</link>
<description><![CDATA[
The repeating subunit of chromatin, the nucleosome, includes two copies of each of the four core histones, and several recent studies have reported that asymmetrically-modified nucleosomes occur at regulatory elements in vivo. To probe the mechanisms by which histone modifications are read out, we designed an obligate pair of H3 heterodimers, termed H3X and H3Y, which we extensively validated genetically and biochemically. Comparing the effects of asymmetric histone tail point mutants with those of symmetric double mutants revealed that a single methylated H3K36 per nucleosome was sufficient to silence cryptic transcription in vivo. We also demonstrate the utility of this system for analysis of histone modification crosstalk, using mass spectrometry to separately identify modifications on each H3 molecule within asymmetric nucleosomes. The ability to generate asymmetric nucleosomes in vivo and in vitro provides a powerful and generalizable tool to probe the mechanisms by which H3 tails are read out by effector proteins in the cell.
]]></description>
<dc:creator>Ichikawa, Y.</dc:creator>
<dc:creator>Connelly, C. F.</dc:creator>
<dc:creator>Appleboim, A.</dc:creator>
<dc:creator>Jacobi, H.</dc:creator>
<dc:creator>Abshiru, N. A.</dc:creator>
<dc:creator>Chou, H.-J.</dc:creator>
<dc:creator>Chen, Y.</dc:creator>
<dc:creator>Sharma, U.</dc:creator>
<dc:creator>Zheng, Y.</dc:creator>
<dc:creator>Thomas, P. M.</dc:creator>
<dc:creator>Chen, H. V.</dc:creator>
<dc:creator>Bajaj, V.</dc:creator>
<dc:creator>Kelleher, N. L.</dc:creator>
<dc:creator>Friedman, N.</dc:creator>
<dc:creator>Bolon, D. N.</dc:creator>
<dc:creator>Rando, O. J.</dc:creator>
<dc:creator>Kaufman, P. D.</dc:creator>
<dc:date>2017-07-31</dc:date>
<dc:identifier>doi:10.1101/170811</dc:identifier>
<dc:title><![CDATA[A synthetic biology approach to probing nucleosome symmetry]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/099861v1?rss=1">
<title>
<![CDATA[
Genomic rearrangements near genes leading to upregulation across a diverse subset of human cancers 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/099861v1?rss=1"
</link>
<description><![CDATA[
Using a dataset of somatic Structural Variants (SVs) in cancers from 2658 patients--1220 with corresponding gene expression data--we identified hundreds of genes for which the nearby presence (within 100kb) of an SV breakpoint was associated with altered expression. For the vast majority of these genes, expression was increased rather than decreased with corresponding SV event. Well-known up-regulated cancer-associated genes impacted by this phenomenon included TERT, MDM2, CDK4, ERBB2, CD274, PDCD1LG2, and IGF2. SVs upstream of TERT involved ~3% of cancer cases and were most frequent in liver-biliary, melanoma, sarcoma, stomach, and kidney cancers. SVs associated with up-regulation of PD1 and PDL1 genes involved ~1% of non-amplified cases. For many genes, SVs were significantly associated with either increased numbers or greater proximity of enhancer regulatory elements near the gene. DNA methylation near the gene promoter was often increased with nearby SV breakpoint, which may involve inactivation of repressor elements.nnAbbreviations
]]></description>
<dc:creator>Creighton, C.</dc:creator>
<dc:creator>Zhang, Y.</dc:creator>
<dc:creator>Chen, F.</dc:creator>
<dc:date>2017-01-12</dc:date>
<dc:identifier>doi:10.1101/099861</dc:identifier>
<dc:title><![CDATA[Genomic rearrangements near genes leading to upregulation across a diverse subset of human cancers]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-01-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/064535v1?rss=1">
<title>
<![CDATA[
A scored human protein-protein interaction network to catalyze genomic interpretation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/064535v1?rss=1"
</link>
<description><![CDATA[
Human protein-protein interaction networks are critical to understanding cell biology and interpreting genetic and genomic data, but are challenging to produce in individual large-scale experiments. We describe a general computational framework that through data integration and quality control provides a scored human protein-protein interaction network (InWeb_IM). Juxtaposed with five comparable resources, InWeb_IM has 2.8 times more interactions (~585K) and a superior functional signal showing that the added interactions reflect real cellular biology. InWeb_IM is a versatile resource for accurate and cost-efficient functional interpretation of massive genomic datasets illustrated by annotating candidate genes from >4,700 cancer genomes and genes involved in neuropsychiatric diseases.
]]></description>
<dc:creator>Taibo Li</dc:creator>
<dc:creator>Rasmus Wernersson</dc:creator>
<dc:creator>Rasmus Borup Hansen</dc:creator>
<dc:creator>Heiko Horn</dc:creator>
<dc:creator>Johnathan M Mercer</dc:creator>
<dc:creator>Greg Slodkowicz</dc:creator>
<dc:creator>Christopher Workman</dc:creator>
<dc:creator>Olga Regina</dc:creator>
<dc:creator>Kristoffer Rapacki</dc:creator>
<dc:creator>Hans-Henrik Staerfeldt</dc:creator>
<dc:creator>Soren Brunak</dc:creator>
<dc:creator>Thomas S Jensen</dc:creator>
<dc:creator>Kasper Lage</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-07-19</dc:date>
<dc:identifier>doi:10.1101/064535</dc:identifier>
<dc:title><![CDATA[A scored human protein-protein interaction network to catalyze genomic interpretation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-07-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/057398v1?rss=1">
<title>
<![CDATA[
Systematic analysis of transcriptional and post-transcriptional regulation of metabolism in yeast 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/057398v1?rss=1"
</link>
<description><![CDATA[
Cells react to extracellular perturbations with complex and intertwined responses. Systematic identification of the regulatory mechanisms that control these responses is still a challenge and requires tailored analyses integrating different types of molecular data. Here we acquired time-resolved metabolomics measurements in yeast under salt and pheromone stimulation and developed a machine learning approach to explore regulatory associations between metabolism and signal transduction. Existing phosphoproteomics measurements under the same conditions and kinase-substrate regulatory interactions were used to estimate the enzymatic activity of signalling kinases. Our approach identified informative associations between kinases and metabolic enzymes capable of predicting metabolic changes. We extended our analysis to two studies containing transcriptomics, phosphoproteomics and metabolomics measurements across a comprehensive panel of kinases/phosphatases knockouts and time-resolved perturbations to the nitrogen metabolism, conveying a total of 143 unique conditions. Our approach accurately estimated the change in activity of transcription factors, kinases and phosphatases and these were capable of building predictive models to infer the metabolic adaptations of previously unseen conditions across different dynamic experiments. Time-resolved experiments were significantly more informative than genetic perturbations to infer metabolic adaptation. This difference may be due to the indirect nature of the associations and of general cellular states that can hinder the identification of causal relationships. This work provides a novel genome-scale integrative analysis to propose putative transcriptional and post-translational regulatory mechanisms of metabolic processes.
]]></description>
<dc:creator>Emanuel Gonçalves</dc:creator>
<dc:creator>Zrinka Raguz</dc:creator>
<dc:creator>Mattia Zampieri</dc:creator>
<dc:creator>Omar Wagih</dc:creator>
<dc:creator>David Ochoa</dc:creator>
<dc:creator>Uwe Sauer</dc:creator>
<dc:creator>Pedro Beltrao</dc:creator>
<dc:creator>Julio Saez-Rodriguez</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-06-23</dc:date>
<dc:identifier>doi:10.1101/057398</dc:identifier>
<dc:title><![CDATA[Systematic analysis of transcriptional and post-transcriptional regulation of metabolism in yeast]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-06-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/149153v1?rss=1">
<title>
<![CDATA[
Mutational signatures of DNA mismatch repair deficiency in C. elegans and human cancers 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/149153v1?rss=1"
</link>
<description><![CDATA[
1.Throughout their lifetime cells are subject to extrinsic and intrinsic mutational processes leaving behind characteristic signatures in the genome. One of these, DNA mismatch repair (MMR) deficiency leads to hypermutation and is found in different cancer types. While it is possible to associate mutational signatures extracted from human cancers with possible mutational processes the exact causation is often unknown. Here we use C. elegans genome sequencing of pms-2 and mlh-1 knockouts to reveal the mutational patterns linked to C. elegans MMR deficiency and their dependency on endogenous replication errors and errors caused by deletion of the polymerase {varepsilon} subunit pole-4. Signature extraction from 215 human colorectal and 289 gastric adenocarcinomas revealed three MMR-associated signatures one of which closely resembles the C. elegans MMR spectrum. A characteristic difference between human and worm MMR deficiency is the lack of elevated levels of NCG>NTG mutations in C. elegans, likely caused by the absence of cytosine (CpG) methylation in worms. The other two human MMR signatures may reflect the interaction between MMR deficiency and other mutagenic processes, but their exact cause remains unknown. In summary, combining information from genetically defined models and cancer samples allows for better aligning mutational signatures to causal mutagenic processes.
]]></description>
<dc:creator>Meier, B.</dc:creator>
<dc:creator>Volkova, N.</dc:creator>
<dc:creator>Hong, Y.</dc:creator>
<dc:creator>Schofield, P.</dc:creator>
<dc:creator>Campbell, P. J.</dc:creator>
<dc:creator>Gerstung, M.</dc:creator>
<dc:creator>Gartner, A.</dc:creator>
<dc:date>2017-06-13</dc:date>
<dc:identifier>doi:10.1101/149153</dc:identifier>
<dc:title><![CDATA[Mutational signatures of DNA mismatch repair deficiency in C. elegans and human cancers]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/181339v1?rss=1">
<title>
<![CDATA[
Patterns of structural variation in human cancer 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/181339v1?rss=1"
</link>
<description><![CDATA[
A key mutational process in cancer is structural variation, in which rearrangements delete, amplify or reorder genomic segments ranging in size from kilobases to whole chromosomes. We developed methods to group, classify and describe structural variants, applied to >2,500 cancer genomes. Nine signatures of structural variation emerged. Deletions have trimodal size distribution; assort unevenly across tumour types and patients; enrich in late-replicating regions; and correlate with inversions. Tandem duplications also have trimodal size distribution, but enrich in early-replicating regions, as do unbalanced translocations. Replication-based mechanisms of rearrangement generate varied chromosomal structures with low-level copy number gains and frequent inverted rearrangements. One prominent structure consists of 1-7 templates copied from distinct regions of the genome strung together within one locus. Such  cycles of templated insertions correlate with tandem duplications, frequently activating the telomerase gene, TERT, in liver cancer. Cancers access many rearrangement processes, flexibly sculpting the genome to maximise oncogenic potential.
]]></description>
<dc:creator>Li, Y.</dc:creator>
<dc:creator>Roberts, N.</dc:creator>
<dc:creator>Weischenfeldt, J.</dc:creator>
<dc:creator>Wala, J. A.</dc:creator>
<dc:creator>Shapira, O.</dc:creator>
<dc:creator>Schumacher, S.</dc:creator>
<dc:creator>Khurana, E.</dc:creator>
<dc:creator>Korbel, J. O.</dc:creator>
<dc:creator>Imielinski, M.</dc:creator>
<dc:creator>Beroukhim, R.</dc:creator>
<dc:creator>Campbell, P.</dc:creator>
<dc:date>2017-08-27</dc:date>
<dc:identifier>doi:10.1101/181339</dc:identifier>
<dc:title><![CDATA[Patterns of structural variation in human cancer]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/126953v1?rss=1">
<title>
<![CDATA[
MAPseq: Improved Speed, Accuracy And Consistency In Ribosomal RNA Sequence Analysis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/126953v1?rss=1"
</link>
<description><![CDATA[
Metagenomic sequencing has become crucial to studying microbial communities, but meaningful taxonomic analysis and inter-comparison of such data are still hampered by technical limitations, between-study design variability and inconsistencies between taxonomies used. Here we present MAPseq, a framework for reference-based rRNA metagenomic analysis that is up to 30% more accurate (F1/2 score) and up to one hundred times faster than existing solutions, providing in a single run multiple taxonomy classifications and hierarchical OTU mappings, for both amplicon and shotgun sequencing strategies, and for datasets of virtually any size. Availability: Source code and binaries are freely available at http://meringlab.org/software/mapseq/
]]></description>
<dc:creator>Matias Rodrigues, J. F.</dc:creator>
<dc:creator>Schmidt, T. S.</dc:creator>
<dc:creator>Tackmann, J.</dc:creator>
<dc:creator>von Mering, C.</dc:creator>
<dc:date>2017-04-12</dc:date>
<dc:identifier>doi:10.1101/126953</dc:identifier>
<dc:title><![CDATA[MAPseq: Improved Speed, Accuracy And Consistency In Ribosomal RNA Sequence Analysis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/073973v1?rss=1">
<title>
<![CDATA[
Overcoming confounding plate effects in differential expression analyses of single-cell RNA-seq data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/073973v1?rss=1"
</link>
<description><![CDATA[
An increasing number of studies are using single-cell RNA-sequencing (scRNA-seq) to characterize the gene expression profiles of individual cells. One common analysis applied to scRNA-seq data involves detecting differentially expressed (DE) genes between cells in different biological groups. However, many experiments are designed such that the cells to be compared are processed in separate plates or chips, meaning that the groupings are confounded with systematic plate effects. This confounding aspect is frequently ignored in DE analyses of scRNA-seq data. In this article, we demonstrate that failing to consider plate effects in the statistical model results in loss of type I error control. A solution is proposed whereby counts are summed from all cells in each plate and the count sums for all plates are used in the DE analysis. This restores type I error control in the presence of plate effects without compromising detection power in simulated data. Summation is also robust to varying numbers and library sizes of cells on each plate. Similar results are observed in DE analyses of real data where the use of count sums instead of single-cell counts improves specificity and the ranking of relevant genes. This suggests that summation can assist in maintaining statistical rigour in DE analyses of scRNA-seq data with plate effects.
]]></description>
<dc:creator>Aaron TL Lun</dc:creator>
<dc:creator>John C Marioni</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-09-08</dc:date>
<dc:identifier>doi:10.1101/073973</dc:identifier>
<dc:title><![CDATA[Overcoming confounding plate effects in differential expression analyses of single-cell RNA-seq data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-09-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/314716v1?rss=1">
<title>
<![CDATA[
Analysis of the human kinome and phosphatome reveals diseased signaling networks induced by overexpression 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/314716v1?rss=1"
</link>
<description><![CDATA[
Kinase and phosphatase overexpression drives tumorigenesis and drug resistance in many cancer types. Signaling networks reprogrammed by protein overexpression remain largely uncharacterized, hindering discovery of paths to therapeutic intervention. We previously developed a single cell proteomics approach based on mass cytometry that enables quantitative assessment of overexpression effects on the signaling network. Here we applied this approach in a human kinome- and phosphatome-wide study to assess how 649 individually overexpressed proteins modulate the cancer-related signaling network in HEK293T cells. Based on these data we expanded the functional classification of human kinases and phosphatases and detected 208 novel signaling relationships. In the signaling dynamics analysis, we showed that increased ERK-specific phosphatases sustained proliferative signaling, and using a novel combinatorial overexpression approach, we confirmed this phosphatase-driven mechanism of cancer progression. Finally, we identified 54 proteins that caused ligand-independent ERK activation with potential as biomarkers for drug resistance in cells carrying BRAF mutations.
]]></description>
<dc:creator>Lun, X.-K.</dc:creator>
<dc:creator>Szklarczyk, D.</dc:creator>
<dc:creator>Gabor, A.</dc:creator>
<dc:creator>Dobberstein, N.</dc:creator>
<dc:creator>Zanotelli, V. R. T.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:creator>von Mering, C.</dc:creator>
<dc:creator>Bodenmiller, B.</dc:creator>
<dc:date>2018-05-04</dc:date>
<dc:identifier>doi:10.1101/314716</dc:identifier>
<dc:title><![CDATA[Analysis of the human kinome and phosphatome reveals diseased signaling networks induced by overexpression]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/255380v1?rss=1">
<title>
<![CDATA[
Single-molecule dynamics and genome-wide transcriptomics reveal that NF-kB (p65)-DNA binding times can be decoupled from transcriptional activation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/255380v1?rss=1"
</link>
<description><![CDATA[
Transcription factors (TFs) regulate gene expression in both prokaryotes and eukaryotes by recognizing and binding to specific DNA promoter sequences. In higher eukaryotes, it remains unclear how the duration of TF binding to DNA relates to downstream transcriptional output. Here, we address this question for the transcriptional activator NF-{kappa}B (p65), by live-cell single molecule imaging of TF-DNA binding kinetics and genome-wide quantification of p65-mediated transcription. We used mutants of p65, perturbing either the DNA binding domain (DBD) or the protein-protein transactivation domain (TAD). We found that p65-DNA binding time was predominantly determined by its DBD and directly correlated with its transcriptional output as long as the TAD is intact. Surprisingly, mutation or deletion of the TAD did not modify p65-DNA binding stability, suggesting that the p65 TAD generally contributes neither to the assembly of an "enhanceosome," nor to the active removal of p65 from putative specific binding sites. However, TAD removal did reduce p65-mediated transcriptional activation, indicating that protein-protein interactions act to translate the long-lived p65-DNA binding into productive transcription.nnAuthor SummaryTo control transcription of a certain gene or a group of genes, both eukaryotes and prokaryotes express specialized proteins, transcription factors (TFs). During gene activation, TFs bind gene promotor sequences to recruit the transcriptional machinery including DNA polymerase II. TFs are often multi-subunit proteins containing a DNA-binding domain (DBD) as well as a protein-protein interaction interface. It was suggested that the duration of a TF-DNA binding event 1) depends on these two subunits and 2) dictates the outcome, i.e. the amount of mRNA produced from an activated gene. We set out to address these hypotheses using the transcriptional activator NF-{kappa}B (p65) as well as a number of mutants affecting different functional subunits. Using a combination of live-cell microscopy and RNA sequencing, we show that p65 DNA-binding time indeed correlates with the transcriptional output, but that this relationship depends on, and hence can be uncoupled by altering, the protein-protein interaction capacity. Our results suggest that, while p65 DNA binding times are dominated by the DBD, a transcriptional output can only be achieved with a functional protein-protein interaction subunit.
]]></description>
<dc:creator>Callegari, A.</dc:creator>
<dc:creator>Sieben, C.</dc:creator>
<dc:creator>Benke, A.</dc:creator>
<dc:creator>Suter, D.</dc:creator>
<dc:creator>Fierz, B.</dc:creator>
<dc:creator>Mazza, D.</dc:creator>
<dc:creator>Manley, S.</dc:creator>
<dc:date>2018-01-28</dc:date>
<dc:identifier>doi:10.1101/255380</dc:identifier>
<dc:title><![CDATA[Single-molecule dynamics and genome-wide transcriptomics reveal that NF-kB (p65)-DNA binding times can be decoupled from transcriptional activation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/334110v1?rss=1">
<title>
<![CDATA[
Depolymerized lamins link nuclear envelope breakdown to mitotic transcriptional quiescence 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/334110v1?rss=1"
</link>
<description><![CDATA[
The nuclear envelope, a defining feature of eukaryotic cells, restricts DNA-dependent processes including gene transcription to the nucleus. The nuclear lamina is an integral component of the animal nuclear envelope, composed of polymers of nuclear lamin proteins1,2. Upon mitosis, the nuclear lamina disassembles, the nuclear envelope breaks down, and transcription becomes quiescent3,4. We report here a direct molecular link between nuclear lamina disassembly and mitotic transcriptional quiescence. We found that, at the G2 cell-cycle phase immediately preceding mitosis, nuclear lamin A/C (LMNA) became phosphorylated at Ser22 and depolymerized from the nuclear lamina. Depolymerized LMNA accumulated in the nuclear interior and physically associated with active cis-regulatory elements genome-wide. Depolymerized LMNA-associated sites were overrepresented near genes repressed by LMNA, suggesting that depolymerized LMNA participates in transcriptional repression at G2. Consistently, depolymerized LMNA-target genes underwent a steep expression decline from S to G2/M. Furthermore, LMNA deletion caused inappropriate RNA Polymerase II (Pol II) accumulation downstream of Pol II pause sites at promoters and enhancers genome-wide, leading to inappropriate and excessive transcriptional elongation. A subset of depolymerized LMNA-target genes were upregulated in fibroblasts of patients with Hutchinson-Gilford progeria, a premature aging disorder caused by LMNA mutations5, raising the possibility that defects in depolymerized LMNA-mediated mitotic transcriptional quiescence contribute to progeria pathogenesis. These observations support a model in which depolymerized LMNA targets active regulatory elements to promote RNA Pol II pausing preceding mitosis, coupling nuclear envelope breakdown to mitotic transcriptional quiescence.
]]></description>
<dc:creator>Ikegami, K.</dc:creator>
<dc:creator>Secchia, S.</dc:creator>
<dc:creator>Lieb, J. D.</dc:creator>
<dc:creator>Moskowitz, I. P.</dc:creator>
<dc:date>2018-05-30</dc:date>
<dc:identifier>doi:10.1101/334110</dc:identifier>
<dc:title><![CDATA[Depolymerized lamins link nuclear envelope breakdown to mitotic transcriptional quiescence]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/249482v1?rss=1">
<title>
<![CDATA[
The genome of the biting midge Culicoides sonorensis and gene expression analyses of vector competence for Bluetongue virus 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/249482v1?rss=1"
</link>
<description><![CDATA[
BackgroundThe use of the new genomic technologies has led to major advances in control of several arboviruses of medical importance such as Dengue. However, the development of tools and resources available for vectors of non-zoonotic arboviruses remains neglected. Biting midges of the genus Culicoides transmit some of the most important arboviruses of wildlife and livestock worldwide, with a global impact on economic productivity, health and welfare. The absence of a suitable reference genome has hindered genomic analyses to date in this important genus of vectors. In the present study, the genome of Culicoides sonorensis, a vector of bluetongue virus (BTV) in the USA, has been sequenced to provide the first reference genome for these vectors. In this study, we also report the use of the reference genome to perform initial transcriptomic analyses of vector competence for BTV.nnResultsOur analyses reveal that the genome is 197.4 Mb, assembled in 7,974 scaffolds. Its annotation using the transcriptomic data generated in this study and in a previous study has identified 15,629 genes. Gene expression analyses of C. sonorensis females infected with BTV performed in this study revealed 165 genes that were differentially expressed between vector competent and refractory females. Two candidate genes, glutathione S-transferase (gst) and the antiviral helicase ski2, previously recognized as involved in vector competence for BTV in C. sonorensis (gst) and repressing dsRNA virus propagation (ski2), were confirmed in this study.nnConclusionsThe reference genome of C. sonorensis has enabled preliminary analyses of the gene expression profiles of vector competent and refractory individuals. The genome and transcriptomes generated in this study provide suitable tools for future research on arbovirus transmission. These provide a significant resource for these vector lineage, which diverged from other major Dipteran vector families over 200 million years ago. The genome will be a valuable source of comparative data for other important Dipteran vector families including mosquitoes (Culicidae) and sandflies (Psychodidae), and yield potential targets for transgenic modification in vector control and functional studies.
]]></description>
<dc:creator>Morales Hojas, R.</dc:creator>
<dc:creator>Hinsley, M.</dc:creator>
<dc:creator>Armean, I. M.</dc:creator>
<dc:creator>Silk, R.</dc:creator>
<dc:creator>Harrup, L. E.</dc:creator>
<dc:creator>Gonzalez-Uriarte, A.</dc:creator>
<dc:creator>Veronesi, E.</dc:creator>
<dc:creator>Campbell, L.</dc:creator>
<dc:creator>Nayduch, D.</dc:creator>
<dc:creator>Saski, C.</dc:creator>
<dc:creator>Tabachnick, W. J.</dc:creator>
<dc:creator>Kersey, P.</dc:creator>
<dc:creator>Carpenter, S.</dc:creator>
<dc:creator>Fife, M.</dc:creator>
<dc:date>2018-01-17</dc:date>
<dc:identifier>doi:10.1101/249482</dc:identifier>
<dc:title><![CDATA[The genome of the biting midge Culicoides sonorensis and gene expression analyses of vector competence for Bluetongue virus]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/163188v1?rss=1">
<title>
<![CDATA[
The WYL domain of the Thermotoga elfii PIF1 helicase is an accessory single-stranded DNA binding module 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/163188v1?rss=1"
</link>
<description><![CDATA[
PIF1 family helicases are conserved from bacteria to man. With the exception of the well-studied yeast PIF1 helicases (e.g., ScPif1 and ScRrm3), however, very little is known about how these enzymes help maintain genome stability. Indeed, we lack a basic understanding of the protein domains found N- and C-terminal to the characteristic central PIF1 helicase domain in these proteins. Here, using chimeric constructs, we show that the ScPif1 and ScRrm3 helicase domains are interchangeable and that the N-terminus of ScRrm3 is important for its function in vivo. This suggests that PIF1 family helicases evolved functional modules fused to a generic motor domain. To investigate this hypothesis, we characterized the biochemical activities of the PIF1 helicase from the thermophilic bacterium Thermotoga elfii (TePif1), which contains a C-terminal WYL domain of unknown function. Like helicases from other thermophiles, recombinant TePif1 was easily prepared, thermostable in vitro, and displayed activities similar to its eukaryotic homologs. We also found that the WYL domain was necessary for high-affinity single-stranded DNA (ssDNA) binding and affected both ATPase and helicase activities. Deleting the WYL domain from TePif1 or mutating conserved residues in the predicted ssDNA binding site uncoupled ATPase activity and DNA unwinding, leading to higher rates of ATP hydrolysis but less efficient DNA helicase activity. Our findings suggest that the domains of unknown function found in eukaryotic PIF1 helicases may also confer functional specificity and additional activities to these enzymes, which should be investigated in future work.
]]></description>
<dc:creator>Andis, N. M.</dc:creator>
<dc:creator>Sausen, C. W.</dc:creator>
<dc:creator>Alladin, A.</dc:creator>
<dc:creator>Bochman, M.</dc:creator>
<dc:date>2017-07-13</dc:date>
<dc:identifier>doi:10.1101/163188</dc:identifier>
<dc:title><![CDATA[The WYL domain of the Thermotoga elfii PIF1 helicase is an accessory single-stranded DNA binding module]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/094755v1?rss=1">
<title>
<![CDATA[
Dissecting cancer resistance to therapies with cell-type-specific dynamic logic models 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/094755v1?rss=1"
</link>
<description><![CDATA[
Therapies targeting specific molecular processes, in particular kinases, are major strategies to treat cancer. Genomic features are commonly used as biomarkers for drug sensitivity, but our ability to stratify patients based on these features is still limited. As response to kinase inhibitors is a dynamic process affecting largely signal transduction, we investigated the association between cell-specific dynamic signaling pathways and drug sensitivity. We measured 14 phosphoproteins under 43 different perturbed conditions (combination of 5 stimuli and 7 inhibitors) for 14 colorectal cancer cell-lines, and built cell-line-specific dynamic logic models of the underlying signaling network. Model parameters, representing pathway dynamics, were used as features to predict sensitivity to a panel of 27 drugs. This analysis revealed associations between cell-specific signaling pathways and drug sensitivity for 14 of the drugs, 9 of which have no genomic biomarker. Following one of these associations, we validated a drug combination predicted to overcome resistance to MEK inhibitors by co-blockade of GSK3. These results underscore the value of perturbation-based studies to find biomarkers and combination therapies complementing those based on a static genomic characterization.
]]></description>
<dc:creator>Eduati, F.</dc:creator>
<dc:creator>Doldan-Martelli, V.</dc:creator>
<dc:creator>Klinger, B.</dc:creator>
<dc:creator>Cokelaer, T.</dc:creator>
<dc:creator>Sieber, A.</dc:creator>
<dc:creator>Kogera, F.</dc:creator>
<dc:creator>Dorel, M.</dc:creator>
<dc:creator>Garnett, M. J.</dc:creator>
<dc:creator>Bluthgen, N.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:date>2016-12-16</dc:date>
<dc:identifier>doi:10.1101/094755</dc:identifier>
<dc:title><![CDATA[Dissecting cancer resistance to therapies with cell-type-specific dynamic logic models]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-12-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/265447v1?rss=1">
<title>
<![CDATA[
A functional landscape of chronic kidney disease entities from public transcriptomic data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/265447v1?rss=1"
</link>
<description><![CDATA[
To develop efficient therapies and identify novel early biomarkers for chronic kidney disease an understanding of the molecular mechanisms orchestrating it is essential. We here set out to understand how differences in CKD origin are reflected in gene expression. To this end, we integrated publicly available human glomerular microarray gene expression data for nine kidney disease entities that account for a majority of CKD worldwide. We included data from five distinct studies and compared glomerular gene expression profiles to that of non-tumor parts of kidney cancer nephrectomy tissues. A major challenge was the integration of the data from different sources, platforms and conditions, that we mitigated with a bespoke stringent procedure. This allowed us to perform a global transcriptome-based delineation of different kidney disease entities, obtaining a landscape of their similarities and differences based on the genes that acquire a consistent differential expression between each kidney disease entity and nephrectomy tissue. Furthermore, we derived functional insights by inferring activity of signaling pathways and transcription factors from the collected gene expression data, and identified potential drug candidates based on expression signature matching. We validated representative findings by immunostaining in human kidney biopsies indicating e.g. that the transcription factor FOXM1 is significantly and specifically expressed in parietal epithelial cells in RPGN whereas not expressed in control kidney tissue. These results provide a foundation to comprehend the specific molecular mechanisms underlying different kidney disease entities, that can pave the way to identify biomarkers and potential therapeutic targets. To facilitate this, we provide our results as a free interactive web application: https://saezlab.shinyapps.io/ckd_landscape/.

Translational StatementChronic kidney disease is a combination of entities with different etiologies. We integrate and analyse transcriptomics analysis of glomerular from different entities to dissect their different pathophysiology, what might help to identify novel entity-specific therapeutic targets.
]]></description>
<dc:creator>Tajti, F.</dc:creator>
<dc:creator>Antoranz, A.</dc:creator>
<dc:creator>Ibrahim, M. M.</dc:creator>
<dc:creator>Kim, H.</dc:creator>
<dc:creator>Ceccarelli, F.</dc:creator>
<dc:creator>Kuppe, C.</dc:creator>
<dc:creator>Alexopoulos, L. G.</dc:creator>
<dc:creator>Kramann, R.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:date>2018-02-14</dc:date>
<dc:identifier>doi:10.1101/265447</dc:identifier>
<dc:title><![CDATA[A functional landscape of chronic kidney disease entities from public transcriptomic data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/235838v1?rss=1">
<title>
<![CDATA[
Multiple laboratory mouse reference genomes define strain specific haplotypes and novel functional loci 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/235838v1?rss=1"
</link>
<description><![CDATA[
The most commonly employed mammalian model organism is the laboratory mouse. A wide variety of genetically diverse inbred mouse strains, representing distinct physiological states, disease susceptibilities, and biological mechanisms have been developed over the last century. We report full length draft de novo genome assemblies for 16 of the most widely used inbred strains and reveal for the first time extensive strain-specific haplotype variation. We identify and characterise 2,567 regions on the current Genome Reference Consortium mouse reference genome exhibiting the greatest sequence diversity between strains. These regions are enriched for genes involved in defence and immunity, and exhibit enrichment of transposable elements and signatures of recent retrotransposition events. Combinations of alleles and genes unique to an individual strain are commonly observed at these loci, reflecting distinct strain phenotypes. Several immune related loci, some in previously identified QTLs for disease response have novel haplotypes not present in the reference that may explain the phenotype. We used these genomes to improve the mouse reference genome resulting in the completion of 10 new gene structures, and 62 new coding loci were added to the reference genome annotation. Notably this high quality collection of genomes revealed a previously unannotated gene (Efcab3-like) encoding 5,874 amino acids, one of the largest known in the rodent lineage. Interestingly, Efcab3-like-/- mice exhibit severe size anomalies in four regions of the brain suggesting a mechanism of Efcab3-like regulating brain development.
]]></description>
<dc:creator>Lilue, J.</dc:creator>
<dc:creator>Doran, A. G.</dc:creator>
<dc:creator>Fiddes, I. T.</dc:creator>
<dc:creator>Abrudan, M.</dc:creator>
<dc:creator>Armstrong, J.</dc:creator>
<dc:creator>Bennett, R.</dc:creator>
<dc:creator>Chow, W.</dc:creator>
<dc:creator>Collins, J.</dc:creator>
<dc:creator>Czechanski, A.</dc:creator>
<dc:creator>Danecek, P.</dc:creator>
<dc:creator>Diekhans, M.</dc:creator>
<dc:creator>Dolle, D.-D.</dc:creator>
<dc:creator>Dunn, M.</dc:creator>
<dc:creator>Durbin, R.</dc:creator>
<dc:creator>Earl, D.</dc:creator>
<dc:creator>Ferguson-Smith, A.</dc:creator>
<dc:creator>Flicek, P.</dc:creator>
<dc:creator>Flint, J.</dc:creator>
<dc:creator>Frankish, A.</dc:creator>
<dc:creator>Fu, B.</dc:creator>
<dc:creator>Gerstein, M.</dc:creator>
<dc:creator>Gilbert, J.</dc:creator>
<dc:creator>Goodstadt, L.</dc:creator>
<dc:creator>Harrow, J.</dc:creator>
<dc:creator>Howe, K.</dc:creator>
<dc:creator>Kolmogorov, M.</dc:creator>
<dc:creator>Koenig, S.</dc:creator>
<dc:creator>Lelliott, C.</dc:creator>
<dc:creator>Loveland, J.</dc:creator>
<dc:creator>Mott, R.</dc:creator>
<dc:creator>Muir, P.</dc:creator>
<dc:creator>Navarro, F.</dc:creator>
<dc:creator>Odom, D.</dc:creator>
<dc:creator>Park, N.</dc:creator>
<dc:creator>Pelan, S.</dc:creator>
<dc:creator>Phan, S. K.</dc:creator>
<dc:creator>Quail, M.</dc:creator>
<dc:creator>Reinholdt, L.</dc:creator>
<dc:creator>Romoth, L.</dc:creator>
<dc:creator>Shirley, L.</dc:creator>
<dc:creator>Sisu, C.</dc:creator>
<dc:creator>Sjoberg-Herrera, M.</dc:creator>
<dc:creator>Stanke, M.</dc:creator>
<dc:creator>Steward, C.</dc:creator>
<dc:creator>Thomas, M.</dc:creator>
<dc:creator>Threadgold, G.</dc:creator>
<dc:creator>Thybert, D</dc:creator>
<dc:date>2018-02-12</dc:date>
<dc:identifier>doi:10.1101/235838</dc:identifier>
<dc:title><![CDATA[Multiple laboratory mouse reference genomes define strain specific haplotypes and novel functional loci]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/217489v1?rss=1">
<title>
<![CDATA[
Single cell transcriptomics of regulatory T cells reveals trajectories of tissue adaptation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/217489v1?rss=1"
</link>
<description><![CDATA[
Non-lymphoid tissues (NLTs) harbour a pool of adaptive immune cells, the development and phenotype of which remains largely unexplored. Here, we used single-cell RNA-seq to characterise CD4+ regulatory (Treg) and memory (Tmem) T cells in mouse skin and colon, the respective draining lymph nodes and spleen. From this data, we modelled a continuous lymphoid-to-NLT trajectory for Treg, and reconstructed the mechanisms of cell migration and NLT adaption. This revealed a shared transcriptional programme of NLT priming in both skin and colon-associated lymph nodes, followed by tissue-specific adaptation. Predicted migration kinetics were validated using a melanoma-induction model, emphasizing the relevance of key regulators and receptors, including Batf, Rora, Ccr8, Samsn1. Finally, we profiled human blood and NLT Treg and Tmem cells, identifying cross-mammalian conserved tissue signatures. In summary, we have identified molecular signals mediating NLT Treg recruitment and tissue adaptation through the combined use of computational prediction and in vivo validation.
]]></description>
<dc:creator>Miragaia, R. J.</dc:creator>
<dc:creator>Gomes, T.</dc:creator>
<dc:creator>Chomka, A.</dc:creator>
<dc:creator>Jardine, L.</dc:creator>
<dc:creator>Riedel, A.</dc:creator>
<dc:creator>Hegazy, A. N.</dc:creator>
<dc:creator>Lindeman, I.</dc:creator>
<dc:creator>Emerton, G.</dc:creator>
<dc:creator>Krausgruber, T.</dc:creator>
<dc:creator>Shields, J.</dc:creator>
<dc:creator>Haniffa, M.</dc:creator>
<dc:creator>Powrie, F.</dc:creator>
<dc:creator>Teichmann, S. A.</dc:creator>
<dc:date>2017-11-22</dc:date>
<dc:identifier>doi:10.1101/217489</dc:identifier>
<dc:title><![CDATA[Single cell transcriptomics of regulatory T cells reveals trajectories of tissue adaptation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/168641v1?rss=1">
<title>
<![CDATA[
Noise control is a primary function of microRNAs and post-transcriptional regulation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/168641v1?rss=1"
</link>
<description><![CDATA[
microRNAs are pervasive post-transcriptional regulators of protein-coding genes in multicellular organisms. Two fundamentally different models have been proposed for the function of microRNAs in gene regulation. In the first model, microRNAs act as repressors, reducing protein concentrations by accelerating mRNA decay and inhibiting translation. In the second model, in contrast, the role of microRNAs is not to reduce protein concentrations per se but to reduce fluctuations in these concentrations. Here we present genome-wide evidence that mammalian microRNAs frequently function as noise controllers rather than repressors. Moreover, we show that post-transcriptional noise control has been widely adopted across species from bacteria to animals, with microRNAs specifically employed to reduce noise in regulatory and context-specific processes in animals. Our results substantiate the detrimental nature of expression noise, reveal a universal strategy to control it, and suggest that microRNAs represent an evolutionary innovation for adaptive noise control in animals.nnHighlightsO_LIGenome-wide evidence that microRNAs function as noise controllers for genes with context-specific functionsnC_LIO_LIPost-transcriptional noise control is universal from bacteria to animalsnC_LIO_LIAnimals have evolved noise control for regulatory and context-specific processesnC_LI
]]></description>
<dc:creator>Schmiedel, J.</dc:creator>
<dc:creator>Marks, D. S.</dc:creator>
<dc:creator>Lehner, B.</dc:creator>
<dc:creator>Bluthgen, N.</dc:creator>
<dc:date>2017-07-26</dc:date>
<dc:identifier>doi:10.1101/168641</dc:identifier>
<dc:title><![CDATA[Noise control is a primary function of microRNAs and post-transcriptional regulation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/117267v1?rss=1">
<title>
<![CDATA[
Flipping between Polycomb repressed and active transcriptional states introduces noise in gene expression 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/117267v1?rss=1"
</link>
<description><![CDATA[
Polycomb repressive complexes (PRCs) are important histone modifiers, which silence gene expression, yet there exists a subset of PRC-bound genes actively transcribed by RNA polymerase II (RNAPII). It is likely that the role of PRC is to dampen expression of these PRC-active genes. However, it is unclear how this flipping between chromatin states alters the kinetics of transcriptional burst size and frequency relative to genes with exclusively activating marks. To investigate this, we integrate histone modifications and RNAPII states derived from bulk ChIP-seq data with single-cell RNA-sequencing data. We find that PRC-active genes have a greater cell-to-cell variation in expression than active genes with the same mean expression levels, and validate these results by knockout experiments. We also show that PRC-active genes are clustered on chromosomes in both two and three dimensions, and interactions with active enhancers promote a stabilization of gene expression noise. These findings provide new insights into how chromatin regulation modulates stochastic gene expression and transcriptional bursting, with implications for regulation of pluripotency and development.
]]></description>
<dc:creator>Kar, G.</dc:creator>
<dc:creator>Kim, J. K.</dc:creator>
<dc:creator>Kolodziejczyk, A. A.</dc:creator>
<dc:creator>Natarajan, K. N.</dc:creator>
<dc:creator>Triglia, E. T.</dc:creator>
<dc:creator>Mifsud, B.</dc:creator>
<dc:creator>Elderkin, S.</dc:creator>
<dc:creator>Marioni, J. C.</dc:creator>
<dc:creator>Pombo, A.</dc:creator>
<dc:creator>Teichmann, S. A.</dc:creator>
<dc:date>2017-03-16</dc:date>
<dc:identifier>doi:10.1101/117267</dc:identifier>
<dc:title><![CDATA[Flipping between Polycomb repressed and active transcriptional states introduces noise in gene expression]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-03-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/116038v1?rss=1">
<title>
<![CDATA[
Structural basis for EarP-mediated arginine glycosylation of translation elongation factor EF-P 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/116038v1?rss=1"
</link>
<description><![CDATA[
Glycosylation is a universal strategy to post-translationally modify proteins. The recently discovered arginine rhamnosylation activates the polyproline specific bacterial translation elongation factor EF-P. EF-P is rhamnosylated on arginine 32 by the glycosyltransferase EarP. However, the enzymatic mechanism remains elusive. In the present study, we solved the crystal structure of EarP from Pseudomonas putida. The enzyme is composed of two opposing domains with Rossmann-folds, thus constituting a GT-B glycosyltransferase. While TDP-rhamnose is located within a highly conserved pocket of the C-domain, EarP recognizes the EF-P via its KOW-like N-domain. Based on our structural data combined with an in vitro /in vivo enzyme characterization, we propose a mechanism of inverting arginine glycosylation. As EarP is essential for pathogenicity in P. aeruginosa our study provides the basis for targeted inhibitor design.
]]></description>
<dc:creator>Krafczyk, R.</dc:creator>
<dc:creator>Macosek, J.</dc:creator>
<dc:creator>Gast, D.</dc:creator>
<dc:creator>Wunder, S.</dc:creator>
<dc:creator>Jagtap, P. K. A.</dc:creator>
<dc:creator>Mitra, P.</dc:creator>
<dc:creator>Jha, A. K.</dc:creator>
<dc:creator>Rohr, J.</dc:creator>
<dc:creator>Hoffmann-Roeder, A.</dc:creator>
<dc:creator>Jung, K.</dc:creator>
<dc:creator>Hennig, J.</dc:creator>
<dc:creator>Lassak, J.</dc:creator>
<dc:date>2017-03-11</dc:date>
<dc:identifier>doi:10.1101/116038</dc:identifier>
<dc:title><![CDATA[Structural basis for EarP-mediated arginine glycosylation of translation elongation factor EF-P]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-03-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/235010v1?rss=1">
<title>
<![CDATA[
The IRE1a-XBP1 pathway promotes T helper cell differentiation by resolving secretory stress and accelerating proliferation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/235010v1?rss=1"
</link>
<description><![CDATA[
The IRE1a-XBP1 pathway, a conserved adaptive mediator of the unfolded protein response, is indispensable for the development of secretory cells. It maintains endoplasmic reticulum homeostasis by facilitating protein folding and enhancing secretory capacity of the cells. Its role in immune cells is emerging. It is involved in dendritic cell, plasma cell and eosinophil development and differentiation. Using genome-wide approaches, integrating ChIPmentation and mRNA-sequencing data, we have elucidated the regulatory circuitry governed by the IRE1a-XBP1 pathway in type-2 T helper cells (Th2). We show that the XBP1 transcription factor is activated by splicing in vivo in T helper cell lineages. We report a comprehensive repertoire of XBP1 target genes in Th2 lymphocytes. We found that the pathway is conserved across cell types in terms of resolving secretory stress, and has T helper cell-specific functions in controlling activation-dependent Th2 cell proliferation and regulating cytokine expression in addition to secretion. These results provide a detailed picture of the regulatory map governed by the XBP1 transcription factor during Th2 lymphocyte activation.
]]></description>
<dc:creator>Pramanik, J.</dc:creator>
<dc:creator>Chen, X.</dc:creator>
<dc:creator>Kar, G.</dc:creator>
<dc:creator>Gomes, T.</dc:creator>
<dc:creator>Henriksson, J.</dc:creator>
<dc:creator>Miao, Z.</dc:creator>
<dc:creator>Natarajan, K.</dc:creator>
<dc:creator>McKenzie, A. N. J.</dc:creator>
<dc:creator>Mahata, B.</dc:creator>
<dc:creator>Teichmann, S. A.</dc:creator>
<dc:date>2017-12-15</dc:date>
<dc:identifier>doi:10.1101/235010</dc:identifier>
<dc:title><![CDATA[The IRE1a-XBP1 pathway promotes T helper cell differentiation by resolving secretory stress and accelerating proliferation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/150813v1?rss=1">
<title>
<![CDATA[
Crosslinkers both drive and brake cytoskeletal remodeling and furrowing in cytokinesis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/150813v1?rss=1"
</link>
<description><![CDATA[
Cytokinesis and other cell shape changes are driven by the actomyosin contractile cytoskeleton. The molecular rearrangements that bring about contractility in non-muscle cells are currently debated. Specifically, both filament sliding by myosin motors, as well as cytoskeletal crosslinking by myosins and non-motor crosslinkers, are thought to promote contractility. Here, we examined how the abundance of motor and non-motor crosslinkers controls the speed of cytokinetic furrowing. We built a minimal model to simulate the contractile dynamics of the C. elegans zygote cytokinetic ring. This model predicted that intermediate levels of non-motor crosslinkers would allow maximal contraction speed, which we found to be the case for the scaffold protein anillin, in vivo. Our model also demonstrated a non-linear relationship between the abundance of motor ensembles and contraction speed. In vivo, thorough depletion of non-muscle myosin II delayed furrow initiation, slowed F-actin alignment, and reduced maximum contraction speed, but partial depletion allowed faster-than-expected kinetics. Thus, both motor and non-motor crosslinkers promote cytokinetic ring closure when present at low levels, but act as a brake when present at higher levels. Together, our findings extend the growing appreciation for the roles of crosslinkers, but reveal that they not only drive but also brake cytoskeletal remodeling.
]]></description>
<dc:creator>Descovich, C. P.</dc:creator>
<dc:creator>Cortes, D. B.</dc:creator>
<dc:creator>Ryan, S.</dc:creator>
<dc:creator>Nash, J.</dc:creator>
<dc:creator>Zhang, L.</dc:creator>
<dc:creator>Maddox, P. S.</dc:creator>
<dc:creator>Nedelec, F.</dc:creator>
<dc:creator>Maddox, A. S.</dc:creator>
<dc:date>2017-06-16</dc:date>
<dc:identifier>doi:10.1101/150813</dc:identifier>
<dc:title><![CDATA[Crosslinkers both drive and brake cytoskeletal remodeling and furrowing in cytokinesis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/172072v1?rss=1">
<title>
<![CDATA[
The contributions of the actin machinery to endocytic membrane bending and vesicle formation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/172072v1?rss=1"
</link>
<description><![CDATA[
Branched and crosslinked actin networks mediate cellular processes that move and shape membranes. To understand how actin contributes during the different stages of endocytic membrane reshaping, we analysed deletion mutants of yeast actin network components using a hybrid imaging approach that combines live imaging with correlative microscopy. We could thereby temporally dissect the effects of different actin network perturbations, revealing distinct stages of actin-based membrane reshaping. Our data show that initiation of membrane bending requires the actin network to be physically linked to the plasma membrane and to be optimally crosslinked. Once initiated, the membrane invagination process is driven by nucleation and polymerization of new actin filaments, independently of the degree of cross-linking and unaffected by a surplus of actin network components. A key transition occurs 2 seconds before scission when the filament nucleation rate drops. From that time point on, invagination growth and vesicle scission are driven by an expansion of the assembled actin network. The expansion is sensitive to the amount of filamentous actin and its crosslinking. Our results suggest that the mechanism by which actin reshapes the membrane adapts to force requirements that vary during the progress of endocytosis.
]]></description>
<dc:creator>Picco, A.</dc:creator>
<dc:creator>Kukulski, W.</dc:creator>
<dc:creator>Manenschijn, H. E.</dc:creator>
<dc:creator>Specht, T.</dc:creator>
<dc:creator>Briggs, J. A. G.</dc:creator>
<dc:creator>Kaksonen, M.</dc:creator>
<dc:date>2017-08-03</dc:date>
<dc:identifier>doi:10.1101/172072</dc:identifier>
<dc:title><![CDATA[The contributions of the actin machinery to endocytic membrane bending and vesicle formation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/103192v1?rss=1">
<title>
<![CDATA[
The Nucleosome Remodelling and Deacetylation complex restricts Mediator access to enhancers to control transcription 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/103192v1?rss=1"
</link>
<description><![CDATA[
A number of different chromatin remodelling complexes in mammalian cells are implicated in the control of gene expression. The genetic requirements for many such complex components have been described, and the biochemical activities of complex components characterised in vitro, yet the molecular mechanisms by which these biochemical activities impact transcriptional regulation in vivo remain ill-defined. Using an inducible system with fine temporal resolution, we show that the Nucleosome Remodelling and Deacetylation (NuRD) complex directly regulates chromatin architecture at enhancer regions in ES cells, in turn influencing the activity of RNA polymerase II via Mediator. Through this mechanism NuRD restricts Mediator access to enhancer chromatin during lineage commitment, thereby enabling appropriate transcriptional regulation. In contrast, acetylation levels of histone H3 lysine 27 are not immediately impacted by NuRD activity, correlating with transcriptional response only after expression levels have changed. These findings provide a detailed, molecular picture of genome-wide modulation of lineage-specific transcription by an abundant chromatin remodelling complex.
]]></description>
<dc:creator>Xenophontos, M.</dc:creator>
<dc:creator>Reynolds, N.</dc:creator>
<dc:creator>Gharbi, S.</dc:creator>
<dc:creator>Johnstone, E.</dc:creator>
<dc:creator>Signolet, J.</dc:creator>
<dc:creator>Floyd, R.</dc:creator>
<dc:creator>Ralser, M.</dc:creator>
<dc:creator>Borneloev, S.</dc:creator>
<dc:creator>Dietmann, S.</dc:creator>
<dc:creator>Loos, R.</dc:creator>
<dc:creator>Bertone, P.</dc:creator>
<dc:creator>Hendrich, B.</dc:creator>
<dc:date>2017-01-25</dc:date>
<dc:identifier>doi:10.1101/103192</dc:identifier>
<dc:title><![CDATA[The Nucleosome Remodelling and Deacetylation complex restricts Mediator access to enhancers to control transcription]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-01-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/035360v1?rss=1">
<title>
<![CDATA[
A Critical Review on the Use of Support Values in Tree Viewers and Bioinformatics Toolkits 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/035360v1?rss=1"
</link>
<description><![CDATA[
Phylogenetic trees are routinely visualized to present and interpret the evolutionary relationships of species. Virtually all empirical evolutionary data studies contain a visualization of the inferred tree with branch support values. Ambiguous semantics in tree file formats can lead to erroneous tree visualizations and therefore to incorrect interpretations of phylogenetic analyses.nnHere, we discuss problems that can and do arise when displaying branch values on trees after re-rooting. Branch values are typically stored as node labels in the widely-used Newick tree format. However, such values are attributes of branches. Storing them as node labels can therefore yield errors when re-rooting trees. This depends on the mostly implicit semantics that tools deploy to interpret node labels.nnWe reviewed 10 tree viewers and 10 bioinformatics toolkits that can display and re-root trees. We found that 14 out of 20 of these tools do not permit users to select the semantics of node labels. Thus, unaware users might obtain incorrect results when rooting trees inferred by common phylogenetic inference programs. We illustrate such incorrect mappings for several test cases and real examples taken from the literature. This review has already led to improvements and workarounds in 8 of the tested tools. We suggest tools should provide an option that explicitly forces users to define the semantics of node labels.
]]></description>
<dc:creator>Lucas Czech</dc:creator>
<dc:creator>Jaime Huerta-Cepas</dc:creator>
<dc:creator>Alexandros Stamatakis</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-12-25</dc:date>
<dc:identifier>doi:10.1101/035360</dc:identifier>
<dc:title><![CDATA[A Critical Review on the Use of Support Values in Tree Viewers and Bioinformatics Toolkits]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-12-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/126276v1?rss=1">
<title>
<![CDATA[
Sub-minute phosphoregulation of cell-cycle systems during Plasmodium gamete formation revealed by a high-resolution time course 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/126276v1?rss=1"
</link>
<description><![CDATA[
Malaria parasites are protists of the genus Plasmodium, whose transmission to mosquitoes is initiated by the production of gametes. Male gametogenesis is an extremely rapid process that is tightly controlled to produce eight flagellated microgametes from a single haploid gametocyte within 10 minutes after ingestion by a mosquito. Regulation of the cell cycle is poorly understood in divergent eukaryotes like Plasmodium, where the highly synchronous response of gametocytes to defined chemical and physical stimuli from the mosquito has proved to be a powerful model to identify specific phosphorylation events critical for cell-cycle progression. To reveal the wider network of phosphorylation signalling in a systematic and unbiased manner, we have measured a high-resolution time course of the phosphoproteome of P. berghei gametocytes during the first minute of gametogenesis. The data show an extremely broad response in which distinct cell-cycle events such as initiation of DNA replication and mitosis are rapidly induced and simultaneously regulated. We identify several protein kinases and phosphatases that are likely central in the gametogenesis signalling pathway and validate our analysis by investigating the phosphoproteomes of mutants in two of them, CDPK4 and SRPK1. We show these protein kinases to have distinct influences over the phosphorylation of similar downstream targets that are consistent with their distinct cellular functions, which is revealed by a detailed phenotypic analysis of an SRPK1 mutant. Together, the results show that key cell-cycle systems in Plasmodium undergo simultaneous and rapid phosphoregulation. We demonstrate how a highly resolved time-course of dynamic phosphorylation events can generate deep insights into the unusual cell biology of a divergent eukaryote, which serves as a model for an important group of human pathogens.
]]></description>
<dc:creator>Invergo, B.</dc:creator>
<dc:creator>Brochet, M.</dc:creator>
<dc:creator>Yu, L.</dc:creator>
<dc:creator>Choudhary, J.</dc:creator>
<dc:creator>Beltrao, P.</dc:creator>
<dc:creator>Billker, O.</dc:creator>
<dc:date>2017-04-10</dc:date>
<dc:identifier>doi:10.1101/126276</dc:identifier>
<dc:title><![CDATA[Sub-minute phosphoregulation of cell-cycle systems during Plasmodium gamete formation revealed by a high-resolution time course]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/077701v1?rss=1">
<title>
<![CDATA[
Population-level characterization of pathway alterations with SLAPenrich dissects heterogeneity of cancer hallmark acquisition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/077701v1?rss=1"
</link>
<description><![CDATA[
Cancer hallmarks are evolutionary traits required by a tumour to develop. While extensively characterised, the way these traits are achieved through the accumulation of somatic mutations in key biological pathways is not fully understood. To shed light on this subject, we characterised the landscape of pathway alterations associated with somatic mutations observed in 4,415 patients across ten cancer types, using 374 orthogonal pathway gene-sets mapped onto canonical cancer hallmarks. Towards this end, we developed SLAPenrich: a computational method based on population-level statistics, freely available as an open source R package. Assembling the identified pathway alterations into sets of hallmark signatures allowed us to connect somatic mutations to clinically interpretable cancer mechanisms. Further, we explored the heterogeneity of these signatures, in terms of ratio of altered pathways associated with each individual hallmark, assuming that this is reflective of the extent of selective advantage provided to the cancer type under consideration. Our analysis revealed the predominance of certain hallmarks in specific cancer types, thus suggesting different evolutionary trajectories across cancer lineages.nnFinally, although many pathway alteration enrichments are guided by somatic mutations in frequently altered high-confidence cancer genes, excluding these driver mutations preserves the hallmark heterogeneity signatures, thus the detected hallmarks predominance across cancer types. As a consequence, we propose the hallmark signatures as a ground truth to characterise tails of infrequent genomic alterations and identify potential novel cancer driver genes and networks.
]]></description>
<dc:creator>Francesco Iorio</dc:creator>
<dc:creator>Luz Garcia-Alonso</dc:creator>
<dc:creator>Jonathan Brammeld</dc:creator>
<dc:creator>Inigo Martincorena</dc:creator>
<dc:creator>David R Wille</dc:creator>
<dc:creator>Ultan McDermott</dc:creator>
<dc:creator>Julio Saez-Rodriguez</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-09-27</dc:date>
<dc:identifier>doi:10.1101/077701</dc:identifier>
<dc:title><![CDATA[Population-level characterization of pathway alterations with SLAPenrich dissects heterogeneity of cancer hallmark acquisition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-09-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/235085v1?rss=1">
<title>
<![CDATA[
H2AFX AND MDC1 PROTECT GENOMIC INTEGRITY IN MALE GERM CELLS BY PROMOTING RECOMBINATION AND ACTIVATION OF THE RECOMBINATION-DEPENDENT CHECKPOINT 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/235085v1?rss=1"
</link>
<description><![CDATA[
In somatic cells, H2afx and Mdc1 are close functional partners in DNA repair and damage response. However, it is not known whether they are also involved in the maintenance of genome integrity in meiosis. By analyzing chromosome dynamics in H2afx-/- spermatocytes, we found that synapsis of the autosomes and X-Y chromosomes were impaired in a relevant fraction of cells. Such defect correlated with an abnormal recombination profile. Conversely, Mdc1 was dispensable for the synapsis of the autosomes, and only played a minor role in X-Y synapsis, relatively to H2afx. This suggested that those genes have non-overlapping functions in chromosome synapsis. However, we observed that both genes play a similar role in the assembly of MLH3 onto chromosomes, a key step in crossover formation. Moreover, we showed that H2afx and Mdc1 cooperate in promoting the activation of the recombination-dependent checkpoint, a mechanism that restrains the differentiation of cells with unrepaired DSBs. This occurs by a mechanism that involves P53. Overall, our data showed that, in male germ cells, H2afx and Mdc1 promote the maintenance of genome integrity.
]]></description>
<dc:creator>Testa, E.</dc:creator>
<dc:creator>Nardozi, D.</dc:creator>
<dc:creator>Antinozzi, C.</dc:creator>
<dc:creator>Faieta, M.</dc:creator>
<dc:creator>Di Cecca, S.</dc:creator>
<dc:creator>Caggiano, C.</dc:creator>
<dc:creator>Fukuda, T.</dc:creator>
<dc:creator>Bonanno, E.</dc:creator>
<dc:creator>Zenkun, L.</dc:creator>
<dc:creator>Maldonado, A.</dc:creator>
<dc:creator>Roig, I.</dc:creator>
<dc:creator>Di Giacomo, M.</dc:creator>
<dc:creator>Barchi, M.</dc:creator>
<dc:date>2017-12-15</dc:date>
<dc:identifier>doi:10.1101/235085</dc:identifier>
<dc:title><![CDATA[H2AFX AND MDC1 PROTECT GENOMIC INTEGRITY IN MALE GERM CELLS BY PROMOTING RECOMBINATION AND ACTIVATION OF THE RECOMBINATION-DEPENDENT CHECKPOINT]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/115659v1?rss=1">
<title>
<![CDATA[
Quantitative evaluation of two-photon calcium imaging modalities for high-speed volumetric calcium imaging in scattering brain tissue 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/115659v1?rss=1"
</link>
<description><![CDATA[
Considerable efforts are currently being devoted to enhance the speed, spatial resolution and the size of the 3D sample volumes in which calcium imaging methods can capture neuronal network activity in different model systems. In the mammalian brain, tissue scattering severely limits the use of parallel acquisition techniques such as wide-field imaging and, as a consequence, methods based on two-photon point-scanning (2PM) have become the method of choice. However, 2PM faces severe restrictions due to technical limitations such as scan speed, laser power, and those related to the fluorescent probes, calling for conceptually new approaches to enhance the performance of two-photon calcium imaging schemes. Here we provide a detailed quantitative evaluation and comparison of different excitation/detection modalities from the perspective of detecting neuronal activity that are based on different point-spread functions (PSF), laser repetition rates and sampling strategies. We demonstrate the conditions for which imaging speed and signal-to-noise ratio are optimized for a given average power. Our results are based on numerical simulations which are informed by experimentally measured parameters and show that volumetric field of view and acquisition speed can be considerably improved compared to traditional 2PM schemes by a holistic optimization approach.
]]></description>
<dc:creator>Weisenburger, S.</dc:creator>
<dc:creator>Prevedel, R.</dc:creator>
<dc:creator>Vaziri, A.</dc:creator>
<dc:date>2017-03-10</dc:date>
<dc:identifier>doi:10.1101/115659</dc:identifier>
<dc:title><![CDATA[Quantitative evaluation of two-photon calcium imaging modalities for high-speed volumetric calcium imaging in scattering brain tissue]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-03-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/049205v1?rss=1">
<title>
<![CDATA[
Omics Discovery Index - Discovering and Linking Public Omics Datasets 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/049205v1?rss=1"
</link>
<description><![CDATA[
Biomedical data, in particular omics datasets are being generated at an unprecedented rate. This is due to the falling costs of generating experimental data, improved accuracy and better accessibility to different omics platforms such as genomics, proteomics and metabolomics1,2. As a result, the number of deposited datasets in public repositories originating from various omics approaches has increased dramatically in recent years. With strong support from scientific journals and funders, public data sharing is increasingly considered to be a good scientific practice, facilitating the confirmation of original results, increasing the reproducibility of the analyses, enabling the exploration of new or related hypotheses, and fostering the identification of potential errors, discouraging fraud3. This increase in public data deposition of omics results is a good starting point, but opens up a series of new challenges. For example the research community must now find more efficient ways for storing, organizing and providing access to biomedical data across platforms. These challenges range from achieving a common representation framework for the datasets and the associated metadata from different omics fields, to the availability of efficient methods, protocols and file formats for data exchange between multiple repositories. Therefore, there is a great need for development of new platforms and applications to make possible to search datasets across different omics fields, making such information accessible to the end-user. The FAIR paradigm describes a set of guiding principles to address many of these issues, and aims to make data Findable, Accessible, Interoperable and Re-usable(https://www.force11.org/group/fairgroup/fairprinciples).
]]></description>
<dc:creator>Yasset Perez-Riverol</dc:creator>
<dc:creator>Mingze Bai</dc:creator>
<dc:creator>Felipe Leprevost</dc:creator>
<dc:creator>Silvano Squizzato</dc:creator>
<dc:creator>Young Mi Park</dc:creator>
<dc:creator>Ove Kenneth Haug</dc:creator>
<dc:creator>Adam J. Carroll</dc:creator>
<dc:creator>Dylan Spalding</dc:creator>
<dc:creator>Justin Paschall</dc:creator>
<dc:creator>Mingxun Wang</dc:creator>
<dc:creator>Noemi del-Toro</dc:creator>
<dc:creator>Tobias Ternent</dc:creator>
<dc:creator>Peng Zhang</dc:creator>
<dc:creator>Nicola Buso</dc:creator>
<dc:creator>Nuno Bandeira</dc:creator>
<dc:creator>Eric Deutsch</dc:creator>
<dc:creator>David S. Campbell</dc:creator>
<dc:creator>Ronald C. Beavis</dc:creator>
<dc:creator>Reza Salek</dc:creator>
<dc:creator>Alexey Nesvizhskii</dc:creator>
<dc:creator>Susanna-Assunta Sansone</dc:creator>
<dc:creator>Christoph Steinbeck</dc:creator>
<dc:creator>Rodrigo Lopez</dc:creator>
<dc:creator>Juan Antonio Vizcaino</dc:creator>
<dc:creator>Peipei Ping</dc:creator>
<dc:creator>Henning Hermjakob</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-04-18</dc:date>
<dc:identifier>doi:10.1101/049205</dc:identifier>
<dc:title><![CDATA[Omics Discovery Index - Discovering and Linking Public Omics Datasets]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-04-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/247882v1?rss=1">
<title>
<![CDATA[
Functional interaction of low-homology FRPs from different cyanobacteria with Synechocystis OCP 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/247882v1?rss=1"
</link>
<description><![CDATA[
Photosynthesis requires a balance between efficient light harvesting and protection against photodamage. The cyanobacterial photoprotection system uniquely relies on the functioning of the photoactive orange carotenoid protein (OCP) that under intense illumination provides fluorescence quenching of the light-harvesting antenna complexes, phycobilisomes. The recently identified fluorescence recovery protein (FRP) binds to the photoactivated OCP and accelerates its relaxation into the basal form, completing the regulatory circle. The molecular mechanism of FRP functioning is largely controversial. Moreover, since the available knowledge has mainly been gained from studying Synechocystis proteins, the cross-species conservation of the FRP mechanism remains unexplored. Besides phylogenetic analysis, we performed a detailed structural-functional analysis of two selected low-homology FRPs by comparing them with Synechocystis FRP (SynFRP). While adopting similar dimeric conformations in solution and preserving binding preferences of SynFRP toward various OCP variants, the low-homology FRPs demonstrated distinct binding stoichiometries and differentially accentuated features of this functional interaction. By providing clues to understand the FRP mechanism universally, our results also establish foundations for upcoming structural investigations necessary to elucidate the FRP-dependent regulatory mechanism.
]]></description>
<dc:creator>Slonimskiy, Y. B.</dc:creator>
<dc:creator>Maksimov, E. G.</dc:creator>
<dc:creator>Lukashev, E. P.</dc:creator>
<dc:creator>Moldenhauer, M.</dc:creator>
<dc:creator>Jeffries, C. M.</dc:creator>
<dc:creator>Svergun, D. I.</dc:creator>
<dc:creator>Friedrich, T.</dc:creator>
<dc:creator>Sluchanko, N. N.</dc:creator>
<dc:date>2018-01-15</dc:date>
<dc:identifier>doi:10.1101/247882</dc:identifier>
<dc:title><![CDATA[Functional interaction of low-homology FRPs from different cyanobacteria with Synechocystis OCP]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/313031v1?rss=1">
<title>
<![CDATA[
Comprehensive variant effect predictions of single nucleotide variants in model organisms 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/313031v1?rss=1"
</link>
<description><![CDATA[
The effect of single nucleotide variants (SNVs) in coding and non-coding regions is of great interest in genetics. Although many computational methods aim to elucidate the effects of SNVs on cellular mechanisms, it is not straightforward to comprehensively cover different molecular effects. To address this we compiled and benchmarked sequence and structure-based variant effect predictors and we analyzed the impact of nearly all possible amino acid and nucleotide variants in the reference genomes of H. sapiens, S. cerevisiae and E. coli. Studied mechanisms include protein stability, interaction interfaces, post-translational modifications and transcription factor binding sites. We apply this resource to the study of natural and disease coding variants. We also show how variant effects can be aggregated to generate protein complex burden scores that uncover protein complex to phenotype associations based on a set of newly generated growth profiles of 93 sequenced S. cerevisiae strains in 43 conditions. This resource is available through mutfunc, a tool by which users can query precomputed predictions by providing amino acid or nucleotide-level variants.
]]></description>
<dc:creator>Wagih, O.</dc:creator>
<dc:creator>Busby, B.</dc:creator>
<dc:creator>Galardini, M.</dc:creator>
<dc:creator>Memon, D.</dc:creator>
<dc:creator>Typas, A.</dc:creator>
<dc:creator>Beltrao, P.</dc:creator>
<dc:date>2018-05-02</dc:date>
<dc:identifier>doi:10.1101/313031</dc:identifier>
<dc:title><![CDATA[Comprehensive variant effect predictions of single nucleotide variants in model organisms]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/126466v1?rss=1">
<title>
<![CDATA[
Cell type boundaries organize plant development 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/126466v1?rss=1"
</link>
<description><![CDATA[
In plants the dorsoventral boundary of leaves defines an axis of symmetry through the centre of the organ separating the top (dorsal) and bottom (ventral) tissues. Although the positioning of this boundary is critical for leaf morphogenesis, how the boundary is established and how it influences development remains unclear. Using live-imaging and perturbation experiments we show that leaf orientation, morphology and position are pre-patterned by HD-ZIPIII and KAN gene expression in the shoot, leading to a model in which dorsoventral genes coordinate to regulate plant development by localizing auxin response between their expression domains. However we also find that auxin levels feedback on dorsoventral patterning by spatially organizing HD-ZIPIII and KAN expression in the shoot periphery. By demonstrating that the regulation of these genes by auxin also governs their response to wounds, our results also provide a parsimonious explanation for the influence of wounds on leaf dorsoventrality.nnOnce sentence summaryCell type boundaries regulate plant development
]]></description>
<dc:creator>Heisler, M. G.</dc:creator>
<dc:creator>Caggiano, M. P.</dc:creator>
<dc:creator>Yu, X.</dc:creator>
<dc:creator>Bhatia, N.</dc:creator>
<dc:creator>Larsson, A.</dc:creator>
<dc:creator>Ram, H.</dc:creator>
<dc:creator>Ohno, C. K.</dc:creator>
<dc:creator>Sappl, P.</dc:creator>
<dc:creator>Meyerowitz, E. M.</dc:creator>
<dc:creator>Jonsson, H.</dc:creator>
<dc:date>2017-04-11</dc:date>
<dc:identifier>doi:10.1101/126466</dc:identifier>
<dc:title><![CDATA[Cell type boundaries organize plant development]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/309831v1?rss=1">
<title>
<![CDATA[
A rapid and robust method for single cell chromatin accessibility profiling 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/309831v1?rss=1"
</link>
<description><![CDATA[
The assay for transposase-accessible chromatin using sequencing (ATAC-seq) is widely used to identify regulatory regions throughout the genome. However, very few studies have been performed at the single cell level (scATAC-seq) due to technical challenges. Here we developed a simple and robust plate-based scATAC-seq method, combining upfront bulk Tn5 tagging with single-nuclei sorting. We demonstrated that our method worked robustly across various systems, including fresh and cryopreserved cells from primary tissues. By profiling over 3,000 splenocytes, we identify distinct immune cell types and reveal cell type-specific regulatory regions and related transcription factors.
]]></description>
<dc:creator>Chen, X.</dc:creator>
<dc:creator>Natarajan, K. N.</dc:creator>
<dc:creator>Teichmann, S. A.</dc:creator>
<dc:date>2018-04-27</dc:date>
<dc:identifier>doi:10.1101/309831</dc:identifier>
<dc:title><![CDATA[A rapid and robust method for single cell chromatin accessibility profiling]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/080796v1?rss=1">
<title>
<![CDATA[
An improved assembly and annotation of the allohexaploid wheat genome identifies complete families of agronomic genes and provides genomic evidence for chromosomal translocations. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/080796v1?rss=1"
</link>
<description><![CDATA[
Advances in genome sequencing and assembly technologies are generating many high quality genome sequences, but assemblies of large, repeat-rich polyploid genomes, such as that of bread wheat, remain fragmented and incomplete. We have generated a new wheat whole-genome shotgun sequence assembly using a combination of optimised data types and an assembly algorithm designed to deal with large and complex genomes. The new assembly represents more than 78% of the genome with a scaffold N50 of 88.8kbp that has a high fidelity to the input data. Our new annotation combines strand-specific Illumina RNAseq and PacBio full-length cDNAs to identify 104,091 high confidence protein-coding genes and 10,156 non-coding RNA genes. We confirmed three known and identified one novel genome rearrangements. Our approach enables the rapid and scalable assembly of wheat genomes, the identification of structural variants, and the definition of complete gene models, all powerful resources for trait analysis and breeding of this key global crop. [Supplemental material is available for this article.]
]]></description>
<dc:creator>Clavijo, B. J.</dc:creator>
<dc:creator>Venturini, L.</dc:creator>
<dc:creator>Schudoma, C.</dc:creator>
<dc:creator>Garcia Accinelli, G.</dc:creator>
<dc:creator>Kaithakottil, G.</dc:creator>
<dc:creator>Wright, J.</dc:creator>
<dc:creator>Borrill, P.</dc:creator>
<dc:creator>Kettleborough, G.</dc:creator>
<dc:creator>Heavens, D.</dc:creator>
<dc:creator>Chapman, H.</dc:creator>
<dc:creator>Lipcombe, J.</dc:creator>
<dc:creator>Barker, T.</dc:creator>
<dc:creator>Lu, F.-H.</dc:creator>
<dc:creator>McKenzie, N.</dc:creator>
<dc:creator>Raats, D.</dc:creator>
<dc:creator>Ramirez Gonzalez, R. H.</dc:creator>
<dc:creator>Coince, A.</dc:creator>
<dc:creator>Peel, N.</dc:creator>
<dc:creator>Percival-Alwyn, L.</dc:creator>
<dc:creator>Duncan, O.</dc:creator>
<dc:creator>Trosch, J.</dc:creator>
<dc:creator>Yu, G.</dc:creator>
<dc:creator>Bolser, D.</dc:creator>
<dc:creator>Naamati, G.</dc:creator>
<dc:creator>Kerhornou, A.</dc:creator>
<dc:creator>Spannagl, M.</dc:creator>
<dc:creator>Gundlach, H.</dc:creator>
<dc:creator>Haberer, G.</dc:creator>
<dc:creator>Davey, R. P.</dc:creator>
<dc:creator>Fosker, C.</dc:creator>
<dc:creator>Di Palma, F.</dc:creator>
<dc:creator>Phillips, A.</dc:creator>
<dc:creator>Millar, A. H.</dc:creator>
<dc:creator>Kersey, P. J.</dc:creator>
<dc:creator>Uauy, C.</dc:creator>
<dc:creator>Krasileva, K. V.</dc:creator>
<dc:creator>Swarbreck, D.</dc:creator>
<dc:creator>Bevan, M. W.</dc:creator>
<dc:creator>Clark, M. D.</dc:creator>
<dc:date>2016-10-13</dc:date>
<dc:identifier>doi:10.1101/080796</dc:identifier>
<dc:title><![CDATA[An improved assembly and annotation of the allohexaploid wheat genome identifies complete families of agronomic genes and provides genomic evidence for chromosomal translocations.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-10-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/024356v1?rss=1">
<title>
<![CDATA[
Landscape and dynamics of transcription initiation in the malaria parasite Plasmodium falciparum 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/024356v1?rss=1"
</link>
<description><![CDATA[
The lack of a comprehensive map of transcription start sites (TSS) across the highly AT-rich genome of P. falciparum has hindered progress towards deciphering the molecular mechanisms that underly the timely regulation of gene expression in this malaria parasite. Using high-throughput sequencing technologies, we generated a comprehensive atlas of transcription initiation events at single nucleotide-resolution during the parasite intra-erythrocytic developmental cycle. This detailed analysis of TSS usage enabled us to define architectural features of plasmodial promoters. We demonstrate that TSS selection and strength are constrained by local nucleotide composition. Furthermore, we provide evidence for coordinate and stage-specific TSS usage from distinct sites within the same transcriptional unit, thereby producing transcript isoforms, a subset of which are developmentally regulated. This work offers a framework for further investigations into the interactions between genomic sequences and regulatory factors governing the complex transcriptional program of this major human pathogen.
]]></description>
<dc:creator>Sophie Adjalley</dc:creator>
<dc:creator>Christophe Chabbert</dc:creator>
<dc:creator>Bernd Klaus</dc:creator>
<dc:creator>Vicent Pelechano</dc:creator>
<dc:creator>Lars Steinmetz</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-08-10</dc:date>
<dc:identifier>doi:10.1101/024356</dc:identifier>
<dc:title><![CDATA[Landscape and dynamics of transcription initiation in the malaria parasite Plasmodium falciparum]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-08-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/119784v1?rss=1">
<title>
<![CDATA[
Assessing The Reliability Of Spike-In Normalization For Analyses Of Single-Cell RNA Sequencing Data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/119784v1?rss=1"
</link>
<description><![CDATA[
By profiling the transcriptomes of individual cells, single-cell RNA sequencing provides unparalleled resolution to study cellular heterogeneity. However, this comes at the cost of high technical noise, including cell-specific biases in capture efficiency and library generation. One strategy for removing these biases is to add a constant amount of spike-in RNA to each cell, and to scale the observed expression values so that the coverage of spike-in RNA is constant across cells. This approach has previously been criticized as its accuracy depends on the precise addition of spike-in RNA to each sample, and on similarities in behaviour (e.g., capture efficiency) between the spike-in and endogenous transcripts. Here, we perform mixture experiments using two different sets of spike-in RNA to quantify the variance in the amount of spike-in RNA added to each well in a plate-based protocol. We also obtain an upper bound on the variance due to differences in behaviour between the two spike-in sets. We demonstrate that both factors are small contributors to the total technical variance and have only minor effects on downstream analyses such as detection of highly variable genes and clustering. Our results suggest that spike-in normalization is reliable enough for routine use in single-cell RNA sequencing data analyses.
]]></description>
<dc:creator>Lun, A. T.</dc:creator>
<dc:creator>Calero-Nieto, F. J.</dc:creator>
<dc:creator>Haim-Vilmovsky, L.</dc:creator>
<dc:creator>Gottgens, B.</dc:creator>
<dc:creator>Marioni, J. C.</dc:creator>
<dc:date>2017-03-23</dc:date>
<dc:identifier>doi:10.1101/119784</dc:identifier>
<dc:title><![CDATA[Assessing The Reliability Of Spike-In Normalization For Analyses Of Single-Cell RNA Sequencing Data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-03-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/126136v1?rss=1">
<title>
<![CDATA[
Dense And Accurate Whole-Chromosome Haplotyping Of Individual Genomes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/126136v1?rss=1"
</link>
<description><![CDATA[
The diploid nature of the genome is neglected in many analyses done today, where a genome is perceived as a set of unphased variants with respect to a reference genome. Many important biological phenomena such as compound heterozygosity and epistatic effects between enhancers and target genes, however, can only be studied when haplotype-resolved genomes are available. This lack of haplotype-level analyses can be explained by a dearth of methods to produce dense and accurate chromosome-length haplotypes at reasonable costs. Here we introduce an integrative phasing strategy that combines global, but sparse haplotypes obtained from strand-specific single cell sequencing (Strand-seq) with dense, yet local, haplotype information available through long-read or linked-read sequencing. Our experiments provide comprehensive guidance on favorable combinations of Strand-seq libraries and sequencing coverages to obtain complete and genome-wide haplotypes of a single individual genome (NA12878) at manageable costs. We were able to reliably assign > 95% of alleles to their parental haplotypes using as few as 10 Strand-seq libraries in combination with 10-fold coverage PacBio data or, alternatively, 10X Genomics linked-read sequencing data. We conclude that the combination of Strand-seq with different sequencing technologies represents an attractive solution to chart the unique genetic variation of diploid genomes.
]]></description>
<dc:creator>Porubsky, D.</dc:creator>
<dc:creator>Garg, S.</dc:creator>
<dc:creator>Sanders, A. D.</dc:creator>
<dc:creator>Korbel, J. O.</dc:creator>
<dc:creator>Guryev, V.</dc:creator>
<dc:creator>Lansdorp, P. M.</dc:creator>
<dc:creator>Marschall, T.</dc:creator>
<dc:date>2017-04-10</dc:date>
<dc:identifier>doi:10.1101/126136</dc:identifier>
<dc:title><![CDATA[Dense And Accurate Whole-Chromosome Haplotyping Of Individual Genomes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/158659v1?rss=1">
<title>
<![CDATA[
Repeat associated mechanisms of genome evolution and function revealed by the Mus caroli and Mus pahari genomes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/158659v1?rss=1"
</link>
<description><![CDATA[
Understanding the mechanisms driving lineage-specific evolution in both primates and rodents has been hindered by the lack of sister clades with a similar phylogenetic structure having high-quality genome assemblies. Here, we have created chromosome-level assemblies of the Mus caroli and Mus pahari genomes. Together with the Mus musculus and Rattus norvegicus genomes, this set of rodent genomes is similar in divergence times to the Hominidae (human-chimpanzee-gorilla-orangutan). By comparing the evolutionary dynamics between the Muridae and Hominidae, we identified punctate events of chromosome reshuffling that shaped the ancestral karyotype of Mus musculus and Mus caroli between 3 to 6 MYA, but that are absent in the Hominidae. In fact, Hominidae show between four-and seven-fold lower rates of nucleotide change and feature turnover in both neutral and functional sequences suggesting an underlying coherence to the Muridae acceleration. Our system of matched, high-quality genome assemblies revealed how specific classes of repeats can play lineage-specific roles in related species. For example, recent LINE activity has remodeled protein-coding loci to a greater extent across the Muridae than the Hominidae, with functional consequences at the species level such as reproductive isolation. Furthermore, we charted a Muridae-specific retrotransposon expansion at unprecedented resolution, revealing how a single nucleotide mutation transformed a specific SINE element into an active CTCF binding site carrier specifically in Mus caroli. This process resulted in thousands of novel, species-specific CTCF binding sites. Our results demonstrate that the comparison of matched phylogenetic sets of genomes will be an increasingly powerful strategy for understanding mammalian biology.
]]></description>
<dc:creator>Thybert, D.</dc:creator>
<dc:creator>Roller, M.</dc:creator>
<dc:creator>Navarro, F. C. P.</dc:creator>
<dc:creator>Fiddes, I.</dc:creator>
<dc:creator>Streeter, I.</dc:creator>
<dc:creator>Feig, C.</dc:creator>
<dc:creator>Martin-Galvez, D.</dc:creator>
<dc:creator>Kolmogorov, M.</dc:creator>
<dc:creator>Janousek, V.</dc:creator>
<dc:creator>Akanni, W.</dc:creator>
<dc:creator>Aken, B.</dc:creator>
<dc:creator>Aldridge, S.</dc:creator>
<dc:creator>Chakrapani, V.</dc:creator>
<dc:creator>Chow, W.</dc:creator>
<dc:creator>Clarke, L.</dc:creator>
<dc:creator>Cummins, C.</dc:creator>
<dc:creator>Doran, A.</dc:creator>
<dc:creator>Dunn, M.</dc:creator>
<dc:creator>Goodstadt, L.</dc:creator>
<dc:creator>Howe, K.</dc:creator>
<dc:creator>Howell, M.</dc:creator>
<dc:creator>Josselin, A.-A.</dc:creator>
<dc:creator>Karn, R. C.</dc:creator>
<dc:creator>Laukaitis, C. M.</dc:creator>
<dc:creator>Jingtao, L.</dc:creator>
<dc:creator>Martin, F.</dc:creator>
<dc:creator>Muffato, M.</dc:creator>
<dc:creator>Quail, M. A.</dc:creator>
<dc:creator>Sisu, C.</dc:creator>
<dc:creator>Stanke, M.</dc:creator>
<dc:creator>Stefflova, K.</dc:creator>
<dc:creator>Van Oosterhout, C.</dc:creator>
<dc:creator>Veyrunes, F.</dc:creator>
<dc:creator>Ward, B.</dc:creator>
<dc:creator>Yang, F.</dc:creator>
<dc:creator>Yazdanifar, G.</dc:creator>
<dc:creator>Zadissa, A.</dc:creator>
<dc:creator>Adams, D.</dc:creator>
<dc:creator>Brazma, A.</dc:creator>
<dc:creator>Gerstein, M.</dc:creator>
<dc:creator>Paten, B.</dc:creator>
<dc:creator>Pham, S.</dc:creator>
<dc:creator>Keane, T.</dc:creator>
<dc:creator>Odom, D. T.</dc:creator>
<dc:creator>Flicek, P.</dc:creator>
<dc:date>2017-07-02</dc:date>
<dc:identifier>doi:10.1101/158659</dc:identifier>
<dc:title><![CDATA[Repeat associated mechanisms of genome evolution and function revealed by the Mus caroli and Mus pahari genomes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/199547v1?rss=1">
<title>
<![CDATA[
Deciphering programs of transcriptional regulation by combined deconvolution of multiple omics layers 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/199547v1?rss=1"
</link>
<description><![CDATA[
Metazoans are crucially dependent on multiple layers of gene regulatory mechanisms which allow them to control gene expression across developmental stages, tissues and cell types. Multiple recent research consortia have aimed to generate comprehensive datasets to profile the activity of these cell type- and condition-specific regulatory landscapes across many different cell lines and primary cells. However, extraction of genes or regulatory elements specific to certain entities from these datasets remains challenging. We here propose a novel method based on non-negative matrix factorization for disentangling and associating huge multi-assay datasets including chromatin accessibility and gene expression data. Taking advantage of implementations of NMF algorithms in the GPU CUDA environment full datasets composed of tens of thousands of genes as well as hundreds of samples can be processed without the need for prior feature selection to reduce the input size. Applying this framework to multiple layers of genomic data derived from human blood cells we unravel mechanisms of regulation of cell type-specific expression in T-cells and monocytes.
]]></description>
<dc:creator>Huebschmann, D.</dc:creator>
<dc:creator>Kurzawa, N.</dc:creator>
<dc:creator>Steinhauser, S.</dc:creator>
<dc:creator>Rentzsch, P.</dc:creator>
<dc:creator>Kraemer, S.</dc:creator>
<dc:creator>Andresen, C.</dc:creator>
<dc:creator>Park, J.</dc:creator>
<dc:creator>Eils, R.</dc:creator>
<dc:creator>Schlesner, M.</dc:creator>
<dc:creator>Herrmann, C.</dc:creator>
<dc:date>2017-10-08</dc:date>
<dc:identifier>doi:10.1101/199547</dc:identifier>
<dc:title><![CDATA[Deciphering programs of transcriptional regulation by combined deconvolution of multiple omics layers]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/138685v1?rss=1">
<title>
<![CDATA[
Joint Profiling Of Chromatin Accessibility, DNA Methylation And Transcription In Single Cells 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/138685v1?rss=1"
</link>
<description><![CDATA[
Parallel single-cell sequencing protocols represent powerful methods for investigating regulatory relationships, including epigenome-transcriptome interactions. Here, we report a novel single-cell method for parallel chromatin accessibility, DNA methylation and transcriptome profiling. scNMT-seq (single-cell nucleosome, methylation and transcription sequencing) uses a GpC methyltransferase to label open chromatin followed by bisulfite and RNA sequencing. We validate scNMT-seq by applying it to differentiating mouse embryonic stem cells, finding links between all three molecular layers and revealing dynamic coupling between epigenomic layers during differentiation.
]]></description>
<dc:creator>Clark, S. J.</dc:creator>
<dc:creator>Argelaguet, R.</dc:creator>
<dc:creator>Kapourani, C.-A.</dc:creator>
<dc:creator>Stubbs, T. M.</dc:creator>
<dc:creator>Lee, H. J.</dc:creator>
<dc:creator>Krueger, F.</dc:creator>
<dc:creator>Sanguinetti, G.</dc:creator>
<dc:creator>Kelsey, G.</dc:creator>
<dc:creator>Marioni, J. C.</dc:creator>
<dc:creator>Stegle, O.</dc:creator>
<dc:creator>Reik, W.</dc:creator>
<dc:date>2017-05-17</dc:date>
<dc:identifier>doi:10.1101/138685</dc:identifier>
<dc:title><![CDATA[Joint Profiling Of Chromatin Accessibility, DNA Methylation And Transcription In Single Cells]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/073734v1?rss=1">
<title>
<![CDATA[
Prefrontal cortical control of a brainstem social behavior circuit 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/073734v1?rss=1"
</link>
<description><![CDATA[
The prefrontal cortex plays a critical role in adjusting an organisms behavior to its environment. In particular, numerous studies have implicated the prefrontal cortex in the control of social behavior, but the neural circuits that mediate these effects remain unknown. Here we investigated behavioral adaptation to social defeat in mice and uncovered a critical contribution of neural projections from the medial prefrontal cortex to the dorsal periaqueductal grey, a brainstem area vital for defensive responses. Social defeat caused a weakening of functional connectivity between these two areas and selective inhibition of these projections mimicked the behavioral effects of social defeat. These findings define a specific neural projection by which the prefrontal cortex can control and adapt social behavior.
]]></description>
<dc:creator>Tamara B. Franklin</dc:creator>
<dc:creator>Bianca A. Silva</dc:creator>
<dc:creator>Zinaida Perova</dc:creator>
<dc:creator>Livia Marrone</dc:creator>
<dc:creator>Maria E. Masferrer</dc:creator>
<dc:creator>Yang Zhan</dc:creator>
<dc:creator>Angie Kaplan</dc:creator>
<dc:creator>Louise Greetham</dc:creator>
<dc:creator>Voilaine Verrechia</dc:creator>
<dc:creator>Andreas Halman</dc:creator>
<dc:creator>Sara Pagella</dc:creator>
<dc:creator>Alexei L. Vyssotski</dc:creator>
<dc:creator>Anna Illarianova</dc:creator>
<dc:creator>Tiago Branco</dc:creator>
<dc:creator>Cornelius T. Gross</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-09-09</dc:date>
<dc:identifier>doi:10.1101/073734</dc:identifier>
<dc:title><![CDATA[Prefrontal cortical control of a brainstem social behavior circuit]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-09-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/147777v1?rss=1">
<title>
<![CDATA[
Integrating long-range connectivity information into de Bruijn graphs 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/147777v1?rss=1"
</link>
<description><![CDATA[
MotivationThe de Bruijn graph is a simple and efficient data structure that is used in many areas of sequence analysis including genome assembly, read error correction and variant calling. The data structure has a single parameter k, is straightforward to implement and is tractable for large genomes with high sequencing depth. It also enables representation of multiple samples simultaneously to facilitate comparison. However, unlike the string graph, a de Bruijn graph does not retain long range information that is inherent in the read data. For this reason, applications that rely on de Bruijn graphs can produce sub-optimal results given their input.nnResultsWe present a novel assembly graph data structure: the Linked de Bruijn Graph (LdBG). Constructed by adding annotations on top of a de Bruijn graph, it stores long range connectivity information through the graph. We show that with error-free data it is possible to losslessly store and recover sequence from a Linked de Bruijn graph. With assembly simulations we demonstrate that the LdBG data structure outperforms both the de Bruijn graph and the String Graph Assembler (SGA). Finally we apply the LdBG to Klebsiella pneumoniae short read data to make large (12 kbp) variant calls, which we validate using PacBio sequencing data, and to characterise the genomic context of drug-resistance genes.nnAvailabilityLinked de Bruijn Graphs and associated algorithms are implemented as part of McCortex, available under the MIT license at https://github.com/mcvean/mccortex.nnContactturner.isaac@gmail.com.
]]></description>
<dc:creator>Turner, I.</dc:creator>
<dc:creator>Garimella, K. V.</dc:creator>
<dc:creator>Iqbal, Z.</dc:creator>
<dc:creator>McVean, G.</dc:creator>
<dc:date>2017-06-08</dc:date>
<dc:identifier>doi:10.1101/147777</dc:identifier>
<dc:title><![CDATA[Integrating long-range connectivity information into de Bruijn graphs]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/413211v1?rss=1">
<title>
<![CDATA[
Modularity, criticality and evolvability of a developmental gene regulatory network 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/413211v1?rss=1"
</link>
<description><![CDATA[
The existence of discrete phenotypic traits suggests that the complex regulatory processes which produce them are functionally modular. These processes are usually represented by networks. Only modular networks can be partitioned into intelligible subcircuits able to evolve relatively independently. Traditionally, functional modularity is approximated by detection of modularity in network structure. However, the correlation between structure and function is loose. Many regulatory networks exhibit modular behaviour without structural modularity. Here we partition an experimentally tractable regulatory network--the gap gene system of dipteran insects--using an alternative approach. We show that this system, although not structurally modular, is composed of dynamical modules driving different aspects of whole-network behaviour. All these subcircuits share the same regulatory structure, but differ in components and sensitivity to regulatory interactions. Some subcircuits are in a state of criticality while others are not, which explains the observed differential evolvability of the various expression features in the system.
]]></description>
<dc:creator>Verd, B.</dc:creator>
<dc:creator>Monk, N. A.</dc:creator>
<dc:creator>Jaeger, J.</dc:creator>
<dc:date>2018-09-10</dc:date>
<dc:identifier>doi:10.1101/413211</dc:identifier>
<dc:title><![CDATA[Modularity, criticality and evolvability of a developmental gene regulatory network]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/168716v1?rss=1">
<title>
<![CDATA[
Architecture of TAF11/TAF13/TBP complex suggests novel regulatory state in General Transcription Factor TFIID function 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/168716v1?rss=1"
</link>
<description><![CDATA[
General transcription factor TFIID is a key component of RNA polymerase II transcription initiation. Human TFIID is a megadalton-sized complex comprising TATA-binding protein (TBP) and 13 TBP-associated factors (TAFs). TBP binds to core promoter DNA, recognizing the TATA-box. We identified a ternary complex formed by TBP and the histone fold (HF) domain-containing TFIID subunits TAF11 and TAF13. We demonstrate that TAF11/TAF13 competes for TBP binding with TATA-box DNA, and also with the N-terminal domain of TAF1 previously implicated in TATA-box mimicry. In an integrative approach combining crystal coordinates, biochemical analyses and data from cross-linking mass-spectrometry (CLMS), we determine the architecture of the TAF11/TAF13/TBP complex, revealing TAF11/TAF13 interaction with the DNA binding surface of TBP. We identify a highly conserved C-terminal TBP-binding domain (CTID) in TAF13 which is essential for supporting cell growth. Our results thus have implications for cellular TFIID assembly and suggest a novel regulatory state for TFIID function.
]]></description>
<dc:creator>Gupta, K.</dc:creator>
<dc:creator>Watson, A. A.</dc:creator>
<dc:creator>Baptista, T.</dc:creator>
<dc:creator>Scheer, E.</dc:creator>
<dc:creator>Chambers, A. L.</dc:creator>
<dc:creator>Koehler, C.</dc:creator>
<dc:creator>Zou, J.</dc:creator>
<dc:creator>Obong-Ebong, I.</dc:creator>
<dc:creator>Kandiah, E.</dc:creator>
<dc:creator>Temblador, A.</dc:creator>
<dc:creator>Round, A.</dc:creator>
<dc:creator>Forest, E.</dc:creator>
<dc:creator>Man, P.</dc:creator>
<dc:creator>Bieniossek, C.</dc:creator>
<dc:creator>Laue, E. D.</dc:creator>
<dc:creator>Lemke, E. A.</dc:creator>
<dc:creator>Rappsilber, J.</dc:creator>
<dc:creator>Robinson, C. V.</dc:creator>
<dc:creator>Devys, D.</dc:creator>
<dc:creator>Tora, L.</dc:creator>
<dc:creator>Berger, I.</dc:creator>
<dc:date>2017-07-26</dc:date>
<dc:identifier>doi:10.1101/168716</dc:identifier>
<dc:title><![CDATA[Architecture of TAF11/TAF13/TBP complex suggests novel regulatory state in General Transcription Factor TFIID function]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/095695v1?rss=1">
<title>
<![CDATA[
Mechanism of Nuclear Movements in a Multinucleated Cell 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/095695v1?rss=1"
</link>
<description><![CDATA[
Multinucleated cells are important in many organisms but the mechanisms governing the movements of nuclei sharing a common cytoplasm are not understood. In the hyphae of the plant pathogenic fungus Ashbya gossypii, nuclei move back and forth, occasionally bypassing each other, and, preventing the formation of nuclear clusters, this is essential for genetic stability. These movements depend on cytoplasmic microtubules emanating from the nuclei, that are pulled by dynein motors anchored at the cortex. Using 3D stochastic simulations with parameters constrained by the literature, we predict the cortical anchors density from the characteristics of nuclear movements. Altogether, the model accounts for the complex nuclear movements seen in vivo, using a minimal set of experimentally determined ingredients. Interestingly, these ingredients power the oscillations of the anaphase spindle in budding yeast, but in A. gossypii this system is not restricted to a specific nuclear cycle stage, possibly as a result of adaptation to hyphal growth and multinuclearity.
]]></description>
<dc:creator>Gibeaux, R.</dc:creator>
<dc:creator>Politi, A.</dc:creator>
<dc:creator>Philippsen, P.</dc:creator>
<dc:creator>Nedelec, F.</dc:creator>
<dc:date>2016-12-20</dc:date>
<dc:identifier>doi:10.1101/095695</dc:identifier>
<dc:title><![CDATA[Mechanism of Nuclear Movements in a Multinucleated Cell]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-12-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/023309v1?rss=1">
<title>
<![CDATA[
destiny – diffusion maps for large-scale single-cell data in R 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/023309v1?rss=1"
</link>
<description><![CDATA[
SummaryDiffusion maps are a spectral method for non-linear dimension reduction and have recently been adapted for the visualization of single cell expression data. Here we present destiny, an efficient R implementation of the diffusion map algorithm. Our package includes a single-cell specific noise model allowing for missing and censored values. In contrast to previous implementations, we further present an efficient nearest-neighbour approximation that allows for the processing of hundreds of thousands of cells and a functionality for projecting new data on existing diffusion maps. We exemplarily apply destiny to a recent time-resolved mass cytometry dataset of cellular reprogramming.nnAvailability and implementationdestiny is an open-source R/Bioconductor package http://bioconductor.org/packages/ destiny also available at https://www.helmholtz-muenchen.de/icb/destiny. A detailed vignette describing functions and workflows is provided with the package.nnContactcarsten.marr@helmholtz-muenchen.de, f.buettner@helmholtz-muenchen.de
]]></description>
<dc:creator>Philipp Angerer</dc:creator>
<dc:creator>Laleh Haghverdi</dc:creator>
<dc:creator>Maren Büttner</dc:creator>
<dc:creator>Fabian Theis</dc:creator>
<dc:creator>Carsten Marr</dc:creator>
<dc:creator>Florian Buettner</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-07-27</dc:date>
<dc:identifier>doi:10.1101/023309</dc:identifier>
<dc:title><![CDATA[destiny – diffusion maps for large-scale single-cell data in R]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-07-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/203554v1?rss=1">
<title>
<![CDATA[
Genomics in healthcare: GA4GH looks to 2022 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/203554v1?rss=1"
</link>
<description><![CDATA[
The Global Alliance for Genomics and Health (GA4GH), the standards-setting body in genomics for healthcare, aims to accelerate biomedical advancement globally. We describe the differences between healthcare- and research-driven genomics, discuss the implications of global, population-scale collections of human data for research, and outline mission-critical considerations in ethics, regulation, technology, data protection, and society. We present a crude model for estimating the rate of healthcare-funded genomes worldwide that accounts for the preparedness of each country for genomics, and infers a progression of cancer-related sequencing over time. We estimate that over 60 million patients will have their genome sequenced in a healthcare context by 2025. This represents a large technical challenge for healthcare systems, and a huge opportunity for research. We identify eight major practical, principled arguments to support the position that virtual cohorts of 100 million people or more would have tangible research benefits.
]]></description>
<dc:creator>Birney, E.</dc:creator>
<dc:creator>Vamathevan, J.</dc:creator>
<dc:creator>Goodhand, P.</dc:creator>
<dc:date>2017-10-15</dc:date>
<dc:identifier>doi:10.1101/203554</dc:identifier>
<dc:title><![CDATA[Genomics in healthcare: GA4GH looks to 2022]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/203232v1?rss=1">
<title>
<![CDATA[
Cell-specific modulation of nuclear pore complexes controls cell cycle entry during asymmetric division 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/203232v1?rss=1"
</link>
<description><![CDATA[
The acquisition of cellular identity is coupled to changes in the nuclear periphery and nuclear pore complexes (NPCs). Whether and how these changes determine cell fate remains unclear. We have uncovered a mechanism regulating NPC acetylation to direct cell fate after asymmetric division in budding yeast. The lysine deacetylase Hos3 associates specifically with daughter cell NPCs during mitosis to delay cell cycle entry (Start). Hos3-dependent deacetylation of nuclear basket and central channel nucleoporins establishes daughter cell-specific nuclear accumulation of the transcriptional repressor Whi5 during anaphase and perinuclear silencing of the CLN2 gene in the following G1 phase. Hos3-dependent coordination of both events restrains Start in daughter but not in mother cells. We propose that deacetylation modulates transport-dependent and - independent functions of NPCs, leading to differential cell cycle progression in mother and daughter cells. Similar mechanisms might regulate NPC functions in specific cell types and/or cell cycle stages in multicellular organisms.
]]></description>
<dc:creator>Kumar, A.</dc:creator>
<dc:creator>Sharma, P.</dc:creator>
<dc:creator>Shcheprova, Z.</dc:creator>
<dc:creator>Daulny, A.</dc:creator>
<dc:creator>Sanmartin, T.</dc:creator>
<dc:creator>Matucci, I.</dc:creator>
<dc:creator>Funaya, C.</dc:creator>
<dc:creator>Beato, M.</dc:creator>
<dc:creator>Mendoza, M.</dc:creator>
<dc:date>2017-10-14</dc:date>
<dc:identifier>doi:10.1101/203232</dc:identifier>
<dc:title><![CDATA[Cell-specific modulation of nuclear pore complexes controls cell cycle entry during asymmetric division]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/067900v1?rss=1">
<title>
<![CDATA[
An Atlas of Human Kinase Regulation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/067900v1?rss=1"
</link>
<description><![CDATA[
The coordinated regulation of protein kinases is a rapid mechanism that integrates diverse cues and swiftly determines appropriate cellular responses. However, our understanding of cellular decision-making has been limited by the small number of simultaneously monitored phospho-regulatory events. Here, we have estimated changes in activity in 215 human kinases in 399 conditions from a compilation of nearly 3 million phosphopeptide quantifications. This atlas identifies commonly regulated kinases as those that are central in the signaling network and defines the logic relationships between kinase pairs. Co-regulation along the conditions predicts kinase-complex and kinase-substrate associations. Additionally, the kinase regulation profile acts as a molecular fingerprint to identify related and opposing signaling states. Using this atlas, we identified essential mediators of stem cell differentiation, modulators of Salmonella infection and new targets of AKT1. This provides a global view of human phosphorylation-based signaling and the necessary context to better understand kinase driven decision-making.
]]></description>
<dc:creator>David Ochoa</dc:creator>
<dc:creator>Mindaugas Jonikas</dc:creator>
<dc:creator>Robert T Lawrence</dc:creator>
<dc:creator>Bachir El Debs</dc:creator>
<dc:creator>Joel Selkrig</dc:creator>
<dc:creator>Athanasios Typas</dc:creator>
<dc:creator>Judit Villen</dc:creator>
<dc:creator>Silvia Santos</dc:creator>
<dc:creator>Pedro Beltrao</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-08-04</dc:date>
<dc:identifier>doi:10.1101/067900</dc:identifier>
<dc:title><![CDATA[An Atlas of Human Kinase Regulation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-08-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/337915v1?rss=1">
<title>
<![CDATA[
Benchmark and integration of resources for the estimation of human transcription factor activities 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/337915v1?rss=1"
</link>
<description><![CDATA[
Prediction of transcription factor (TF) activities from the gene expression of their targets (i.e. TF regulon) is becoming a widely-used approach to characterize the functional status of transcriptional regulatory circuits. Several strategies and datasets have been proposed to link the target genes likely regulated by a TF, each one providing a different level of evidence. The most established ones are: (i) manually curated repositories, (ii) interactions derived from ChIP-seq binding data, (iii) in silico prediction of TF binding on gene promoters, and (iv) reverse-engineered regulons from large gene expression datasets. However, it is not known how these different sources of regulons affect the TF activity estimations, and thereby downstream analysis and interpretation. Here we compared the accuracy and biases of these strategies to define human TF regulons by means of their ability to predict changes in TF activities in three reference benchmark datasets. We assembled a collection of TF-target interactions among 1,541 TFs, and evaluated how the different molecular and regulatory properties of the TFs, such as the DNA-binding domain, specificities or mode of interaction with the chromatin, affect the predictions of TF activity changes. We assessed their coverage and found little overlap on the regulons derived from each strategy and better performance by literature-curated information followed by ChIP-seq data. We provide an integrated resource of all TF-target interactions derived through these strategies with a confidence score, as a resource for enhanced prediction of TF activities.
]]></description>
<dc:creator>Garcia-Alonso, L.</dc:creator>
<dc:creator>Ibrahim, M. M.</dc:creator>
<dc:creator>Turei, D.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:date>2018-06-03</dc:date>
<dc:identifier>doi:10.1101/337915</dc:identifier>
<dc:title><![CDATA[Benchmark and integration of resources for the estimation of human transcription factor activities]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/094011v1?rss=1">
<title>
<![CDATA[
On expert curation and sustainability: UniProtKB/Swiss-Prot as a case study 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/094011v1?rss=1"
</link>
<description><![CDATA[
MOTIVATIONBiological knowledgebases, such as UniProtKB/Swiss-Prot, constitute an essential component of daily scientific research by offering distilled, summarized, and computable knowledge extracted from the literature by expert curators. While knowledgebases play an increasingly important role in the scientific community, the question of their sustainability is raised due to the growth of biomedical literature.nnRESULTSBy using UniProtKB/Swiss-Prot as a case study, we address this question by using different literature triage approaches. With the assistance of the PubTator text-mining tool, we tagged more than 10,000 articles to assess the ratio of papers relevant for curation. We first show that curators read and evaluate many more papers than they curate, and that measuring the number of curated publications is insufficient to provide a complete picture. We show that a large fraction of published papers found in PubMed is not relevant for curation in UniProtKB/Swiss-Prot and demonstrate that, despite appearances, expert curation is sustainable.nnAVAILABILITYUniProt is freely available at http://www.uniprot.org/.nnCONTACTsylvain.poux@sib.swiss
]]></description>
<dc:creator>Poux, S.</dc:creator>
<dc:creator>Arighi, C. N.</dc:creator>
<dc:creator>Magrane, M.</dc:creator>
<dc:creator>Bateman, A.</dc:creator>
<dc:creator>Wei, C.-H.</dc:creator>
<dc:creator>Lu, Z.</dc:creator>
<dc:creator>Boutet, E.</dc:creator>
<dc:creator>Bye-A-Jee, H.</dc:creator>
<dc:creator>Famiglietti, M. L.</dc:creator>
<dc:creator>Roechert, B.</dc:creator>
<dc:date>2016-12-14</dc:date>
<dc:identifier>doi:10.1101/094011</dc:identifier>
<dc:title><![CDATA[On expert curation and sustainability: UniProtKB/Swiss-Prot as a case study]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-12-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/287862v1?rss=1">
<title>
<![CDATA[
Circadian protein regulation in the green lineage I. A phospho-dawn anticipates light onset before proteins peak in daytime. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/287862v1?rss=1"
</link>
<description><![CDATA[
Diel regulation of protein levels and protein modification had been less studied than transcript rhythms. Here, we compare transcriptome data under light-dark cycles to partial proteome and phosphoproteome data, assayed using shotgun mass-spectrometry, from the alga Ostreococcus tauri, the smallest free-living eukaryote. 10% of quantified proteins but two-thirds of phosphoproteins were rhythmic. Mathematical modelling showed that light-stimulated protein synthesis can account for the observed clustering of protein peaks in the daytime. Prompted by night-peaking and apparently dark-stable proteins, we also tested cultures under prolonged darkness, where the proteome changed less than under the diel cycle. The dark-stable, prasinophyte-specific proteins were also reported to accumulate when O. tauri formed lipid droplets. In the phosphoproteome, 39% of rhythmic phospho-sites reached peak levels just before dawn. This anticipatory phosphorylation suggests that a clock-regulated phospho-dawn prepares green cells for daytime functions. Acid-directed and proline-directed protein phosphorylation sites were regulated in antiphase, implicating the clock-related, casein kinases 1 and 2 in phase-specific regulation, alternating with the CMGC protein kinase family. Understanding the dynamic phosphoprotein network should be facilitated by the minimal kinome and proteome of O. tauri. The data are available from ProteomeXchange, with identifiers PXD001734, PXD001735 and PXD002909. This submission updates a previous version, posted on bioRxiv on 4th April 2018, as https://www.biorxiv.org/content/10.1101/287862v1

HighlightThe phosphorylation of most protein sites was rhythmic under light-dark cycles, and suggested circadian control by particular kinases. Day-peaking, rhythmic proteins likely reflect light-stimulated protein synthesis in this microalga.
]]></description>
<dc:creator>Noordally, Z. B.</dc:creator>
<dc:creator>Hindle, M. M.</dc:creator>
<dc:creator>Martin, S. F.</dc:creator>
<dc:creator>Seaton, D. D.</dc:creator>
<dc:creator>Simpson, I.</dc:creator>
<dc:creator>Le Bihan, T.</dc:creator>
<dc:creator>Millar, A. J.</dc:creator>
<dc:date>2018-04-04</dc:date>
<dc:identifier>doi:10.1101/287862</dc:identifier>
<dc:title><![CDATA[Circadian protein regulation in the green lineage I. A phospho-dawn anticipates light onset before proteins peak in daytime.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/338822v1?rss=1">
<title>
<![CDATA[
Genome-scale oscillations in DNA methylation during exit from pluripotency 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/338822v1?rss=1"
</link>
<description><![CDATA[
Pluripotency is accompanied by the erasure of parental epigenetic memory with naive pluripotent cells exhibiting global DNA hypomethylation both in vitro and in vivo. Exit from pluripotency and priming for differentiation into somatic lineages is associated with genome-wide de novo DNA methylation. We show that during this phase, coexpression of enzymes required for DNA methylation turnover, DNMT3s and TETs, promotes cell-to-cell variability in this epigenetic mark. Using a combination of single-cell sequencing and quantitative biophysical modelling, we show that this variability is associated with coherent, genome-scale, oscillations in DNA methylation with an amplitude dependent on CpG density. Analysis of parallel single-cell transcriptional and epigenetic profiling provides evidence for oscillatory dynamics both in vitro and in vivo. These observations provide fresh insights into the emergence of epigenetic heterogeneity during early embryo development, indicating that dynamic changes in DNA methylation might influence early cell fate decisions.nnHighlightsO_LICo-expression of DNMT3s and TETs drive genome-scale oscillations of DNA methylationnC_LIO_LIOscillation amplitude is greatest at a CpG density characteristic of enhancersnC_LIO_LICell synchronisation reveals oscillation period and link with primary transcriptsnC_LIO_LIMultiomic single-cell profiling provides evidence for oscillatory dynamics in vivonC_LI
]]></description>
<dc:creator>Rulands, S.</dc:creator>
<dc:creator>Lee, H. J.</dc:creator>
<dc:creator>Clark, S. J.</dc:creator>
<dc:creator>Angermueller, C.</dc:creator>
<dc:creator>Smallwood, S. A.</dc:creator>
<dc:creator>Krueger, F.</dc:creator>
<dc:creator>Mohammed, H.</dc:creator>
<dc:creator>Dean, W.</dc:creator>
<dc:creator>Nichols, J.</dc:creator>
<dc:creator>Rugg-Gunn, P.</dc:creator>
<dc:creator>Kelsey, G.</dc:creator>
<dc:creator>Stegle, O.</dc:creator>
<dc:creator>Simons, B. D.</dc:creator>
<dc:creator>Reik, W.</dc:creator>
<dc:date>2018-06-05</dc:date>
<dc:identifier>doi:10.1101/338822</dc:identifier>
<dc:title><![CDATA[Genome-scale oscillations in DNA methylation during exit from pluripotency]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/212811v1?rss=1">
<title>
<![CDATA[
Post-catalytic spliceosome structure reveals mechanism of 3'-splice site selection 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/212811v1?rss=1"
</link>
<description><![CDATA[
Introns are removed from eukaryotic mRNA precursors by the spliceosome in two transesterification reactions - branching and exon ligation. Following branching, the 5'-exon remains paired to U5 snRNA loop 1, but the mechanism of 3'-splice site recognition during exon ligation has remained unclear. Here we present the 3.7[A] cryo-EM structure of the yeast P complex spliceosome immediately after exon ligation. The 3'-splice site AG dinucleotide is recognised through non-Watson-Crick pairing with the 5'-splice site and the branch point adenosine. A conserved loop of Prp18 together with the -finger and the RNaseH domain of Prp8 clamp the docked 3'-splice site and 3'-exon. The step 2 factors Prp18 and Slu7 and the C-terminal domain of Yju2 stabilise a conformation competent for 3'-splice site docking and exon ligation. The structure accounts for the strict conservation of the GU and AG dinucleotides of the introns and provides insight into the catalytic mechanism of exon ligation.
]]></description>
<dc:creator>Wilkinson, M. E.</dc:creator>
<dc:creator>Fica, S. M.</dc:creator>
<dc:creator>Galej, W. P.</dc:creator>
<dc:creator>Norman, C. M.</dc:creator>
<dc:creator>Newman, A. J.</dc:creator>
<dc:creator>NAGAI, K.</dc:creator>
<dc:date>2017-11-01</dc:date>
<dc:identifier>doi:10.1101/212811</dc:identifier>
<dc:title><![CDATA[Post-catalytic spliceosome structure reveals mechanism of 3'-splice site selection]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/192195v1?rss=1">
<title>
<![CDATA[
Promoter architecture determines co-translational regulation of mRNA 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/192195v1?rss=1"
</link>
<description><![CDATA[
Information that regulates gene expression is encoded throughout each gene but if different regulatory regions can be understood in isolation, or if they interact, is unknown. Here we measure mRNA levels for 10,000 open reading frames (ORFs) transcribed from either an inducible or constitutive promoter. We find that the strength of co-translational regulation on mRNA levels is determined by promoter architecture. Using a novel computational-genetic screen of 6402 RNA-seq experiments we identify the RNA helicase Dbp2 as the mechanism by which co-translational regulation is reduced specifically for inducible promoters. Finally, we find that for constitutive genes, but not inducible genes, most of the information encoding regulation of mRNA levels in response to changes in growth rate is encoded in the ORF and not in the promoter. Thus the ORF sequence is a major regulator of gene expression, and a non-linear interaction between promoters and ORFs determines mRNA levels.
]]></description>
<dc:creator>Espinar Calvo, M. L.</dc:creator>
<dc:creator>Schikora Tamarit, M. A.</dc:creator>
<dc:creator>Domingo Espinos, J.</dc:creator>
<dc:creator>Carey, L. B.</dc:creator>
<dc:date>2017-09-22</dc:date>
<dc:identifier>doi:10.1101/192195</dc:identifier>
<dc:title><![CDATA[Promoter architecture determines co-translational regulation of mRNA]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/437947v1?rss=1">
<title>
<![CDATA[
The Hox Transcription Factor Ubx stabilizes Lineage Commitment by Suppressing Cellular Plasticity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/437947v1?rss=1"
</link>
<description><![CDATA[
During development cells become gradually restricted in their differentiation potential by the repression of alternative cell fates. While we know that the Polycomb complex plays a crucial role in this process, it still remains unclear how alternative fate genes are specifically targeted for silencing in different cell lineages. We address this question by studying Ultrabithorax (Ubx), a multi-lineage transcription factor (TF) of the Hox class, in the mesodermal and neuronal lineages using sorted nuclei of Drosophila embryos and by interfering with Ubx in mesodermal cells that have already initiated differentiation. We find that Ubx is a key regulator of lineage development, as its mesoderm-specific depletion leads to the de-repression of many genes normally expressed in other lineages. Ubx silences expression of alternative fate genes by interacting with and retaining the Polycomb Group (PcG) protein Pleiohomeotic (Pho) at Ubx targeted genomic regions, thereby setting repressive chromatin marks in a lineage-dependent manner. In sum, our study demonstrates that Ubx stabilizes lineage choice by suppressing the multi-potency encoded in the genome in a lineage-specific manner via its interaction with Pho. This mechanism may explain why the Hox code is maintained throughout the lifecycle, since it seems to set a block to transdifferentiation in many adult cells.
]]></description>
<dc:creator>Domsch, K.</dc:creator>
<dc:creator>Carnesecchi, J.</dc:creator>
<dc:creator>Disela, V.</dc:creator>
<dc:creator>Friedrich, J.</dc:creator>
<dc:creator>Trost, N.</dc:creator>
<dc:creator>Ermakova, O.</dc:creator>
<dc:creator>Polychronidou, M.</dc:creator>
<dc:creator>Lohmann, I.</dc:creator>
<dc:date>2018-10-08</dc:date>
<dc:identifier>doi:10.1101/437947</dc:identifier>
<dc:title><![CDATA[The Hox Transcription Factor Ubx stabilizes Lineage Commitment by Suppressing Cellular Plasticity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/234955v1?rss=1">
<title>
<![CDATA[
Real-time search of all bacterial and viral genomic data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/234955v1?rss=1"
</link>
<description><![CDATA[
Genome sequencing of pathogens is now ubiquitous in microbiology, and the sequence archives are effectively no longer searchable for arbitrary sequences. Furthermore, the exponential increase of these archives is likely to be further spurred by automated diagnostics. To unlock their use for scientific research and real-time surveillance we have combined knowledge about bacterial genetic variation with ideas used in web-search, to build a DNA search engine for microbial data that can grow incrementally. We indexed the complete global corpus of bacterial and viral whole genome sequence data (447,833 genomes), using four orders of magnitude less storage than previous methods. The method allows future scaling to millions of genomes. This renders the global archive accessible to sequence search, which we demonstrate with three applications: ultra-fast search for resistance genes MCR1-3, analysis of host-range for 2827 plasmids, and quantification of the rise of antibiotic resistance prevalence in the sequence archives.
]]></description>
<dc:creator>Bradley, P.</dc:creator>
<dc:creator>den Bakker, H.</dc:creator>
<dc:creator>Rocha, E.</dc:creator>
<dc:creator>McVean, G.</dc:creator>
<dc:creator>Iqbal, Z.</dc:creator>
<dc:date>2017-12-15</dc:date>
<dc:identifier>doi:10.1101/234955</dc:identifier>
<dc:title><![CDATA[Real-time search of all bacterial and viral genomic data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/234930v1?rss=1">
<title>
<![CDATA[
Specificity of RNAi, LNA and CRISPRi as loss-of-function methods in transcriptional analysis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/234930v1?rss=1"
</link>
<description><![CDATA[
Loss-of-function (LOF) methods, such as RNA interference (RNAi), antisense oligonucleotides or CRISPR-based genome editing, provide unparalleled power for studying the biological function of genes of interest. When coupled with transcriptomic analyses, LOF methods allow researchers to dissect networks of transcriptional regulation. However, a major concern is nonspecific targeting, which involves depletion of transcripts other than those intended. The off-target effects of each of these common LOF methods have yet to be compared at the whole-transcriptome level. Here, we systematically and experimentally compared non-specific activity of RNAi, antisense oligonucleotides and CRISPR interference (CRISPRi). All three methods yielded non-negligible offtarget effects in gene expression, with CRISPRi exhibiting clonal variation in the transcriptional profile. As an illustrative example, we evaluated the performance of each method for deciphering the role of a long noncoding RNA (lncRNA) with unknown function. Although all LOF methods reduced expression of the candidate lncRNA, each method yielded different sets of differentially expressed genes upon knockdown as well as a different cellular phenotype. Therefore, to definitively confirm the functional role of a transcriptional regulator, we recommend the simultaneous use of at least two different LOF methods and the inclusion of multiple, specifically designed negative controls.
]]></description>
<dc:creator>Stojic, L.</dc:creator>
<dc:creator>Lun, A.</dc:creator>
<dc:creator>Mangei, J.</dc:creator>
<dc:creator>Mascalchi, P.</dc:creator>
<dc:creator>Quarantotti, V.</dc:creator>
<dc:creator>Barr, A.</dc:creator>
<dc:creator>Bakal, C.</dc:creator>
<dc:creator>Marioni, J.</dc:creator>
<dc:creator>Gergely, F.</dc:creator>
<dc:creator>Odom, D.</dc:creator>
<dc:date>2017-12-15</dc:date>
<dc:identifier>doi:10.1101/234930</dc:identifier>
<dc:title><![CDATA[Specificity of RNAi, LNA and CRISPRi as loss-of-function methods in transcriptional analysis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/360602v1?rss=1">
<title>
<![CDATA[
Nearly all new protein-coding predictions in the CHESS database are not protein-coding 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/360602v1?rss=1"
</link>
<description><![CDATA[
In a 2018 paper posted to bioRxiv, Pertea et al. presented the CHESS database, a new catalog of human gene annotations that includes 1,178 new protein-coding predictions. These are based on evidence of transcription in human tissues and homology to earlier annotations in human and other mammals. Here, we reanalyze the evidence used by CHESS, and find that nearly all protein-coding predictions are false positives. We find that 86% overlap transposons marked by RepeatMasker that are known to frequently result in false positive protein-coding predictions. More than half are homologous to only nine Alu-derived primate sequences corresponding to an erroneous and previously withdrawn Pfam protein domain. The entire set shows poor evolutionary conservation and PhyloCSF protein-coding evolutionary signatures indistinguishable from noncoding RNAs, indicating lack of protein-coding constraint. Only four predictions are supported by mass spectrometry evidence, and even those matches are inconclusive. Overall, the new protein-coding predictions are unsupported by any credible experimental or evolutionary evidence of function, result primarily from homology to genes incorrectly classified as protein-coding, and are unlikely to encode functional proteins.
]]></description>
<dc:creator>Jungreis, I.</dc:creator>
<dc:creator>Tress, M. L.</dc:creator>
<dc:creator>Mudge, J.</dc:creator>
<dc:creator>Sisu, C.</dc:creator>
<dc:creator>Hunt, T.</dc:creator>
<dc:creator>Johnson, R.</dc:creator>
<dc:creator>Uszczynska-Ratajczak, B.</dc:creator>
<dc:creator>Lagarde, J.</dc:creator>
<dc:creator>Wright, J.</dc:creator>
<dc:creator>Muir, P.</dc:creator>
<dc:creator>Gerstein, M.</dc:creator>
<dc:creator>Guigo, R.</dc:creator>
<dc:creator>Kellis, M.</dc:creator>
<dc:creator>Frankish, A.</dc:creator>
<dc:creator>Flicek, P.</dc:creator>
<dc:creator>The GENCODE Consortium,</dc:creator>
<dc:date>2018-07-02</dc:date>
<dc:identifier>doi:10.1101/360602</dc:identifier>
<dc:title><![CDATA[Nearly all new protein-coding predictions in the CHESS database are not protein-coding]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/236471v1?rss=1">
<title>
<![CDATA[
A protein standard that emulates homology for the characterization of protein inference algorithms 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/236471v1?rss=1"
</link>
<description><![CDATA[
A natural way to benchmark the performance of an analytical experimental setup is to use samples of known content, and see to what degree one can correctly infer the content of such a sample from the data. For shotgun proteomics, one of the inherent problems of interpreting data is that the measured analytes are peptides and not the actual proteins themselves. As some proteins share proteolytic peptides, there might be more than one possible causative set of proteins resulting in a given set of peptides and there is a need for mechanisms that infer proteins from lists of detected peptides. A weakness of commercially available samples of known content is that they consist of proteins that are deliberately selected for producing tryptic peptides that are unique to a single protein. Unfortunately, such samples do not expose any complications in protein inference. For a realistic benchmark of protein inference procedures, there is, therefore, a need for samples of known content where the present proteins share peptides with known absent proteins. Here, we present such a standard, that is based on E. coli expressed human protein fragments. To illustrate the usage of this standard, we benchmark a set of different protein inference procedures on the data. We observe that inference procedures excluding shared peptides provide more accurate estimates of errors compared to methods that include information from shared peptides, while still giving a reasonable performance in terms of the number of identified proteins. We also demonstrate that using a sample of known protein content without proteins with shared tryptic peptides can give a false sense of accuracy for many protein inference methods.
]]></description>
<dc:creator>The, M.</dc:creator>
<dc:creator>Edfors, F.</dc:creator>
<dc:creator>Perez-Riverol, Y.</dc:creator>
<dc:creator>Payne, S. H.</dc:creator>
<dc:creator>Hoopmann, M. R.</dc:creator>
<dc:creator>Palmblad, M.</dc:creator>
<dc:creator>Forsström, B.</dc:creator>
<dc:creator>Käll, L.</dc:creator>
<dc:date>2017-12-19</dc:date>
<dc:identifier>doi:10.1101/236471</dc:identifier>
<dc:title><![CDATA[A protein standard that emulates homology for the characterization of protein inference algorithms]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/234492v1?rss=1">
<title>
<![CDATA[
Single-cell RNA-sequencing redefines blood cell type classification in mosquitoes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/234492v1?rss=1"
</link>
<description><![CDATA[
Mosquito blood cells are ancestral immune cells that help control infection by vector-borne pathogens. Despite their importance, little is known about mosquito blood cell biology beyond the ambiguous morphological and functional criteria used for their classification. Here we combined the power of single-cell RNA-sequencing, imaging flow cytometry and single-molecule RNA hybridization to analyze blood cells of the malaria mosquito Anopheles gambiae. By demonstrating that blood cells express nearly half of the mosquito transcriptome, our dataset represents an unprecedented view into their transcriptional machinery. Analyses of differentially expressed genes identified transcriptional signatures of two distinct cell types that challenge the current morphology-based classification of these cells. We further demonstrated an active transfer of a cellular marker between blood cells that confounds their identity. We propose that cell-to-cell exchange is broadly relevant for cell type classification and may account for the remarkable cellular diversity observed in nature.
]]></description>
<dc:creator>Severo, M. S.</dc:creator>
<dc:creator>Landry, J. J. M.</dc:creator>
<dc:creator>Lindquist, R. L.</dc:creator>
<dc:creator>Goosmann, C.</dc:creator>
<dc:creator>Brinkmann, V.</dc:creator>
<dc:creator>Collier, P.</dc:creator>
<dc:creator>Hauser, A. E.</dc:creator>
<dc:creator>Benes, V.</dc:creator>
<dc:creator>Teichmann, S. A.</dc:creator>
<dc:creator>Levashina, E. A.</dc:creator>
<dc:date>2017-12-15</dc:date>
<dc:identifier>doi:10.1101/234492</dc:identifier>
<dc:title><![CDATA[Single-cell RNA-sequencing redefines blood cell type classification in mosquitoes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/209114v1?rss=1">
<title>
<![CDATA[
Terminal uridylyltransferases target RNA viruses as part of the innate immune system in animals 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/209114v1?rss=1"
</link>
<description><![CDATA[
RNA viruses are a major threat to animals and plants. RNA interference (RNAi) and the interferon response provide innate antiviral defense against RNA viruses. Here we performed a large-scale screen using C. elegans and its natural pathogen, the Orsay virus (OrV), and identified cde-1 as important for antiviral defense. CDE-1 is a homologue of the mammalian TUT4/7 terminal uridylyltransferases; its catalytic activity is required for its antiviral function. CDE-1 uridylates the 3' end of the OrV RNA genome and promotes its degradation, independently of the RNAi pathway. Likewise, TUT4/7 uridylate influenza A virus (IAV) mRNAs in mammalian cells. Deletion of TUT4/7 leads to increased IAV mRNA and protein levels. We have defined 3' terminal uridylation of viral RNAs as a conserved antiviral defense mechanism.
]]></description>
<dc:creator>Le Pen, J.</dc:creator>
<dc:creator>Jiang, H.</dc:creator>
<dc:creator>Di Domenico, T.</dc:creator>
<dc:creator>Kneuss, E.</dc:creator>
<dc:creator>Kosalka, J.</dc:creator>
<dc:creator>Morgan, M.</dc:creator>
<dc:creator>Much, C.</dc:creator>
<dc:creator>Rudolph, K. L. M.</dc:creator>
<dc:creator>Enright, A. J.</dc:creator>
<dc:creator>O'Carroll, D.</dc:creator>
<dc:creator>Wang, D.</dc:creator>
<dc:creator>Miska, E. A.</dc:creator>
<dc:date>2017-10-25</dc:date>
<dc:identifier>doi:10.1101/209114</dc:identifier>
<dc:title><![CDATA[Terminal uridylyltransferases target RNA viruses as part of the innate immune system in animals]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/165118v1?rss=1">
<title>
<![CDATA[
Correcting batch effects in single-cell RNA sequencing data by matching mutual nearest neighbours. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/165118v1?rss=1"
</link>
<description><![CDATA[
The presence of batch effects is a well-known problem in experimental data analysis, and single- cell RNA sequencing (scRNA-seq) is no exception. Large-scale scRNA-seq projects that generate data from different laboratories and at different times are rife with batch effects that can fatally compromise integration and interpretation of the data. In such cases, computational batch correction is critical for eliminating uninteresting technical factors and obtaining valid biological conclusions. However, existing methods assume that the composition of cell populations are either known or the same across batches. Here, we present a new strategy for batch correction based on the detection of mutual nearest neighbours in the high-dimensional expression space. Our approach does not rely on pre-defined or equal population compositions across batches, only requiring that a subset of the population be shared between batches. We demonstrate the superiority of our approach over existing methods on a range of simulated and real scRNA-seq data sets. We also show how our method can be applied to integrate scRNA-seq data from two separate studies of early embryonic development.
]]></description>
<dc:creator>Haghverdi, L.</dc:creator>
<dc:creator>Lun, A. T. L.</dc:creator>
<dc:creator>Morgan, M. D.</dc:creator>
<dc:creator>Marioni, J. C.</dc:creator>
<dc:date>2017-07-18</dc:date>
<dc:identifier>doi:10.1101/165118</dc:identifier>
<dc:title><![CDATA[Correcting batch effects in single-cell RNA sequencing data by matching mutual nearest neighbours.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/234872v1?rss=1">
<title>
<![CDATA[
Distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/234872v1?rss=1"
</link>
<description><![CDATA[
Droplet-based single-cell RNA sequencing protocols have dramatically increased the throughput and efficiency of single-cell transcriptomics studies. A key computational challenge when processing these data is to distinguish libraries for real cells from empty droplets. Existing methods for cell calling set a minimum threshold on the total unique molecular identifier (UMI) count for each library, which indiscriminately discards cell libraries with low UMI counts. Here, we describe a new statistical method for calling cells from droplet-based data, based on detecting significant deviations from the expression profile of the ambient solution. Using simulations, we demonstrate that our method has greater power than existing approaches for detecting cell libraries with low UMI counts, while controlling the false discovery rate among detected cells. We also apply our method to real data, where we show that the use of our method results in the retention of distinct cell types that would otherwise have been discarded.
]]></description>
<dc:creator>Lun, A.</dc:creator>
<dc:creator>Riesenfeld, S.</dc:creator>
<dc:creator>Andrews, T.</dc:creator>
<dc:creator>Dao, T. P.</dc:creator>
<dc:creator>Gomes, T.</dc:creator>
<dc:creator>participants in the 1st Human Cell Atlas Jamboree,</dc:creator>
<dc:creator>Marioni, J.</dc:creator>
<dc:date>2018-04-04</dc:date>
<dc:identifier>doi:10.1101/234872</dc:identifier>
<dc:title><![CDATA[Distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/137992v1?rss=1">
<title>
<![CDATA[
A Balance Between Regulatory Constraints And Pathogen Pressure Shapes The Evolution Of Innate Immunity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/137992v1?rss=1"
</link>
<description><![CDATA[
As the first line of defence against pathogens, cells mount an innate immune response, which is highly variable from cell to cell. The response must be potent yet carefully controlled to avoid self-damage. How these constraints have shaped the evolution of innate immunity remains poorly understood. Here, we characterise this programmes transcriptional divergence between species and expression variability across cells. Using bulk and single-cell transcriptomics in primate and rodent fibroblasts challenged with an immune stimulus, we reveal a striking architecture of the innate immune response. Rapidly diverging genes, including cytokines and chemokines, also vary across cells and have distinct promoter structures. Conversely, genes involved in response regulation, such as transcription factors and kinases, are conserved between species and display low cell-to-cell variability. We suggest that this unique expression pattern, observed across species and conditions, has evolved as a mechanism for fine-tuned regulation, to achieve an effective but balanced response.
]]></description>
<dc:creator>Hagai, T.</dc:creator>
<dc:creator>Chen, X.</dc:creator>
<dc:creator>Miragaia, R. J.</dc:creator>
<dc:creator>Gomes, T.</dc:creator>
<dc:creator>Rostom, R.</dc:creator>
<dc:creator>Kunowska, N.</dc:creator>
<dc:creator>Proserpio, V.</dc:creator>
<dc:creator>Donati, G.</dc:creator>
<dc:creator>Bossini-Castillo, L.</dc:creator>
<dc:creator>Naamati, G.</dc:creator>
<dc:creator>Emerton, G.</dc:creator>
<dc:creator>Trynka, G.</dc:creator>
<dc:creator>Kondova, I.</dc:creator>
<dc:creator>Denis, M.</dc:creator>
<dc:creator>Teichmann, S.</dc:creator>
<dc:date>2017-05-15</dc:date>
<dc:identifier>doi:10.1101/137992</dc:identifier>
<dc:title><![CDATA[A Balance Between Regulatory Constraints And Pathogen Pressure Shapes The Evolution Of Innate Immunity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/190330v1?rss=1">
<title>
<![CDATA[
The whole-genome panorama of cancer drivers 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/190330v1?rss=1"
</link>
<description><![CDATA[
The advance of personalized cancer medicine requires the accurate identification of the mutations driving each patients tumor. However, to date, we have only been able to obtain partial insights into the contribution of genomic events to tumor development. Here, we design a comprehensive approach to identify the driver mutations in each patients tumor and obtain a whole-genome panorama of driver events across more than 2,500 tumors from 37 types of cancer. This panorama includes coding and non-coding point mutations, copy number alterations and other genomic rearrangements of somatic origin, and potentially predisposing germline variants. We demonstrate that genomic events are at the root of virtually all tumors, with each carrying on average 4.6 driver events. Most individual tumors harbor a unique combination of drivers, and we uncover the most frequent co-occurring driver events. Half of all cancer genes are affected by several types of driver mutations. In summary, the panorama described here provides answers to fundamental questions in cancer genomics and bridges the gap between cancer genomics and personalized cancer medicine.
]]></description>
<dc:creator>Sabarinathan, R.</dc:creator>
<dc:creator>Pich, O.</dc:creator>
<dc:creator>Martincorena, I.</dc:creator>
<dc:creator>Rubio-Perez, C.</dc:creator>
<dc:creator>Juul, M.</dc:creator>
<dc:creator>Wala, J.</dc:creator>
<dc:creator>Schumacher, S.</dc:creator>
<dc:creator>Shapira, O.</dc:creator>
<dc:creator>Sidiropoulos, N.</dc:creator>
<dc:creator>Waszak, S.</dc:creator>
<dc:creator>Tamborero, D.</dc:creator>
<dc:creator>Mularoni, L.</dc:creator>
<dc:creator>Rheinbay, E.</dc:creator>
<dc:creator>Hornshoj, H.</dc:creator>
<dc:creator>Deu-Pons, J.</dc:creator>
<dc:creator>Muinos, F.</dc:creator>
<dc:creator>Bertl, J.</dc:creator>
<dc:creator>Guo, Q.</dc:creator>
<dc:creator>Weischenfeldt, J.</dc:creator>
<dc:creator>Korbel, J. O.</dc:creator>
<dc:creator>Getz, G.</dc:creator>
<dc:creator>Campbell, P. J.</dc:creator>
<dc:creator>Pedersen, J. S.</dc:creator>
<dc:creator>Beroukhim, R.</dc:creator>
<dc:creator>Perez-Gonzalez, A.</dc:creator>
<dc:creator>Lopez-Bigas, N.</dc:creator>
<dc:creator>PCAWG Drivers and Functional Interpretation Group,</dc:creator>
<dc:creator>ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Net,</dc:creator>
<dc:date>2017-09-20</dc:date>
<dc:identifier>doi:10.1101/190330</dc:identifier>
<dc:title><![CDATA[The whole-genome panorama of cancer drivers]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/111856v1?rss=1">
<title>
<![CDATA[
Gene fusion between CDKN1A and RAB44 caused by exon skipping like mechanism due to disruption of a splice site 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/111856v1?rss=1"
</link>
<description><![CDATA[
Splicing contributes to gene regulation and protein diversity, while abnormal splicing underlies both hereditary diseases and cancers. Various mutations that disrupt splicing factors, exonic or intronic splicing enhancers or silencers, as well as splice sites, could be responsible for abnormal splicing. Characterization of abnormal splicing events is not only helpful for understanding the molecular processes linking mutations to disease phenotypes, but also provides promising targets for targeted therapies. In addition, CRISPR/Cas9 editing could be benefited once more attention is given to potential abnormal splicing outcomes other than off-target effects at the DNA level. Although large-scale multiplexed genome editing has been demonstrated in yeast, and has also been attempted for particular exons or genes in other eukaryotic cells to achieve saturation, in practice it is much more difficult to measure splicing consequences with genome-wide saturation editing in human cells. Instead, massive somatic mutations accumulated in cancer cohorts provide invaluable opportunities to study somatic mutation-associated splicing events. Abnormal splicing is not necessarily limited to single genes. Transcript fusion is a special form of abnormal splicing that connects two or more genes due to splicing on a transcriptional level (rather than chromosomal translocations such as BCR-ABL in chronic myeloid leukemia). It could arise from conventional splicing on read-through transcripts when the two genes are next to each other and on the same strand, or from trans-splicing when two genes are on different chromosomes, strands or far away - a few cases had been reported. However, it was found that these fusions not only occurred in tumors but also in normal tissues; there was limited investigation regarding how the fusion could happen, whether it be due to mutations or not, and what the downstream perturbations were. Here, in an effort to characterize somatic mutation-associated abnormal splicing (especially in its simplest form, exon skipping events), we identified over one hundred such events in various tumors, including those in MET, PTEN and TP53. Surprisingly, we detected a recurrent, but previously undescribed, tumor-specific transcript fusion event between the cyclin-dependent kinase inhibitor CDKN1A and the RAS oncogene family gene RAB44. By creating genome-edited cell lines, we demonstrate a causal relationship between splice-site mutations in CDKN1A and the fusion to the RAB44 transcript. We further provide evidence that the fusion arises from a readthrough transcript that escapes exosome-mediated degradation when the splice-site mutation occurred, and we show that the presence of the fusion transcript correlates with TP53 inactivation and CDK activation. The strong tissue specificity of RAB44 and the relatively high prevalence of this transcript fusion in multiple types of cancers warrants further study which could inform subclassifications of these cancers and the development of targeted therapies.
]]></description>
<dc:creator>Sun, H.</dc:creator>
<dc:creator>Wu, J.</dc:creator>
<dc:creator>Zhu, C.</dc:creator>
<dc:creator>Aiyar, R.</dc:creator>
<dc:creator>Jakob, P.</dc:creator>
<dc:creator>Mueller, W.</dc:creator>
<dc:creator>Wei, W.</dc:creator>
<dc:creator>Steinmetz, L.</dc:creator>
<dc:date>2017-03-02</dc:date>
<dc:identifier>doi:10.1101/111856</dc:identifier>
<dc:title><![CDATA[Gene fusion between CDKN1A and RAB44 caused by exon skipping like mechanism due to disruption of a splice site]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-03-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/169375v1?rss=1">
<title>
<![CDATA[
Alpha-synuclein fibrils induce autophagy in microglial cells as a consequence of lysosomal damage. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/169375v1?rss=1"
</link>
<description><![CDATA[
Autophagy is a constitutive lysosomal catabolic pathway that degrades damaged organelles and protein aggregates. In Parkinsons disease, the synaptic protein alpha-synuclein (AS) accumulates in neuronal cell bodies and axons. Recent studies indicate that aggregation-prone proteins can spread to other brain cells - such as glia - contributing to progressive deterioration.nnAlthough autophagic dysfunction and protein aggregation have been linked to several neurodegenerative disorders, exact mechanisms are not clear and most work was done in neurons and not on microglial cells.nnHere we report that AS fibrils but not monomers induce lysosomal damage and autophagy in microglial cells and we extensively characterized the dynamics of this response by both live-cell imaging and correlative light-electron microscopy (CLEM). In addition, we found that autophagy inhibition in these cells impairs mitochondrial quality and leads to microglial cell death. We propose that AS accumulation in lysosomes leads to lysosomal damage, which in turn activates canonical autophagy as a rescue mechanism.nnOur results provide novel findings about the interaction between AS and the autophagy pathway in microglial cells, which may be important for targeting protein misfolding-associated neurodegenerative diseases.
]]></description>
<dc:creator>Bussi, C.</dc:creator>
<dc:creator>Peralta Ramos, J. M.</dc:creator>
<dc:creator>Arroyo, D. S.</dc:creator>
<dc:creator>Gallea, J. I.</dc:creator>
<dc:creator>Ronchi, P.</dc:creator>
<dc:creator>Kolovou, A.</dc:creator>
<dc:creator>Wang, J. M.</dc:creator>
<dc:creator>Florey, O.</dc:creator>
<dc:creator>Celej, M. S.</dc:creator>
<dc:creator>Schwab, Y.</dc:creator>
<dc:creator>Ktistakis, N. T.</dc:creator>
<dc:creator>Iribarren, P.</dc:creator>
<dc:date>2017-07-27</dc:date>
<dc:identifier>doi:10.1101/169375</dc:identifier>
<dc:title><![CDATA[Alpha-synuclein fibrils induce autophagy in microglial cells as a consequence of lysosomal damage.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/247700v1?rss=1">
<title>
<![CDATA[
Mutation accumulation differentially impacts ageing in mammalian tissues 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/247700v1?rss=1"
</link>
<description><![CDATA[
Medawars mutation accumulation (MA) hypothesis explains ageing by the declining force of natural selection with age: slightly deleterious germline mutations that are functional in old age are not effectively eliminated by selection and therefore lead to ageing-related phenotypes. Although widely cited, empirical support for the MA hypothesis, particularly molecular evidence, has remained limited. Here we test one of its predictions, that genes relatively highly expressed in old adults vs. young adults should be under weaker purifying selection than those relatively highly expressed in young adults. To do so, we combine 23 RNA-sequencing and 35 microarray gene expression datasets (including 9 tissues from 5 mammalian species) with protein and regulatory sequence conservation estimates across mammals. We identify age-related decrease in transcriptome conservation (ADICT) in four tissues, brain, liver, lung, and artery, but not in other tissues, most notably muscle and heart. ADICT is driven both by decreased expression of highly conserved genes and up-regulation of poorly conserved genes during ageing, in line with the MA hypothesis. Lowly conserved and up-regulated genes in ADICT-associated tissues have overlapping functional properties, particularly involving apoptosis and inflammation, with no evidence for a history of positive selection. Our results suggest that tissues vary in how evolution has shaped their ageing patterns. We find that in some tissues, genes up-regulated during ageing, possibly in response to accumulating cellular and histological damage, are under weaker purifying selection than other genes. We propose that accumulation of slightly deleterious substitutions in these genes may underlie their suboptimal regulation and activity during ageing, shaping senescent phenotypes such as inflammaging.
]]></description>
<dc:creator>Turan, Z. G.</dc:creator>
<dc:creator>Parvizi, P.</dc:creator>
<dc:creator>Donertas, H. M.</dc:creator>
<dc:creator>Tung, J.</dc:creator>
<dc:creator>Khaitovich, P.</dc:creator>
<dc:creator>Somel, M.</dc:creator>
<dc:date>2018-01-15</dc:date>
<dc:identifier>doi:10.1101/247700</dc:identifier>
<dc:title><![CDATA[Mutation accumulation differentially impacts ageing in mammalian tissues]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/275032v1?rss=1">
<title>
<![CDATA[
CELLector: Genomics Guided Selection of Cancer in vitro Models 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/275032v1?rss=1"
</link>
<description><![CDATA[
The selection of appropriate cancer models is a key prerequisite for maximising translational potential and clinical relevance of in-vitro oncology studies.

We developed CELLector: a computational method (implemented in an open source R Shiny application and R package) allowing researchers to select the most relevant cancer cell lines in a patient-genomic guided fashion. CELLector leverages tumour genomics data to identify recurrent sub-types with associated genomic signatures. It then evaluates these signatures in cancer cell lines to rank them and prioritise their selection. This enables users to choose appropriate models for inclusion/exclusion in retrospective analyses and future studies. Moreover this allows bridging data from cancer cell line screens to precisely defined sub-cohorts of primary tumours. Here, we demonstrate usefulness and applicability of our method through example use cases, showing how it can be used to prioritise the development of new in-vitro models and to effectively unveil patient-derived multivariate prognostic and therapeutic markers.

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC="FIGDIR/small/275032v3_ufig1.gif" ALT="Figure 1">
View larger version (41K):
org.highwire.dtl.DTLVardef@11f46b1org.highwire.dtl.DTLVardef@5a207aorg.highwire.dtl.DTLVardef@10a57edorg.highwire.dtl.DTLVardef@12b332_HPS_FORMAT_FIGEXP  M_FIG C_FIG
]]></description>
<dc:creator>Najgebauer, H.</dc:creator>
<dc:creator>Yang, M.</dc:creator>
<dc:creator>Francies, H.</dc:creator>
<dc:creator>Stronach, E. A.</dc:creator>
<dc:creator>Garnett, M. J.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:creator>Iorio, F.</dc:creator>
<dc:date>2018-03-03</dc:date>
<dc:identifier>doi:10.1101/275032</dc:identifier>
<dc:title><![CDATA[CELLector: Genomics Guided Selection of Cancer in vitro Models]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/447367v1?rss=1">
<title>
<![CDATA[
Unraveling the polygenic architecture of complex traits using blood eQTL meta-analysis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/447367v1?rss=1"
</link>
<description><![CDATA[
SummaryWhile many disease-associated variants have been identified through genome-wide association studies, their downstream molecular consequences remain unclear.nnTo identify these effects, we performed cis- and trans-expression quantitative trait locus (eQTL) analysis in blood from 31,684 individuals through the eQTLGen Consortium.nnWe observed that cis-eQTLs can be detected for 88% of the studied genes, but that they have a different genetic architecture compared to disease-associated variants, limiting our ability to use cis-eQTLs to pinpoint causal genes within susceptibility loci.nnIn contrast, trans-eQTLs (detected for 37% of 10,317 studied trait-associated variants) were more informative. Multiple unlinked variants, associated to the same complex trait, often converged on trans-genes that are known to play central roles in disease etiology.nnWe observed the same when ascertaining the effect of polygenic scores calculated for 1,263 genome-wide association study (GWAS) traits. Expression levels of 13% of the studied genes correlated with polygenic scores, and many resulting genes are known to drive these traits.
]]></description>
<dc:creator>Vosa, U.</dc:creator>
<dc:creator>Claringbould, A.</dc:creator>
<dc:creator>Westra, H.-J.</dc:creator>
<dc:creator>Bonder, M. J.</dc:creator>
<dc:creator>Deelen, P.</dc:creator>
<dc:creator>Zeng, B.</dc:creator>
<dc:creator>Kirsten, H.</dc:creator>
<dc:creator>Saha, A.</dc:creator>
<dc:creator>Kreuzhuber, R.</dc:creator>
<dc:creator>Kasela, S.</dc:creator>
<dc:creator>Pervjakova, N.</dc:creator>
<dc:creator>Alvaes, I.</dc:creator>
<dc:creator>Fave, M.-J.</dc:creator>
<dc:creator>Agbessi, M.</dc:creator>
<dc:creator>Christiansen, M.</dc:creator>
<dc:creator>Jansen, R.</dc:creator>
<dc:creator>Seppälä, I.</dc:creator>
<dc:creator>Tong, L.</dc:creator>
<dc:creator>Teumer, A.</dc:creator>
<dc:creator>Schramm, K.</dc:creator>
<dc:creator>Hemani, G.</dc:creator>
<dc:creator>Verlouw, J.</dc:creator>
<dc:creator>Yaghootkar, H.</dc:creator>
<dc:creator>Sönmez, R.</dc:creator>
<dc:creator>Andrew, A. A.</dc:creator>
<dc:creator>Kukushkina, V.</dc:creator>
<dc:creator>Kalnapenkis, A.</dc:creator>
<dc:creator>Rüeger, S.</dc:creator>
<dc:creator>Porcu, E.</dc:creator>
<dc:creator>Kronberg-Guzman, J.</dc:creator>
<dc:creator>Kettunen, J.</dc:creator>
<dc:creator>Powell, J.</dc:creator>
<dc:creator>Lee, B.</dc:creator>
<dc:creator>Zhang, F.</dc:creator>
<dc:creator>Arindrarto, W.</dc:creator>
<dc:creator>Beutner, F.</dc:creator>
<dc:creator>BIOS Consortium,</dc:creator>
<dc:creator>Brugge, H.</dc:creator>
<dc:creator>i2QTL Consortium,</dc:creator>
<dc:creator>Dmitrieva, J.</dc:creator>
<dc:creator>Elansary, M.</dc:creator>
<dc:creator>Fairfax, B. P.</dc:creator>
<dc:creator>Georges, M.</dc:creator>
<dc:creator>He</dc:creator>
<dc:date>2018-10-19</dc:date>
<dc:identifier>doi:10.1101/447367</dc:identifier>
<dc:title><![CDATA[Unraveling the polygenic architecture of complex traits using blood eQTL meta-analysis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/323956v1?rss=1">
<title>
<![CDATA[
An insulin, AMPK, and steroid hormone-mediated metabolic switch regulates the transition between growth and diapause in C. elegans 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/323956v1?rss=1"
</link>
<description><![CDATA[
The balance between growth and quiescence depends on the global metabolic state. The dauer larva of C. elegans, a developmentally arrested stage for survival under adverse environment, undergoes a major metabolic transition. Here, we show that this switch involves the concerted activity of several regulatory pathways. Whereas the steroid hormone receptor DAF-12 controls dauer morphogenesis, the insulin pathway maintains low energy expenditure through DAF-16/FoxO, which also requires AAK-2/AMPK. DAF-12 and AAK-2 separately promote a shift in the molar ratios between competing enzymes at two key branch points within the central carbon metabolic pathway. This way, carbon atoms are diverted from the TCA cycle and directed to gluconeogenesis. When both AAK-2 and DAF-12 are suppressed, the TCA cycle is active and the developmental arrest is bypassed. Hence, the metabolic status of each developmental stage is defined by stoichiometric ratios within the constellation of metabolic enzymes and controls the transition between growth and quiescence.
]]></description>
<dc:creator>Penkov, S.</dc:creator>
<dc:creator>Erkut, C.</dc:creator>
<dc:creator>Oertel, J.</dc:creator>
<dc:creator>Galli, R.</dc:creator>
<dc:creator>Vorkel, D.</dc:creator>
<dc:creator>Verbavatz, J.-M.</dc:creator>
<dc:creator>Koch, E.</dc:creator>
<dc:creator>Fahmy, K.</dc:creator>
<dc:creator>Kurzchalia, T. V.</dc:creator>
<dc:date>2018-05-16</dc:date>
<dc:identifier>doi:10.1101/323956</dc:identifier>
<dc:title><![CDATA[An insulin, AMPK, and steroid hormone-mediated metabolic switch regulates the transition between growth and diapause in C. elegans]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/193144v1?rss=1">
<title>
<![CDATA[
Multi-platform discovery of haplotype-resolved structural variation in human genomes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/193144v1?rss=1"
</link>
<description><![CDATA[
The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, and strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three human parent-child trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs ([&ge;]50 bp) per human genome. We also discover 156 inversions per genome--most of which previously escaped detection. Fifty-eight of the inversions we discovered intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The method and the dataset serve as a gold standard for the scientific community and we make specific recommendations for maximizing structural variation sensitivity for future large-scale genome sequencing studies.
]]></description>
<dc:creator>Chaisson, M. J. P.</dc:creator>
<dc:creator>Sanders, A. D.</dc:creator>
<dc:creator>Zhao, X.</dc:creator>
<dc:creator>Malhotra, A.</dc:creator>
<dc:creator>Porubsky, D.</dc:creator>
<dc:creator>Rausch, T.</dc:creator>
<dc:creator>Gardner, E. J.</dc:creator>
<dc:creator>Rodriguez, O.</dc:creator>
<dc:creator>Guo, L.</dc:creator>
<dc:creator>Collins, R. L.</dc:creator>
<dc:creator>Fan, X.</dc:creator>
<dc:creator>Wen, J.</dc:creator>
<dc:creator>Handsaker, R. E.</dc:creator>
<dc:creator>Fairley, S.</dc:creator>
<dc:creator>Kronenberg, Z. N.</dc:creator>
<dc:creator>Kong, X.</dc:creator>
<dc:creator>Hormozdiari, F.</dc:creator>
<dc:creator>Lee, D.</dc:creator>
<dc:creator>Wenger, A. M.</dc:creator>
<dc:creator>Hastie, A.</dc:creator>
<dc:creator>Antaki, D.</dc:creator>
<dc:creator>Audano, P.</dc:creator>
<dc:creator>Brand, H.</dc:creator>
<dc:creator>Cantsilieris, S.</dc:creator>
<dc:creator>Cao, H.</dc:creator>
<dc:creator>Cerveira, E.</dc:creator>
<dc:creator>Chen, C.</dc:creator>
<dc:creator>Chen, X.</dc:creator>
<dc:creator>Chin, C.-S.</dc:creator>
<dc:creator>Chong, Z.</dc:creator>
<dc:creator>Chuang, N. T.</dc:creator>
<dc:creator>Church, D. M.</dc:creator>
<dc:creator>Clarke, L.</dc:creator>
<dc:creator>Farrell, A.</dc:creator>
<dc:creator>Flores, J.</dc:creator>
<dc:creator>Galeev, T.</dc:creator>
<dc:creator>David, G.</dc:creator>
<dc:creator>Gujral, M.</dc:creator>
<dc:creator>Guryev, V.</dc:creator>
<dc:creator>Haynes-Heaton, W.</dc:creator>
<dc:creator>Korlach, J.</dc:creator>
<dc:creator>Kumar, S.</dc:creator>
<dc:creator>Kwon, J. Y.</dc:creator>
<dc:creator>Lee, J. E.</dc:creator>
<dc:creator>Lee, J.</dc:creator>
<dc:creator>Lee, W.-P.</dc:creator>
<dc:creator>Lee,</dc:creator>
<dc:date>2017-09-23</dc:date>
<dc:identifier>doi:10.1101/193144</dc:identifier>
<dc:title><![CDATA[Multi-platform discovery of haplotype-resolved structural variation in human genomes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/144162v1?rss=1">
<title>
<![CDATA[
Accurate And Fast Feature Selection Workflow For High-Dimensional Omics Data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/144162v1?rss=1"
</link>
<description><![CDATA[
We are moving into the age of  Big Data in biomedical research and bioinformatics. This trend could be encapsulated in this simple formula: D = S x F, where the volume of data generated (D) increases in both dimensions: the number of samples (S) and the number of sample features (F). Frequently, a typical bioinformatics problem (e.g. classification) includes redundant and irrelevant features that can result, in the worst-case scenario, in false positive results. Then, Feature Selection (FS) constitutes an enormous challenge. Despite the number and diversity of algorithms available, the proper choice of an approach for facing a specific problem often falls in a  grey zone. In this study, we select a subset of FS methods to develop an efficient workflow and an R package for bioinformatics machine learning problems. We cover relevant issues concerning FS, ranging from domains problems to algorithm solutions and computational tools. Finally, we use seven different proteomics and gene expression datasets to evaluate the workflow and guide the FS process.
]]></description>
<dc:creator>Perez-Riverol, Y.</dc:creator>
<dc:creator>Kun, M.</dc:creator>
<dc:creator>Vizcaino, J. A.</dc:creator>
<dc:creator>Hitz, M.-P.</dc:creator>
<dc:creator>Audain, E.</dc:creator>
<dc:date>2017-06-02</dc:date>
<dc:identifier>doi:10.1101/144162</dc:identifier>
<dc:title><![CDATA[Accurate And Fast Feature Selection Workflow For High-Dimensional Omics Data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/380907v1?rss=1">
<title>
<![CDATA[
A positive feedback loop drives centrosome maturation in flies 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/380907v1?rss=1"
</link>
<description><![CDATA[
Centrosomes are formed when mother centrioles recruit pericentriolar material (PCM) around themselves. The PCM expands dramatically as cells prepare to enter mitosis (a process termed centrosome maturation), but it is unclear how this expansion is achieved. In flies, Spd-2 and Cnn form an extensive scaffold around the mother centriole that recruits other components of the mitotic PCM, and the Polo-dependent phosphorylation of Cnn at the centrosome is crucial for scaffold assembly. Here we show that, like Cnn, Spd-2 is specifically phosphorylated at centrosomes. This phosphorylation appears to create multiple phosphorylated S-S/T(p) motifs that allow Spd-2 to recruit Polo to the expanding scaffold. If Spd-2 cannot recruit Polo to the expanding scaffold, the scaffold is initially assembled around the mother centriole, but it cannot expand outwards, and centrosome maturation fails. We conclude that Spd-2, Polo and Cnn cooperate to form a positive feedback loop that drives the dramatic expansion of the mitotic centrosome in flies.
]]></description>
<dc:creator>Alvarez Rodrigo, I.</dc:creator>
<dc:creator>Conduit, P. T.</dc:creator>
<dc:creator>Baumbach, J.</dc:creator>
<dc:creator>Novak, Z. A.</dc:creator>
<dc:creator>Aydogan, M. G.</dc:creator>
<dc:creator>Wainman, A.</dc:creator>
<dc:creator>Raff, J. W.</dc:creator>
<dc:date>2018-07-31</dc:date>
<dc:identifier>doi:10.1101/380907</dc:identifier>
<dc:title><![CDATA[A positive feedback loop drives centrosome maturation in flies]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/381335v1?rss=1">
<title>
<![CDATA[
In silico prioritization of transporter-drug relationships from drug sensitivity screens 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/381335v1?rss=1"
</link>
<description><![CDATA[
The interplay between drugs and cell metabolism is a key factor in determining both compound potency and toxicity. In particular, how and to what extent transmembrane transporters affect drug uptake and disposition is currently only partially understood. Most transporter proteins belong to two protein families: the ATP-Binding Cassette (ABC) transporter family, whose members are often involved in xenobiotic efflux and drug resistance, and the large and heterogeneous family of Solute carriers (SLCs). We recently argued that SLCs are collectively a rather neglected gene group, with most of its members still poorly characterized, and thus likely to include many yet-to-be-discovered associations with drugs. We searched publicly available resources and literature to define the currently known set of drugs transported by ABCs or SLCs, which involved ~500 drugs and more than 100 transporters. In order to extend this set, we then mined the largest publicly available pharmacogenomics dataset, which involves approximately 1000 molecularly annotated cancer cell lines and their response to 265 chemical compounds, and used regularized linear regression models (Elastic Net, LASSO) to predict drug responses based on SLC and ABC data (expression levels, SNVs, CNVs). The most predictive models included both known and previously unidentified associations between drugs and transporters. To our knowledge, this represents the first application of regularized linear regression to this set of genes, providing an extensive prioritization of potentially pharmacologically interesting interactions.
]]></description>
<dc:creator>Cesar-Razquin, A.</dc:creator>
<dc:creator>Girardi, E.</dc:creator>
<dc:creator>Yang, M.</dc:creator>
<dc:creator>Brehme, M.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:creator>Superti-Furga, G.</dc:creator>
<dc:date>2018-07-31</dc:date>
<dc:identifier>doi:10.1101/381335</dc:identifier>
<dc:title><![CDATA[In silico prioritization of transporter-drug relationships from drug sensitivity screens]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/139972v1?rss=1">
<title>
<![CDATA[
Telomerecat: A Ploidy-Agnostic Method For Estimating Telomere Length From Whole Genome Sequencing Data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/139972v1?rss=1"
</link>
<description><![CDATA[
Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, technical replicates, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype.
]]></description>
<dc:creator>Farmery, J. H. R.</dc:creator>
<dc:creator>Smith, M. L.</dc:creator>
<dc:creator>NIHR BioResource - Rare Diseases,</dc:creator>
<dc:creator>Lynch, A. G.</dc:creator>
<dc:date>2017-05-19</dc:date>
<dc:identifier>doi:10.1101/139972</dc:identifier>
<dc:title><![CDATA[Telomerecat: A Ploidy-Agnostic Method For Estimating Telomere Length From Whole Genome Sequencing Data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/164012v1?rss=1">
<title>
<![CDATA[
β-catenin has both conserved and novel functions in the sponge Ephydatia muelleri 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/164012v1?rss=1"
</link>
<description><![CDATA[
{beta}-catenin acts as a transcriptional co-activator in the Wnt/{beta}-catenin signaling pathway and a cytoplasmic effector in cadherin-based cell adhesion. These functions are ancient within animals, but the earliest steps in {beta}-catenin evolution remain unresolved due to limited data from key lineages - sponges, ctenophores and placozoans. Previous studies in sponges have characterized {beta}-catenin expression dynamics and used GSK3B antagonists to ectopically activate the Wnt/{beta}-catenin pathway; both approaches rely upon untested assumptions about the conservation of {beta}-catenin function and regulation in sponges. Here, we test these assumptions using an antibody raised against {beta}-catenin from the sponge Ephydatia muelleri. We find that cadherin-complex genes co-precipitate with endogenous Em {beta}-catenin from cell lysates, but that Wnt pathway components do not. However, through immunostaining we detect both cell boundary and nuclear populations, and we find evidence that Em {beta}-catenin is a conserved substrate of GSK3B. Collectively, these data support conserved roles for Em {beta}-catenin in both cell adhesion and Wnt signaling. Additionally, we find evidence for an Em {beta}-catenin population associated with the distal ends of F-actin stress fibers in apparent cell-substrate adhesion structures that resemble focal adhesions. This finding suggests a fundamental difference in the adhesion properties of sponge tissues relative to other animals, in which the adhesion functions of {beta}-catenin are typically restricted to cell-cell adhesions.
]]></description>
<dc:creator>Schippers, K. J.</dc:creator>
<dc:creator>Nichols, S. A.</dc:creator>
<dc:date>2017-07-15</dc:date>
<dc:identifier>doi:10.1101/164012</dc:identifier>
<dc:title><![CDATA[β-catenin has both conserved and novel functions in the sponge Ephydatia muelleri]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/268227v1?rss=1">
<title>
<![CDATA[
A High-Resolution Genetic Map for the Laboratory Rat 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/268227v1?rss=1"
</link>
<description><![CDATA[
An accurate and high-resolution genetic map is critical for mapping complex traits, yet the resolution of the current rat genetic map is far lower than human and mouse, and has not been updated since the original ensen-Seaman map in 2004. For the first time, we have refined the rat genetic map to sub-centimorgan (cM) r solution (<0.02 cM) by using 95,769 genetic markers and 870 informative meioses from a cohort of 528 heterogeneous stock (HS) rats. Global recombination rates in the revised sex-averaged map (0.66 cM/Mb) did not difeer compared to the historical map (0.65 cM/Mb); however, substantial refinement was made to the localization of highly recombinant regions within the revised map. Also for the first time, sex-specific rat genetic maps were generated, which revealed both genomewide and fine-scale variation in recombination rates between male and female rats. Reanalysis of multiple quantitative trait loci (QTL) using the historical and refined rat genetic maps demonstrated marked changes to QTL localization, shape, and effect size. As a resource to the rat research community, we have provided revised centimorgan positions for all physical positions within the rat genome and commonly used genetic markers for trait mapping, including 44,828 SSLP markers and the RATDIV genotyping array. Collectively, this study provides a substantial improvement to the rat genetic map and an unprecedented resource for analysis of complex traits and recombination in the rat.
]]></description>
<dc:creator>Littrell, J.</dc:creator>
<dc:creator>Tsaih, S.-W.</dc:creator>
<dc:creator>Baud, A.</dc:creator>
<dc:creator>Rastas, P. M. A.</dc:creator>
<dc:creator>Solberg-Woods, L.</dc:creator>
<dc:creator>Flister, M.</dc:creator>
<dc:date>2018-02-20</dc:date>
<dc:identifier>doi:10.1101/268227</dc:identifier>
<dc:title><![CDATA[A High-Resolution Genetic Map for the Laboratory Rat]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/236364v1?rss=1">
<title>
<![CDATA[
In toto fluorescence live imaging in scuttle fly Megaselia abdita reveals gradual transitions towards a novel extraembryonic architecture. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/236364v1?rss=1"
</link>
<description><![CDATA[
Extraembryonic tissues contribute to animal development, which often entails spreading over embryo or yolk. Apart from changes in cell shape, the requirements for this tissue spreading are not well understood. Here we analyze spreading of the extraembryonic serosa in the scuttle fly Megaselia abdita. The serosa forms from a columnar blastoderm anlage, becomes a squamous epithelium, and eventually spreads over the embryo proper. We describe the dynamics of this process in long-term, whole-embryo time-lapse recordings, demonstrating that free serosa spreading is preceded by a prolonged pause in tissue expansion. Closer examination of this pause reveals mechanical coupling to the underlying yolk sac, which is later released. We find mechanical coupling prolonged and serosa spreading impaired after knockdown of M. abdita Matrix metalloprotease 1. We conclude that tissue-tissue interactions provide a critical functional element to constrain spreading epithelia.nnImpact StatementExtraembryonic tissue spreading in the scuttle fly Megaselia abdita requires mechanical decoupling from the underlying yolk sac.
]]></description>
<dc:creator>Caroti, F.</dc:creator>
<dc:creator>Gonzalez Avalos, E.</dc:creator>
<dc:creator>Gonzalez Avalos, P.</dc:creator>
<dc:creator>Kromm, D.</dc:creator>
<dc:creator>Noeske, V.</dc:creator>
<dc:creator>Wosch, M.</dc:creator>
<dc:creator>Schütz, L.</dc:creator>
<dc:creator>Hufnagel, L.</dc:creator>
<dc:creator>Lemke, S.</dc:creator>
<dc:date>2017-12-18</dc:date>
<dc:identifier>doi:10.1101/236364</dc:identifier>
<dc:title><![CDATA[In toto fluorescence live imaging in scuttle fly Megaselia abdita reveals gradual transitions towards a novel extraembryonic architecture.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/350868v1?rss=1">
<title>
<![CDATA[
Staged developmental mapping and X chromosome transcriptional dynamics during mouse spermatogenesis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/350868v1?rss=1"
</link>
<description><![CDATA[
Understanding male fertility requires an in-depth characterisation of spermatogenesis, the developmental process by which male gametes are generated. Spermatogenesis occurs continuously throughout a males reproductive window and involves a complex sequence of developmental steps, both of which make this process difficult to decipher at the molecular level. To overcome this, we transcriptionally profiled single cells from multiple distinct stages during the first wave of spermatogenesis, where the most mature germ cell type is known. This naturally enriches for spermatogonia and somatic cell types present at very low frequencies in adult testes. Our atlas, available as a shiny app (https://marionilab.cruk.cam.ac.uk/SpermatoShiny), allowed us to reconstruct the three main processes of spermatogenesis: spermatogonial differentiation, meiosis, and spermiogenesis. Additionally, we profiled the chromatin changes associated with meiotic silencing of the X chromosome, revealing a set of genes specifically and strongly repressed by H3K9me3 in the spermatocyte stage, but which escape post-meiotic silencing in spermatids.
]]></description>
<dc:creator>Ernst, C.</dc:creator>
<dc:creator>Eling, N.</dc:creator>
<dc:creator>Martinez-Jimenez, C. P.</dc:creator>
<dc:creator>Marioni, J. C.</dc:creator>
<dc:creator>Odom, D. T.</dc:creator>
<dc:date>2018-06-20</dc:date>
<dc:identifier>doi:10.1101/350868</dc:identifier>
<dc:title><![CDATA[Staged developmental mapping and X chromosome transcriptional dynamics during mouse spermatogenesis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/060004v1?rss=1">
<title>
<![CDATA[
PASP - a whole-transcriptome poly(A) tail length determination assay for the Illumina platform 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/060004v1?rss=1"
</link>
<description><![CDATA[
The poly(A) tail, co-transcriptionally added to most eukaryotic RNAs, plays an important role in post-transcriptional regulation through modulating mRNA stability and translational efficiency. The length of the poly(A) tail is dynamic, decreasing or increasing in response to various stimuli through the action of enzymatic complexes, and changes in tail length are exploited in regulatory pathways implicated in various biological processes.nnTo date, assessment of poly(A) tail length has mostly relied on protocols targeting only a few transcripts. We present PASP ( poly(A) tail sequencing protocol), a whole-transcriptome approach to measure tail lengths -- including a computational pipeline implementing all necessary analyses. PASP uses direct Illumina sequencing of cDNA fragments obtained through G-tailing of poly(A)-selected mRNA followed by fragmentation and reverse transcription.nnAnalysis of reads corresponding to spike-in poly(A) tracts of known length indicated that mean tail lengths can be confidently measured, given sufficient coverage. We further explored the utility of our approach by comparing tail lengths estimated from wild type and {Delta}ccr4-1/pan2 mutant yeasts. The yeast whole-transcriptome tail length distributions showed high consistency between biological replicates, and the expected upward shift in tail lengths in the mutant samples was detected. This suggests that PASP is suitable for the assessment of global polyadenylation status in yeast.nnThe correlation of per-transcript mean tail lengths between biological and technical replicates was low (higher between mutant samples). Both, however, reached high values after filtering for transcripts with greater coverage. We also compare our results with those of other methods. We identify a number of improvements that could be used in future PASP experiments and, based on our results, believe that direct sequencing of poly(A) tails can become the method of choice for studying polyadenylation using the Illumina platform
]]></description>
<dc:creator>Botond Sipos</dc:creator>
<dc:creator>Adrian M Stütz</dc:creator>
<dc:creator>Greg Slodkowicz</dc:creator>
<dc:creator>Tim Massingham</dc:creator>
<dc:creator>Jan Korbel</dc:creator>
<dc:creator>Nick Goldman</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-06-21</dc:date>
<dc:identifier>doi:10.1101/060004</dc:identifier>
<dc:title><![CDATA[PASP - a whole-transcriptome poly(A) tail length determination assay for the Illumina platform]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-06-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/058529v1?rss=1">
<title>
<![CDATA[
SourceData - a semantic platform for curating and searching figures 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/058529v1?rss=1"
</link>
<description><![CDATA[
Here we present SourceData (http://sourcedata.embo.org), a platform that allows researchers and publishers to share scientific figures and, when available, the underlying source data in a way that is machine-readable and findable. SourceData is unique in its focus on the core of scientific evidence--data presented in figures--and its capability to make papers searchable based on their data content and hence directly couple data to improved discoverability. SourceData aims at establishing a selfreinforcing data  ecosystem that bridges the conventional visual and narrative description of research findings with a machine-readable representation of data and hypotheses.nnIn molecular and cell biology, most of the data that result from hypothesis-driven research are exclusively available in the form of figures or tables in published papers. In spite of their importance for the understanding of biological processes and human di ...
]]></description>
<dc:creator>Robin Liechti</dc:creator>
<dc:creator>Nancy George</dc:creator>
<dc:creator>Sara El-Gebali</dc:creator>
<dc:creator>Lou Götz</dc:creator>
<dc:creator>Isaac Crespo</dc:creator>
<dc:creator>Ioannis Xenarios</dc:creator>
<dc:creator>Thomas Lemberger</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-06-13</dc:date>
<dc:identifier>doi:10.1101/058529</dc:identifier>
<dc:title><![CDATA[SourceData - a semantic platform for curating and searching figures]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-06-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/035949v1?rss=1">
<title>
<![CDATA[
Beyond comparisons of means: understanding changes in gene expression at the single-cell level 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/035949v1?rss=1"
</link>
<description><![CDATA[
Single-cell RNA sequencing (scRNA-seq) can be used to characterise differences in gene expression patterns between pre-specified populations of cells. Traditionally, differential expression tools are restricted to the study of changes in overall expression between cell populations. However, such analyses do not take full advantage of the rich information provided by scRNA-seq. In this article, we present a Bayesian hierarchical model which can be used to study changes in expression that lie beyond comparisons of means. In particular, our method can highlight genes that undergo changes in cell-to-cell heterogeneity between the populations but whose overall expression is preserved. Evidence supporting these changes is quantified using a probabilistic approach based on tail posterior probabilities, where a probability cut-off is calibrated through the expected false discovery rate. Our method incorporates a built-in normalisation strategy and quantifies technical artefacts by borrowing information from technical spike-in genes. Control experiments validate the performance of our approach. Finally, we compare expression patterns of mouse embryonic stem cells between different stages of the cell cycle, revealing substantial differences in cellular heterogeneity.
]]></description>
<dc:creator>Catalina A Vallejos</dc:creator>
<dc:creator>Sylvia Richardson</dc:creator>
<dc:creator>John C Marioni</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-01-05</dc:date>
<dc:identifier>doi:10.1101/035949</dc:identifier>
<dc:title><![CDATA[Beyond comparisons of means: understanding changes in gene expression at the single-cell level]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-01-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/124719v1?rss=1">
<title>
<![CDATA[
Literature Evidence in Open Targets - a target validation platform 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/124719v1?rss=1"
</link>
<description><![CDATA[
BackgroundWe present the Europe PMC literature component of Open Targets - a target validation platform that integrates various evidence to aid drug target identification and validation. The component identifies target-disease associations in documents and ranks the documents based on their confidence from the Europe PMC literature database, by using rules utilising expert-provided heuristic information and serves the platform regularly with the up-to-date data since December, 2015.nnResultsCurrently, there are a total number of 1168365 distinct target-disease associations text mined from >26 million PubMed abstracts and >1.2 million Open Access full text articles. Our comparative analyses on the current available evidence data in the platform revealed that 850179 of these associations are exclusively identified by literature mining.nnConclusionThis component helps the platforms users by providing the most relevant literature hits for a given target and disease. The text mining evidence along with the other types of evidence can be explored visually through https://www.targetvalidation.org and all the evidence data is available for download in json format from https://www.targetvalidation.org/downloads/data.
]]></description>
<dc:creator>Kafkas, S.</dc:creator>
<dc:creator>Dunham, I.</dc:creator>
<dc:creator>McEntyre, J.</dc:creator>
<dc:date>2017-04-06</dc:date>
<dc:identifier>doi:10.1101/124719</dc:identifier>
<dc:title><![CDATA[Literature Evidence in Open Targets - a target validation platform]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/212290v1?rss=1">
<title>
<![CDATA[
Molecular mechanism of the dual regulation of bacterial iron sulfur cluster biogenesis by CyaY and IscX 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/212290v1?rss=1"
</link>
<description><![CDATA[
IscX (or YfhJ) is a protein of unknown function which takes part in the iron-sulfur cluster assembly machinery, a highly specialised and essential metabolic pathway. IscX binds to iron with low affinity and interacts with IscS, the desulfurase central to cluster assembly. Previous studies have suggested a competition between IscX and CyaY, the bacterial ortholog of frataxin, for the same binding surface of IscS. This competition could suggest a link between the two proteins with a functional significance. Using a hybrid approach, we show here that IscX is a modulator of the inhibitory properties of CyaY: by competing for the same site on IscS, the presence of IscX rescues the rates of enzymatic cluster formation which are inhibited by CyaY. The effect is stronger at low iron concentrations, whereas it becomes negligible at high iron concentrations. These results strongly suggest that iron-sulfur cluster assembly is an exquisite example of an enzymatic process which requires a double regulation under the control of iron as the effector.
]]></description>
<dc:creator>Pastore, A.</dc:creator>
<dc:creator>Adinolfi, S.</dc:creator>
<dc:creator>Puglisi, R.</dc:creator>
<dc:creator>Crack, J.</dc:creator>
<dc:creator>Iannuzzi, C.</dc:creator>
<dc:creator>Dal Piaz, F.</dc:creator>
<dc:creator>Konarev, P.</dc:creator>
<dc:creator>Svergun, D.</dc:creator>
<dc:creator>Martin, S.</dc:creator>
<dc:creator>Le Brun, N.</dc:creator>
<dc:date>2017-11-03</dc:date>
<dc:identifier>doi:10.1101/212290</dc:identifier>
<dc:title><![CDATA[Molecular mechanism of the dual regulation of bacterial iron sulfur cluster biogenesis by CyaY and IscX]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/220921v1?rss=1">
<title>
<![CDATA[
The global distribution and spread of the mobilized colistin resistance gene mcr-1 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/220921v1?rss=1"
</link>
<description><![CDATA[
Colistin represents one of the very few available drugs for treating infections caused by carbapenem resistant Enterobacteriaceae (CRE). As such, the recent plasmid-mediated spread of the mobilized colistin resistance gene mcr-1 poses a significant public health threat requiring global monitoring and surveillance. In this work, we characterize the global distribution of mcr-1 using a dataset of 457 mcr-1 positive sequenced isolates consisting of currently publicly available mcr-1 carrying sequences combined with an additional 110 newly sequenced mcr-1 positive isolates from China. We find mcr-1 in a diversity of plasmid backgrounds but identify an immediate background common to all mcr-1 sequences. Our analyses establish that all mcr-1 elements in circulation descend from the same initial mobilization of mcr-1 by an ISApl1 transposon in the mid 2000s (2002-2008; 95% higher posterior density), followed by a dramatic demographic expansion, which led to its current global distribution. Our results provide the first systematic phylogenetic analysis of the origin and spread of mcr-1, and emphasize the importance of understanding the movement of mobile elements carrying antibiotic resistance genes across multiple levels of genomic organization.
]]></description>
<dc:creator>Wang, R.</dc:creator>
<dc:creator>van Dorp, L.</dc:creator>
<dc:creator>Shaw, L.</dc:creator>
<dc:creator>Bradley, P.</dc:creator>
<dc:creator>Wang, Q.</dc:creator>
<dc:creator>Wang, X.</dc:creator>
<dc:creator>Jin, L.</dc:creator>
<dc:creator>Zhang, Q.</dc:creator>
<dc:creator>Liu, Y.</dc:creator>
<dc:creator>Rieux, A.</dc:creator>
<dc:creator>Dorai-Schneiders, T.</dc:creator>
<dc:creator>Weinert, L. A.</dc:creator>
<dc:creator>Iqbal, Z.</dc:creator>
<dc:creator>Didelot, X.</dc:creator>
<dc:creator>Wang, H.</dc:creator>
<dc:creator>Balloux, F.</dc:creator>
<dc:date>2017-11-17</dc:date>
<dc:identifier>doi:10.1101/220921</dc:identifier>
<dc:title><![CDATA[The global distribution and spread of the mobilized colistin resistance gene mcr-1]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/341735v1?rss=1">
<title>
<![CDATA[
SKEMPI 2.0: An updated benchmark of changes in protein-protein binding energy, kinetics and thermodynamics upon mutation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/341735v1?rss=1"
</link>
<description><![CDATA[
MotivationUnderstanding the relationship between the sequence, structure, binding energy, binding kinetics and binding thermodynamics of protein-protein interactions is crucial to understanding cellular signaling, the assembly and regulation of molecular complexes, the mechanisms through which mutations lead to disease, and protein engineering.nnResultsWe present SKEMPI 2.0, a major update to our database of binding free energy changes upon mutation for structurally resolved protein-protein interactions. This version now contains manually curated binding data for 7085 mutations, an increase of 133%, including changes in kinetics for 1844 mutations, enthalpy and entropy changes for 443 mutations, and 440 mutations which abolish detectable binding.nnAvailabilityThe database is available at https://life.bsc.es/pid/skempi2/
]]></description>
<dc:creator>Jankauskaite, J.</dc:creator>
<dc:creator>Jimenez-Garcia, B.</dc:creator>
<dc:creator>Dapkunas, J.</dc:creator>
<dc:creator>Fernandez-Recio, J.</dc:creator>
<dc:creator>Moal, I. H.</dc:creator>
<dc:date>2018-06-07</dc:date>
<dc:identifier>doi:10.1101/341735</dc:identifier>
<dc:title><![CDATA[SKEMPI 2.0: An updated benchmark of changes in protein-protein binding energy, kinetics and thermodynamics upon mutation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/032573v1?rss=1">
<title>
<![CDATA[
BioJS-HGV Viewer: Genetic Variation Visualizer 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/032573v1?rss=1"
</link>
<description><![CDATA[
MotivationStudying the pattern of genetic variants is a primary step in deciphering the basis of biological diversity, identifying key  driver variants that affect disease states and evolution of a species. Catalogs of genetic variants contain vast numbers of variants and are growing at an exponential rate, but lack an interactive exploratory interface.nnResultsWe present BioJS-HGV Viewer, a BioJS component to represent and visualize genetic variants pooled from different sources. The tool displays sequences and variants at different levels of detail, facilitating representation of variant sites and annotations in a user friendly and interactive manner.nnAvailabilitySource code for BioJS-HGV Viewer is available at: https://github.com/saketkc/biojs-genetic-variation-viewernnA demo is available at: http://saketkc.github.io/biojs-genetic-variation-viewernnContact: martin@ebi.ac.uk
]]></description>
<dc:creator>Saket Choudhary</dc:creator>
<dc:creator>Leyla Garcia</dc:creator>
<dc:creator>Andrew Nightingale</dc:creator>
<dc:creator>Maria-Jesus Martin</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-11-22</dc:date>
<dc:identifier>doi:10.1101/032573</dc:identifier>
<dc:title><![CDATA[BioJS-HGV Viewer: Genetic Variation Visualizer]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-11-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/183046v1?rss=1">
<title>
<![CDATA[
Hemodynamic forces tune the arrest, adhesion and extravasation of circulating tumor cells 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/183046v1?rss=1"
</link>
<description><![CDATA[
Metastatic seeding is driven by cell-intrinsic and environmental cues, yet the contribution of biomechanics is poorly known. We aim to elucidate the impact of blood flow on the arrest and the extravasation of circulating tumor cells (CTCs) in vivo. Using the zebrafish embryo, we show that arrest of CTCs occurs in vessels with favorable flow profiles where flow forces control the adhesion efficacy of CTCs to the endothelium. We biophysically identified the threshold values of flow and adhesion forces allowing successful arrest of CTCs. In addition, flow forces fine-tune tumor cell extravasation by impairing the remodeling properties of the endothelium. Importantly, we also observe endothelial remodeling at arrest sites of CTCs in mouse brain capillaries. Finally, we observed that human supratentorial brain metastases preferably develop in areas with low perfusion. Altogether, these results demonstrate that hemodynamic profiles at metastatic sites regulate key steps of extravasation preceding metastatic outgrowth.
]]></description>
<dc:creator>Follain, G.</dc:creator>
<dc:creator>Osmani, N.</dc:creator>
<dc:creator>Azevedo, S.</dc:creator>
<dc:creator>Allio, G.</dc:creator>
<dc:creator>Mercier, L.</dc:creator>
<dc:creator>Karreman, M.</dc:creator>
<dc:creator>Solecki, G.</dc:creator>
<dc:creator>Fekonja, N.</dc:creator>
<dc:creator>Hille, C.</dc:creator>
<dc:creator>Chabannes, V.</dc:creator>
<dc:creator>Dolle, G.</dc:creator>
<dc:creator>Metivet, T.</dc:creator>
<dc:creator>Prudhomme, C.</dc:creator>
<dc:creator>Ruthensteiner, B.</dc:creator>
<dc:creator>Kemmling, A.</dc:creator>
<dc:creator>Siemonsen, S.</dc:creator>
<dc:creator>Schneider, T.</dc:creator>
<dc:creator>Fiehler, J.</dc:creator>
<dc:creator>Glatzel, M.</dc:creator>
<dc:creator>Winkler, F.</dc:creator>
<dc:creator>Schwab, Y.</dc:creator>
<dc:creator>Pantel, K.</dc:creator>
<dc:creator>Harlepp, S.</dc:creator>
<dc:creator>Goetz, J. G.</dc:creator>
<dc:date>2017-08-31</dc:date>
<dc:identifier>doi:10.1101/183046</dc:identifier>
<dc:title><![CDATA[Hemodynamic forces tune the arrest, adhesion and extravasation of circulating tumor cells]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/086728v1?rss=1">
<title>
<![CDATA[
Balance of microtubule stiffness and cortical tension determines the size of blood cells with marginal band across species 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/086728v1?rss=1"
</link>
<description><![CDATA[
The fast blood stream of animals is associated with large shear stresses. Consequently, blood cells have evolved a special morphology and a specific internal architecture allowing them to maintain their integrity over several weeks. For instance, non-mammalian red blood cells, mammalian erythroblasts and platelets have a peripheral ring of microtubules, called the marginal band, that flattens the overall cell morphology by pushing on the cell cortex. In this article, we model how the shape of these cells stems from the balance between marginal band elasticity and cortical tension. We predict that the diameter of the cell scales with the total microtubule polymer, and verify the predicted law across a wide range of species. Our analysis also shows that the combination of the marginal band rigidity and cortical tension increases the ability of the cell to withstand forces without deformation. Finally, we model the marginal band coiling that occurs during the disc-to-sphere transition observed for instance at the onset of blood platelet activation. We show that when cortical tension increases faster than crosslinkers can unbind, the marginal band will coil, whereas if the tension increases slower, the marginal band may shorten as microtubules slide relative to each other.nnSignificance StatementMany blood cells have a discoidal shape, which is essential for them to function properly within the organism. For some cells, such as blood platelets, this shape is due to the interplay between the elasticity of the marginal band, which is a closed ring of stiff filaments called microtubules, and the tension of the cell cortex, a polymer scaffold associated with the plasma membrane. Dmitrieff et al. examined how cell size is determined by the mechanical balance between these two components. Remarkably, the theory is confirmed over nearly three orders of magnitudes, by data collected from 25 species. The theory also shows how the composite structure is adapted to resist transient mechanical challenges, as encountered in the blood stream.
]]></description>
<dc:creator>Dmitrieff, S.</dc:creator>
<dc:creator>Alsina, A.</dc:creator>
<dc:creator>Mathur, A.</dc:creator>
<dc:creator>Nedelec, F.</dc:creator>
<dc:date>2016-11-09</dc:date>
<dc:identifier>doi:10.1101/086728</dc:identifier>
<dc:title><![CDATA[Balance of microtubule stiffness and cortical tension determines the size of blood cells with marginal band across species]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-11-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/418988v1?rss=1">
<title>
<![CDATA[
Nodal and Eph signalling relay drives the transition between apical constriction and apico-basal shortening during ascidian endoderm invagination 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/418988v1?rss=1"
</link>
<description><![CDATA[
Gastrulation is the first major morphogenetic event during animal embryogenesis. Ascidian gastrulation starts with the invagination of 10 endodermal precursor cells between the 64- and late 112-cell stages. This process occurs in the absence of endodermal cell division and in two steps, driven by myosin-dependent contractions of the acto-myosin network. First, endoderm precursors constrict their apex. Second, they shorten apico-basally, while retaining small apical surfaces, thereby causing invagination. The mechanisms controlling the endoderm mitotic delay, the step 1 to step 2 transition, and apico-basal shortening have remained elusive. Here, we demonstrate the conserved role during invagination of Nodal and Eph signalling in two distantly related ascidian species (Phallusia mammillata and Ciona intestinalis). We show that the transition to step 2 is controlled by Nodal relayed by Eph signalling and that Eph signalling has a Nodal-independent role in mitotic delay. Interestingly, both Nodal and Eph signals are dispensable for endodermal germ layer fate specification.

Summary statementIdentification of a regulatory developmental signalling sub-network driving endoderm cell shape changes during ascidian endoderm invagination, not involved in cell fate specification.
]]></description>
<dc:creator>Fiuza, U.-M.</dc:creator>
<dc:creator>Negishi, T.</dc:creator>
<dc:creator>Rouan, A.</dc:creator>
<dc:creator>Yasuo, H.</dc:creator>
<dc:creator>Lemaire, P.</dc:creator>
<dc:date>2018-09-15</dc:date>
<dc:identifier>doi:10.1101/418988</dc:identifier>
<dc:title><![CDATA[Nodal and Eph signalling relay drives the transition between apical constriction and apico-basal shortening during ascidian endoderm invagination]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/289868v1?rss=1">
<title>
<![CDATA[
Onset of differentiation is posttranscriptionally controlled in adult neural stem cells 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/289868v1?rss=1"
</link>
<description><![CDATA[
The contribution of posttranscriptional regulation of gene expression to neural stem cell differentiation during tissue homeostasis remains elusive. Here we show highly dynamic changes in protein synthesis along differentiation of stem cells to neurons in vivo. Examination of individual transcripts using RiboTag mouse models reveals that neural stem cells efficiently translate abundant transcripts, whereas translation becomes increasingly controlled with the onset of differentiation. Stem cell generation of early neuroblasts involves translational repression of a subset of mRNAs including the stem cell-identity factors Sox2 and Pax6 as well as translation machinery components. In silico motif analysis identifies a pyrimidine-rich motif (PRM) in this repressed subset. A drop in mTORC1 activity at the onset of differentiation selectively blocks translation of PRM-containing transcripts. Our data uncovers how a drop in mTORC1 allows robust simultaneous posttranscriptional repression of key stem cell identity-factors and translation-components and thereby stemness exit and migration.
]]></description>
<dc:creator>Baser, A.</dc:creator>
<dc:creator>Dang, Y.</dc:creator>
<dc:creator>Skabkin, M.</dc:creator>
<dc:creator>Guelcueler Balta, G.</dc:creator>
<dc:creator>Kalamakis, G.</dc:creator>
<dc:creator>Kleber, S.</dc:creator>
<dc:creator>Goepferich, M.</dc:creator>
<dc:creator>Schefzik, R.</dc:creator>
<dc:creator>Santos Lopez, A.</dc:creator>
<dc:creator>Llorens Bobadilla, E.</dc:creator>
<dc:creator>Schultz, C.</dc:creator>
<dc:creator>Fischer, B.</dc:creator>
<dc:creator>Martin-Villalba, A.</dc:creator>
<dc:date>2018-03-27</dc:date>
<dc:identifier>doi:10.1101/289868</dc:identifier>
<dc:title><![CDATA[Onset of differentiation is posttranscriptionally controlled in adult neural stem cells]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/265256v1?rss=1">
<title>
<![CDATA[
Modelling cell-cell interactions from spatial molecular data with spatial variance component analysis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/265256v1?rss=1"
</link>
<description><![CDATA[
Technological advances allow for assaying multiplexed spatially resolved RNA and protein expression profiling of individual cells, thereby capturing physiological tissue contexts of single cell variation. While methods for the high-throughput generation of spatial expression profiles are increasingly accessible, computational methods for studying the relevance of the spatial organization of tissues on cell-cell heterogeneity are only beginning to emerge. Here, we present spatial variance component analysis (SVCA), a computational framework for the analysis of spatial molecular data. SVCA enables quantifying the effect of cell-cell interactions, as well as environmental and intrinsic cell features on the expression levels of individual genes or proteins. In application to a breast cancer Imaging Mass Cytometry dataset, our model allows for robustly estimating spatial variance signatures, identifying cell-cell interactions as a major driver of expression heterogeneity. Finally, we apply SVCA to high-dimensional imaging-derived RNA data, where we identify molecular pathways that are linked to cell-cell interactions.
]]></description>
<dc:creator>Arnol, D.</dc:creator>
<dc:creator>Schapiro, D.</dc:creator>
<dc:creator>Bodenmiller, B.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:creator>Stegle, O.</dc:creator>
<dc:date>2018-02-14</dc:date>
<dc:identifier>doi:10.1101/265256</dc:identifier>
<dc:title><![CDATA[Modelling cell-cell interactions from spatial molecular data with spatial variance component analysis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/431890v1?rss=1">
<title>
<![CDATA[
Dppa2 and Dppa4 directly regulate the Dux driven zygotic transcriptional programme 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/431890v1?rss=1"
</link>
<description><![CDATA[
The molecular regulation of zygotic genome activation (ZGA) in mammals remains poorly understood. Primed mouse embryonic stem cells contain a rare subset of "2C-like" cells that are epigenetically and transcriptionally similar to the two cell embryo and thus represent an ideal system for studying ZGA transcription regulation. Recently, the transcription factor Dux, expressed exclusively in the minor wave of ZGA, was described to activate many downstream ZGA transcripts. However, it remains unknown what upstream maternal factors initiate ZGA either in a Dux dependent or independent manner. Here we performed a candidate-based overexpression screen, identifying, amongst others, Developmental Pluripotency Associated 2 (Dppa2) and 4 (Dppa4) as positive regulators of 2C-like cells and ZGA transcription. In the germ line, promoter DNA demethylation coincides with upregulation of Dppa2 and Dppa4 which remain expressed until E7.5 when their promoters are remethylated. Furthermore, Dppa2 and Dppa4 are also expressed during iPSC reprogramming at the time 2C-like ZGA transcription transiently peaks. Through a combination of overexpression, knockdown, knockout and rescue experiments, together with transcriptional analyses, we show that Dppa2 and Dppa4 directly regulate the 2C-like cell population and associated transcripts, including Dux and the Zscan4 cluster. Importantly, we tease apart the molecular hierarchy in which the 2C-like transcriptional programme is initiated and stabilised. Dppa2 and Dppa4 require Dux to initiate 2C-like ZGA transcription, suggesting they act upstream by directly regulating Dux. Supporting this, ChIP-seq analysis revealed Dppa2 and Dppa4 bind to the Dux promoter and gene body and drive its expression. Zscan4c is also able to induce 2C-like cells in wild type cells, but, in contrast to Dux, can no longer do so in Dppa2/4 double knockout cells, suggesting it may act to stabilise rather than drive the transcriptional network. Our findings suggest a model in which Dppa2/4 binding to the Dux promoter leads to Dux upregulation and activation of the 2C-like transcriptional programme which is subsequently reinforced by Zscan4c.
]]></description>
<dc:creator>Eckersley-Maslin, M. A.</dc:creator>
<dc:creator>Alda-Catalinas, C.</dc:creator>
<dc:creator>Blotenburg, M.</dc:creator>
<dc:creator>Kreibich, E.</dc:creator>
<dc:creator>Krueger, C.</dc:creator>
<dc:creator>Reik, W.</dc:creator>
<dc:date>2018-10-01</dc:date>
<dc:identifier>doi:10.1101/431890</dc:identifier>
<dc:title><![CDATA[Dppa2 and Dppa4 directly regulate the Dux driven zygotic transcriptional programme]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/166066v1?rss=1">
<title>
<![CDATA[
The cis-regulatory dynamics of embryonic development at single cell resolution 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/166066v1?rss=1"
</link>
<description><![CDATA[
Single cell measurements of gene expression are providing new insights into lineage commitment, yet the regulatory changes underlying individual cell trajectories remain elusive. Here, we profiled chromatin accessibility in over 20,000 single nuclei across multiple stages of Drosophila embryogenesis. Our data reveal heterogeneity in the regulatory landscape prior to gastrulation that reflects anatomical position, a feature that aligns with future cell fate. During mid embryogenesis, tissue granularity emerges such that cell types can be inferred by their chromatin accessibility, while maintaining a signature of their germ layer of origin. We identify over 30,000 distal elements with tissue-specific accessibility. Using transgenic embryos, we tested the germ layer specificity of a subset of predicted enhancers, achieving near-perfect accuracy. Overall, these data demonstrate the power of shotgun single cell profiling of embryos to resolve dynamic changes in open chromatin during development, and to uncover the cis-regulatory programs of germ layers and cell types.
]]></description>
<dc:creator>Cusanovich, D. A.</dc:creator>
<dc:creator>Reddington, J. P.</dc:creator>
<dc:creator>Garfield, D. A.</dc:creator>
<dc:creator>Daza, R.</dc:creator>
<dc:creator>Marco-Ferreres, R.</dc:creator>
<dc:creator>Christiansen, L.</dc:creator>
<dc:creator>Qiu, X.</dc:creator>
<dc:creator>Steemers, F.</dc:creator>
<dc:creator>Trapnell, C.</dc:creator>
<dc:creator>Shendure, J.</dc:creator>
<dc:creator>Furlong, E. E. M.</dc:creator>
<dc:date>2017-07-20</dc:date>
<dc:identifier>doi:10.1101/166066</dc:identifier>
<dc:title><![CDATA[The cis-regulatory dynamics of embryonic development at single cell resolution]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/213603v1?rss=1">
<title>
<![CDATA[
Interoperable and scalable metabolomics data analysis with microservices 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/213603v1?rss=1"
</link>
<description><![CDATA[
Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed in parallel using the Kubernetes container orchestrator. The access point is a virtual research environment which can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and established workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry studies, one nuclear magnetic resonance spectroscopy study and one fluxomics study, showing that the method scales dynamically with increasing availability of computational resources. We achieved a complete integration of the major software suites resulting in the first turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, multivariate statistics, and metabolite identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science.
]]></description>
<dc:creator>Emami Khoonsari, P.</dc:creator>
<dc:creator>Moreno, P.</dc:creator>
<dc:creator>Bergmann, S.</dc:creator>
<dc:creator>Burman, J.</dc:creator>
<dc:creator>Capuccini, M.</dc:creator>
<dc:creator>Carone, M.</dc:creator>
<dc:creator>Cascante, M.</dc:creator>
<dc:creator>de Atauri, P.</dc:creator>
<dc:creator>Foguet, C.</dc:creator>
<dc:creator>Gonzalez-Beltran, A.</dc:creator>
<dc:creator>Hankemeier, T.</dc:creator>
<dc:creator>Haug, K.</dc:creator>
<dc:creator>He, S.</dc:creator>
<dc:creator>Herman, S.</dc:creator>
<dc:creator>Johnson, D.</dc:creator>
<dc:creator>Kale, N.</dc:creator>
<dc:creator>Larsson, A.</dc:creator>
<dc:creator>Neumann, S.</dc:creator>
<dc:creator>Peters, K.</dc:creator>
<dc:creator>Pireddu, L.</dc:creator>
<dc:creator>Rocca-Serra, P.</dc:creator>
<dc:creator>Roger, P.</dc:creator>
<dc:creator>Rueedi, R.</dc:creator>
<dc:creator>Ruttkies, C.</dc:creator>
<dc:creator>Sadawi, N.</dc:creator>
<dc:creator>Salek, R. M.</dc:creator>
<dc:creator>Sansone, S.-A.</dc:creator>
<dc:creator>Schober, D.</dc:creator>
<dc:creator>Selivanov, V.</dc:creator>
<dc:creator>Thevenot, E. A.</dc:creator>
<dc:creator>van Vliet, M.</dc:creator>
<dc:creator>Zanetti, G.</dc:creator>
<dc:creator>Steinbeck, C.</dc:creator>
<dc:creator>Kultima, K.</dc:creator>
<dc:creator>Spjuth, O.</dc:creator>
<dc:date>2017-11-03</dc:date>
<dc:identifier>doi:10.1101/213603</dc:identifier>
<dc:title><![CDATA[Interoperable and scalable metabolomics data analysis with microservices]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/089359v1?rss=1">
<title>
<![CDATA[
The Image Data Resource: A Scalable Platform for Biological Image Data Access, Integration, and Dissemination 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/089359v1?rss=1"
</link>
<description><![CDATA[
Access to primary research data is vital for the advancement of science. To extend the data types supported by community repositories, we built a prototype Image Data Resource (IDR) that collects and integrates imaging data acquired across many different imaging modalities. IDR links high-content screening, super-resolution microscopy, time-lapse and digital pathology imaging experiments to public genetic or chemical databases, and to cell and tissue phenotypes expressed using controlled ontologies. Using this integration, IDR facilitates the analysis of gene networks and reveals functional interactions that are inaccessible to individual studies. To enable re-analysis, we also established a computational resource based on IPython notebooks that allows remote access to the entire IDR. IDR is also an open source platform that others can use to publish their own image data. Thus IDR provides both a novel on-line resource and a software infrastructure that promotes and extends publication and re-analysis of scientific image data.
]]></description>
<dc:creator>Williams, E.</dc:creator>
<dc:creator>Moore, J.</dc:creator>
<dc:creator>Li, S. W.</dc:creator>
<dc:creator>Rustici, G.</dc:creator>
<dc:creator>Tarkowska, A.</dc:creator>
<dc:creator>Chessel, A.</dc:creator>
<dc:creator>Leo, S.</dc:creator>
<dc:creator>Antal, B.</dc:creator>
<dc:creator>Ferguson, R. K.</dc:creator>
<dc:creator>Sarkans, U.</dc:creator>
<dc:creator>Brazma, A.</dc:creator>
<dc:creator>Carazo-Salas, R. E.</dc:creator>
<dc:creator>Swedlow, J.</dc:creator>
<dc:date>2016-11-24</dc:date>
<dc:identifier>doi:10.1101/089359</dc:identifier>
<dc:title><![CDATA[The Image Data Resource: A Scalable Platform for Biological Image Data Access, Integration, and Dissemination]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-11-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/144923v1?rss=1">
<title>
<![CDATA[
Dual Function For Tango1 In Secretion Of Bulky Cargo And In ER-Golgi Morphology 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/144923v1?rss=1"
</link>
<description><![CDATA[
Tango1 helps the efficient delivery of large proteins to the cell surface. We show here that loss of Tango1, in addition to interfering with protein secretion, causes ER stress and defects in cell and ER/Golgi morphology. We find that the previously observed dependence of smaller cargos on Tango1 is a secondary effect, due to an indirect requirement: if large cargos like Dumpy, which we identify here as a new Tango1 cargo, are removed from the cell, non-bulky proteins re-enter the secretory pathway. Removal of the blocking cargo also attenuates the ER-stress response, and cell morphology is restored. Thus, failures in the secretion of non-bulky proteins, ER stress and defective cell morphology are secondary consequences of the retention of cargo. By contrast, the ERES defects in Tango1-depleted cells persist in the absence of bulky cargo, showing that they are due to a secretion-independent function of Tango1. Therefore, the maintenance of proper ERES architecture may be a primary function for Tango1.
]]></description>
<dc:creator>Rios-Barrera, L. D.</dc:creator>
<dc:creator>Sigurbjornsdottir, S.</dc:creator>
<dc:creator>Baer, M.</dc:creator>
<dc:creator>Leptin, M.</dc:creator>
<dc:date>2017-06-01</dc:date>
<dc:identifier>doi:10.1101/144923</dc:identifier>
<dc:title><![CDATA[Dual Function For Tango1 In Secretion Of Bulky Cargo And In ER-Golgi Morphology]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/302257v1?rss=1">
<title>
<![CDATA[
NAD(P)HX repair deficiency causes central metabolic perturbations in yeast and human cells 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/302257v1?rss=1"
</link>
<description><![CDATA[
NADHX and NADPHX are hydrated and redox inactive forms of the NADH and NADPH cofactors, known to inhibit several dehydrogenases in vitro. A metabolite repair system that is conserved in all domains of life and that comprises the two enzymes NAD(P)HX dehydratase and NAD(P)HX epimerase, allows reconversion of both the S- and R-epimers of NADHX and NADPHX to the normal cofactors. An inherited deficiency in this system has recently been shown to cause severe neurometabolic disease in children. Although evidence for the presence of NAD(P)HX has been obtained in plant and human cells, little is known about the mechanism of formation of these derivatives in vivo and their potential effects on cell metabolism. Here, we show that NAD(P)HX dehydratase deficiency in yeast leads to an important, temperature-dependent NADHX accumulation in quiescent cells with a concomitant depletion of intracellular NAD+ and serine pools. We demonstrate that NADHX potently inhibits the first step of the serine synthesis pathway in yeast. Human cells deficient in the NAD(P)HX dehydratase also accumulated NADHX and showed decreased viability. In addition, those cells consumed more glucose and produced more lactate, potentially indicating impaired mitochondrial function. Our results provide first insights into how NADHX accumulation affects cellular functions and pave the way for a better understanding of the mechanism(s) underlying the rapid and severe neurodegeneration leading to early death in NADHX repair deficient children.
]]></description>
<dc:creator>Becker-Kettern, J.</dc:creator>
<dc:creator>Paczia, N.</dc:creator>
<dc:creator>Conrotte, J.-F.</dc:creator>
<dc:creator>Zhu, C.</dc:creator>
<dc:creator>Fiehn, O.</dc:creator>
<dc:creator>Jung, P. P.</dc:creator>
<dc:creator>Steinmetz, L. M.</dc:creator>
<dc:creator>Linster, C. L.</dc:creator>
<dc:date>2018-04-16</dc:date>
<dc:identifier>doi:10.1101/302257</dc:identifier>
<dc:title><![CDATA[NAD(P)HX repair deficiency causes central metabolic perturbations in yeast and human cells]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/167445v1?rss=1">
<title>
<![CDATA[
beachmat: a Bioconductor C++ API for accessing single-cell genomics data from a variety of R matrix types 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/167445v1?rss=1"
</link>
<description><![CDATA[
Recent advances in single-cell RNA sequencing have dramatically increased the number of cells that can be profiled in a single experiment. This provides unparalleled resolution to study cellular heterogeneity within biological processes such as differentiation. However, the explosion of data that are generated from such experiments poses a challenge to the existing computational infrastructure for statistical data analysis. In particular, large matrices holding expression values for each gene in each cell require sparse or file-backed representations for manipulation with the popular R programming language. Here, we describe a C++ interface named beachmat, which enables agnostic data access from various matrix representations. This allows package developers to write efficient C++ code that is interoperable with simple, sparse and HDF5-backed matrices, amongst others. We perform simulations to examine the performance of beachmat on each matrix representation, and we demonstrate how beachmat can be incorporated into the code of other packages to drive analyses of a very large single-cell data set.
]]></description>
<dc:creator>Lun, A. T. L.</dc:creator>
<dc:creator>Pages, H.</dc:creator>
<dc:creator>Smith, M. L.</dc:creator>
<dc:date>2017-07-24</dc:date>
<dc:identifier>doi:10.1101/167445</dc:identifier>
<dc:title><![CDATA[beachmat: a Bioconductor C++ API for accessing single-cell genomics data from a variety of R matrix types]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/098996v1?rss=1">
<title>
<![CDATA[
A global perspective on bioinformatics training needs 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/098996v1?rss=1"
</link>
<description><![CDATA[
In the last decade, life-science research has become increasingly data-intensive and computational. Nevertheless, basic bioinformatics and data stewardship are still only rarely taught in life-science degree programmes, creating a widening skills gap that spans educational levels and career roles. To better understand this situation, we ran surveys to determine how the skills dearth is affecting the need for bioinformatics training worldwide. Perhaps unsurprisingly, we found that respondents wanted more short courses to help boost their expertise and confidence in data analysis and interpretation. However, it was evident that most respondents appreciated their need for training only after designing their experiments and collecting their data. This is clearly rather late in the research workflow, and suboptimal from a training perspective, as skills acquired to address a specific need at a particular time are seldom retained, engendering a cycle of low confidence in trainees. To ensure that such skill gaps do not continue to create barriers to the progress of research, we argue that universities should strive to bring their life-science curricula into the digital-data era. Meanwhile, the demand for point-of-need training in bioinformatics and data stewardship will grow. While this situation persists, international groups like GOBLET are increasing their efforts to enlarge the community of trainers and quench the global thirst for bioinformatics training.
]]></description>
<dc:creator>Brazas, M. D.</dc:creator>
<dc:creator>Brooksbank, C.</dc:creator>
<dc:creator>Jimenez, R. C.</dc:creator>
<dc:creator>Blackford, S.</dc:creator>
<dc:creator>Palagi, P. M.</dc:creator>
<dc:creator>De Las Rivas, J.</dc:creator>
<dc:creator>Ouellette, B. F. F.</dc:creator>
<dc:creator>Kumuthini, J.</dc:creator>
<dc:creator>Korpelainen, E.</dc:creator>
<dc:creator>Lewitter, F.</dc:creator>
<dc:creator>van Gelder, C. W. G.</dc:creator>
<dc:creator>Mulder, N.</dc:creator>
<dc:creator>Corpas, M.</dc:creator>
<dc:creator>Schneider, M. V.</dc:creator>
<dc:creator>Tan, T. W.</dc:creator>
<dc:creator>Clements, D.</dc:creator>
<dc:creator>Davies, A.</dc:creator>
<dc:creator>Attwood, T. K.</dc:creator>
<dc:date>2017-02-27</dc:date>
<dc:identifier>doi:10.1101/098996</dc:identifier>
<dc:title><![CDATA[A global perspective on bioinformatics training needs]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-02-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/148684v1?rss=1">
<title>
<![CDATA[
Comprehensive genome and transcriptome analysis reveals genetic basis for gene fusions in cancer 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/148684v1?rss=1"
</link>
<description><![CDATA[
Gene fusions are an important class of cancer-driving events with therapeutic and diagnostic values, yet their underlying genetic mechanisms have not been systematically characterized. Here by combining RNA and whole genome DNA sequencing data from 1188 donors across 27 cancer types we obtained a list of 3297 high-confidence tumour-specific gene fusions, 82% of which had structural variant (SV) support and 2372 of which were novel. Such a large collection of RNA and DNA alterations provides the first opportunity to systematically classify the gene fusions at a mechanistic level. While many could be explained by single SVs, numerous fusions involved series of structural rearrangements and thus are composite fusions. We discovered 75 fusions of a novel class of inter-chromosomal composite fusions, termed bridged fusions, in which a third genomic location bridged two different genes. In addition, we identified 522 fusions involving non-coding genes and 157 ORF-retaining fusions, in which the complete open reading frame of one gene was fused to the UTR region of another. Although only a small proportion (5%) of the discovered fusions were recurrent, we found a set of highly recurrent fusion partner genes, which exhibited strong 5 or 3 bias and were significantly enriched for cancer genes. Our findings broaden the view of the gene fusion landscape and reveal the general properties of genetic alterations underlying gene fusions for the first time.
]]></description>
<dc:creator>Fonseca, N. A.</dc:creator>
<dc:creator>He, Y.</dc:creator>
<dc:creator>Greger, L.</dc:creator>
<dc:creator>- PCAWG-3,</dc:creator>
<dc:creator>Brazma, A.</dc:creator>
<dc:creator>Zhang, Z.</dc:creator>
<dc:date>2017-06-12</dc:date>
<dc:identifier>doi:10.1101/148684</dc:identifier>
<dc:title><![CDATA[Comprehensive genome and transcriptome analysis reveals genetic basis for gene fusions in cancer]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/117812v1?rss=1">
<title>
<![CDATA[
Identifiers for the 21st century:How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/117812v1?rss=1"
</link>
<description><![CDATA[
In many disciplines, data is highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline ten lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers; we also outline important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.
]]></description>
<dc:creator>McMurry, J.</dc:creator>
<dc:creator>Juty, N.</dc:creator>
<dc:creator>Blomberg, N.</dc:creator>
<dc:creator>Burdett, A.</dc:creator>
<dc:creator>Conlin, T.</dc:creator>
<dc:creator>Conte, N.</dc:creator>
<dc:creator>Courtot, M.</dc:creator>
<dc:creator>Deck, J.</dc:creator>
<dc:creator>Dumontier, M.</dc:creator>
<dc:creator>Fellows, D.</dc:creator>
<dc:creator>Gonzalez-Beltran, A.</dc:creator>
<dc:creator>Gormanns, P.</dc:creator>
<dc:creator>Grethe, J.</dc:creator>
<dc:creator>Hastings, J.</dc:creator>
<dc:creator>Hermjakob, H.</dc:creator>
<dc:creator>Heriche, J.-K.</dc:creator>
<dc:creator>Ison, J.</dc:creator>
<dc:creator>Jimenez, R.</dc:creator>
<dc:creator>Jupp, S.</dc:creator>
<dc:creator>Kunze, J.</dc:creator>
<dc:creator>Laibe, C.</dc:creator>
<dc:creator>Le Novere, N.</dc:creator>
<dc:creator>Malone, J. R.</dc:creator>
<dc:creator>Martin, M.-J.</dc:creator>
<dc:creator>McEntyre, J.</dc:creator>
<dc:creator>Morris, C.</dc:creator>
<dc:creator>Muilu, J.</dc:creator>
<dc:creator>Mueller, W.</dc:creator>
<dc:creator>Rocca-Serra, P.</dc:creator>
<dc:creator>Sansone, S.-A.</dc:creator>
<dc:creator>Sariyar, M.</dc:creator>
<dc:creator>Snoep, J.</dc:creator>
<dc:creator>Stanford, N. J.</dc:creator>
<dc:creator>Soiland-Reyes, S.</dc:creator>
<dc:creator>Swainston, N.</dc:creator>
<dc:creator>Washington, N.</dc:creator>
<dc:creator>Williams, A.</dc:creator>
<dc:creator>Wimalaratne, S.</dc:creator>
<dc:creator>Winfree, L.</dc:creator>
<dc:creator>Wolstencroft, K.</dc:creator>
<dc:creator>Goble, C.</dc:creator>
<dc:creator>Mungall, C.</dc:creator>
<dc:creator>Haendel, M.</dc:creator>
<dc:creator>Parkinson,</dc:creator>
<dc:date>2017-03-20</dc:date>
<dc:identifier>doi:10.1101/117812</dc:identifier>
<dc:title><![CDATA[Identifiers for the 21st century:How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-03-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/251686v1?rss=1">
<title>
<![CDATA[
Ciliary and rhabdomeric photoreceptor-cell circuits form a spectral depth gauge in marine zooplankton 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/251686v1?rss=1"
</link>
<description><![CDATA[
Ciliary and rhabdomeric photoreceptor cells represent two main lines of photoreceptor evolution in animals. The two photoreceptor-cell types coexist in some animals, however how they functionally integrate is unknown. We used connectomics to map synaptic paths between ciliary and rhabdomeric photoreceptors in the planktonic larva of the annelid Platynereis and found that ciliary photoreceptors are presynaptic to the rhabdomeric circuit. The behaviors mediated by the ciliary and rhabdomeric cells also interact hierarchically. The ciliary photoreceptors are UV-sensitive and mediate downward swimming to non-directional UV light, a behavior absent in ciliary-opsin knockouts. UV avoidance antagonizes positive phototaxis mediated by the rhabdomeric eyes so that vertical swimming direction is determined by the ratio of blue/UV light. Since this ratio increases with depth, Platynereis larvae may use it as a depth gauge during planktonic migration. Our results revealed a functional integration of ciliary and rhabdomeric photoreceptors with implications for eye and photoreceptor evolution.
]]></description>
<dc:creator>Veraszto, C.</dc:creator>
<dc:creator>Guhmann, M.</dc:creator>
<dc:creator>Jia, H.</dc:creator>
<dc:creator>Rajan, V. B. V.</dc:creator>
<dc:creator>Bezares-Calderon, L. A.</dc:creator>
<dc:creator>Lopez, C. P.</dc:creator>
<dc:creator>Randel, N.</dc:creator>
<dc:creator>Shahidi, R.</dc:creator>
<dc:creator>Michiels, N. K.</dc:creator>
<dc:creator>Yokoyama, S.</dc:creator>
<dc:creator>Tessmar-Raible, K.</dc:creator>
<dc:creator>Jekely, G.</dc:creator>
<dc:date>2018-01-22</dc:date>
<dc:identifier>doi:10.1101/251686</dc:identifier>
<dc:title><![CDATA[Ciliary and rhabdomeric photoreceptor-cell circuits form a spectral depth gauge in marine zooplankton]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/034330v1?rss=1">
<title>
<![CDATA[
Data-driven hypothesis weighting increases detection power in multiple testing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/034330v1?rss=1"
</link>
<description><![CDATA[
Hypothesis weighting is a powerful approach for improving the power of data analyses that employ multiple testing. However, in general it is not evident how to choose the weights. We describe IHW, a method for data-driven hypothesis weighting that makes use of informative covariates that are independent of the test statistic under the null, but informative of each tests power or prior probability of the null hypothesis. Covariates can be continuous or categorical and need not fulfill any particular assumptions. The method increases statistical power in applications while controlling the false discovery rate (FDR) and produces additional insight by revealing the covariate-weight relationship. Independent hypothesis weighting is a practical approach to discovery of associations in large datasets.
]]></description>
<dc:creator>Nikolaos Ignatiadis</dc:creator>
<dc:creator>Bernd Klaus</dc:creator>
<dc:creator>Judith Zaugg</dc:creator>
<dc:creator>Wolfgang Huber</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-12-13</dc:date>
<dc:identifier>doi:10.1101/034330</dc:identifier>
<dc:title><![CDATA[Data-driven hypothesis weighting increases detection power in multiple testing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-12-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/438234v1?rss=1">
<title>
<![CDATA[
Using the drug-protein interactome to identify anti-ageing compounds for humans 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/438234v1?rss=1"
</link>
<description><![CDATA[
Advancing age is the dominant risk factor for most of the major killer diseases in developed countries. Hence, ameliorating the effects of ageing may prevent multiple diseases simultaneously. Drugs licensed for human use against specific diseases have proved to be effective in extending lifespan and healthspan in animal models, suggesting that there is scope for drug repurposing in humans. New bioinformatic methods to identify and prioritise potential anti-ageing compounds for humans are therefore of interest. In this study, we first used drug-protein interaction information, to rank 1,147 drugs by their likelihood of targeting ageing-related gene products in humans. Among 19 statistically significant drugs, 6 have already been shown to have pro-longevity properties in animal models (p < 0.001). Using the targets of each drug, we established its association with ageing at multiple levels of biological actions including pathways, functions and protein interactions. Finally, combining all the data, we calculated a comprehensive ranked list of drugs that predicted tanespimycin, an inhibitor of HSP-90, as the top-ranked novel anti-ageing candidate. We experimentally validated the pro-longevity effect of tanespimycin through its HSP-90 target in Caenorhabditis elegans.nnAuthor SummaryHuman life expectancy is continuing to increase worldwide, as a result of successive improvements in living conditions and medical care. Although this trend is to be celebrated, advancing age is the major risk factor for multiple impairments and chronic diseases. As a result, the later years of life are often spent in poor health and lowered quality of life. However, these effects of ageing are not inevitable, because very long-lived people often suffer rather little ill-health at the end of their lives. Furthermore, laboratory experiments have shown that animals fed with specific drugs can live longer and with fewer age-related diseases than their untreated companions. We therefore need to identify drugs with anti-ageing properties for humans. We have therefore used computers to search for drugs that affect components and processes known to be important in human ageing. This approach worked, because it was able to re-discover several drugs known to increase lifespan in animal models, plus some new ones, including one that we tested experimentally and validated in this study. These drugs are now a high priority for animal testing and for exploring effects on human ageing.
]]></description>
<dc:creator>Fuentealba Valenzuela, M.</dc:creator>
<dc:creator>Donertas, H. M.</dc:creator>
<dc:creator>Williams, R.</dc:creator>
<dc:creator>Labbadia, J.</dc:creator>
<dc:creator>Thornton, J.</dc:creator>
<dc:creator>Partridge, L.</dc:creator>
<dc:date>2018-10-08</dc:date>
<dc:identifier>doi:10.1101/438234</dc:identifier>
<dc:title><![CDATA[Using the drug-protein interactome to identify anti-ageing compounds for humans]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/176487v1?rss=1">
<title>
<![CDATA[
A pan cancer analysis of promoter activity highlights the regulatory role of alternative transcription start sites and their association with noncoding mutations 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/176487v1?rss=1"
</link>
<description><![CDATA[
Most human protein-coding genes are regulated by multiple, distinct promoters, suggesting that the choice of promoter is as important as its level of transcriptional activity. While the role of promoters as driver elements in cancer has been recognized, the contribution of alternative promoters to regulation of the cancer transcriptome remains largely unexplored. Here we infer active promoters using RNA-Seq data from 1,188 cancer samples with matched whole genome sequencing data. We find that alternative promoters are a major contributor to context-specific regulation of isoform expression and that alternative promoters are frequently deregulated in cancer, affecting known cancer-genes and novel candidates. Our study suggests that a highly dynamic landscape of active promoters shapes the cancer transcriptome, opening many opportunities to further explore the interplay of regulatory mechanism and noncoding somatic mutations with transcriptional aberrations in cancer.
]]></description>
<dc:creator>Demircioglu, D.</dc:creator>
<dc:creator>Kindermans, M.</dc:creator>
<dc:creator>Nandi, T.</dc:creator>
<dc:creator>Cukuroglu, E.</dc:creator>
<dc:creator>Calabrese, C.</dc:creator>
<dc:creator>Fonseca, N. A.</dc:creator>
<dc:creator>Kahles, A.</dc:creator>
<dc:creator>Lehmann, K.</dc:creator>
<dc:creator>Stegle, O.</dc:creator>
<dc:creator>PCAWG-3,</dc:creator>
<dc:creator>PCAWG-Network,</dc:creator>
<dc:creator>Brazma, A.</dc:creator>
<dc:creator>Brooks, A.</dc:creator>
<dc:creator>Rätsch, G.</dc:creator>
<dc:creator>Tan, P.</dc:creator>
<dc:creator>Göke, J.</dc:creator>
<dc:date>2017-08-15</dc:date>
<dc:identifier>doi:10.1101/176487</dc:identifier>
<dc:title><![CDATA[A pan cancer analysis of promoter activity highlights the regulatory role of alternative transcription start sites and their association with noncoding mutations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/310029v1?rss=1">
<title>
<![CDATA[
The landscape of selection in 551 Esophageal Adenocarcinomas defines genomic biomarkers for the clinic 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/310029v1?rss=1"
</link>
<description><![CDATA[
Esophageal Adenocarcinoma (EAC) is a poor prognosis cancer type with rapidly rising incidence. Our understanding of genetic events which drive EAC development is limited and there are few molecular biomarkers for prognostication or therapeutics. We have accumulated a cohort of 551 genomically characterised EACs (73% WGS and 27% WES) with clinical annotation and matched RNA-seq. Using a variety of driver gene detection methods, we discover 77 EAC driver genes (73% novel) and 21 non-coding driver elements (95% novel), and describe mutation and CNV types with specific functional impact. We identify a mean of 4.4 driver events per case derived from both copy number events and mutations. We compare driver mutation rates to the exome-wide mutational excess calculated using Non-synonymous vs Synonymous mutation rates (dNdS). We observe mutual exclusivity or co-occurrence of events within and between a number of EAC pathways (GATA factors, Core Cell cycle genes, TP53 regulators and the SWI/SNF complex) suggestive of important functional relationships. These driver variants correlate with tumour differentiation, sex and prognosis. Poor prognostic indicators (SMAD4, GATA4) are verified in independent cohorts with significant predictive value. Over 50% of EACs contain sensitising events for CDK4/6 inhibitors which are highly correlated with clinically relevant sensitivity in a panel EAC cell lines and organoids.
]]></description>
<dc:creator>Frankell, A. M.</dc:creator>
<dc:creator>Jammula, S.</dc:creator>
<dc:creator>Contino, G.</dc:creator>
<dc:creator>Killcoyne, S. S.</dc:creator>
<dc:creator>Abbas, S.</dc:creator>
<dc:creator>Perner, J.</dc:creator>
<dc:creator>Bower, L.</dc:creator>
<dc:creator>Devonshire, G.</dc:creator>
<dc:creator>Grehan, N.</dc:creator>
<dc:creator>Mok, J.</dc:creator>
<dc:creator>O'Donovan, M.</dc:creator>
<dc:creator>Macrae, S.</dc:creator>
<dc:creator>Tavare, S.</dc:creator>
<dc:creator>Fitzgerald, R. C.</dc:creator>
<dc:creator>the Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium,</dc:creator>
<dc:date>2018-04-28</dc:date>
<dc:identifier>doi:10.1101/310029</dc:identifier>
<dc:title><![CDATA[The landscape of selection in 551 Esophageal Adenocarcinomas defines genomic biomarkers for the clinic]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/328138v1?rss=1">
<title>
<![CDATA[
Combined single cell profiling of expression and DNA methylation reveals splicing regulation and heterogeneity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/328138v1?rss=1"
</link>
<description><![CDATA[
BackgroundAlternative splicing is a key regulatory mechanism in eukaryotic cells and increases the effective number of functionally distinct gene products. Using bulk RNA sequencing, splicing variation has been studied across human tissues and in genetically diverse populations. This has identified disease-relevant splicing events, as well as associations between splicing and genomic variations, including sequence composition and conservation. However, variability in splicing between single cells from the same tissue or cell type and its determinants remain poorly understood.nnResultsWe applied parallel DNA methylation and transcriptome sequencing to differentiating human induced pluripotent stem cells to characterize splicing variation (exon skipping) and its determinants. Our results shows that variation in single-cell splicing can be accurately predicted based on local sequence composition and genomic features. We observe moderate but consistent contributions from local DNA methylation profiles to splicing variation across cells. A combined model that is built based on sequence as well as DNA methylation information accurately predicts different splicing modes of individual cassette exons (AUC=0.85). These categories include the conventional inclusion and exclusion patterns, but also more subtle modes of cell-to-cell variation in splicing. Finally, we identified and characterized associations between DNA methylation and splicing changes during cell differentiation.nnConclusionsOur study yields new insights into alternative splicing at the single-cell level and reveals a previously underappreciated link between DNA methylation variation and splicing.
]]></description>
<dc:creator>Linker, S. M.</dc:creator>
<dc:creator>Urban, L.</dc:creator>
<dc:creator>Clark, S.</dc:creator>
<dc:creator>Chhatriwala, M.</dc:creator>
<dc:creator>Amatya, S.</dc:creator>
<dc:creator>McCarthy, D.</dc:creator>
<dc:creator>Ebersberger, I.</dc:creator>
<dc:creator>Vallier, L.</dc:creator>
<dc:creator>Reik, W.</dc:creator>
<dc:creator>Stegle, O.</dc:creator>
<dc:creator>Bonder, M. J.</dc:creator>
<dc:date>2018-05-22</dc:date>
<dc:identifier>doi:10.1101/328138</dc:identifier>
<dc:title><![CDATA[Combined single cell profiling of expression and DNA methylation reveals splicing regulation and heterogeneity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/407031v1?rss=1">
<title>
<![CDATA[
Modeling of DNA methylation in cis reveals principles of chromatin folding in vivo in the absence of crosslinking and ligation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/407031v1?rss=1"
</link>
<description><![CDATA[
Mammalian chromosomes are folded into an intricate hierarchy of structural domains, within which topologically associating domains (TADs) and CTCF-associated loops partition the physical interactions between regulatory sequences. Current understanding of chromosome folding largely relies on chromosome conformation capture (3C)-based experiments, where chromosomal interactions are detected as ligation products after crosslinking of chromatin. To measure chromosome structure in vivo, quantitatively and without relying on crosslinking and ligation, we have implemented a new method named damC. DamC combines DNA-methylation based detection of chromosomal interactions with next-generation sequencing and a biophysical model of methylation kinetics. DamC performed in mouse embryonic stem cells provides the first in vivo validation of the existence of TADs and CTCF loops, confirms 3C-based measurements of the scaling of contact probabilities within TADs, and provides evidence that mammalian chromatin in vivo is essentially rigid below 5 kilobases. Combining damC with transposon-mediated genomic engineering shows that new loops can be formed between ectopically introduced and endogenous CTCF sites, which alters the partitioning of physical interactions within TADs. This establishes damC as a crosslinking-and ligation-free framework to measure and modify chromosome interactions combined with a solid theoretical background for rigorous data interpretation. This orthogonal approach to 3C validates the existence of key structural features of mammalian chromosomes and provides novel insights into how chromosome structure within TADs can be manipulated.
]]></description>
<dc:creator>Redolfi, J.</dc:creator>
<dc:creator>Zhan, Y.</dc:creator>
<dc:creator>Valdes, C.</dc:creator>
<dc:creator>Kryzhanovska, M.</dc:creator>
<dc:creator>Misteli Guerreiro, I.</dc:creator>
<dc:creator>Iesmantavicius, V.</dc:creator>
<dc:creator>Tiana, G.</dc:creator>
<dc:creator>Pollex, T.</dc:creator>
<dc:creator>Kind, J.</dc:creator>
<dc:creator>Smallwood, S.</dc:creator>
<dc:creator>de Laat, W.</dc:creator>
<dc:creator>Giorgetti, L.</dc:creator>
<dc:date>2018-09-03</dc:date>
<dc:identifier>doi:10.1101/407031</dc:identifier>
<dc:title><![CDATA[Modeling of DNA methylation in cis reveals principles of chromatin folding in vivo in the absence of crosslinking and ligation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/131714v1?rss=1">
<title>
<![CDATA[
Structural Basis Of STAT2 Recognition By IRF9 Reveals Molecular Insights Into ISGF3 Function 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/131714v1?rss=1"
</link>
<description><![CDATA[
Cytokine signalling is mediated by the activation of distinct sets of structurally homologous JAK and STAT signalling molecules, which control nuclear gene expression and cell fate. A significant expansion in the gene regulatory repertoire controlled by JAK/STAT signalling has arisen by the selective interaction of STATs with IRF transcription factors. Type I interferons (IFN), the major antiviral cytokines, trigger the formation of the ISGF3 complex containing STAT1, STAT2 and IRF9. ISGF3 regulates the expression of IFN-stimulated genes (ISGs). ISGF3 assembly depends on selective interaction between IRF9, through its IRF-association domain (IAD), with the coiled-coil domain (CCD) of STAT2. Here, we report the crystal structures of the IRF9-IAD alone and in a complex with STAT2-CCD. Despite similarity in the overall structure among respective paralogs, the surface features of the IRF9-IAD and STAT2- CCD have diverged to enable specific interaction between these family members, thus enabling ISGF3 formation and expression of ISGs.
]]></description>
<dc:creator>Rengachari, S.</dc:creator>
<dc:creator>Groiss, S.</dc:creator>
<dc:creator>Devos, J.</dc:creator>
<dc:creator>Caron, E.</dc:creator>
<dc:creator>Grandvaux, N.</dc:creator>
<dc:creator>Panne, D.</dc:creator>
<dc:date>2017-04-28</dc:date>
<dc:identifier>doi:10.1101/131714</dc:identifier>
<dc:title><![CDATA[Structural Basis Of STAT2 Recognition By IRF9 Reveals Molecular Insights Into ISGF3 Function]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/277491v1?rss=1">
<title>
<![CDATA[
VarQ: a tool for the structural analysis of Human Protein Variants 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/277491v1?rss=1"
</link>
<description><![CDATA[
Understanding the functional effect of Single Amino acid Substitutions (SAS), derived from the occurrence of single nucleotide variants (SNVs), and their relation to disease development is a major issue in clinical genomics. Even though there are several bioinformatic algorithms and servers that predict if a SAS can be pathogenic or not they give little or non-information on the actual effect on the protein function. Moreover, many of these algorithms are able to predict an effect that no necessarily translates directly into pathogenicity. VarQ Web Server is an online tool that given an UniProt id automatically analyzes known and user provided SAS for their effect on protein activity, folding, aggregation and protein interactions among others. VarQ assessment was performed over a set of previously manually curated variants, showing its ability to correctly predict the phenotypic outcome and its underlying cause. This resource is available online at http://varq.qb.fcen.uba.ar/.nnContact: lradusky@qb.fcen.uba.arnnSupporting Information & Tutorials may be found in the webpage of the tool.
]]></description>
<dc:creator>Radusky, L.</dc:creator>
<dc:creator>Modenutti, C. P.</dc:creator>
<dc:creator>Delgado, J.</dc:creator>
<dc:creator>Bustamante, J. P.</dc:creator>
<dc:creator>Vishnopolska, S.</dc:creator>
<dc:creator>Kiel, C.</dc:creator>
<dc:creator>Serrano, L.</dc:creator>
<dc:creator>Marti, M.</dc:creator>
<dc:creator>Turjanski, A. G.</dc:creator>
<dc:date>2018-03-07</dc:date>
<dc:identifier>doi:10.1101/277491</dc:identifier>
<dc:title><![CDATA[VarQ: a tool for the structural analysis of Human Protein Variants]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/446492v1?rss=1">
<title>
<![CDATA[
Reverse GWAS: Using Genetics to Identify and Model Phenotypic Subtypes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/446492v1?rss=1"
</link>
<description><![CDATA[
Recent and classical work has revealed biologically and medically significant subtypes in complex diseases and traits. However, relevant subtypes are often unknown, unmeasured, or actively debated, making automatic statistical approaches to subtype definition particularly valuable. We propose reverse GWAS (RGWAS) to identify and validate subtypes using genetics and multiple traits: while GWAS seeks the genetic basis of a given trait, RGWAS seeks to define trait subtypes with distinct genetic bases. Unlike existing approaches relying on off-the-shelf clustering methods, RGWAS uses a bespoke decomposition, MFMR, to model covariates, binary traits, and population structure. We use extensive simulations to show these features can be crucial for power and calibration. We validate RGWAS in practice by recovering known stress subtypes in major depressive disorder. We then show the utility of RGWAS by identifying three novel subtypes of metabolic traits. We biologically validate these metabolic subtypes with SNP-level tests and a novel polygenic test: the former recover known metabolic GxE SNPs; the latter suggests genetic heterogeneity may explain substantial missing heritability. Crucially, statins, which are widely prescribed and theorized to increase diabetes risk, have opposing effects on blood glucose across metabolic subtypes, suggesting potential have potential translational value.nnAuthor summaryComplex diseases depend on interactions between many known and unknown genetic and environmental factors. However, most studies aggregate these strata and test for associations on average across samples, though biological factors and medical interventions can have dramatically different effects on different people. Further, more-sophisticated models are often infeasible because relevant sources of heterogeneity are not generally known a priori. We introduce Reverse GWAS to simultaneously split samples into homogeneoues subtypes and to learn differences in genetic or treatment effects between subtypes. Unlike existing approaches to computational subtype identification using high-dimensional trait data, RGWAS accounts for covariates, binary disease traits and, especially, population structure; these features are each invaluable in extensive simulations. We validate RGWAS by recovering known genetic subtypes of major depression. We demonstrate RGWAS is practically useful in a metabolic study, finding three novel subtypes with both SNP- and polygenic-level heterogeneity. Importantly, RGWAS can uncover differential treatment response: for example, we show that statin, a common drug and potential type 2 diabetes risk factor, may have opposing subtype-specific effects on blood glucose.
]]></description>
<dc:creator>Dahl, A.</dc:creator>
<dc:creator>Cai, N.</dc:creator>
<dc:creator>Ko, A.</dc:creator>
<dc:creator>Laakso, M.</dc:creator>
<dc:creator>Pajukanta, P.</dc:creator>
<dc:creator>Flint, J.</dc:creator>
<dc:creator>Zaitlen, N.</dc:creator>
<dc:date>2018-10-17</dc:date>
<dc:identifier>doi:10.1101/446492</dc:identifier>
<dc:title><![CDATA[Reverse GWAS: Using Genetics to Identify and Model Phenotypic Subtypes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/354316v1?rss=1">
<title>
<![CDATA[
Systematic Characterization of RhoGEF/RhoGAP Regulatory Proteins Reveals Organization Principles of Rho GTPase Signaling 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/354316v1?rss=1"
</link>
<description><![CDATA[
Rho GTPases control cell morphogenesis and thus fundamental processes in all eukaryotes. They are regulated by 145 RhoGEF and RhoGAP multi-domain proteins in humans. How the Rho signaling system is organized to generate localized responses in cells and prevent their spreading is not understood. Here, we systematically characterized the substrate specificities, localization and interactome of the RhoGEFs/RhoGAPs and revealed their critical role in contextualizing and spatially delimiting Rho signaling. They localize to multiple compartments providing positional information, are extensively interconnected to jointly coordinate their signaling networks and are widely autoinhibited to remain sensitive to local activation. RhoGAPs exhibit lower substrate specificity than RhoGEFs and may contribute to preserving Rho activity gradients. Our approach led us to uncover a multi-RhoGEF complex downstream of G-protein-coupled receptors controlling a Cdc42/RhoA crosstalk. The spatial organization of Rho signaling thus differs from other small GTPases and expands the repertoire of mechanisms governing localized signaling activity.
]]></description>
<dc:creator>Rocks, O.</dc:creator>
<dc:creator>Mueller, P. M.</dc:creator>
<dc:creator>Rademacher, J.</dc:creator>
<dc:creator>Bagshaw, R. D.</dc:creator>
<dc:creator>Alp, K. M.</dc:creator>
<dc:creator>Giudice, G.</dc:creator>
<dc:creator>Heinrich, L. E.</dc:creator>
<dc:creator>Barth, C.</dc:creator>
<dc:creator>Eccles, R. L.</dc:creator>
<dc:creator>Sanchez-Castro, M.</dc:creator>
<dc:creator>Mbamalu, G.</dc:creator>
<dc:creator>Tucholska, M.</dc:creator>
<dc:creator>Spatt, L.</dc:creator>
<dc:creator>Wortmann, C.</dc:creator>
<dc:creator>Czajkowski, M. T.</dc:creator>
<dc:creator>Welke, R. W.</dc:creator>
<dc:creator>Zhang, S.</dc:creator>
<dc:creator>Nguyen, V.</dc:creator>
<dc:creator>Brandeburg, L.</dc:creator>
<dc:creator>Rrustemi, T.</dc:creator>
<dc:creator>Trnka, P.</dc:creator>
<dc:creator>Freitag, K.</dc:creator>
<dc:creator>Larsen, B.</dc:creator>
<dc:creator>Popp, O.</dc:creator>
<dc:creator>Colwill, K.</dc:creator>
<dc:creator>Mertins, P.</dc:creator>
<dc:creator>Gingras, A.-C.</dc:creator>
<dc:creator>Bakal, C.</dc:creator>
<dc:creator>Pertz, O.</dc:creator>
<dc:creator>Roth, F. P.</dc:creator>
<dc:creator>Pawson, T.</dc:creator>
<dc:creator>Petsalaki, E.</dc:creator>
<dc:date>2018-06-24</dc:date>
<dc:identifier>doi:10.1101/354316</dc:identifier>
<dc:title><![CDATA[Systematic Characterization of RhoGEF/RhoGAP Regulatory Proteins Reveals Organization Principles of Rho GTPase Signaling]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/143321v1?rss=1">
<title>
<![CDATA[
SpatialDE - Identification Of Spatially Variable Genes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/143321v1?rss=1"
</link>
<description><![CDATA[
Technological advances have enabled low-input RNA-sequencing, paving the way for assaying transcriptome variation in spatial contexts, including in tissues. While the generation of spatially resolved transcriptome maps is increasingly feasible, computational methods for analysing the resulting data are not established. Existing analysis strategies either ignore the spatial component of gene expression variation, or require discretization of the cells into coarse grained groups.nnTo address this, we have developed SpatialDE, a computational framework for identifying and characterizing spatially variable genes. Our method generalizes variable gene selection, as used in population-and single-cell studies, to spatial expression profiles. To illustrate the broad utility of our approach, we apply SpatialDE to spatial transcriptomics data, and to data from single cell methods based on multiplexed in situ hybridisation (SeqFISH and MERFISH). SpatialDE enables the statistically robust identification of spatially variable genes, thereby identifying genes with known disease implications, several of which are missed by conventional variable gene selection. Additionally, to enable gene-expressed based histology, SpatialDE implements a spatial gene clustering model which we call "automatic expression histology," allowing to classify genes into groups with distinct spatial patterns.
]]></description>
<dc:creator>Svensson, V.</dc:creator>
<dc:creator>Teichmann, S. A.</dc:creator>
<dc:creator>Stegle, O.</dc:creator>
<dc:date>2017-05-28</dc:date>
<dc:identifier>doi:10.1101/143321</dc:identifier>
<dc:title><![CDATA[SpatialDE - Identification Of Spatially Variable Genes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/276493v1?rss=1">
<title>
<![CDATA[
Epigallocatechin-3-Gallate Improves Facial Dysmorphology Associated with Down Syndrome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/276493v1?rss=1"
</link>
<description><![CDATA[
In Down syndrome (DS), the overall genetic imbalance caused by trisomy of chromosome 21 leads to a complex pleiotropic phenotype that involves a recognizable set of facial traits. Several studies have shown the potential of epigallocatechin-3-gallate (EGCG), a green tea flavanol, as a therapeutic tool for alleviating different developmental alterations associated with DS, such as cognitive impairment, skull dysmorphologies, and skeletal deficiencies. Here we provide for the first time experimental and clinical evidence of the potential benefits of EGCG treatment to facial morphology. Our results showed that mouse models treated with low dose of EGCG during pre- and postnatal development improved facial dysmorphology. However, the same treatment at high dose produced disparate facial morphology changes with an extremely wide and abnormal range of variation. Our observational study in humans revealed that EGCG treatment since early in development is associated with intermediate facial phenotypes and significant facial improvement scores. Overall, our findings suggest a potential beneficial effect of ECGC on facial development, which requires further research to pinpoint the optimal dosages of EGCG that reliably improve DS phenotypes. Current evidence warns against the non-prescribed intake of this supplement as a health-promoting measure.
]]></description>
<dc:creator>Starbuck, J.</dc:creator>
<dc:creator>Llambrich, S.</dc:creator>
<dc:creator>Gonzalez, R.</dc:creator>
<dc:creator>Albaiges, J.</dc:creator>
<dc:creator>Sarle, A.</dc:creator>
<dc:creator>Wouters, J.</dc:creator>
<dc:creator>Gonzalez, A.</dc:creator>
<dc:creator>Sevillano, X.</dc:creator>
<dc:creator>Sharpe, J.</dc:creator>
<dc:creator>de la Torre, R.</dc:creator>
<dc:creator>Dierssen, M.</dc:creator>
<dc:creator>Vande Velde, G.</dc:creator>
<dc:creator>Martinez-Abadias, N.</dc:creator>
<dc:date>2018-03-05</dc:date>
<dc:identifier>doi:10.1101/276493</dc:identifier>
<dc:title><![CDATA[Epigallocatechin-3-Gallate Improves Facial Dysmorphology Associated with Down Syndrome]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/200972v1?rss=1">
<title>
<![CDATA[
Placozoans are eumetazoans related to Cnidaria 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/200972v1?rss=1"
</link>
<description><![CDATA[
The phylogenetic placement of the morphologically simple placozoans is crucial to understanding the evolution of complex animal traits. Here, we examine the influence of adding new genomes from placozoans to a large dataset designed to study the deepest splits in the animal phylogeny. Using site-heterogeneous substitution models, we show that it is possible to obtain strong support, in both amino acid and reduced-alphabet matrices, for either a sister-group relationship between Cnidaria and Placozoa, or for Cnidaria and Bilateria (=Planulozoa), also seen in most published work to date, depending on the orthologues selected to construct the matrix. We demonstrate that a majority of genes show evidence of compositional heterogeneity, and that the support for Planulozoa can be assigned to this source of systematic error. In interpreting this placozoan-cnidarian clade, we caution against a peremptory reading of placozoans as secondarily reduced forms of little relevance to broader discussions of early animal evolution.
]]></description>
<dc:creator>Laumer, C. E.</dc:creator>
<dc:creator>Gruber-Vodicka, H.</dc:creator>
<dc:creator>Hadfield, M. G.</dc:creator>
<dc:creator>Pearse, V. B.</dc:creator>
<dc:creator>Riesgo, A.</dc:creator>
<dc:creator>Marioni, J. C.</dc:creator>
<dc:creator>Giribet, G.</dc:creator>
<dc:date>2017-10-11</dc:date>
<dc:identifier>doi:10.1101/200972</dc:identifier>
<dc:title><![CDATA[Placozoans are eumetazoans related to Cnidaria]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/068072v1?rss=1">
<title>
<![CDATA[
A damped oscillator imposes temporal order on posterior gap gene expression in Drosophila 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/068072v1?rss=1"
</link>
<description><![CDATA[
Insects determine their body segments in two different ways. Short-germband insects, such as the flour beetle Tribolium castaneum, use a molecular clock to establish segments sequentially. In contrast, long-germband insects, such as the vinegar fly Drosophila melanogaster, determine all segments simultaneously through a hierarchical cascade of gene regulation. Gap genes constitute the first layer of the Drosophila segmentation gene hierarchy, downstream of maternal gradients such as that of Caudal (Cad). We use data-driven mathematical modelling and phase space analysis to show that shifting gap domains in the posterior half of the Drosophila embryo are an emergent property of a robust damped oscillator mechanism, suggesting that the regulatory dynamics underlying long- and short-germband segmentation are much more similar than previously thought. In Tribolium, Cad has been proposed to modulate the frequency of the segmentation oscillator. Surprisingly, our simulations and experiments show that the shift rate of posterior gap domains is independent of maternal Cad levels in Drosophila. Our results suggest a novel evolutionary scenario for the short- to long-germband transition, and help explain why this transition occurred convergently multiple times during the radiation of the holometabolan insects.nnAuthor summaryDifferent insect species exhibit one of two distinct modes of determining their body segments during development: they either use a molecular oscillator to position segments sequentially, or they generate segments simultaneously through a hierarchical gene-regulatory cascade. The sequential mode is ancestral, while the simultaneous mode has been derived from it independently several times during evolution. In this paper, we present evidence which suggests that simultaneous segmentation also involves an oscillator in the posterior of the embryo of the vinegar fly, Drosophila melanogaster. This surprising result indicates that both modes of segment determination are much more similar than previously thought. Such similarity provides an important step towards explaining the frequent evolutionary transitions between sequential and simultaneous segmentation.
]]></description>
<dc:creator>Berta Verd</dc:creator>
<dc:creator>Erik Clark</dc:creator>
<dc:creator>Anton Crombach</dc:creator>
<dc:creator>Johannes Jaeger</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-08-05</dc:date>
<dc:identifier>doi:10.1101/068072</dc:identifier>
<dc:title><![CDATA[A damped oscillator imposes temporal order on posterior gap gene expression in Drosophila]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-08-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/152579v1?rss=1">
<title>
<![CDATA[
The proBAM and proBed standard formats: enabling a seamless integration of genomics and proteomics data. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/152579v1?rss=1"
</link>
<description><![CDATA[
On behalf of The Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI), we are here introducing two novel standard data formats, proBAM and proBed, that have been developed to address the current challenges of integrating mass spectrometry based proteomics data with genomics and transcriptomics information in proteogenomics studies. proBAM and proBed are adaptations from the well-defined, widely used file formats SAM/BAM and BED respectively, and both have been extended to meet specific requirements entailed by proteomics data. Therefore, existing popular genomics tools such as SAMtools and Bedtools, and several very popular genome browsers, can be used to manipulate and visualize these formats already out-of-the-box. We also highlight that a number of specific additional software tools, properly supporting the proteomics information available in these formats, are now available providing functionalities such as file generation, file conversion, and data analysis. All the related documentation to the formats, including the detailed file format specifications, and example files are accessible at http://www.psidev.info/probam and http://www.psidev.info/probed.
]]></description>
<dc:creator>Menschaert, G.</dc:creator>
<dc:creator>Wang, X.</dc:creator>
<dc:creator>Jones, A. R.</dc:creator>
<dc:creator>Ghali, F.</dc:creator>
<dc:creator>Fenyo, D.</dc:creator>
<dc:creator>Olexiouk, V.</dc:creator>
<dc:creator>Zhang, B.</dc:creator>
<dc:creator>Deutsch, E. W.</dc:creator>
<dc:creator>Ternent, T.</dc:creator>
<dc:creator>Vizcaino, J. A.</dc:creator>
<dc:date>2017-06-20</dc:date>
<dc:identifier>doi:10.1101/152579</dc:identifier>
<dc:title><![CDATA[The proBAM and proBed standard formats: enabling a seamless integration of genomics and proteomics data.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/269068v1?rss=1">
<title>
<![CDATA[
Ubiquitous abundance distribution of non-dominant plankton across the world’s ocean 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/269068v1?rss=1"
</link>
<description><![CDATA[
Species Abundance Distributions (SADs) bear the imprint of ecological processes that shape biological communities, and are therefore used to discriminate among different scenarios of community assembly. Even though empirical distributions appear to follow a handful of qualitative laws, it is still unclear if and how quantitative variation in SADs reflects peculiar features of the communities and their environmental context. Here, we use the extensive dataset generated by the Tara Oceans expedition for marine microbial eukaryotes (protists) and an adaptive algorithm to explore how SADs vary across plankton communities in the global ocean. We show that the decay in abundance of non-dominant OTUs, comprising over 99% of local richness, is commonly governed by a power-law. The power-law exponent varies by less than 10% across locations and shows no biogeographical signature, but is weakly modulated by cell size. Our findings suggest that large-scale ubiquitous ecological processes govern the assembly of non-dominant plankton throughout the global ocean.
]]></description>
<dc:creator>Ser-Giacomi, E.</dc:creator>
<dc:creator>Zinger, L.</dc:creator>
<dc:creator>Malviya, S.</dc:creator>
<dc:creator>De Vargas, C.</dc:creator>
<dc:creator>Karsenti, E.</dc:creator>
<dc:creator>Bowler, C.</dc:creator>
<dc:creator>De Monte, S.</dc:creator>
<dc:date>2018-02-21</dc:date>
<dc:identifier>doi:10.1101/269068</dc:identifier>
<dc:title><![CDATA[Ubiquitous abundance distribution of non-dominant plankton across the world’s ocean]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/127894v1?rss=1">
<title>
<![CDATA[
Transcript Isoform Differences Across Human Tissues Are Predominantly Driven By Alternative Start And Termination Sites Of Transcription 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/127894v1?rss=1"
</link>
<description><![CDATA[
Most human genes have multiple transcription start and polyadenylation sites, as well as alternatively spliced exons. Although such transcript isoform diversity contributes to the differentiation between cell types, the importance of contributions from the different isoform generating processes is unclear. To address this question, we used 798 samples from the Genotype-Tissue Expression (GTEx) to investigate cell type dependent differences in exon usage of over 18,000 protein-coding genes in 23 cell types. We found tissue-dependent isoform usage in about half of expressed genes. Overall, tissue-dependent splicing accounted only for a minority of tissue-dependent exon usage, most of which was consistent with alternative transcription start and termination sites. We verified this result on a second, independent dataset, Cap Analysis of Gene Expression (CAGE) data from the FANTOM consortium, which confirmed widespread tissue-dependent usage of alternative transcription start sites. Our analysis identifies transcription start and termination sites as the principal drivers of isoform diversity across tissues. Moreover, our results indicate that most tissue-dependent splicing involves untranslated exons and therefore may not have consequences at the proteome level.
]]></description>
<dc:creator>Reyes, A.</dc:creator>
<dc:creator>Huber, W.</dc:creator>
<dc:date>2017-04-17</dc:date>
<dc:identifier>doi:10.1101/127894</dc:identifier>
<dc:title><![CDATA[Transcript Isoform Differences Across Human Tissues Are Predominantly Driven By Alternative Start And Termination Sites Of Transcription]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/166223v1?rss=1">
<title>
<![CDATA[
GDSCTools for Mining Pharmacogenomic Interactions in Cancer 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/166223v1?rss=1"
</link>
<description><![CDATA[
MotivationLarge pharmacogenomic screenings integrate heterogeneous cancer genomic data sets as well as anti-cancer drug responses on thousand human cancer cell lines. Mining this data to identify new therapies for cancer sub-populations would benefit from common data structures, modular computational biology tools and user-friendly interfaces.nnResultsWe have developed GDSCTools: a software aimed at the identification of clinically relevant genomic markers of drug response. The Genomics of Drug Sensitivity in Cancer (GDSC) database (www.cancerRxgene.org) integrates heterogeneous cancer genomic data sets as well as anti-cancer drug responses on a thousand cancer cell lines. Including statistical tools (ANOVA) and predictive methods (Elastic Net), as well as common data structures, GDSCTools allows users to reproduce published results from GDSC, to analyse their own drug responses or genomic datasets, and to implement new analytical methods.nnContactthomas.cokelaer@pasteur.fr
]]></description>
<dc:creator>Cokelaer, T.</dc:creator>
<dc:creator>Chen, E.</dc:creator>
<dc:creator>Iorio, F.</dc:creator>
<dc:creator>Menden, M. P.</dc:creator>
<dc:creator>Lightfoot, H.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:creator>Mathew, G. J.</dc:creator>
<dc:date>2017-07-20</dc:date>
<dc:identifier>doi:10.1101/166223</dc:identifier>
<dc:title><![CDATA[GDSCTools for Mining Pharmacogenomic Interactions in Cancer]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/138537v1?rss=1">
<title>
<![CDATA[
A Theory That Predicts Behaviors Of Disordered Cytoskeletal Networks 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/138537v1?rss=1"
</link>
<description><![CDATA[
Morphogenesis in animal tissues is largely driven by tensions of actomyosin networks, generated by an active contractile process that can be reconstituted in vitro. Although the network components and their properties are known, the requirements for contractility are still poorly understood. Here, we describe a theory that predicts whether an isotropic network will contract, expand, or conserve its dimensions. This analytical theory correctly predicts the behavior of simulated networks consisting of filaments with varying combinations of connectors, and reveals conditions under which networks of rigid filaments are either contractile or expansile. Our results suggest that pulsatility is an intrinsic behavior of contractile networks if the filaments are not stable but turn over. The theory offers a unifying framework to think about mechanisms of contractions or expansion. It provides a foundation for the study of a broad range of processes involving cytoskeletal networks, and a basis for designing synthetic networks.
]]></description>
<dc:creator>Belmonte, J.</dc:creator>
<dc:creator>Leptin, M.</dc:creator>
<dc:creator>Nedelec, F.</dc:creator>
<dc:date>2017-05-16</dc:date>
<dc:identifier>doi:10.1101/138537</dc:identifier>
<dc:title><![CDATA[A Theory That Predicts Behaviors Of Disordered Cytoskeletal Networks]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/066027v1?rss=1">
<title>
<![CDATA[
The druggable genome and support for target identification and validation in drug development 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/066027v1?rss=1"
</link>
<description><![CDATA[
Target identification (identifying the correct drug targets for each disease) and target validation (demonstrating the effect of target perturbation on disease biomarkers and disease end-points) are essential steps in drug development. We showed previously that biomarker and disease endpoint associations of single nucleotide polymorphisms (SNPs) in a gene encoding a drug target accurately depict the effect of modifying the same target with a pharmacological agent; others have shown that genomic support for a target is associated with a higher rate of drug development success. To delineate drug development (including repurposing) opportunities arising from this paradigm, we connected complex disease- and biomarker-associated loci from genome wide association studies (GWAS) to an updated set of genes encoding druggable human proteins, to compounds with bioactivity against these targets and, where these were licensed drugs, to clinical indications. We used this set of genes to inform the design of a new genotyping array, to enable druggable genome-wide association studies for drug target selection and validation in human disease.
]]></description>
<dc:creator>Chris Finan</dc:creator>
<dc:creator>Anna Gaulton</dc:creator>
<dc:creator>Felix Kruger</dc:creator>
<dc:creator>Tom Lumbers</dc:creator>
<dc:creator>Tina Shah</dc:creator>
<dc:creator>Jorgen Engmann</dc:creator>
<dc:creator>Luana Galver</dc:creator>
<dc:creator>Ryan Kelly</dc:creator>
<dc:creator>Anneli Karlsson</dc:creator>
<dc:creator>Rita Santos</dc:creator>
<dc:creator>John Overington</dc:creator>
<dc:creator>Aroon Hingorani</dc:creator>
<dc:creator>Juan Pablo Casas</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-07-26</dc:date>
<dc:identifier>doi:10.1101/066027</dc:identifier>
<dc:title><![CDATA[The druggable genome and support for target identification and validation in drug development]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-07-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/362517v1?rss=1">
<title>
<![CDATA[
Super-resolution fight club: A broad assessment of 2D & 3D single-molecule localization microscopy software 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/362517v1?rss=1"
</link>
<description><![CDATA[
With the widespread uptake of 2D and 3D single molecule localization microscopy, a large set of different data analysis packages have been developed to generate super-resolution images. To guide researchers on the optimal analytical software for their experiments, we have designed, in a large community effort, a competition to extensively characterise and rank these options. We generated realistic simulated datasets for popular imaging modalities - 2D, astigmatic 3D, biplane 3D, and double helix 3D - and evaluated 36 participant packages against these data. This provides the first broad assessment of 3D single molecule localization microscopy software, provides a holistic view of how the latest 2D and 3D single molecule localization software perform in realistic conditions, and ultimately provides insight into the current limits of the field.
]]></description>
<dc:creator>Sage, D.</dc:creator>
<dc:creator>Pham, T.-A.</dc:creator>
<dc:creator>Babcock, H.</dc:creator>
<dc:creator>Lukes, T.</dc:creator>
<dc:creator>Pengo, T.</dc:creator>
<dc:creator>Velmurugan, R.</dc:creator>
<dc:creator>Herbert, A.</dc:creator>
<dc:creator>Agarwal, A.</dc:creator>
<dc:creator>Colabrese, S.</dc:creator>
<dc:creator>Wheeler, A.</dc:creator>
<dc:creator>Archetti, A.</dc:creator>
<dc:creator>Rieger, B.</dc:creator>
<dc:creator>Ober, R.</dc:creator>
<dc:creator>Hagen, G. M.</dc:creator>
<dc:creator>Sibarita, J.-B.</dc:creator>
<dc:creator>Ries, J.</dc:creator>
<dc:creator>Henriques, R.</dc:creator>
<dc:creator>Unser, M.</dc:creator>
<dc:creator>Holden, S.</dc:creator>
<dc:date>2018-07-04</dc:date>
<dc:identifier>doi:10.1101/362517</dc:identifier>
<dc:title><![CDATA[Super-resolution fight club: A broad assessment of 2D & 3D single-molecule localization microscopy software]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/297960v1?rss=1">
<title>
<![CDATA[
Analyzing the symmetrical arrangement of structural repeats in proteins with CE-Symm 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/297960v1?rss=1"
</link>
<description><![CDATA[
Many proteins fold into highly regular and repetitive three dimensional structures. The analysis of structural patterns and repeated elements is fundamental to understand protein function and evolution. We present recent improvements to the CE-Symm tool for systematically detecting and analyzing the internal symmetry and structural repeats in proteins. In addition to the accurate detection of internal symmetry, the tool is now capable of i) reporting the type of symmetry, ii) identifying the smallest repeating unit, iii) describing the arrangement of repeats with transformation operations and symmetry axes, and iv) comparing the similarity of all the internal repeats at the residue level. CE-Symm 2.0 helps the user investigate proteins with a robust and intuitive sequence-to-structure analysis, with many applications in protein classification, functional annotation and evolutionary studies. We describe the algorithmic extensions of the method and demonstrate its applications to the study of interesting cases of protein evolution.nnAvailabilit: CE-Symm is an open source tool integrated into the BioJava library(www.biojava.org)and freely available at https://github.com/rcsb/symmetry.
]]></description>
<dc:creator>Bliven, S. E.</dc:creator>
<dc:creator>Lafita, A.</dc:creator>
<dc:creator>Rose, P. W.</dc:creator>
<dc:creator>Capitani, G.</dc:creator>
<dc:creator>Prlic, A.</dc:creator>
<dc:creator>Bourne, P.</dc:creator>
<dc:date>2018-04-09</dc:date>
<dc:identifier>doi:10.1101/297960</dc:identifier>
<dc:title><![CDATA[Analyzing the symmetrical arrangement of structural repeats in proteins with CE-Symm]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/141879v1?rss=1">
<title>
<![CDATA[
Phenotype prediction in an Escherichia coli strain panel 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/141879v1?rss=1"
</link>
<description><![CDATA[
Understanding how genetic variation contributes to phenotypic differences is a fundamental question in biology. Here, we set to predict fitness defects of an individual using mechanistic models of the impact of genetic variants combined with prior knowledge of gene function. We assembled a diverse panel of 696 Escherichia coli strains for which we obtained genomes and measured growth phenotypes in 214 conditions. We integrated variant effect predictors to derive gene-level probabilities of loss of function for every gene across strains. We combined these probabilities with information on conditional gene essentiality in the reference K-12 strain to predict the strains growth defects, providing significant predictions for up to 38% of tested conditions. The putative causal variants were validated in complementation assays highlighting commonly perturbed pathways in evolution for the emergence of growth phenotypes. Altogether, our work illustrates the power of integrating high-throughput gene function assays to predict the phenotypes of individuals.nnHighlightsO_LIAssembled a reference panel of E. coli strainsnC_LIO_LIGenotyped and high-throughput phenotyped the E. coli reference strain panelnC_LIO_LIReliably predicted the impact of genetic variants in up to 38% of tested conditionsnC_LIO_LIHighlighted common genetic pathways for the emergence of deleterious phenotypesnC_LI
]]></description>
<dc:creator>Galardini, M.</dc:creator>
<dc:creator>Koumoutsi, A.</dc:creator>
<dc:creator>Herrera-Dominguez, L.</dc:creator>
<dc:creator>Cordero Varela, J. A.</dc:creator>
<dc:creator>Telzerow, A.</dc:creator>
<dc:creator>Wagih, O.</dc:creator>
<dc:creator>Wartel, M.</dc:creator>
<dc:creator>Clermont, O.</dc:creator>
<dc:creator>Denamur, E.</dc:creator>
<dc:creator>Typas, A.</dc:creator>
<dc:creator>Beltrao, P.</dc:creator>
<dc:date>2017-05-24</dc:date>
<dc:identifier>doi:10.1101/141879</dc:identifier>
<dc:title><![CDATA[Phenotype prediction in an Escherichia coli strain panel]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/226811v1?rss=1">
<title>
<![CDATA[
A genome-wide resource for high-throughput genomic tagging of yeast ORFs 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/226811v1?rss=1"
</link>
<description><![CDATA[
Here we describe a C-SWAT library for high-throughput tagging of Saccharomyces cerevisiae ORFs. It consists of 5661 strains with an acceptor module inserted after each ORF, which can be efficiently replaced with tags or regulatory elements. We validate the library with targeted sequencing and demonstrate its use by tagging the yeast proteome with bright fluorescent proteins, determining how sequences downstream of ORFs influence protein expression and localizing previously undetected proteins.
]]></description>
<dc:creator>Meurer, M.</dc:creator>
<dc:creator>Duan, Y.</dc:creator>
<dc:creator>Sass, E.</dc:creator>
<dc:creator>Kats, I.</dc:creator>
<dc:creator>Herbst, K.</dc:creator>
<dc:creator>Buchmuller, B. C.</dc:creator>
<dc:creator>Dederer, V.</dc:creator>
<dc:creator>Huber, F.</dc:creator>
<dc:creator>Kirrmaier, D.</dc:creator>
<dc:creator>Stefl, M.</dc:creator>
<dc:creator>Van Laer, K.</dc:creator>
<dc:creator>Dick, T. P.</dc:creator>
<dc:creator>Lemberg, M. K.</dc:creator>
<dc:creator>Khmelinskii, A.</dc:creator>
<dc:creator>Levy, E. D.</dc:creator>
<dc:creator>Knop, M.</dc:creator>
<dc:date>2017-11-30</dc:date>
<dc:identifier>doi:10.1101/226811</dc:identifier>
<dc:title><![CDATA[A genome-wide resource for high-throughput genomic tagging of yeast ORFs]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/114108v1?rss=1">
<title>
<![CDATA[
Alzheimer related genes show accelerated evolution 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/114108v1?rss=1"
</link>
<description><![CDATA[
Alzheimer's disease (AD) is a neurodegenerative disorder of unknown cause with complex genetic and environmental traits. Here, we show that gene structures of loci, that show AD-associated changes in their expression, evolve faster than the genome at large. This phylogenetic trait of AD suggests a critical pathogenetic role of recent adaptive evolution of human brain and might have far reaching consequences with respect to the appropriateness of model systems and the development of disease-modifying strategies.
]]></description>
<dc:creator>Nitsche, A.</dc:creator>
<dc:creator>Reiche, K.</dc:creator>
<dc:creator>Ueberham, U.</dc:creator>
<dc:creator>Arnold, C.</dc:creator>
<dc:creator>Hackermueller, J.</dc:creator>
<dc:creator>Horn, F.</dc:creator>
<dc:creator>Stadler, P. F.</dc:creator>
<dc:creator>Arendt, T.</dc:creator>
<dc:date>2017-03-07</dc:date>
<dc:identifier>doi:10.1101/114108</dc:identifier>
<dc:title><![CDATA[Alzheimer related genes show accelerated evolution]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-03-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/269811v1?rss=1">
<title>
<![CDATA[
Tracing the Transitions from Pluripotency to Germ Cell Fate with CRISPR Screening 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/269811v1?rss=1"
</link>
<description><![CDATA[
Early mammalian development entails a series of cell fate transitions that includes transit through naive pluripotency to post-implantation epiblast. This subsequently gives rise to primordial germ cells (PGC), the founding population of the germline lineage. To investigate the gene regulatory networks that control these critical cell fate decisions, we developed a compound-reporter system to track cellular identity in a model of PGC specification (PGC-like cells; PGCLC), and coupled it with unbiased genome-wide CRISPR screening. This enabled identification of key genes both for exit from pluripotency and for acquisition of PGC fate, with further characterisation revealing a central role for the transcription factors Nr5a2 and Zfp296 in germline ontogeny. Abrogation of these genes results in significantly impaired PGCLC development due to widespread activation (Nr5a2-/-) or inhibition (Zfp296-/-) of WNT pathway components. This leads to aberrant upregulation of the somatic programme or failure to appropriately activate germline genes in PGCLC, respectively, and consequently loss of germ cell identity. Overall our study places Zfp296 and Nr5a2 as key components of an expanded PGC gene regulatory network, and outlines a transferable strategy for identifying critical regulators of complex cell fate transitions.
]]></description>
<dc:creator>Hackett, J. A.</dc:creator>
<dc:creator>Huang, Y.</dc:creator>
<dc:creator>Gunesdogan, U.</dc:creator>
<dc:creator>Holm-Gretarsson, K.</dc:creator>
<dc:creator>Kobayashi, T.</dc:creator>
<dc:creator>Surani, A. M.</dc:creator>
<dc:date>2018-02-22</dc:date>
<dc:identifier>doi:10.1101/269811</dc:identifier>
<dc:title><![CDATA[Tracing the Transitions from Pluripotency to Germ Cell Fate with CRISPR Screening]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/074773v1?rss=1">
<title>
<![CDATA[
A bromodomain-DNA interaction facilitates acetylation-dependent bivalent nucleosome recognition by the BET protein BRDT 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/074773v1?rss=1"
</link>
<description><![CDATA[
Bromodomains are critical components of many chromatin modifying/remodeling proteins and are emerging therapeutic targets, yet how they interact with nucleosomes, rather than acetylated peptides, remains unclear. Using BRDT as a model, we characterized how the BET family of bromodomains interacts with site-specifically acetylated nucleosomes. We find that BRDT interacts with nucleosomes through its first (BD1), but not second (BD2) bromodomain, and that acetylated histone recognition by BD1 is complemented by a novel bromodomain-DNA interaction. Simultaneous DNA and histone recognition enhances BRDT's nucleosome binding affinity, specificity, and ability to localize to and compact acetylated chromatin. Conservation of DNA binding in bromodomains of BRD2, BRD3 and BRD4, indicates that bivalent nucleosome recognition is a key feature of these bromodomains and possibly others. Our results elucidate the molecular mechanism of BRDT association with nucleosomes and identify new structural features of BET bromodomains that may be targeted for therapeutic inhibition.
]]></description>
<dc:creator>Thomas CR Miller</dc:creator>
<dc:creator>Bernd Simon</dc:creator>
<dc:creator>Vladimir Rybin</dc:creator>
<dc:creator>Helga Grötsch</dc:creator>
<dc:creator>Sandrine Curtet</dc:creator>
<dc:creator>Saadi Khochbin</dc:creator>
<dc:creator>Teresa Carlomagno</dc:creator>
<dc:creator>Christoph W Müller</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-09-12</dc:date>
<dc:identifier>doi:10.1101/074773</dc:identifier>
<dc:title><![CDATA[A bromodomain-DNA interaction facilitates acetylation-dependent bivalent nucleosome recognition by the BET protein BRDT]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-09-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/186478v1?rss=1">
<title>
<![CDATA[
Avoiding ascertainment bias in the maximum likelihood inference of phylogenies based on truncated data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/186478v1?rss=1"
</link>
<description><![CDATA[
Some phylogenetic datasets omit data matrix positions at which all taxa share the same state. For sequence data this may be because of a focus on single nucleotide polymorphisms (SNPs) or the use of a technique such as restriction site-associated DNA sequencing (RADseq) that concentrates attention onto regions of differences. With morphological data, it is common to omit states that show no variation across the data studied. It is already known that failing to correct for the ascertainment bias of omitting constant positions can lead to overestimates of evolutionary divergence, as the lack of constant sites is explained as high divergence rather than as a deliberate data selection technique. Previous approaches to using corrections to the likelihood function in order to avoid ascertainment bias have either required knowledge of the omitted positions, or have modified the likelihood function to reflect the omitted data. In this paper we indicate that the technique used to date for this latter approach is a conditional maximum likelihood (CML) method. An alternative approach -- unconditional maximum likelihood (UML) -- is also possible. We investigate the performance of CML and UML and find them to have almost identical performance in the phylogenetic SNP dataset context. We also make some observations about the nucleotide frequencies observed in SNP datasets, indicating that these can differ systematically from the overall equilibrium base frequencies of the substitution process. This suggests that model parameters representing base frequencies should be estimated by maximum likelihood, and not by empirical (counting) methods.
]]></description>
<dc:creator>Tamuri, A.</dc:creator>
<dc:creator>Goldman, N.</dc:creator>
<dc:date>2017-09-09</dc:date>
<dc:identifier>doi:10.1101/186478</dc:identifier>
<dc:title><![CDATA[Avoiding ascertainment bias in the maximum likelihood inference of phylogenies based on truncated data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/111542v1?rss=1">
<title>
<![CDATA[
Dynamics of ASC speck formation during skin inflammatory responses in vivo 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/111542v1?rss=1"
</link>
<description><![CDATA[
Activated danger or pathogen sensors trigger assembly of the inflammasome adaptor ASC into specks, large signalling platforms considered hallmarks of inflammasome activation. Because a lack of in vivo tools has prevented the study of endogenous ASC dynamics, we generated a live ASC reporter through CRISPR/Cas9 tagging of the endogenous gene in zebrafish. We see strong ASC expression in the skin and other epithelia that act as barriers to insult. A toxic stimulus triggered speck formation and rapid pyroptosis in keratinocytes in vivo. Macrophages engulfed and digested this speck-containing pyroptotic debris. A 3D ultrastructural reconstruction based on CLEM of in vivo assembled specks revealed a compact network of highly intercrossed filaments, whereas PYD or CARD alone formed filamentous aggregates. The effector caspase is recruited through PYD, whose overexpression induced pyroptosis, but after substantial delay. Therefore, formation of a single compact speck and rapid cell death induction in vivo requires full-length ASC.nnOne Sentence SummaryWith a new endogenous ASC real-time reporter we characterize speck dynamics in vivo as well as the concomitant pyroptosis speck formation causes in keratinocytes.
]]></description>
<dc:creator>Kuri Rodriguez, P. S.</dc:creator>
<dc:creator>Schieber, N.</dc:creator>
<dc:creator>Thumberger, T.</dc:creator>
<dc:creator>Wittbrodt, J.</dc:creator>
<dc:creator>Schwab, Y.</dc:creator>
<dc:creator>Leptin, M.</dc:creator>
<dc:date>2017-02-27</dc:date>
<dc:identifier>doi:10.1101/111542</dc:identifier>
<dc:title><![CDATA[Dynamics of ASC speck formation during skin inflammatory responses in vivo]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-02-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/202077v1?rss=1">
<title>
<![CDATA[
Identifying accurate metagenome and amplicon software via a meta-analysis of benchmarking studies 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/202077v1?rss=1"
</link>
<description><![CDATA[
Environmental DNA sequencing has rapidly become a widely-used technique for investigating a range of questions, particularly related to health and environmental monitoring. There has also been a proliferation of bioinformatic tools for analysing metagenomic and amplicon datasets, which makes selecting adequate tools a significant challenge. A number of benchmark studies have been undertaken; however, these can present conflicting results. We have applied a robust Z-score ranking procedure and a network meta-analysis method to identify software tools that are generally accurate for mapping DNA sequences to taxonomic hierarchies. Based upon these results we have identified some tools and computational strategies that produce robust predictions.
]]></description>
<dc:creator>Gardner, P. P.</dc:creator>
<dc:creator>Watson, R. J.</dc:creator>
<dc:creator>Morgan, X. C.</dc:creator>
<dc:creator>Draper, J. L.</dc:creator>
<dc:creator>Finn, R. D.</dc:creator>
<dc:creator>Morales, S. E.</dc:creator>
<dc:creator>Stott, M. B.</dc:creator>
<dc:date>2017-10-12</dc:date>
<dc:identifier>doi:10.1101/202077</dc:identifier>
<dc:title><![CDATA[Identifying accurate metagenome and amplicon software via a meta-analysis of benchmarking studies]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/093906v1?rss=1">
<title>
<![CDATA[
Rapid identification of optimal drug combinations for personalized cancer therapy using microfluidics 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/093906v1?rss=1"
</link>
<description><![CDATA[
Functional screening of live patient cancer cells holds great potential for personalized medicine and allows to overcome the limited translatability of results from existing in-vitro and ex-vivo screening models. Here we present a plug-based microfluidics approach enabling the testing of drug combinations directly on cancer cells from patient biopsies. The entire procedure takes less than 48 hours after surgery and does not require ex vivo cultivation. We screened more than 1100 samples for different primary human tumors (each with 56 conditions and at least 20 replicates), and obtained highly specific sensitivity profiles. This approach allowed us to derive optimal treatment options which we further validated in two different pancreatic cancer cell lines. This workflow should pave the way for rapid determination of optimal personalized cancer therapies at assay costs of less than US$ 150 per patient.
]]></description>
<dc:creator>Eduati, F.</dc:creator>
<dc:creator>Utharala, R.</dc:creator>
<dc:creator>Madhavan, D.</dc:creator>
<dc:creator>Neumann, U. P.</dc:creator>
<dc:creator>Cramer, T.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:creator>Merten, C. A.</dc:creator>
<dc:date>2016-12-14</dc:date>
<dc:identifier>doi:10.1101/093906</dc:identifier>
<dc:title><![CDATA[Rapid identification of optimal drug combinations for personalized cancer therapy using microfluidics]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-12-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/434720v1?rss=1">
<title>
<![CDATA[
Targeting neuronal and glial cell types with synthetic promoter AAVs in mice, non-human primates, and humans 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/434720v1?rss=1"
</link>
<description><![CDATA[
Targeting genes to specific neuronal or glial cell types is valuable both for understanding and for repairing brain circuits. Adeno-associated viral vectors (AAVs) are frequently used for gene delivery, but targeting expression to specific cell types is a challenge. We created a library of 230 AAVs, each with a different synthetic promoter designed using four independent strategies. We show that ~11% of these AAVs specifically target expression to neuronal and glial cell types in the mouse retina, mouse brain, non-human primate retina in vivo, and in the human retina in vitro. We demonstrate applications for recording, stimulation, and molecular characterization, as well as the intersectional and combinatorial labeling of cell types. These resources and approaches allow economic, fast, and efficient cell-type targeting in a variety of species, both for fundamental science and for gene therapy.
]]></description>
<dc:creator>Juettner, J.</dc:creator>
<dc:creator>Szabo, A.</dc:creator>
<dc:creator>Gross-Scherf, B.</dc:creator>
<dc:creator>Morikawa, R.</dc:creator>
<dc:creator>Rompani, S.</dc:creator>
<dc:creator>Teixeira, M.</dc:creator>
<dc:creator>Hantz, P.</dc:creator>
<dc:creator>Szikra, T.</dc:creator>
<dc:creator>Esposti, F.</dc:creator>
<dc:creator>Cowan, C.</dc:creator>
<dc:creator>Bharioke, A.</dc:creator>
<dc:creator>Patino, C.</dc:creator>
<dc:creator>Keles, O.</dc:creator>
<dc:creator>Roth, C.</dc:creator>
<dc:creator>Kusnyerik, A.</dc:creator>
<dc:creator>Gerber-Hollbach, N.</dc:creator>
<dc:creator>Azoulay, T.</dc:creator>
<dc:creator>Hartl, D.</dc:creator>
<dc:creator>Krebs, A.</dc:creator>
<dc:creator>Schuebeler, D.</dc:creator>
<dc:creator>Hajdu, R.</dc:creator>
<dc:creator>Lukats, A.</dc:creator>
<dc:creator>Nemeth, J.</dc:creator>
<dc:creator>Nagy, Z.</dc:creator>
<dc:creator>Wu, K.-C.</dc:creator>
<dc:creator>Wu, R.-H.</dc:creator>
<dc:creator>Xiang, L.</dc:creator>
<dc:creator>Fang, X.-L.</dc:creator>
<dc:creator>Jin, Z.-B.</dc:creator>
<dc:creator>Goldblum, D.</dc:creator>
<dc:creator>Hasler, P.</dc:creator>
<dc:creator>Scholl, H.</dc:creator>
<dc:creator>Krol, J.</dc:creator>
<dc:creator>Roska, B.</dc:creator>
<dc:date>2018-10-04</dc:date>
<dc:identifier>doi:10.1101/434720</dc:identifier>
<dc:title><![CDATA[Targeting neuronal and glial cell types with synthetic promoter AAVs in mice, non-human primates, and humans]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/375345v1?rss=1">
<title>
<![CDATA[
Kipoi: accelerating the community exchange and reuse of predictive models for genomics 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/375345v1?rss=1"
</link>
<description><![CDATA[
Advanced machine learning models applied to large-scale genomics datasets hold the promise to be major drivers for genome science. Once trained, such models can serve as a tool to probe the relationships between data modalities, including the effect of genetic variants on phenotype. However, lack of standardization and limited accessibility of trained models have hampered their impact in practice. To address this, we present Kipoi, a collaborative initiative to define standards and to foster reuse of trained models in genomics. Already, the Kipoi repository contains over 2,000 trained models that cover canonical prediction tasks in transcriptional and post-transcriptional gene regulation. The Kipoi model standard grants automated software installation and provides unified interfaces to apply and interpret models. We illustrate Kipoi through canonical use cases, including model benchmarking, transfer learning, variant effect prediction, and building new models from existing ones. By providing a unified framework to archive, share, access, use, and build on models developed by the community, Kipoi will foster the dissemination and use of machine learning models in genomics.
]]></description>
<dc:creator>Avsec, Z.</dc:creator>
<dc:creator>Kreuzhuber, R.</dc:creator>
<dc:creator>Israeli, J.</dc:creator>
<dc:creator>Xu, N.</dc:creator>
<dc:creator>Cheng, J.</dc:creator>
<dc:creator>Shrikumar, A.</dc:creator>
<dc:creator>Banerjee, A.</dc:creator>
<dc:creator>Kim, D. S.</dc:creator>
<dc:creator>Urban, L.</dc:creator>
<dc:creator>Kundaje, A.</dc:creator>
<dc:creator>Stegle, O.</dc:creator>
<dc:creator>Gagneur, J.</dc:creator>
<dc:date>2018-07-24</dc:date>
<dc:identifier>doi:10.1101/375345</dc:identifier>
<dc:title><![CDATA[Kipoi: accelerating the community exchange and reuse of predictive models for genomics]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/163907v1?rss=1">
<title>
<![CDATA[
Online resources for PCAWG data exploration, visualization, and discovery 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/163907v1?rss=1"
</link>
<description><![CDATA[
The Pan-Cancer Analysis of Whole Genomes (PCAWG) project has generated, to our knowledge, the largest whole-genome cancer sequencing resource to date. Here we provide a users guide to the five publicly available online data exploration and visualization tools introduced in the PCAWG marker paper: The ICGC Data Portal, UCSC Xena, Expression Atlas, PCAWG-Scout, and Chromothripsis Explorer. We detail use cases and analyses for each tool, show how they incorporate outside resources from the larger genomics ecosystem, as well as demonstrate how the tools can be used together to more deeply understand tumor biology. Together, these tools enable researchers to dynamically query complex genomics data and integrate external information, enabling and enhancing PCAWG data interpretation. More information on these tools and their capabilities is available from The PCAWG Data Portals and Visualizations Page (http://docs.icgc.org/pcawg).
]]></description>
<dc:creator>Goldman, M</dc:creator>
<dc:creator>Zhang, J</dc:creator>
<dc:creator>Fonseca, N</dc:creator>
<dc:creator>Xiang, Q</dc:creator>
<dc:creator>Craft, B</dc:creator>
<dc:creator>Piñeiro-Yáñez, E</dc:creator>
<dc:creator>O'Connor, B</dc:creator>
<dc:creator>Bazant, W</dc:creator>
<dc:creator>Barrera, E</dc:creator>
<dc:creator>Muñoz, A</dc:creator>
<dc:creator>Petryszak, R</dc:creator>
<dc:creator>Füllgrabe, A</dc:creator>
<dc:creator>Al-Shahrour, F</dc:creator>
<dc:creator>Keays, M</dc:creator>
<dc:creator>Haussler, D</dc:creator>
<dc:creator>Weinstein, J</dc:creator>
<dc:creator>Huber, W</dc:creator>
<dc:creator>Valencia, A</dc:creator>
<dc:creator>Papatheodorou, I</dc:creator>
<dc:creator>Zhu, J</dc:creator>
<dc:creator>Ferreti, V</dc:creator>
<dc:creator>Vazquez, M</dc:creator>
<dc:date>2017-07-14</dc:date>
<dc:identifier>doi:10.1101/163907</dc:identifier>
<dc:title><![CDATA[Online resources for PCAWG data exploration, visualization, and discovery]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/380238v1?rss=1">
<title>
<![CDATA[
Studying the fate of tumor extracellular vesicles at high spatio-temporal resolution using the zebrafish embryo 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/380238v1?rss=1"
</link>
<description><![CDATA[
Tumor extracellular vesicles (tumor EVs) mediate the communication between tumor and stromal cells mostly to the benefit of tumor progression. Notably, tumor EVs have been reported to travel in the blood circulation, reach specific distant organs and locally modify the microenvironment. However, visualizing these events in vivo still faces major hurdles. Here, we show a new method for tracking individual circulating tumor EVs in a living organism: we combine novel, bright and specific fluorescent membrane probes, MemBright, with the transparent zebrafish embryo as an animal model. We provide the first description of tumor EVs hemodynamic behavior and document their arrest before internalization. Using transgenic lines, we show that circulating tumor EVs are uptaken by endothelial cells and blood patrolling macrophages, but not by leukocytes, and subsequently stored in acidic degradative compartments. Finally, we prove that the MemBright can be used to follow naturally released tumor EVs in vivo. Overall, our study demonstrates the usefulness and prospects of zebrafish embryo to track tumor EVs in vivo.nnHighlightsO_LIMemBright, a new family of membrane probes, allows for bright and specific staining of EVsnC_LIO_LIZebrafish melanoma EVs are very similar to human and mouse melanoma EVs in morphology and protein contentnC_LIO_LIThe zebrafish embryo is an adapted model to precisely track tumor EVs dynamics and fate in a living organism from light to electron microscopynC_LIO_LICirculating tumor EVs are rapidly uptaken by endothelial cells and patrolling macrophagesnC_LIO_LICorrelated light and electron microscopy can be used in zebrafish to identify cells and compartments uptaking tumor EVsnC_LInnBlurbDispersion of tumor extracellular vesicles (EVs) throughout the body promotes tumor progression. However the behavior of tumor EVs in body fluids remains mysterious due to their small size and the absence of adapted animal model. Here we show that the zebrafish embryo can be used to track circulating tumor EVs in vivo and provide the first high-resolution description of their dissemination and uptake.
]]></description>
<dc:creator>Hyenne, V.</dc:creator>
<dc:creator>Ghoroghi, S.</dc:creator>
<dc:creator>Collot, M.</dc:creator>
<dc:creator>Harlepp, S.</dc:creator>
<dc:creator>Bauer, J.</dc:creator>
<dc:creator>Mercier, L.</dc:creator>
<dc:creator>Busnelli, I.</dc:creator>
<dc:creator>Lefebvre, O.</dc:creator>
<dc:creator>Fekonja, N.</dc:creator>
<dc:creator>Machado, P.</dc:creator>
<dc:creator>Bons, J.</dc:creator>
<dc:creator>Delalande, F.</dc:creator>
<dc:creator>Amor, A. I.</dc:creator>
<dc:creator>Silva, S. G.</dc:creator>
<dc:creator>Verweij, F. J.</dc:creator>
<dc:creator>Van Niel, G.</dc:creator>
<dc:creator>Schwab, Y.</dc:creator>
<dc:creator>Peinado, H.</dc:creator>
<dc:creator>Carapito, C.</dc:creator>
<dc:creator>Klymchenko, A. S.</dc:creator>
<dc:creator>Goetz, J. G.</dc:creator>
<dc:date>2018-07-30</dc:date>
<dc:identifier>doi:10.1101/380238</dc:identifier>
<dc:title><![CDATA[Studying the fate of tumor extracellular vesicles at high spatio-temporal resolution using the zebrafish embryo]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/377390v1?rss=1">
<title>
<![CDATA[
The USTC complex co-opts an ancient machinery to drive piRNA transcription in C. elegans 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/377390v1?rss=1"
</link>
<description><![CDATA[
Piwi-interacting RNAs (piRNAs) engage Piwi proteins to suppress transposons and non-self nucleic acids, maintain genome integrity, and are essential for fertility in a variety of organisms. In C. elegans most piRNA precursors are transcribed from two genomic clusters that contain thousands of individual piRNA transcription units. While a few genes have been shown to be required for piRNA biogenesis the mechanism of piRNA transcription remains elusive. Here we used functional proteomics approaches to identify an upstream sequence transcription complex (USTC) that is essential for piRNA biogenesis. The USTC complex contains PRDE-1, TOFU-4, TOFU-5 and SNPC-4. The USTC complex form a unique piRNA foci in germline nuclei and coat the piRNA cluster genomic loci. USTC factors associate with the Ruby motif just upstream of type I piRNA genes. USTC factors are also mutually dependent for binding to the piRNA clusters and to form the piRNA foci. Interestingly, USTC components bind differentially to piRNAs in the clusters and other non-coding RNA genes. These results reveal USTC as a striking example of the repurposing of a general transcription factor complex to aid in genome defence against transposons.
]]></description>
<dc:creator>Weng, C.</dc:creator>
<dc:creator>Kosalka, A.</dc:creator>
<dc:creator>Berkyurek, A. C.</dc:creator>
<dc:creator>Stempor, P.</dc:creator>
<dc:creator>Feng, X.</dc:creator>
<dc:creator>Mao, H.</dc:creator>
<dc:creator>Zeng, C.</dc:creator>
<dc:creator>Li, W.-J.</dc:creator>
<dc:creator>Yan, Y.-H.</dc:creator>
<dc:creator>Dong, M.-Q.</dc:creator>
<dc:creator>Zuliani, C.</dc:creator>
<dc:creator>Barabas, O.</dc:creator>
<dc:creator>Ahringer, J.</dc:creator>
<dc:creator>Guang, S.</dc:creator>
<dc:creator>Miska, E.</dc:creator>
<dc:date>2018-07-25</dc:date>
<dc:identifier>doi:10.1101/377390</dc:identifier>
<dc:title><![CDATA[The USTC complex co-opts an ancient machinery to drive piRNA transcription in C. elegans]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/377358v1?rss=1">
<title>
<![CDATA[
Subdivision of ancestral scale genetic program underlies origin of feathers and avian scutate scales 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/377358v1?rss=1"
</link>
<description><![CDATA[
Birds and other reptiles possess a diversity of feather and scale-like skin appendages. Feathers are commonly assumed to have originated from ancestral scales in theropod dinosaurs. However, most birds also have scaled feet, indicating birds evolved the capacity to grow both ancestral and derived morphologies. This suggests a more complex evolutionary history than a simple linear transition between feathers and scales. We set out to investigate the evolution of feathers via the comparison of transcriptomes assembled from diverse skin appendages in chicken, emu, and alligator. Our data reveal that feathers and the overlapping  scutate scales of birds share more similar gene expression to each other, and to two types of alligator scales, than they do to the tuberculate  reticulate scales on bird footpads. Accordingly, we propose a history of skin appendage diversification, in which feathers and bird scutate scales arose from ancestral archosaur body scales, whereas reticulate scales arose earlier in tetrapod evolution. We also show that many "feather-specific genes" are also expressed in alligator scales. In-situ hybridization results in feather buds suggest that these genes represent ancestral scale genes that acquired novel roles in feather morphogenesis and were repressed in bird scales. Our findings suggest that the differential reuse, in feathers, and suppression, in bird scales, of genes ancestrally expressed in archosaur scales has been a key factor in the origin of feathers - and may represent an important mechanism for the origin of evolutionary novelties.
]]></description>
<dc:creator>Musser, J. M.</dc:creator>
<dc:creator>Wagner, G. P.</dc:creator>
<dc:creator>Liang, C.</dc:creator>
<dc:creator>Stabile, F. A.</dc:creator>
<dc:creator>Cloutier, A.</dc:creator>
<dc:creator>Baker, A. J.</dc:creator>
<dc:creator>Prum, R. O.</dc:creator>
<dc:date>2018-07-25</dc:date>
<dc:identifier>doi:10.1101/377358</dc:identifier>
<dc:title><![CDATA[Subdivision of ancestral scale genetic program underlies origin of feathers and avian scutate scales]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/336008v1?rss=1">
<title>
<![CDATA[
TET2 binding to enhancers facilitates transcription factor recruitment in hematopoietic cells 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/336008v1?rss=1"
</link>
<description><![CDATA[
The epigenetic regulator TET2 is frequently mutated in hematological diseases. Mutations have been shown to arise in hematopoietic stem cells early in disease development, lead to altered DNA methylation landscapes and to an increased risk of hematopoietic malignancy. Here, we show by genome-wide mapping of TET2 binding sites in different cell types that TET2 localizes to regions of open chromatin and cell-type specific enhancers. We find that deletion of Tet2 in native hematopoiesis as well as fully transformed Acute Myeloid Leukemia (AML) results in changes in transcription factor (TF) activity within these regions, and we demonstrate that loss of TET2 leads to enzymatic activity-dependent attenuation of chromatin binding of the hematopoietic TF CDX4. Together, these findings demonstrate that TET2 activity shapes the local chromatin environment at enhancers to facilitate TF binding and provide a compelling example of how epigenetic dysregulation can affect gene expression patterns and drive disease development.
]]></description>
<dc:creator>Rasmussen, K.</dc:creator>
<dc:creator>Berest, I.</dc:creator>
<dc:creator>Kessler, S.</dc:creator>
<dc:creator>Nishimura, K.</dc:creator>
<dc:creator>Simon-Carrasco, L.</dc:creator>
<dc:creator>Vassilou, G. S.</dc:creator>
<dc:creator>Pedersen, M. T.</dc:creator>
<dc:creator>Christensen, J.</dc:creator>
<dc:creator>Zaugg, J.</dc:creator>
<dc:creator>Helin, K.</dc:creator>
<dc:date>2018-05-31</dc:date>
<dc:identifier>doi:10.1101/336008</dc:identifier>
<dc:title><![CDATA[TET2 binding to enhancers facilitates transcription factor recruitment in hematopoietic cells]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/095380v1?rss=1">
<title>
<![CDATA[
Drug repurposing for ageing research using model organisms 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/095380v1?rss=1"
</link>
<description><![CDATA[
Many increasingly prevalent diseases share a common risk factor: age. However, little is known about pharmaceutical interventions against ageing, despite many genes and pathways shown to be important in the ageing process and numerous studies demonstrating that genetic interventions can lead to a healthier ageing phenotype. An important challenge is to assess the potential to repurpose existing drugs for initial testing on model organisms, where such experiments are possible. To this end, we present a new approach to rank drug-like compounds with known mammalian targets according to their likelihood to modulate ageing in the invertebrates C. elegans and Drosophila. Our approach combines information on genetic effects on ageing, orthology relationships and sequence conservation, 3D protein structures, drug binding and bioavailability. Overall, we rank 743 different drug-like compounds for their likelihood to modulate ageing. We provide various lines of evidence for the successful enrichment of our ranking for compounds modulating ageing, despite sparse public data suitable for validation. The top ranked compounds are thus prime candidates for in vivo testing of their effects on lifespan in C. elegans or Drosophila. As such, these compounds are promising as research tools and ultimately a step towards identifying drugs for a healthier human ageing.
]]></description>
<dc:creator>Ziehm, M.</dc:creator>
<dc:creator>Kaur, S.</dc:creator>
<dc:creator>Ivanov, D. K.</dc:creator>
<dc:creator>Ballester, P. J.</dc:creator>
<dc:creator>Marcus, D.</dc:creator>
<dc:creator>Partridge, L.</dc:creator>
<dc:creator>Thornton, J. M.</dc:creator>
<dc:date>2016-12-22</dc:date>
<dc:identifier>doi:10.1101/095380</dc:identifier>
<dc:title><![CDATA[Drug repurposing for ageing research using model organisms]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-12-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/330654v1?rss=1">
<title>
<![CDATA[
Condensin controls cellular RNA levels through the accurate segregation of chromosomes instead of directly regulating transcription 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/330654v1?rss=1"
</link>
<description><![CDATA[
Condensins are genome organisers that shape chromosomes and promote their accurate transmission. Several studies have also implicated condensins in gene expression, although the mechanisms have remained enigmatic. Here, we report on the role of condensin in gene expression in fission and budding yeasts. In contrast to previous studies, we provide compelling evidence that condensin plays no direct role in the maintenance of the transcriptome, neither during interphase nor during mitosis. We further show that the changes in gene expression in post-mitotic fission yeast cells that result from condensin inactivation are largely a consequence of chromosome missegregation during anaphase, which notably depletes the RNA-exosome from daughter cells. Crucially, preventing karyotype abnormalities in daughter cells restores a normal transcriptome despite condensin inactivation. Thus, chromosome instability, rather than a direct role of condensin in the transcription process, changes gene expression. This knowledge challenges the concept of gene regulation by canonical condensin complexes.
]]></description>
<dc:creator>Hocquet, C.</dc:creator>
<dc:creator>Robellet, X.</dc:creator>
<dc:creator>Modolo, L.</dc:creator>
<dc:creator>Sun, X.-M.</dc:creator>
<dc:creator>Burny, C.</dc:creator>
<dc:creator>Cuylen-Haering, S.</dc:creator>
<dc:creator>Toselli, E.</dc:creator>
<dc:creator>Clauder-Münster, S.</dc:creator>
<dc:creator>Steinmetz, L.</dc:creator>
<dc:creator>Haering, C. H.</dc:creator>
<dc:creator>Marguerat, S.</dc:creator>
<dc:creator>Bernard, P.</dc:creator>
<dc:date>2018-05-25</dc:date>
<dc:identifier>doi:10.1101/330654</dc:identifier>
<dc:title><![CDATA[Condensin controls cellular RNA levels through the accurate segregation of chromosomes instead of directly regulating transcription]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/097196v1?rss=1">
<title>
<![CDATA[
A Data Citation Roadmap for Scholarly Data Repositories 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/097196v1?rss=1"
</link>
<description><![CDATA[
This article presents a practical roadmap for scholarly data repositories to implement data citation in accordance with the Joint Declaration of Data Citation Principles, a synopsis and harmonization of the recommendations of major science policy bodies. The roadmap was developed by the Repositories Expert Group, as part of the Data Citation Implementation Pilot (DCIP) project, an initiative of FORCE11.org and the NIH BioCADDIE (https://biocaddie.org) program. The roadmap makes 11 specific recommendations, grouped into three phases of implementation: a) required steps needed to support the Joint Declaration of Data Citation Principles, b) recommended steps that facilitate article/data publication workflows, and c) optional steps that further improve data citation support provided by data repositories.
]]></description>
<dc:creator>Fenner, M.</dc:creator>
<dc:creator>Crosas, M.</dc:creator>
<dc:creator>Grethe, J.</dc:creator>
<dc:creator>Kennedy, D.</dc:creator>
<dc:creator>Hermjakob, H.</dc:creator>
<dc:creator>Rocca-Serra, P.</dc:creator>
<dc:creator>Berjon, R.</dc:creator>
<dc:creator>Karcher, S.</dc:creator>
<dc:creator>Martone, M.</dc:creator>
<dc:creator>Clark, T.</dc:creator>
<dc:date>2016-12-28</dc:date>
<dc:identifier>doi:10.1101/097196</dc:identifier>
<dc:title><![CDATA[A Data Citation Roadmap for Scholarly Data Repositories]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-12-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/225441v1?rss=1">
<title>
<![CDATA[
Assessing the Gene Regulatory Landscape in 1,188 Human Tumors 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/225441v1?rss=1"
</link>
<description><![CDATA[
Cancer is characterised by somatic genetic variation, but the effect of the majority of non-coding somatic variants and the interface with the germline genome are still unknown. We analysed the whole genome and RNA-Seq data from 1,188 human cancer patients as provided by the Pan-cancer Analysis of Whole Genomes (PCAWG) project to map cis expression quantitative trait loci of somatic and germline variation and to uncover the causes of allele-specific expression patterns in human cancers. The availability of the first large-scale dataset with both whole genome and gene expression data enabled us to uncover the effects of the non-coding variation on cancer. In addition to confirming known regulatory effects, we identified novel associations between somatic variation and expression dysregulation, in particular in distal regulatory elements. Finally, we uncovered links between somatic mutational signatures and gene expression changes, including TERT and LMO2, and we explained the inherited risk factors in APOBEC-related mutational processes. This work represents the first large-scale assessment of the effects of both germline and somatic genetic variation on gene expression in cancer and creates a valuable resource cataloguing these effects.
]]></description>
<dc:creator>Calabrese, C.</dc:creator>
<dc:creator>Lehmann, K.-V.</dc:creator>
<dc:creator>Urban, L.</dc:creator>
<dc:creator>Liu, F.</dc:creator>
<dc:creator>Erkek, S.</dc:creator>
<dc:creator>Fonseca, N.</dc:creator>
<dc:creator>Kahles, A.</dc:creator>
<dc:creator>Kilpinen-Barrett, L. H.</dc:creator>
<dc:creator>Markowski, J.</dc:creator>
<dc:creator>PCAWG-3,</dc:creator>
<dc:creator>Waszak, S.</dc:creator>
<dc:creator>Korbel, J.</dc:creator>
<dc:creator>Zhang, Z.</dc:creator>
<dc:creator>Brazma, A.</dc:creator>
<dc:creator>Raetsch, G.</dc:creator>
<dc:creator>Schwarz, R.</dc:creator>
<dc:creator>Stegle, O.</dc:creator>
<dc:date>2017-11-29</dc:date>
<dc:identifier>doi:10.1101/225441</dc:identifier>
<dc:title><![CDATA[Assessing the Gene Regulatory Landscape in 1,188 Human Tumors]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/347625v1?rss=1">
<title>
<![CDATA[
Understanding trivial challenges of microbial genomics: An assembly example 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/347625v1?rss=1"
</link>
<description><![CDATA[
The perceived "simplicity" of bacterial genomics (these genomes are small and easy to assemble) feeds the decentralized state of the field where computational analysis standards have been slow to evolve. This situation has a historical explanation. In cases of human, mouse, fly, worm and other model organisms there have been large sustained multinational genome sequencing efforts and analysis consortia such as the 1,000 genomes, ENCODE, modENCODE, GTEx and others. These resulted in development and proliferation of common tools, workflows, and data standards. This is not the case in microbiology. After the development of highly parallel sequencing methodologies in mid-2000s bacterial genomes no longer required initiatives of such scale. The flipside of this is the extreme heterogeneity of approaches to many well established microbial genomic analysis problems such as genome assembly. While competition amongst different methods is good, we argue that the quality of data analyses will improve if cutting edge tools are more accessible and microbiologists become more computationally savvy. Here we use genome assembly as an example to highlight current challenges and to provide a possible solution.
]]></description>
<dc:creator>Lariviere, D.</dc:creator>
<dc:creator>Mei, H.</dc:creator>
<dc:creator>Freeberg, M.</dc:creator>
<dc:creator>Taylor, J.</dc:creator>
<dc:creator>Nekrutenko, A.</dc:creator>
<dc:date>2018-06-14</dc:date>
<dc:identifier>doi:10.1101/347625</dc:identifier>
<dc:title><![CDATA[Understanding trivial challenges of microbial genomics: An assembly example]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/303842v1?rss=1">
<title>
<![CDATA[
Highly dynamic chromatin interactions drive neurogenesis through gene regulatory networks 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/303842v1?rss=1"
</link>
<description><![CDATA[
Lineage commitment is a fundamental process that enables the morphogenesis of multicellular organisms from a single pluripotent cell. While many genes involved in the commitment to specific lineages are known, the logic of their joint action is incompletely understood, and predicting the effects of genetic perturbations on lineage commitment is still challenging. Here, we devised a gene regulatory network analysis approach, GRN-loop, to identify key cis-regulatory DNA elements and transcription factors that drive lineage commitment. GRN-loop is based on signal propagation and combines transcription factor binding data with the temporal profiles of gene expression, chromatin state and 3D chromosomal architecture. Applying GRN-loop to a model of morphogen-induced early neural lineage commitment, we discovered a set of driver transcription factors and enhancers, some of them validated in recent data and others hitherto unknown. Our work provides the basis for an integrated understanding of neural lineage commitment, and demonstrates the potential of gene regulatory network analyses informed by 3D chromatin architecture to uncover the key genes and regulatory elements driving developmental processes.
]]></description>
<dc:creator>Malysheva, V.</dc:creator>
<dc:creator>Mendoza-Parra, M. A.</dc:creator>
<dc:creator>Blum, M.</dc:creator>
<dc:creator>Gronemeyer, H.</dc:creator>
<dc:date>2018-04-18</dc:date>
<dc:identifier>doi:10.1101/303842</dc:identifier>
<dc:title><![CDATA[Highly dynamic chromatin interactions drive neurogenesis through gene regulatory networks]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/237214v1?rss=1">
<title>
<![CDATA[
Robust expression variability testing reveals heterogeneous T cell responses 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/237214v1?rss=1"
</link>
<description><![CDATA[
Cell-to-cell transcriptional variability in otherwise homogeneous cell populations plays a crucial role in tissue function and development. Single-cell RNA sequencing can characterise this variability in a transcriptome-wide manner. However, technical variation and the confounding between variability and mean expression estimates hinders meaningful comparison of expression variability between cell populations. To address this problem, we introduce a novel analysis approach that extends the BASiCS statistical framework to derive a residual measure of variability that is not confounded by mean expression. Moreover, we introduce a new and robust procedure for quantifying technical noise in experiments where technical spike-in molecules are not available. We illustrate how our method provides biological insight into the dynamics of cell-to-cell expression variability, highlighting a synchronisation of the translational machinery in immune cells upon activation. Additionally, our approach identifies new patterns of variability across CD4+ T cell differentiation.
]]></description>
<dc:creator>Eling, N.</dc:creator>
<dc:creator>Richard, A. C.</dc:creator>
<dc:creator>Richardson, S.</dc:creator>
<dc:creator>Marioni, J. C.</dc:creator>
<dc:creator>Vallejos, C. A.</dc:creator>
<dc:date>2017-12-21</dc:date>
<dc:identifier>doi:10.1101/237214</dc:identifier>
<dc:title><![CDATA[Robust expression variability testing reveals heterogeneous T cell responses]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/162784v1?rss=1">
<title>
<![CDATA[
Pan-cancer analysis of whole genomes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/162784v1?rss=1"
</link>
<description><![CDATA[
We report the integrative analysis of more than 2,600 whole cancer genomes and their matching normal tissues across 39 distinct tumour types. By studying whole genomes we have been able to catalogue non-coding cancer driver events, study patterns of structural variation, infer tumour evolution, probe the interactions among variants in the germline genome, the tumour genome and the transcriptome, and derive an understanding of how coding and non-coding variations together contribute to driving individual patient's tumours. This work represents the most comprehensive look at cancer whole genomes to date. NOTE TO READERS: This is an incomplete draft of the marker paper for the Pan-Cancer Analysis of Whole Genomes Project, and is intended to provide the background information for a series of in-depth papers that will be posted to BioRixv during the summer of 2017.
]]></description>
<dc:creator>Campbell, P. J.</dc:creator>
<dc:creator>Getz, G.</dc:creator>
<dc:creator>Stuart, J. M.</dc:creator>
<dc:creator>Korbel, J. O.</dc:creator>
<dc:creator>Stein, L. D.</dc:creator>
<dc:creator>- ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Net,</dc:creator>
<dc:date>2017-07-12</dc:date>
<dc:identifier>doi:10.1101/162784</dc:identifier>
<dc:title><![CDATA[Pan-cancer analysis of whole genomes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/425041v1?rss=1">
<title>
<![CDATA[
Tunneling nanotubes contribute to the stroma-mediated imatinib resistance of leukemic cells 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/425041v1?rss=1"
</link>
<description><![CDATA[
Intercellular communication within the bone marrow niche significantly influences leukemogenesis and the sensitivity of leukemic cells to therapy. Tunneling nanotubes (TNTs) are a novel mode of intercellular cross-talk. They are long, thin membranous protrusions that enable the direct transfer of various cargo between cells. Here we show that TNTs are formed between leukemic and bone marrow stromal cells. Fluorescence confocal microscopy with 3D reconstructions, correlative light-electron microscopy and electron tomography provided evidence that TNTs transfer cellular vesicles between cells. The quantitative analysis demonstrated that the stromal cells stimulate TNT-mediated vesicle transfer towards leukemic cells. Transfer of vesicular cargo from stromal cells correlated with increased resistance to anti-leukemic treatment. Moreover, specific sets of proteins with a potential role in survival and the drug response were transferred within these vesicles. Altogether, we found that TNTs are involved in the leukemia-stroma cross-talk and the stroma-mediated cytoprotection of leukemic cells. Our findings implicate TNT connections as a possible target for therapeutic interventions within the leukemia microenvironment to attenuate stroma-conferred protection.
]]></description>
<dc:creator>Kolba, M. D.</dc:creator>
<dc:creator>Dudka, W.</dc:creator>
<dc:creator>Zareba-Koziol, M.</dc:creator>
<dc:creator>Kominek, A.</dc:creator>
<dc:creator>Ronchi, P.</dc:creator>
<dc:creator>Turos, L.</dc:creator>
<dc:creator>Wlodarczyk, J.</dc:creator>
<dc:creator>Schwab, Y.</dc:creator>
<dc:creator>Cysewski, D.</dc:creator>
<dc:creator>Srpan, K.</dc:creator>
<dc:creator>Davis, D. M.</dc:creator>
<dc:creator>Piwocka, K.</dc:creator>
<dc:date>2018-09-25</dc:date>
<dc:identifier>doi:10.1101/425041</dc:identifier>
<dc:title><![CDATA[Tunneling nanotubes contribute to the stroma-mediated imatinib resistance of leukemic cells]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/289363v1?rss=1">
<title>
<![CDATA[
MDM4 is an essential disease driver targeted by 1q gain in Burkitt lymphoma 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/289363v1?rss=1"
</link>
<description><![CDATA[
Oncogenic MYC activation promotes cellular proliferation in Burkitt lymphoma (BL), but also induces cell cycle arrest and apoptosis mediated by TP53, a tumor suppressor gene that is mutated in 40% of BL cases. To identify therapeutic targets in BL, we investigated molecular dependencies in BL cell lines using RNAi-based, loss-of-function screening. By integrating genotypic and RNAi data, we identified a number of genotype-specific dependencies including the dependence of TCF3/ID3 mutant cell lines on TCF3 and of MYD88 mutant cell lines on TLR signaling. TP53 wild-type (TP53wt) BL were dependent on MDM4, a negative regulator of TP53. In BL cell lines, MDM4 knockdown induced cell cycle arrest and decreased tumor growth in a xenograft model in a p53-dependent manner, while small molecule inhibition of the MDM4-p53 interaction restored p53 activity resulting in cell cycle arrest. Consistent with the pathogenic effect of MDM4 upregulation in BL, we found that TP53wt BL samples were enriched for gain of chromosome 1q which includes the MDM4 locus. 1q gain was also enriched across non-BL cancer cell lines (n=789) without TP53 mutation (23% in TP53wt and 12% in TP53mut, p<0.001). In a set of 216 cell lines representing 19 cancer entities from the Achilles project, MDM4 was the strongest genetic dependency in TP53wt cell lines (p<0.001).nnOur findings show that in TP53wt BL, MDM4-mediated inhibition of p53 is a mechanism to evade cell cycle arrest. The data highlight the critical role of p53 as a tumor suppressor in BL, and identifies MDM4 as a key functional target of 1q gain in a wide range of cancers, which is therapeutically targetable.
]]></description>
<dc:creator>Huellein, J.</dc:creator>
<dc:creator>Slabicki, M.</dc:creator>
<dc:creator>Rosolowski, M.</dc:creator>
<dc:creator>Jethwa, A.</dc:creator>
<dc:creator>Habringer, S.</dc:creator>
<dc:creator>Tomska, K.</dc:creator>
<dc:creator>Kurilov, R.</dc:creator>
<dc:creator>Lu, J.</dc:creator>
<dc:creator>Scheinost, S.</dc:creator>
<dc:creator>Wagener, R.</dc:creator>
<dc:creator>Huang, Z.</dc:creator>
<dc:creator>Lukas, M.</dc:creator>
<dc:creator>Yavorska, O.</dc:creator>
<dc:creator>Helferich, H.</dc:creator>
<dc:creator>Scholtysik, R.</dc:creator>
<dc:creator>Bonneau, K.</dc:creator>
<dc:creator>Tedesco, D.</dc:creator>
<dc:creator>Kueppers, R.</dc:creator>
<dc:creator>Klapper, W.</dc:creator>
<dc:creator>Pott, C.</dc:creator>
<dc:creator>Stilgenbauer, S.</dc:creator>
<dc:creator>Burkhardt, B.</dc:creator>
<dc:creator>Loeffler, M.</dc:creator>
<dc:creator>Truemper, L.</dc:creator>
<dc:creator>Hummel, M.</dc:creator>
<dc:creator>Brors, B.</dc:creator>
<dc:creator>Zapatka, M.</dc:creator>
<dc:creator>Siebert, R.</dc:creator>
<dc:creator>Keller, U.</dc:creator>
<dc:creator>Huber, W.</dc:creator>
<dc:creator>Kreuz, M.</dc:creator>
<dc:creator>Zenz, T.</dc:creator>
<dc:creator>MMML consortium,</dc:creator>
<dc:date>2018-04-09</dc:date>
<dc:identifier>doi:10.1101/289363</dc:identifier>
<dc:title><![CDATA[MDM4 is an essential disease driver targeted by 1q gain in Burkitt lymphoma]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/246256v1?rss=1">
<title>
<![CDATA[
Quantification of gene expression patterns to reveal the origins of abnormal morphogenesis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/246256v1?rss=1"
</link>
<description><![CDATA[
The earliest developmental origins of dysmorphologies are poorly understood in many congenital diseases. They often remain elusive because the first signs of genetic misregulation may initiate as subtle changes in gene expression, which can be obscured later in development due to secondary phenotypic effects. We here develop a method to trace back the origins of phenotypic abnormalities by accurately quantifying the 3D spatial distribution of gene expression domains in developing organs. By applying geometric morphometrics to 3D gene expression data obtained by Optical Projection Tomography, our approach is sensitive enough to find regulatory abnormalities never previously detected. We identified subtle but significant differences in gene expression of a downstream target of the Fgfr2 mutation associated with Apert syndrome. Challenging previous reports, we demonstrate that Apert syndrome mouse models can further our understanding of limb defects in the human condition. Our method can be applied to other organ systems and models to investigate the etiology of malformations.
]]></description>
<dc:creator>Martinez-Abadias, N.</dc:creator>
<dc:creator>Mateu Estivill, R.</dc:creator>
<dc:creator>Sastre Tomas, J.</dc:creator>
<dc:creator>Motch Perrine, S.</dc:creator>
<dc:creator>Yoon, M.</dc:creator>
<dc:creator>Robert-Moreno, A.</dc:creator>
<dc:creator>Swoger, J.</dc:creator>
<dc:creator>Russo, L.</dc:creator>
<dc:creator>Kawasaki, K.</dc:creator>
<dc:creator>Richtsmeier, J.</dc:creator>
<dc:creator>Sharpe, J.</dc:creator>
<dc:date>2018-01-11</dc:date>
<dc:identifier>doi:10.1101/246256</dc:identifier>
<dc:title><![CDATA[Quantification of gene expression patterns to reveal the origins of abnormal morphogenesis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/413047v1?rss=1">
<title>
<![CDATA[
Cardelino: Integrating whole exomes and single-cell transcriptomes to reveal phenotypic impact of somatic variants 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/413047v1?rss=1"
</link>
<description><![CDATA[
Decoding the clonal substructures of somatic tissues sheds light on cell growth, development and differentiation in health, ageing and disease. DNA-sequencing, either using bulk or using single-cell assays, has enabled the reconstruction of clonal trees from frequency and co-occurrence patterns of somatic variants. However, approaches to systematically characterize phenotypic and functional variations between individual clones are not established. Here we present cardelino (https://github.com/PMBio/cardelino), a computational method for inferring the clone of origin of individual cells that have been assayed using single-cell RNA-seq (scRNA-seq). After validating our model using simulations, we apply cardelino to matched scRNA-seq and exome sequencing data from 32 human dermal fibroblast lines, identifying hundreds of differentially expressed genes between cells from different somatic clones. These genes are frequently enriched for cell cycle and proliferation pathways, indicating a key role for cell division genes in non-neutral somatic evolution.nnKey findingsO_LIA novel approach for integrating DNA-seq and single-cell RNA-seq data to reconstruct clonal substructure for single-cell transcriptomes.nC_LIO_LIEvidence for non-neutral evolution of clonal populations in human fibroblasts.nC_LIO_LIProliferation and cell cycle pathways are commonly distorted in mutated clonal populations.nC_LI
]]></description>
<dc:creator>McCarthy, D. J.</dc:creator>
<dc:creator>Rostom, R.</dc:creator>
<dc:creator>Huang, Y.</dc:creator>
<dc:creator>Kunz, D. J.</dc:creator>
<dc:creator>Danecek, P.</dc:creator>
<dc:creator>Bonder, M. J.</dc:creator>
<dc:creator>Hagai, T.</dc:creator>
<dc:creator>HipSci Consortium,</dc:creator>
<dc:creator>Wang, W.</dc:creator>
<dc:creator>Gaffney, D. J.</dc:creator>
<dc:creator>Simons, B. D.</dc:creator>
<dc:creator>Stegle, O.</dc:creator>
<dc:creator>Teichmann, S. A.</dc:creator>
<dc:date>2018-09-10</dc:date>
<dc:identifier>doi:10.1101/413047</dc:identifier>
<dc:title><![CDATA[Cardelino: Integrating whole exomes and single-cell transcriptomes to reveal phenotypic impact of somatic variants]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/271510v1?rss=1">
<title>
<![CDATA[
CONSTRUCTION OF WHOLE GENOMES FROM SCAFFOLDS USING SINGLE CELL STRAND-SEQ DATA 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/271510v1?rss=1"
</link>
<description><![CDATA[
Accurate reference genome sequences provide the foundation for modern molecular biology and genomics as the interpretation of sequence data to study evolution, gene expression and epigenetics depends heavily on the quality of the genome assembly used for its alignment. Correctly organising sequenced fragments such as contigs and scaffolds in relation to each other is a critical and often challenging step in the construction of robust genome references. We previously identified misoriented regions in the mouse and human reference assemblies using Strand-seq, a single cell sequencing technique that preserves DNA directionality1, 2. Here we demonstrate the ability of Strand-seq to build and correct full-length chromosomes, by identifying which scaffolds belong to the same chromosome and determining their correct order and orientation, without the need for overlapping sequences. We demonstrate that Strand-seq exquisitely maps assembly fragments into large related groups and chromosome-sized clusters without using new assembly data. Using template strand inheritance as a bi-allelic marker, we employ genetic mapping principles to cluster scaffolds that are derived from the same chromosome and order them within the chromosome based solely on directionality of DNA strand inheritance. We prove the utility of our approach by generating improved genome assemblies for several model organisms including the ferret, pig, Xenopus, zebrafish, Tasmanian devil and the Guinea pig.
]]></description>
<dc:creator>Hills, M.</dc:creator>
<dc:creator>Falconer, E.</dc:creator>
<dc:creator>O'Neil, K.</dc:creator>
<dc:creator>Sanders, A.</dc:creator>
<dc:creator>Howe, K.</dc:creator>
<dc:creator>Guryev, V.</dc:creator>
<dc:creator>Lansdorp, P. M.</dc:creator>
<dc:date>2018-02-26</dc:date>
<dc:identifier>doi:10.1101/271510</dc:identifier>
<dc:title><![CDATA[CONSTRUCTION OF WHOLE GENOMES FROM SCAFFOLDS USING SINGLE CELL STRAND-SEQ DATA]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/149138v1?rss=1">
<title>
<![CDATA[
Real-time detection of condensin-driven DNA compaction reveals a multistep binding mechanism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/149138v1?rss=1"
</link>
<description><![CDATA[
Condensin, a conserved member of the SMC protein family of ring-shaped multi-subunit protein complexes, is essential for structuring and compacting chromosomes. Despite its key role, its molecular mechanism has remained largely unknown. Here, we employ single-molecule magnetic tweezers to measure, in real-time, the compaction of individual DNA molecules by the budding yeast condensin complex. We show that compaction proceeds in large (~200nm) steps, driving DNA molecules into a fully condensed state against forces of up to 2pN. Compaction can be reversed by applying high forces or adding buffer of high ionic strength. While condensin can stably bind DNA in the absence of ATP, ATP hydrolysis by the SMC subunits is required for rendering the association salt-insensitive and for subsequent compaction. Our results indicate that the condensin reaction cycle involves two distinct steps, where condensin first binds DNA through electrostatic interactions before using ATP hydrolysis to encircle the DNA topologically within its ring structure, which initiates DNA compaction. The finding that both binding modes are essential for its DNA compaction activity has important implications for understanding the mechanism of chromosome compaction.
]]></description>
<dc:creator>Eeftens, J. M.</dc:creator>
<dc:creator>Bisht, S.</dc:creator>
<dc:creator>Kerssemakers, J.</dc:creator>
<dc:creator>Haering, C.</dc:creator>
<dc:creator>Dekker, C.</dc:creator>
<dc:date>2017-06-15</dc:date>
<dc:identifier>doi:10.1101/149138</dc:identifier>
<dc:title><![CDATA[Real-time detection of condensin-driven DNA compaction reveals a multistep binding mechanism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/149716v1?rss=1">
<title>
<![CDATA[
Post-translational regulation of metabolism in fumarate hydratase deficient cancer cells 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/149716v1?rss=1"
</link>
<description><![CDATA[
Deregulated signal transduction pathways and energy metabolism are hallmarks of cancer and both play a fundamental role in the process of tumorigenesis. While it is increasingly recognised that signalling and metabolism are highly interconnected, the underpinning mechanisms of their co-regulation are still largely unknown. Here we designed and acquired proteomics, phosphoproteomics, and metabolomics experiments in fumarate hydratase (FH) deficient cells and developed a computational modelling approach to identify putative regulatory phosphorylation-sites of metabolic enzymes. We identified previously reported functionally relevant phosphosites and potentially novel regulatory residues in enzymes of the central carbon metabolism. In particular, we show that pyruvate dehydrogenase (PDHA1) enzymatic activity is inhibited by increased phosphorylation in FH-deficient cells. Our work provides a novel approach to investigate how post-translational modifications of enzymes regulate metabolism and could have important implications for understanding the metabolic transformation of FH-deficient cancers.
]]></description>
<dc:creator>Goncalves, E.</dc:creator>
<dc:creator>Sciacovelli, M.</dc:creator>
<dc:creator>Costa, A. S. H.</dc:creator>
<dc:creator>Johnson, T. I.</dc:creator>
<dc:creator>Machado, D.</dc:creator>
<dc:creator>Frezza, C.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:date>2017-06-13</dc:date>
<dc:identifier>doi:10.1101/149716</dc:identifier>
<dc:title><![CDATA[Post-translational regulation of metabolism in fumarate hydratase deficient cancer cells]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/348433v1?rss=1">
<title>
<![CDATA[
Microbial adaptation to venom is common in snakes and spiders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/348433v1?rss=1"
</link>
<description><![CDATA[
Animal venoms are considered sterile sources of antimicrobial compounds with strong membrane disrupting activity against multi-drug resistant bacteria. However, bite wound infections are common in developing nations. Investigating the oral and venom microbiome of five snake and two spider species, we evidence viable microorganisms potentially unique to venom for black-necked spitting cobras (Naja nigricollis). Among these are two venom-resistant novel sequence types of Enterococcus faecalis; the genome sequence data of these isolates feature an additional 45 genes, nearly half of which improve membrane integrity. Our findings challenge the dogma of venom sterility and indicate an increased primary infection risk in the clinical management of venomous animal bite wounds.

One Sentence SummaryIndependent bacterial colonization of cobra venom drives acquisition of genes antagonistic to venom antimicrobial peptides.
]]></description>
<dc:creator>Esmaeilishirazifard, E.</dc:creator>
<dc:creator>Usher, L.</dc:creator>
<dc:creator>Trim, C.</dc:creator>
<dc:creator>Denise, H.</dc:creator>
<dc:creator>Sangal, V.</dc:creator>
<dc:creator>Tyson, G. H.</dc:creator>
<dc:creator>Barlow, A.</dc:creator>
<dc:creator>Redway, K.</dc:creator>
<dc:creator>Taylor, J. D.</dc:creator>
<dc:creator>Kremmyda-Vlachou, M.</dc:creator>
<dc:creator>Loftus, T. D.</dc:creator>
<dc:creator>Lock, M. M. G.</dc:creator>
<dc:creator>Wright, K.</dc:creator>
<dc:creator>Dalby, A.</dc:creator>
<dc:creator>Snyder, L. A. S.</dc:creator>
<dc:creator>Wuster, W.</dc:creator>
<dc:creator>Trim, S.</dc:creator>
<dc:creator>Moschos, S. A.</dc:creator>
<dc:date>2018-06-16</dc:date>
<dc:identifier>doi:10.1101/348433</dc:identifier>
<dc:title><![CDATA[Microbial adaptation to venom is common in snakes and spiders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/421123v1?rss=1">
<title>
<![CDATA[
RELION-3: new tools for automated high-resolution cryo-EM structure determination 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/421123v1?rss=1"
</link>
<description><![CDATA[
Here, we describe the third major release of relion. CPU-based vector acceleration has been added in addition to GPU support, which provides flexibility in use of resources and avoids memory limitations. Reference-free autopicking with Laplacian-of-Gaussian filtering and execution of jobs from python allows non-interactive processing during acquisition, including 2D-classification, de novo model generation and 3D-classification. Perparticle refinement of CTF parameters and correction of estimated beam tilt provides higher-resolution reconstructions when particles are at different heights in the ice, and/or coma-free alignment has not been optimal. Ewald sphere curvature correction improves resolution for large particles. We illustrate these developments with publicly available data sets: together with a Bayesian approach to beam-induced motion correction it leads to resolution improvements of 0.2-0.7 [A] compared to previous relion versions.
]]></description>
<dc:creator>Zivanov, J.</dc:creator>
<dc:creator>Nakane, T.</dc:creator>
<dc:creator>Forsberg, B.</dc:creator>
<dc:creator>Kimanius, D.</dc:creator>
<dc:creator>Hagen, W. J. H.</dc:creator>
<dc:creator>Lindahl, E.</dc:creator>
<dc:creator>Scheres, S. H. W.</dc:creator>
<dc:date>2018-09-19</dc:date>
<dc:identifier>doi:10.1101/421123</dc:identifier>
<dc:title><![CDATA[RELION-3: new tools for automated high-resolution cryo-EM structure determination]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/446070v1?rss=1">
<title>
<![CDATA[
IsoProt: A fully reproducible one-stop-shop for the analysis of iTRAQ/TMT data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/446070v1?rss=1"
</link>
<description><![CDATA[
Reproducibility has become a major concern in biomedical research. In proteomics, bioinformatic workflows can quickly consist of multiple software tools each with its own set of parameters. Their usage involves the definition of often hundreds of parameters as well as data operations to ensure tool interoperability. Hence a manuscripts methods section is often insufficient to completely describe and reproduce a data analysis workflow. Here we present IsoProt: A complete and reproducible bioinformatic workflow deployed on a portable container environment to analyse data from isobarically-labeled, quantitative proteomics experiments. The workflow uses only open source tools and provides a user-friendly and interactive browser interface to configure and execute the different operations. Once the workflow is executed, the results including the R code to perform statistical analyses can be downloaded as an HTML or PDF document providing a complete record of the performed analyses. IsoProt therefore represents a reproducible bioinformatics workflow that will yield identical results on any computer platform.
]]></description>
<dc:creator>Griss, J.</dc:creator>
<dc:creator>Vinterhalter, G.</dc:creator>
<dc:creator>Schwaemmle, V.</dc:creator>
<dc:date>2018-10-17</dc:date>
<dc:identifier>doi:10.1101/446070</dc:identifier>
<dc:title><![CDATA[IsoProt: A fully reproducible one-stop-shop for the analysis of iTRAQ/TMT data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/225573v1?rss=1">
<title>
<![CDATA[
Mining therapeutic insights from large scale drug screenings with transfer learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/225573v1?rss=1"
</link>
<description><![CDATA[
Despite the abundance of large-scale molecular and drug-response data, the insights gained about the mechanisms underlying treatment efficacy in cancer has been in general limited. Machine learning algorithms applied to those datasets most often are used to provide predictions without interpretation, or reveal single drug-gene association and fail to derive robust insights. We propose to use Macau, a bayesian multitask multi-relational algorithm to generalize from individual drugs and genes and explore the interactions between the drug targets and signaling pathways activation. A typical insight would be: "Activation of pathway Y will confer sensitivity to any drug targeting protein X". We applied our methodology to the Genomics of Drug Sensitivity in Cancer (GDSC) screening, using gene expression of 990 cancer cell lines, activity scores of 11 signaling pathways derived from the tool PROGENy as cell line input and 228 nominal targets for 265 drugs as drug input. These interactions can guide a tissue-specific combination treatment strategy, for example suggesting to modulate a certain pathway to maximize the drug response for a given tissue. We confirmed in literature drug combination strategies derived from our result for brain, skin and stomach tissues. Such an analysis of interactions across tissues might help target discovery, drug repurposing and patient stratification strategies.
]]></description>
<dc:creator>Yang, M.</dc:creator>
<dc:creator>Simm, J.</dc:creator>
<dc:creator>Zakeri, P.</dc:creator>
<dc:creator>Moreau, Y.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:date>2017-11-27</dc:date>
<dc:identifier>doi:10.1101/225573</dc:identifier>
<dc:title><![CDATA[Mining therapeutic insights from large scale drug screenings with transfer learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/246470v1?rss=1">
<title>
<![CDATA[
Harmonizing semantic annotations for computational models in biology 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/246470v1?rss=1"
</link>
<description><![CDATA[
Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition, and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current semantic annotation practices among the COmputational Modeling in BIology NEtwork (COMBINE) community and provide a set of recommendations for building a consensus approach to semantic annotation.
]]></description>
<dc:creator>Neal, M. L.</dc:creator>
<dc:creator>König, M.</dc:creator>
<dc:creator>Nickerson, D.</dc:creator>
<dc:creator>Mısırlı, G.</dc:creator>
<dc:creator>Kalbasi, R.</dc:creator>
<dc:creator>Dräger, A.</dc:creator>
<dc:creator>Atalag, K.</dc:creator>
<dc:creator>Chelliah, V.</dc:creator>
<dc:creator>Cooling, M.</dc:creator>
<dc:creator>Cook, D. L.</dc:creator>
<dc:creator>Crook, S.</dc:creator>
<dc:creator>de Alba, M.</dc:creator>
<dc:creator>Friedman, S. H.</dc:creator>
<dc:creator>Garny, A.</dc:creator>
<dc:creator>Gennari, J. H.</dc:creator>
<dc:creator>Gleeson, P.</dc:creator>
<dc:creator>Golebiewski, M.</dc:creator>
<dc:creator>Hucka, M.</dc:creator>
<dc:creator>Juty, N.</dc:creator>
<dc:creator>Le Novere, N.</dc:creator>
<dc:creator>Myers, C.</dc:creator>
<dc:creator>Olivier, B. G.</dc:creator>
<dc:creator>Sauro, H. M.</dc:creator>
<dc:creator>Scharm, M.</dc:creator>
<dc:creator>Snoep, J. L.</dc:creator>
<dc:creator>Toure, V.</dc:creator>
<dc:creator>Wipat, A.</dc:creator>
<dc:creator>Wolkenhauer, O.</dc:creator>
<dc:creator>Waltemath, D.</dc:creator>
<dc:date>2018-01-23</dc:date>
<dc:identifier>doi:10.1101/246470</dc:identifier>
<dc:title><![CDATA[Harmonizing semantic annotations for computational models in biology]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/388579v1?rss=1">
<title>
<![CDATA[
Fluorescence-Based Detection of Fusion State on a Cryo-EM Grid using Correlated Cryo-Fluorescence and Cryo-Electron Microscopy 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/388579v1?rss=1"
</link>
<description><![CDATA[
Correlated light and electron microscopy (CLEM) has become a popular technique for combining the protein-specific labeling of fluorescence with electron microscopy, both at room and cryogenic temperatures. Fluorescence applications at cryo-temperature have typically been limited to localization of tagged protein oligomers due to known issues of extended triplet state duration, spectral shifts, and reduced photon capture through cryo-CLEM objectives. Here, we consider fluorophore characteristics and behaviors that could enable more extended applications. We describe how dialkylcarbocanine DiD and its autoquenching by resonant energy transfer can be used to distinguish the fusion state of a lipid bilayer at cryo-temperatures. By adapting an established fusion assay to work under cryo-CLEM conditions, we identified areas of fusion between influenza virus-like particles and fluorescently labeled lipid vesicles on a cryo-EM grid. This result demonstrates that cryo-CLEM can be used to localize functions in addition to tagged proteins, and that fluorescence autoquenching by resonant energy transfer can be incorporated successfully into cryo-CLEM approaches. In the case of membrane fusion applications, this method provides both an orthogonal confirmation of functional state independent of the morphological description from cryo-EM and a way to bridge room-temperature kinetic assays and the cryo-EM images.
]]></description>
<dc:creator>Metskas, L. A.</dc:creator>
<dc:creator>Briggs, J. A. G.</dc:creator>
<dc:date>2018-08-10</dc:date>
<dc:identifier>doi:10.1101/388579</dc:identifier>
<dc:title><![CDATA[Fluorescence-Based Detection of Fusion State on a Cryo-EM Grid using Correlated Cryo-Fluorescence and Cryo-Electron Microscopy]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/329995v1?rss=1">
<title>
<![CDATA[
The Human RNA-Binding Proteome and Its Dynamics During Arsenite-Induced Translational Arrest 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/329995v1?rss=1"
</link>
<description><![CDATA[
Proteins and RNA functionally and physically intersect in multiple biological processes, however, currently no universal method is available to purify protein-RNA complexes. Here we introduce XRNAX, a method for the generic purification of protein-crosslinked RNA, and demonstrate its versatility to study the composition and dynamics of protein-RNA interactions by various transcriptomic and proteomic approaches. We show that XRNAX captures all RNA biotypes, and use this to characterize the sub-proteomes that interact with coding and non-coding RNAs (ncRNAs), and to identify hundreds of protein-RNA interfaces. Exploiting the quantitative nature of XRNAX, we observe drastic remodeling of the RNA-bound proteome during arsenite-induced stress, distinct from autophagy-induced changes in the total proteome. In addition, we combine XRNAX with CLIP-seq to validate the interaction of ncRNA with Lamin B and EXOSC2. Thus, XRNAX is a resourceful approach to study structural and compositional aspects of protein-RNA interactions to address fundamental questions in RNA-biology.
]]></description>
<dc:creator>Trendel, J.</dc:creator>
<dc:creator>Schwarzl, T.</dc:creator>
<dc:creator>Prakash, A.</dc:creator>
<dc:creator>Bateman, A.</dc:creator>
<dc:creator>Hentze, M. W.</dc:creator>
<dc:creator>Krijgsveld, J.</dc:creator>
<dc:date>2018-05-30</dc:date>
<dc:identifier>doi:10.1101/329995</dc:identifier>
<dc:title><![CDATA[The Human RNA-Binding Proteome and Its Dynamics During Arsenite-Induced Translational Arrest]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/188581v1?rss=1">
<title>
<![CDATA[
clusterSeq: methods for identifying co-expression in high-throughput sequencing data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/188581v1?rss=1"
</link>
<description><![CDATA[
Summary:Identifying gene co-expression is a significant step in understanding functional relationships between genes. Existing methods primarily depend on analyses of correlation between pairs of genes; however, this neglects structural elements between experimental conditions. We present a novel approach to identifying clusters of co-expressed genes that incorporates these structures.nnAvailability:The methods are released on Bioconductor as the clusterSeq package (https://bioconductor.org/packages/release/bioc/html/clusterSeq.html).nnContact: tjh48@cam.ac.uk
]]></description>
<dc:creator>Hardcastle, T. J.</dc:creator>
<dc:creator>Papatheodorou, I.</dc:creator>
<dc:date>2017-09-13</dc:date>
<dc:identifier>doi:10.1101/188581</dc:identifier>
<dc:title><![CDATA[clusterSeq: methods for identifying co-expression in high-throughput sequencing data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/287045v1?rss=1">
<title>
<![CDATA[
The Drosophila microbiome has a limited influence on sleep, activity, and courtship behaviors 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/287045v1?rss=1"
</link>
<description><![CDATA[
In animals, commensal microbes modulate various physiological functions, including behavior. While microbiota exposure is required for normal behavior in mammals, it is not known how widely this dependency is present in other animal species. We proposed the hypothesis that the microbiome has a major influence on the behavior of the vinegar fly (Drosophila melanogaster), a major invertebrate model organism. Several assays were used to test the contribution of the microbiome on some well-characterized behaviors: defensive behavior, sleep, locomotion, and courtship in microbe-bearing, control flies and two generations of germ-free animals. None of the behaviors were largely influenced by the absence of a microbiome, and the small or moderate effects were not generalizable between replicates and/or generations. These results refute the hypothesis, indicating that the Drosophila microbiome does not have a major influence over several behaviors fundamental to the animals survival and reproduction. The impact of commensal microbes on animal behaviour may not be broadly conserved.
]]></description>
<dc:creator>Selkrig, J.</dc:creator>
<dc:creator>Mohammad, F.</dc:creator>
<dc:creator>Ng, S. H.</dc:creator>
<dc:creator>Chua, J. Y.</dc:creator>
<dc:creator>Tumkaya, T.</dc:creator>
<dc:creator>Ho, J.</dc:creator>
<dc:creator>Chiang, Y. N.</dc:creator>
<dc:creator>Rieger, D.</dc:creator>
<dc:creator>Pettersson, S.</dc:creator>
<dc:creator>Helfrich-Foerster, C.</dc:creator>
<dc:creator>Yew, J.</dc:creator>
<dc:creator>Claridge-Chang, A.</dc:creator>
<dc:date>2018-03-22</dc:date>
<dc:identifier>doi:10.1101/287045</dc:identifier>
<dc:title><![CDATA[The Drosophila microbiome has a limited influence on sleep, activity, and courtship behaviors]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/424473v1?rss=1">
<title>
<![CDATA[
Protein inference using PIA workflows and PSI standard file formats 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/424473v1?rss=1"
</link>
<description><![CDATA[
Proteomics using LC-MS/MS has become one of the main methods to analyze the proteins in biological samples in high-throughput. But the existing mass spectrometry instruments are still limited with respect to resolution and measurable mass ranges, which is one of the main reasons why shotgun proteomics is the major approach. Here, proteins are digested, which leads to the identification and quantification of peptides instead. While often neglected, the important step of protein inference needs to be conducted to infer from the identified peptides to the actual proteins in the original sample.nnIn this work, we highlight some of the previously published and newly added features of the tool PIA - Protein Inference Algorithms, which helps the user with the protein inference of measured samples. We also highlight the importance of the usage of PSI standard file formats, as PIA is the only current software supporting all available standards used for spectrum identification and protein inference. Additionally, we briefly describe the benefits of working with workflow environments for proteomics analyses and show the new features of the PIA nodes for the KNIME Analytics Platform. Finally, we benchmark PIA against a recently published dataset for isoform detection.nnPIA is open source and available for download on GitHub (https://github.com/mpc-bioinformatics/pia) or directly via the community extensions inside the KNIME analytics platform.
]]></description>
<dc:creator>Uszkoreit, J.</dc:creator>
<dc:creator>Perez-Riverol, Y.</dc:creator>
<dc:creator>Eggers, B.</dc:creator>
<dc:creator>Marcus, K.</dc:creator>
<dc:creator>Eisenacher, M.</dc:creator>
<dc:date>2018-09-23</dc:date>
<dc:identifier>doi:10.1101/424473</dc:identifier>
<dc:title><![CDATA[Protein inference using PIA workflows and PSI standard file formats]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/400275v1?rss=1">
<title>
<![CDATA[
Topological data analysis quantifies biological nano-structure from single molecule localization microscopy 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/400275v1?rss=1"
</link>
<description><![CDATA[
The study of complex molecular organisation and nano-structure by localization based microscopy is limited by the available analysis tools. We present a segmentation protocol which, through the application of persistence based clustering, is capable of probing densely packed structures which vary in scale. An increase in segmentation performance over state-of-the-art methods is demonstrated. Moreover we employ persistent homology to move beyond clustering, and quantify the topological structure within data. This provides new information about the preserved shapes formed by molecular architecture. Our methods are flexible and we demonstrate this by applying them to receptor clustering in platelets, nuclear pore components and endocytic proteins. Both 2D and 3D implementations are provided within RSMLM, an R package for pointillist based analysis and batch processing of localization microscopy data.
]]></description>
<dc:creator>Pike, J. A.</dc:creator>
<dc:creator>Khan, A. O.</dc:creator>
<dc:creator>Pallini, C.</dc:creator>
<dc:creator>Thomas, S. G.</dc:creator>
<dc:creator>Mund, M.</dc:creator>
<dc:creator>Ries, J.</dc:creator>
<dc:creator>Poulter, N. S.</dc:creator>
<dc:creator>Styles, I. B.</dc:creator>
<dc:date>2018-08-26</dc:date>
<dc:identifier>doi:10.1101/400275</dc:identifier>
<dc:title><![CDATA[Topological data analysis quantifies biological nano-structure from single molecule localization microscopy]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/236596v1?rss=1">
<title>
<![CDATA[
Recent improvements to the automatic characterization and data collection algorithms on MASSIF-1 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/236596v1?rss=1"
</link>
<description><![CDATA[
Macromolecular crystallography (MX) is now a mature and widely used technique essential in the understanding of biology and medicine. Increases in computing power combined with robotics have enabled not only large numbers of samples to be screened and characterised but also for better decisions to be taken on data collection itself. This led to the development of MASSIF-1 at the ESRF, the worlds first beamline to run fully automatically while making intelligent decisions taking user requirements into account. Since opening in late 2014 the beamline has now processed over 39,000 samples. Improvements have been made to the speed of the sample handling robotics and error management within the software routines. The workflows initially put in place, while highly innovative at the time, have been expanded to include increased complexity and additional intelligence using the information gathered during characterisation, this includes adapting the beam diameter dynamically to match the diffraction volume within the crystal. Complex multi-position and multi-crystal data collections are now also integrated into the selection of experiments available. This has led to increased data quality and throughput allowing even the most challenging samples to be treated automatically.nnSynopsisnnSignificant improvements in the sample location, characterisation and data collection algorithms on the autonomous ESRF beamline MASSIF-1 are described. The workflows now include dynamic beam diameter adjustment and multi-position and multi-crystal data collections.
]]></description>
<dc:creator>Svensson, O.</dc:creator>
<dc:creator>Gilski, M.</dc:creator>
<dc:creator>Nurizzo, D.</dc:creator>
<dc:creator>Bowler, M. W.</dc:creator>
<dc:date>2017-12-19</dc:date>
<dc:identifier>doi:10.1101/236596</dc:identifier>
<dc:title><![CDATA[Recent improvements to the automatic characterization and data collection algorithms on MASSIF-1]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/089094v1?rss=1">
<title>
<![CDATA[
Raoult’s law revisited: accurately predicting equilibrium relative humidity points for humidity control experiments 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/089094v1?rss=1"
</link>
<description><![CDATA[
The humidity surrounding a sample is an important variable in scientific experiments. Biological samples in particular require not just a humid atmosphere but often a relative humidity (RH) that is in equilibrium with a stabilizing solution required to maintain the sample in the same state during measurements. The controlled dehydration of macromolecular crystals can lead to significant increases in crystal order, which often leads to higher diffraction quality. Devices that can accurately control the humidity surrounding crystals on a beamline have led to this technique being increasingly adopted, as experiments become easier and more reproducible. Matching the relative humidity to the mother liquor is the first step to allow the stable mounting of a crystal. In previous work, we measured the equilibrium relative humidity for a range of concentrations of the most commonly used precipitants and showed how this related to Raoults law for the equilibrium vapour pressure of water above a solution. However, a discrepancy between measured values and those predicted by theory could not be explained. Here, we have used a more precise humidity control device to determine equilibrium relative humidity points. The new results are in agreement with Raoults law. We also present a simple argument in statistical mechanics demonstrating that the saturated vapour pressure of a solvent is proportional to its mole fraction in an ideal solution: Raoults Law. The same argument can be extended to the case where solvent and solute molecules are of different size, as is the case with polymers. The results provide a framework for the correct maintenance of the RH surrounding samples.nnSynopsisThe equilibrium relative humidity values for a number of the most commonly used precipitants in biological macromolecule crystallisation have been measured using a new humidity control device. A simple argument in statistical mechanics demonstrates that the saturated vapour pressure of a solvent is proportional to its mole fraction in an ideal solution (Raoults Law). The same argument can be extended to the case where solvent and solute molecules are of different size.
]]></description>
<dc:creator>Bowler, M. G.</dc:creator>
<dc:creator>Bowler, D. R.</dc:creator>
<dc:creator>Bowler, M. W.</dc:creator>
<dc:date>2016-11-22</dc:date>
<dc:identifier>doi:10.1101/089094</dc:identifier>
<dc:title><![CDATA[Raoult’s law revisited: accurately predicting equilibrium relative humidity points for humidity control experiments]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-11-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/208330v1?rss=1">
<title>
<![CDATA[
Germline determinants of the somatic mutation landscape in 2,642 cancer genomes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/208330v1?rss=1"
</link>
<description><![CDATA[
Cancers develop through somatic mutagenesis, however germline genetic variation can markedly contribute to tumorigenesis via diverse mechanisms. We discovered and phased 88 million germline single nucleotide variants, short insertions/deletions, and large structural variants in whole genomes from 2,642 cancer patients, and employed this genomic resource to study genetic determinants of somatic mutagenesis across 39 cancer types. Our analyses implicate damaging germline variants in a variety of cancer predisposition and DNA damage response genes with specific somatic mutation patterns. Mutations in the MBD4 DNA glycosylase gene showed association with elevated C>T mutagenesis at CpG dinucleotides, a ubiquitous mutational process acting across tissues. Analysis of somatic structural variation exposed complex rearrangement patterns, involving cycles of templated insertions and tandem duplications, in BRCA1-deficient tumours. Genome-wide association analysis implicated common genetic variation at the APOBEC3 gene cluster with reduced basal levels of somatic mutagenesis attributable to APOBEC cytidine deaminases across cancer types. We further inferred over a hundred polymorphic L1/LINE elements with somatic retrotransposition activity in cancer. Our study highlights the major impact of rare and common germline variants on mutational landscapes in cancer.
]]></description>
<dc:creator>Waszak, S. M.</dc:creator>
<dc:creator>Tiao, G.</dc:creator>
<dc:creator>Zhu, B.</dc:creator>
<dc:creator>Rausch, T.</dc:creator>
<dc:creator>Muyas, F.</dc:creator>
<dc:creator>Rodriguez-Martin, B.</dc:creator>
<dc:creator>Rabionet, R.</dc:creator>
<dc:creator>Yakneen, S.</dc:creator>
<dc:creator>Escaramis, G.</dc:creator>
<dc:creator>Li, Y.</dc:creator>
<dc:creator>Saini, N.</dc:creator>
<dc:creator>Roberts, S. A.</dc:creator>
<dc:creator>Demidov, G. M.</dc:creator>
<dc:creator>Pitkanen, E.</dc:creator>
<dc:creator>Delaneau, O.</dc:creator>
<dc:creator>Heredia-Genestar, J. M.</dc:creator>
<dc:creator>Weischenfeldt, J.</dc:creator>
<dc:creator>Shringarpure, S. S.</dc:creator>
<dc:creator>Chen, J.</dc:creator>
<dc:creator>Nakagawa, H.</dc:creator>
<dc:creator>Alexandrov, L. B.</dc:creator>
<dc:creator>Drechsel, O.</dc:creator>
<dc:creator>Dursi, L. J.</dc:creator>
<dc:creator>Segre, A. V.</dc:creator>
<dc:creator>Garrison, E.</dc:creator>
<dc:creator>Erkek, S.</dc:creator>
<dc:creator>Habermann, N.</dc:creator>
<dc:creator>Urban, L.</dc:creator>
<dc:creator>Khurana, E.</dc:creator>
<dc:creator>Cafferkey, A.</dc:creator>
<dc:creator>Hayashi, S.</dc:creator>
<dc:creator>Imoto, S.</dc:creator>
<dc:creator>Aaltonen, L. A.</dc:creator>
<dc:creator>Alvarez, E. G.</dc:creator>
<dc:creator>Baez-Ortega, A.</dc:creator>
<dc:creator>Bailey, M.</dc:creator>
<dc:creator>Bosio, M.</dc:creator>
<dc:creator>Bruzos, A. L.</dc:creator>
<dc:creator>Buchhalter, I.</dc:creator>
<dc:creator>Bustamante, C. D.</dc:creator>
<dc:creator>Calabrese, C.</dc:creator>
<dc:creator>DiBiase,</dc:creator>
<dc:date>2017-11-01</dc:date>
<dc:identifier>doi:10.1101/208330</dc:identifier>
<dc:title><![CDATA[Germline determinants of the somatic mutation landscape in 2,642 cancer genomes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/386268v1?rss=1">
<title>
<![CDATA[
iProteinDB: an integrative database of Drosophila post-translational modifications 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/386268v1?rss=1"
</link>
<description><![CDATA[
Post-translational modification (PTM) serves as a regulatory mechanism for protein function, influencing stability, protein interactions, activity and localization, and is critical in many signaling pathways. The best characterized PTM is phosphorylation, whereby a phosphate is added to an acceptor residue, commonly serine, threonine and tyrosine. As proteins are often phosphorylated at multiple sites, identifying those sites that are important for function is a challenging problem. Considering that many phosphorylation sites may be non-functional, prioritizing evolutionarily conserved phosphosites provides a general strategy to identify the putative functional sites with regards to regulation and function. To facilitate the identification of conserved phosphosites, we generated a large-scale phosphoproteomics dataset from Drosophila embryos collected from six closely-related species. We built iProteinDB (https://www.flyrnai.org/tools/iproteindb/), a resource integrating these data with other high-throughput PTM datasets, including vertebrates, and manually curated information for Drosophila. At iProteinDB, scientists can view the PTM landscape for any Drosophila protein and identify predicted functional phosphosites based on a comparative analysis of data from closely-related Drosophila species. Further, iProteinDB enables comparison of PTM data from Drosophila to that of orthologous proteins from other model organisms, including human, mouse, rat, Xenopus laevis, Danio rerio, and Caenorhabditis elegans.
]]></description>
<dc:creator>Hu, Y.</dc:creator>
<dc:creator>Sopko, R.</dc:creator>
<dc:creator>Chung, V.</dc:creator>
<dc:creator>Studer, R. A.</dc:creator>
<dc:creator>Landry, S. D.</dc:creator>
<dc:creator>Liu, D.</dc:creator>
<dc:creator>Rabinow, L.</dc:creator>
<dc:creator>Gnad, F.</dc:creator>
<dc:creator>Beltrao, P.</dc:creator>
<dc:creator>Perrimon, N.</dc:creator>
<dc:date>2018-08-07</dc:date>
<dc:identifier>doi:10.1101/386268</dc:identifier>
<dc:title><![CDATA[iProteinDB: an integrative database of Drosophila post-translational modifications]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/137711v1?rss=1">
<title>
<![CDATA[
The Condensin Complex Is A Mechanochemical Motor That Translocates Along DNA 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/137711v1?rss=1"
</link>
<description><![CDATA[
One Sentence SummarySingle-molecule imaging reveals that eukaryotic condensin is a highly processive DNA-translocating motor complex.nnAbstractCondensin plays crucial roles in chromosome organization and compaction, but the mechanistic basis for its functions remains obscure. Here, we use single-molecule imaging to demonstrate that Saccharomyces cerevisiae condensin is a molecular motor capable of ATP hydrolysis-dependent translocation along double-stranded DNA. Condensins translocation activity is rapid and highly processive, with individual complexes traveling an average distance of [&ge;]10 kilobases at a velocity of [~]60 base pairs per second. Our results suggest that condensin may take steps comparable in length to its [~]50-nanometer coiled-coil subunits, suggestive of a translocation mechanism that is distinct from any reported DNA motor protein. The finding that condensin is a mechanochemical motor has important implications for understanding the mechanisms of chromosome organization and condensation.
]]></description>
<dc:creator>Terekawa, T.</dc:creator>
<dc:creator>Bisht, S.</dc:creator>
<dc:creator>Eeftens, J.</dc:creator>
<dc:creator>Dekker, C.</dc:creator>
<dc:creator>Haering, C.</dc:creator>
<dc:creator>Greene, E.</dc:creator>
<dc:date>2017-05-13</dc:date>
<dc:identifier>doi:10.1101/137711</dc:identifier>
<dc:title><![CDATA[The Condensin Complex Is A Mechanochemical Motor That Translocates Along DNA]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/307629v1?rss=1">
<title>
<![CDATA[
Patterning of a telencephalon-like region in the adult brain of amphioxus 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/307629v1?rss=1"
</link>
<description><![CDATA[
The evolutionary origin of the vertebrate telencephalon remains unsolved. A major challenge has been the identification of homologous brain parts in invertebrate chordates. Here we report evidence for a telencephalic region in the brain of amphioxus, the most basally branching invertebrate chordate. This region is characterised, like its vertebrate counterpart, by the combined expression of the telencephalic markers FoxG1, Emx and Lhx2/9. It is located at the anterior neural border and dorsal-ventrally patterned, as in vertebrates, by the antagonistic expression of Pax4/6 and Nkx2.1, and a ventral Hh signal. This part of the brain develops only after metamorphosis via sustained proliferation of neuronal progenitors at the ventricular zone. This is concomitant with a massive expansion of late differentiating neuronal types as revealed by neuropeptide and neurotransmitter profiling. Overall, our results suggest that the adult amphioxus brain shows remarkable similarities to the vertebrate embryonic brain, thus providing a key missing link in understanding the invertebrate-to-vertebrate transition in chordate brain evolution.
]]></description>
<dc:creator>Benito Gutierrez, E.</dc:creator>
<dc:creator>Stemmer, M.</dc:creator>
<dc:creator>Rohr, S. D.</dc:creator>
<dc:creator>Schumacher, L. N.</dc:creator>
<dc:creator>Tang, J.</dc:creator>
<dc:creator>Marconi, A.</dc:creator>
<dc:creator>Jekely, G.</dc:creator>
<dc:creator>Arendt, D.</dc:creator>
<dc:date>2018-04-25</dc:date>
<dc:identifier>doi:10.1101/307629</dc:identifier>
<dc:title><![CDATA[Patterning of a telencephalon-like region in the adult brain of amphioxus]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/443945v1?rss=1">
<title>
<![CDATA[
Evolution of protein kinase substrate recognition at the active site 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/443945v1?rss=1"
</link>
<description><![CDATA[
Protein kinases catalyse the phosphorylation of target proteins, controlling most cellular processes. The specificity of serine/threonine kinases is partly determined by interactions with a few residues near the phospho-acceptor residue, forming the so-called kinase substrate motif. Kinases have been extensively duplicated throughout evolution but little is known about when in time new target motifs have arisen. Here we show that sequence variation occurring early in the evolution of kinases is dominated by changes in specificity determining residues. We then analysed kinase specificity models, based on known target sites, observing that specificity has remained mostly unchanged for recent kinase duplications. Finally, analysis of phosphorylation data from a taxonomically broad set of 48 eukaryotic species indicates that most phosphorylation motifs are broadly distributed in eukaryotes but not present in prokaryotes. Overall, our results suggest that the set of eukaryotes kinase motifs present today was acquired soon after the eukaryotic last common ancestor and that early expansions of the protein kinase fold rapidly explored the space of possible target motifs.
]]></description>
<dc:creator>Bradley, D.</dc:creator>
<dc:creator>Beltrao, P.</dc:creator>
<dc:date>2018-10-16</dc:date>
<dc:identifier>doi:10.1101/443945</dc:identifier>
<dc:title><![CDATA[Evolution of protein kinase substrate recognition at the active site]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/141150v1?rss=1">
<title>
<![CDATA[
Postmitotic Nuclear Pore Assembly Proceeds By Radial Dilation Of Small ER Membrane Openings 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/141150v1?rss=1"
</link>
<description><![CDATA[
The nuclear envelope has to be reformed after mitosis to create viable daughter cells with closed nuclei. How membrane sealing of DNA and assembly of nuclear pore complexes (NPCs) are achieved and coordinated is poorly understood. Here, we reconstructed nuclear membrane topology and structure of assembling NPCs in a correlative three dimensional electron microscopy time-course of dividing human cells. Our quantitative ultrastructural analysis shows that nuclear membranes form from highly fenestrated ER sheets, whose shrinking holes are stabilized and then dilated into NPCs during inner ring complex assembly, forming thousands of transport channels within minutes. This mechanism is fundamentally different from interphase NPC assembly and explains how mitotic cells can rapidly establish a closed nuclear compartment while making it transport-competent at the same time.
]]></description>
<dc:creator>Otsuka, S.</dc:creator>
<dc:creator>Steyer, A. M.</dc:creator>
<dc:creator>Schorb, M.</dc:creator>
<dc:creator>Heriche, J.-K.</dc:creator>
<dc:creator>Hossain, M. J.</dc:creator>
<dc:creator>Sethi, S.</dc:creator>
<dc:creator>Schwab, Y.</dc:creator>
<dc:creator>Beck, M.</dc:creator>
<dc:creator>Ellenberg, J.</dc:creator>
<dc:date>2017-05-23</dc:date>
<dc:identifier>doi:10.1101/141150</dc:identifier>
<dc:title><![CDATA[Postmitotic Nuclear Pore Assembly Proceeds By Radial Dilation Of Small ER Membrane Openings]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/088906v1?rss=1">
<title>
<![CDATA[
ConfocalGN : a minimalistic confocal image simulator. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/088906v1?rss=1"
</link>
<description><![CDATA[
We developed a user-friendly software to generate synthetic confocal microscopy images from a ground truth specified as a 3D bitmap with pixels of arbitrary size. The software can analyze a real confocal stack to derivate noise parameters and will use them directly to generate new images with similar noise characteristics. Such synthetic images can then be used to assert the quality and robustness of an image analysis pipeline, as well as be used to train machine-learning image analysis procedures. We illustrate the approach with closed curves corresponding to the microtubule ring present in blood platelets.nnAvailability and implementationConfocalGN is written in MATLAB but does not require any toolbox. The source code is distributed under the GPL 3.0 licence on https://github.com/SergeDmi/ConfocalGN.
]]></description>
<dc:creator>Dmitrieff, S.</dc:creator>
<dc:creator>Nedelec, F.</dc:creator>
<dc:date>2016-11-21</dc:date>
<dc:identifier>doi:10.1101/088906</dc:identifier>
<dc:title><![CDATA[ConfocalGN : a minimalistic confocal image simulator.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-11-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/440735v1?rss=1">
<title>
<![CDATA[
Minimal phenotyping yields GWAS hits of low specificity for major depression 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/440735v1?rss=1"
</link>
<description><![CDATA[
Minimal phenotyping refers to the reliance on the use of a small number of self-report items for disease case identification. This strategy has been applied to genome-wide association studies (GWAS) of major depressive disorder (MDD). Here we report that the genotype derived heritability (h2SNP) of depression defined by minimal phenotyping (14%, SE = 0.8%) is lower than strictly defined MDD (26%, SE = 2.2%). This cannot be explained by differences in prevalence between definitions or including cases of lower liability to MDD in minimal phenotyping definitions of depression, but can be explained by misdiagnosis of those without depression or with related conditions as cases of depression. Depression defined by minimal phenotyping is as genetically correlated with strictly defined MDD (rG = 0.81, SE = 0.03) as it is with the personality trait neuroticism (rG = 0.84, SE = 0.05), a trait not defined by the cardinal symptoms of depression. While they both show similar shared genetic liability with neuroticism, a greater proportion of the genome contributes to the minimal phenotyping definitions of depression (80.2%, SE = 0.6%) than to strictly defined MDD (65.8%, SE = 0.6%). We find that GWAS loci identified in minimal phenotyping definitions of depression are not specific to MDD: they also predispose to other psychiatric conditions. Finally, while highly predictive polygenic risk scores can be generated from minimal phenotyping definitions of MDD, the predictive power can be explained entirely by the sample size used to generate the polygenic risk score, rather than specificity for MDD. Our results reveal that genetic analysis of minimal phenotyping definitions of depression identifies non-specific genetic factors shared between MDD and other psychiatric conditions. Reliance on results from minimal phenotyping for MDD may thus bias views of the genetic architecture of MDD and may impede our ability to identify pathways specific to MDD.
]]></description>
<dc:creator>Cai, N.</dc:creator>
<dc:creator>Kendler, K.</dc:creator>
<dc:creator>Flint, J.</dc:creator>
<dc:date>2018-10-11</dc:date>
<dc:identifier>doi:10.1101/440735</dc:identifier>
<dc:title><![CDATA[Minimal phenotyping yields GWAS hits of low specificity for major depression]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/238741v1?rss=1">
<title>
<![CDATA[
Contact-dependent cell communications drive morphological invariance during ascidian embryogenesis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/238741v1?rss=1"
</link>
<description><![CDATA[
Canalization of developmental processes ensures the reproducibility and robustness of embryogenesis within each species. In its extreme form, found in ascidians, early embryonic cell lineages are invariant between embryos within and between species, despite rapid genomic divergence. To resolve this paradox, we used live light-sheet imaging to quantify individual cell behaviors in digitalized embryos and explore the forces that canalize their development. This quantitative approach revealed that individual cell geometries and cell contacts are strongly constrained, and that these constraints are tightly linked to the control of fate specification by local cell inductions. While in vertebrates ligand concentration usually controls cell inductions, we found that this role is fulfilled in ascidians by the area of contacts between signaling and responding cells. We propose that the duality between geometric and genetic control of inductions contributes to the counterintuitive inverse correlation between geometric and genetic variability during embryogenesis.
]]></description>
<dc:creator>Guignard, L.</dc:creator>
<dc:creator>Fiuza, U.-M.</dc:creator>
<dc:creator>Leggio, B.</dc:creator>
<dc:creator>Faure, E.</dc:creator>
<dc:creator>Laussu, J.</dc:creator>
<dc:creator>Hufnagel, L.</dc:creator>
<dc:creator>Malandain, G.</dc:creator>
<dc:creator>Godin, C.</dc:creator>
<dc:creator>Lemaire, P.</dc:creator>
<dc:date>2017-12-24</dc:date>
<dc:identifier>doi:10.1101/238741</dc:identifier>
<dc:title><![CDATA[Contact-dependent cell communications drive morphological invariance during ascidian embryogenesis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/413294v1?rss=1">
<title>
<![CDATA[
Utilisation of staphylococcal immune evasion protein Sbi as a novel vaccine adjuvant 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/413294v1?rss=1"
</link>
<description><![CDATA[
Co-ligation of the B cell antigen receptor with complement receptor 2 on B-cells via a C3d-opsonised antigen complex significantly lowers the threshold required for B cell activation. Consequently, fusions of antigens with C3d polymers have shown great potential in vaccine design. However, these linear arrays of C3d multimers do not mimic the natural opsonisation of antigens with C3d. Here we investigate the potential of using the unique complement activating characteristics of Staphylococcal immune-evasion protein Sbi to develop a pro-vaccine approach that spontaneously coats antigens with C3 degradation products in a natural way. We show that Sbi rapidly triggers the alternative complement pathway through recruitment of complement regulators, forming a tripartite complex that acts as a competitive antagonist of factor H, resulting in enhanced complement consumption. These functional results are corroborated by the structure of this complement activating Sbi-III-IV:C3d:FHR-1 complex. Finally, we demonstrate that Sbi, fused with Mycobacterium tuberculosis antigen Ag85b, causes efficient opsonisation with C3 fragments, thereby enhancing the immune response significantly beyond that of Ag85b alone, providing proof of concept for our pro-vaccine approach.
]]></description>
<dc:creator>Yang, Y.</dc:creator>
<dc:creator>Back, C.</dc:creator>
<dc:creator>Graewert, M.</dc:creator>
<dc:creator>Wahid, A.</dc:creator>
<dc:creator>Denton, H.</dc:creator>
<dc:creator>Kildani, R.</dc:creator>
<dc:creator>Paulin, J.</dc:creator>
<dc:creator>Woerner, K.</dc:creator>
<dc:creator>Kaiser, W.</dc:creator>
<dc:creator>Svergun, D. I.</dc:creator>
<dc:creator>Sartbaeva, A.</dc:creator>
<dc:creator>Watts, A.</dc:creator>
<dc:creator>Marchbank, K.</dc:creator>
<dc:creator>van den Elsen, J. M.</dc:creator>
<dc:date>2018-09-10</dc:date>
<dc:identifier>doi:10.1101/413294</dc:identifier>
<dc:title><![CDATA[Utilisation of staphylococcal immune evasion protein Sbi as a novel vaccine adjuvant]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/232017v1?rss=1">
<title>
<![CDATA[
In situ architecture of the algal nuclear pore complex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/232017v1?rss=1"
</link>
<description><![CDATA[
Nuclear pore complexes (NPCs) span the nuclear envelope and mediate nucleocytoplasmic exchange. They are a hallmark of eukaryotes and are deeply rooted in the evolutionary origin of cellular compartmentalization. NPCs have an elaborate architecture that has been well studied in vertebrates. Whether this architecture is unique or varies significantly in other eukaryotic kingdoms remains unknown, predominantly due to missing in situ structural data. Here, we report the architecture of the algal NPC from the early branching eukaryote Chlamydomonas reinhardtii and compare it to the human NPC. We find that the inner ring of the Chlamydomonas NPC has an unexpectedly large diameter, and the outer rings exhibit an asymmetric oligomeric state that is unprecedented compared to all previously proposed models of NPC architecture. Our study provides evidence that the NPC is subject to substantial structural variation between species. The divergent and conserved features of NPC architecture provide insights into the evolution of the nucleocytoplasmic transport machinery.
]]></description>
<dc:creator>Mosalaganti, S.</dc:creator>
<dc:creator>Kosinski, J.</dc:creator>
<dc:creator>Albert, S.</dc:creator>
<dc:creator>Schaffer, M.</dc:creator>
<dc:creator>Plitzko, J. M.</dc:creator>
<dc:creator>Baumeister, W.</dc:creator>
<dc:creator>Engel, B. D.</dc:creator>
<dc:creator>Beck, M.</dc:creator>
<dc:date>2017-12-10</dc:date>
<dc:identifier>doi:10.1101/232017</dc:identifier>
<dc:title><![CDATA[In situ architecture of the algal nuclear pore complex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/148650v1?rss=1">
<title>
<![CDATA[
Sperm chemotaxis is driven by the slope of the chemoattractant concentration field 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/148650v1?rss=1"
</link>
<description><![CDATA[
Spermatozoa of marine invertebrates are attracted to their conspecific female gamete by diffusive molecules, called chemoattractants, released from the egg investments in a process known as chemotaxis. The information from the egg chemoattractant concentration field is decoded into intracellular Ca2+ concentration ([Ca2+]i) changes that regulate the internal motors that shape the flagellum as it beats. By studying sea urchin species-specific differences in sperm chemoattractant-receptor characteristics we show that receptor density constrains the steepness of the chemoattractant concentration gradient detectable by spermatozoa. Through analyzing different chemoattractant gradient forms, we demonstrate for the first time that Strongylocentrotus purpuratus sperm are chemotactic and this response is consistent with frequency entrainment of two coupled physiological oscillators: i) the stimulus function and ii) the [Ca2+]i changes. We demonstrate that the slope of the chemoattractant gradients provides the coupling force between both oscillators, arising as a fundamental requirement for sperm chemotaxis.
]]></description>
<dc:creator>Ramirez-Gomez, H. V.</dc:creator>
<dc:creator>Jimenez-Sabinina, V.</dc:creator>
<dc:creator>Tuval, I.</dc:creator>
<dc:creator>Velazquez-Perez, M.</dc:creator>
<dc:creator>Beltran, C.</dc:creator>
<dc:creator>Carneiro, J.</dc:creator>
<dc:creator>Wood, C.</dc:creator>
<dc:creator>Darszon, A.</dc:creator>
<dc:creator>Guerrero, A.</dc:creator>
<dc:date>2017-06-10</dc:date>
<dc:identifier>doi:10.1101/148650</dc:identifier>
<dc:title><![CDATA[Sperm chemotaxis is driven by the slope of the chemoattractant concentration field]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/177949v1?rss=1">
<title>
<![CDATA[
The small non-coding vault RNA1-1 acts as a riboregulator of autophagy 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/177949v1?rss=1"
</link>
<description><![CDATA[
Vault RNAs (vtRNA) are small, 88-100nt non-coding RNAs found in many eukaryotes. Although they have been linked to drug resistance, apoptosis and nuclear transport, their function remains unclear. Here we show that a human vtRNA, RNA1-1, specifically binds to the autophagy receptor sequestosome-1/p62. Antisense-mediated depletion of vault RNA1-1 augments, whereas increased vault RNA1-1 expression restricts, autophagic flux in a p62-dependent manner. Bulk autophagy induced by starvation reduces the levels of vault RNA1-1 and the fraction of RNA-bound p62. These findings show that RNAs can act as riboregulators of biological processes by interacting with proteins, and assign a function to a vault RNA.
]]></description>
<dc:creator>Horos, R.</dc:creator>
<dc:creator>Alleaume, A.-M.</dc:creator>
<dc:creator>Kleinendorst, R.</dc:creator>
<dc:creator>Tarafder, A. K.</dc:creator>
<dc:creator>Schwarzl, T.</dc:creator>
<dc:creator>Zielonka, E. M.</dc:creator>
<dc:creator>Adak, A.</dc:creator>
<dc:creator>Castello, A.</dc:creator>
<dc:creator>Huber, W.</dc:creator>
<dc:creator>Sachse, C.</dc:creator>
<dc:creator>Hentze, M. W.</dc:creator>
<dc:date>2017-08-18</dc:date>
<dc:identifier>doi:10.1101/177949</dc:identifier>
<dc:title><![CDATA[The small non-coding vault RNA1-1 acts as a riboregulator of autophagy]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/391920v1?rss=1">
<title>
<![CDATA[
Whole-head recording of chemosensory activity in the marine annelid Platynereis dumerilii 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/391920v1?rss=1"
</link>
<description><![CDATA[
Chemical detection is key to various behaviours in both marine and terrestrial animals. Marine species, though highly diverse, have been underrepresented so far in studies on chemosensory systems, and our knowledge mostly concerns the detection of airborne cues. A broader comparative approach is therefore desirable. Marine annelid worms with their rich behavioural repertoire represent attractive models for chemosensory studies. Here, we study the marine worm Platynereis dumerilii to provide the first comprehensive study of head chemosensory organ physiology in an annelid. By combining microfluidics and calcium imaging, we record neuronal activity in the entire head of early juveniles upon chemical stimulation. We find that Platynereis uses four types of organs to detect stimuli such as alcohols, esters, amino acids and sugars. Antennae, but not nuchal organs or palps as generally hypothesised in annelids, are the main chemosensory organs. We report chemically-evoked activity in possible downstream brain regions including the mushroom bodies, which are anatomically and molecularly similar to insect mushroom bodies. We conclude that chemosensation is a major sensory modality for marine annelids, and propose early Platynereis juveniles as a model to study annelid chemosensory systems.nnnnO_FIG O_LINKSMALLFIG WIDTH=184 HEIGHT=200 SRC="FIGDIR/small/391920_ufig1.gif" ALT="Figure 1">nView larger version (74K):norg.highwire.dtl.DTLVardef@4384corg.highwire.dtl.DTLVardef@10c2563org.highwire.dtl.DTLVardef@6a8a32org.highwire.dtl.DTLVardef@96f06c_HPS_FORMAT_FIGEXP  M_FIG C_FIG
]]></description>
<dc:creator>Chartier, T. F.</dc:creator>
<dc:creator>Deschamps, J.</dc:creator>
<dc:creator>Duerichen, W.</dc:creator>
<dc:creator>Jekely, G.</dc:creator>
<dc:creator>Arendt, D.</dc:creator>
<dc:date>2018-08-14</dc:date>
<dc:identifier>doi:10.1101/391920</dc:identifier>
<dc:title><![CDATA[Whole-head recording of chemosensory activity in the marine annelid Platynereis dumerilii]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/283820v1?rss=1">
<title>
<![CDATA[
Differential encoding of predator fear in the ventromedial hypothalamus and periaqueductal grey 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/283820v1?rss=1"
</link>
<description><![CDATA[
The ventromedial hypothalamus is a central node of the mammalian predator defense network. Stimulation of this structure in rodents and primates elicits abrupt defensive responses, including flight, freezing, sympathetic activation, and panic, while inhibition reduces defensive responses to predators. The major efferent target of the ventromedial hypothalamus is the dorsal periaqueductal grey, and stimulation of this structure also elicits flight, freezing, and sympathetic activation. However, reversible inhibition experiments suggest that the ventromedial hypothalamus and periaqueductal grey play distinct roles in the control of defensive behavior, with the former proposed to encode an internal state necessary for the motivation of defensive responses, while the latter serves as a motor pattern initiator. Here we used electrophysiological recordings of single units in behaving mice exposed to a rat to investigate the encoding of predator fear in the dorsomedial division of the ventromedial hypothalamus and the dorsal periaqueductal grey. Distinct correlates of threat intensity and motor responses were found in both structures, suggesting a distributed encoding of sensory and motor features in the medial hypothalamic-brainstem instinctive network.
]]></description>
<dc:creator>Esteban Masferrer, M.</dc:creator>
<dc:creator>Silva, B. A.</dc:creator>
<dc:creator>Nomoto, K.</dc:creator>
<dc:creator>Lima, S. Q.</dc:creator>
<dc:creator>Gross, C. T.</dc:creator>
<dc:date>2018-03-17</dc:date>
<dc:identifier>doi:10.1101/283820</dc:identifier>
<dc:title><![CDATA[Differential encoding of predator fear in the ventromedial hypothalamus and periaqueductal grey]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/225391v1?rss=1">
<title>
<![CDATA[
Molecule guided laser ablation as a novel therapeutic strategy to control itch. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/225391v1?rss=1"
</link>
<description><![CDATA[
Itch is a major symptom of many chronic skin diseases that can exacerbate inflammation by provoking excessive scratching and causing skin damage. Here we develop a novel technology to control itch through molecular guided delivery of a phototoxic agent and near infrared (IR) illumination of the skin. Exploiting the selective binding of the pruritogen Interleukin-31 to itch sensing cells, we generate an engineered IL31SNAP ligand derivative (IL31K138A-SNAP) that binds to cells but does not evoke signaling or provoke scratching when injected in vivo. Conjugation of IL31K138A-SNAP to the photosensitizer IRDye(R)700DX phthalocyanine (IR700) and injection of the skin results in long-term reversal of scratching behavior evoked by IL31 upon near IR illumination. We further develop a topical preparation of IL31 K138A-SNAP-IR700 that strikingly, reverses behavioral and dermatological indicators in mouse models of Atopic Dermatitis (AD) and the genetic skin disease Familial Primary Localized Cutaneous Amyloidosis (FPLCA). We demonstrate that this therapeutic effect results from selective retraction of itch sensing neurons in the skin, breaking the cycle of itch and disruption of the skins barrier function. Thus, molecule guided photoablation is a powerful new technology for controlling itch and treating inflammatory skin diseases.
]]></description>
<dc:creator>Nocchi, L.</dc:creator>
<dc:creator>D'Attilia, M.</dc:creator>
<dc:creator>Roy, N.</dc:creator>
<dc:creator>Dhandapani, R.</dc:creator>
<dc:creator>Traista, A.</dc:creator>
<dc:creator>Maffei, M.</dc:creator>
<dc:creator>Castaldi, L.</dc:creator>
<dc:creator>Perlas, E.</dc:creator>
<dc:creator>Heppenstall, P. A.</dc:creator>
<dc:date>2017-11-27</dc:date>
<dc:identifier>doi:10.1101/225391</dc:identifier>
<dc:title><![CDATA[Molecule guided laser ablation as a novel therapeutic strategy to control itch.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/314484v1?rss=1">
<title>
<![CDATA[
Polarity sorting drives remodeling of actin-myosin networks 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/314484v1?rss=1"
</link>
<description><![CDATA[
Cytoskeletal networks of actin filaments and myosin motors drive many dynamic cell processes. A key characteristic of these networks is their contractility. Despite intense experimental and theoretical efforts, it is not clear what mechanism favors network contraction over expansion. Recent work points to a dominant role for the nonlinear mechanical response of actin filaments, which can withstand stretching but buckle upon compression. Here we present an alternative mechanism. We study how interactions between actin and myosin-2 at the single filament level translate into contraction at the network scale by performing time-lapse imaging on reconstituted quasi-2D-networks mimicking the cell cortex. We observe myosin end-dwelling after it runs processively along actin filaments. This leads to transport and clustering of actin filament ends and the formation of transiently stable bipolar structures. Further we show that myosin-driven polarity sorting leads to polar actin aster formation, which act as contractile nodes that drive contraction in crosslinked networks. Computer simulations comparing the roles of the end-dwelling mechanism and a buckling-dependent mechanism show that the relative contribution of end-dwelling contraction increases as the network mesh-size decreases.
]]></description>
<dc:creator>Wollrab, V.</dc:creator>
<dc:creator>Belmonte, J. M.</dc:creator>
<dc:creator>Leptin, M.</dc:creator>
<dc:creator>Nedelec, F.</dc:creator>
<dc:creator>Koenderink, G. H.</dc:creator>
<dc:date>2018-05-04</dc:date>
<dc:identifier>doi:10.1101/314484</dc:identifier>
<dc:title><![CDATA[Polarity sorting drives remodeling of actin-myosin networks]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/190975v1?rss=1">
<title>
<![CDATA[
Microglia remodel synapses by presynaptic trogocytosis and spine head filopodia induction 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/190975v1?rss=1"
</link>
<description><![CDATA[
Microglia are highly motile glial cells that are proposed to mediate synaptic pruning during neuronal circuit formation. Disruption of signaling between microglia and neurons leads to an excess of immature synaptic connections, thought to be the result of impaired phagocytosis of synapses by microglia. However, until now the direct phagocytosis of synapses by microglia has not been reported and fundamental questions remain about the precise synaptic structures and phagocytic mechanisms involved. Here we used light sheet fluorescence microscopy to follow microglia-synapse interactions in developing organotypic hippocampal cultures, complemented by three-dimensional ultrastructural characterization using correlative light and electron microscopy (CLEM). Our findings define a set of dynamic microglia-synapse interactions, including the selective partial phagocytosis, or trogocytosis (trogo-: nibble), of presynaptic structures and the induction of postsynaptic spine head filopodia by microglia. These findings allow us to propose a mechanism for the facilitatory role of microglia in synaptic circuits remodeling and maturation.
]]></description>
<dc:creator>Weinhard, L.</dc:creator>
<dc:creator>Neniskyte, U.</dc:creator>
<dc:creator>di Bartolomei, G.</dc:creator>
<dc:creator>Bolasco, G.</dc:creator>
<dc:creator>Machado, P.</dc:creator>
<dc:creator>Schieber, N.</dc:creator>
<dc:creator>Exiga, M.</dc:creator>
<dc:creator>Vadisiute, A.</dc:creator>
<dc:creator>Raggioli, A.</dc:creator>
<dc:creator>Schertel, A.</dc:creator>
<dc:creator>Schwab, Y.</dc:creator>
<dc:creator>Gross, C. T.</dc:creator>
<dc:date>2017-09-19</dc:date>
<dc:identifier>doi:10.1101/190975</dc:identifier>
<dc:title><![CDATA[Microglia remodel synapses by presynaptic trogocytosis and spine head filopodia induction]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/233452v1?rss=1">
<title>
<![CDATA[
Control of mechanical pain hypersensitivity through ligand-targeted photoablation of TrkB positive sensory neurons 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/233452v1?rss=1"
</link>
<description><![CDATA[
SummaryMechanical allodynia is a major symptom of neuropathic pain whereby innocuous touch evokes severe pain. Here we identify a population of peripheral sensory neurons expressing TrkB that are both necessary and sufficient for producing pain from light touch after nerve injury. Mice in which TrkB-Cre expressing neurons are ablated are less sensitive to the lightest touch under basal conditions, and fail to develop mechanical allodynia in a model of neuropathic pain. Moreover, selective optogenetic activation of these neurons after nerve injury evokes marked nociceptive behavior. Using a phototherapeutic approach based upon BDNF, the ligand for TrkB, we perform molecule-guided laser ablation of these neurons and achieve long-term retraction of TrkB positive neurons from the skin and pronounced reversal of mechanical allodynia across multiple types of neuropathic pain. Thus we identify the peripheral neurons which transmit pain from light touch and uncover a novel pharmacological strategy for its treatment.nnHighlightsO_LITrkB+ neurons detect light touch under basal conditionsnC_LIO_LITrkB+ neurons convey mechanical allodynia in neuropathic pain statesnC_LIO_LIA photosensitizing derivative of BDNF allows for photoablation of TrkB+ neuronsnC_LIO_LIBDNF-guided photoablation reverses allodynia in multiple types of neuropathic painnC_LI
]]></description>
<dc:creator>Dhandapani, R.</dc:creator>
<dc:creator>Arokiaraj, C. M.</dc:creator>
<dc:creator>Taberner, F. J.</dc:creator>
<dc:creator>Pacifico, P.</dc:creator>
<dc:creator>Raja, S.</dc:creator>
<dc:creator>Nocchi, L.</dc:creator>
<dc:creator>Portulano, C.</dc:creator>
<dc:creator>Franciosa, F.</dc:creator>
<dc:creator>Maffei, M.</dc:creator>
<dc:creator>Hussain, A. F.</dc:creator>
<dc:creator>Reis, F. d. C.</dc:creator>
<dc:creator>Reymond, L.</dc:creator>
<dc:creator>Perlas, E.</dc:creator>
<dc:creator>Garcovich, S.</dc:creator>
<dc:creator>Barth, S.</dc:creator>
<dc:creator>Johnsson, K.</dc:creator>
<dc:creator>Lechner, S. G.</dc:creator>
<dc:creator>Heppenstall, P. A.</dc:creator>
<dc:date>2017-12-13</dc:date>
<dc:identifier>doi:10.1101/233452</dc:identifier>
<dc:title><![CDATA[Control of mechanical pain hypersensitivity through ligand-targeted photoablation of TrkB positive sensory neurons]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/353136v1?rss=1">
<title>
<![CDATA[
Structural rearrangement of TFIIS- and TFIIF/TFIIE-like subunits in RNA polymerase I transcription complexes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/353136v1?rss=1"
</link>
<description><![CDATA[
RNA polymerase (Pol) I is a 14-subunit enzyme that solely transcribes pre-ribosomal RNA. Cryo-EM structures of Pol I initiation and elongation complexes have given first insights into the molecular mechanisms of Pol I transcription. Here, we present cryo-electron microscopy structures of yeast Pol I elongation complexes (ECs) bound to the nucleotide analog GMPCPP at 3.2 to 3.4 [A] resolution that provide additional insight into the functional interplay between the TFIIE/TFIIF-like A49-A34.5 heterodimer and the TFIIS-like subunit A12.2 present in Pol I. Strikingly, most of the nucleotide-bound ECs lack the A49-A34.5 heterodimer and adopt a Pol II-like conformation, in which the A12.2 C-terminal domain is bound in a previously unobserved position at the A135 surface. Our work suggests a regulatory mechanism of Pol I transcription where the association of the A49-A34.5 heterodimer to Pol I is regulated by subunit A12.2, thereby explaining in vitro biochemical and kinetic data.
]]></description>
<dc:creator>Tafur, L.</dc:creator>
<dc:creator>Sadian, Y.</dc:creator>
<dc:creator>Wetzel, R.</dc:creator>
<dc:creator>Weis, F.</dc:creator>
<dc:creator>Muller, C. W.</dc:creator>
<dc:date>2018-07-03</dc:date>
<dc:identifier>doi:10.1101/353136</dc:identifier>
<dc:title><![CDATA[Structural rearrangement of TFIIS- and TFIIF/TFIIE-like subunits in RNA polymerase I transcription complexes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/319046v1?rss=1">
<title>
<![CDATA[
Evolutionary changes in DNA accessibility and sequence predict divergence of transcription factor binding and enhancer activity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/319046v1?rss=1"
</link>
<description><![CDATA[
Transcription factor (TF) binding is determined by sequence as well as chromatin accessibility. While the role of accessibility in shaping TF-binding landscapes is well recorded, its role in evolutionary divergence of TF binding, which in turn can alter cis-regulatory activities, is not well understood. In this work, we studied the evolution of genome-wide binding landscapes of five major transcription factors (TFs) in the core network of mesoderm specification, between D. melanogaster and D. virilis, and examined its relationship to accessibility and sequence-level changes. We generated chromatin accessibility data from three important stages of embryogenesis in both D. melanogaster and D. virilis, and recorded conservation and divergence patterns. We then used multi-variable models to correlate accessibility and sequence changes to TF binding divergence. We found that accessibility changes can in some cases, e.g., for the master regulator Twist and for earlier developmental stages, more accurately predict binding change than is possible using TF binding motif changes between orthologous enhancers. Accessibility changes also explain a significant portion of the co-divergence of TF pairs. We noted that accessibility and motif changes offer complementary views of the evolution of TF binding, and developed a combined model that captures the evolutionary data much more accurately than either view alone. Finally, we trained machine learning models to predict enhancer activity from TF binding, and used these functional models to argue that motif and accessibility-based predictors of TF binding change can substitute for experimentally measured binding change, for the purpose of predicting evolutionary changes in enhancer activity.
]]></description>
<dc:creator>Peng, P.-C.</dc:creator>
<dc:creator>Khoueiry, P.</dc:creator>
<dc:creator>Girardot, C.</dc:creator>
<dc:creator>Reddington, J. P.</dc:creator>
<dc:creator>Garfield, D. A.</dc:creator>
<dc:creator>Furlong, E. E. M.</dc:creator>
<dc:creator>Sinha, S.</dc:creator>
<dc:date>2018-05-10</dc:date>
<dc:identifier>doi:10.1101/319046</dc:identifier>
<dc:title><![CDATA[Evolutionary changes in DNA accessibility and sequence predict divergence of transcription factor binding and enhancer activity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/381830v1?rss=1">
<title>
<![CDATA[
The Integrated Rapid Infectious Disease Analysis (IRIDA) Platform 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/381830v1?rss=1"
</link>
<description><![CDATA[
Whole genome sequencing (WGS) is a powerful tool for public health infectious disease investigations owing to its higher resolution, greater efficiency, and cost-effectiveness over traditional genotyping methods. Implementation of WGS in routine public health microbiology laboratories is impeded by a lack of user-friendly automated and semi-automated pipelines, restrictive jurisdictional data sharing policies, and the proliferation of non-interoperable analytical and reporting systems. To address these issues, we developed the Integrated Rapid Infectious Disease Analysis (IRIDA) platform (irida.ca), a user-friendly, decentralized, open-source bioinformatics and analytical web platform to support real-time infectious disease outbreak investigations using WGS data. Instances can be independently installed on local high-performance computing infrastructure, enabling private and secure data management and analyses according to organizational policies and governance. IRIDAs data management capabilities enable secure upload, storage and sharing of all WGS data and metadata. The core platform currently includes pipelines for quality control, assembly, annotation, variant detection, phylogenetic analysis, in silico serotyping, multi-locus sequence typing, and genome distance calculation. Analysis pipeline results can be visualized within the platform through dynamic line lists and integrated phylogenomic clustering for research and discovery, and for enhancing decision-making support and hypothesis generation in epidemiological investigations. Communication and data exchange between instances are provided through customizable access controls. IRIDA complements centralized systems, empowering local analytics and visualizations for genomics-based microbial pathogen investigations. IRIDA is currently transforming the Canadian public health ecosystem and is freely available at https://github.com/phac-nml/irida and www.irida.ca.nnImpact StatementWhole genome sequencing (WGS) is revolutionizing infectious disease analysis and surveillance due to its cost effectiveness, utility, and improved analytical power. To date, no "one-size-fits-all" genomics platform has been universally adopted, owing to differences in national (and regional) health information systems, data sharing policies, computational infrastructures, lack of interoperability and prohibitive costs. The Integrated Rapid Infectious Disease Analysis (IRIDA) platform is a user-friendly, decentralized, open-source bioinformatics and analytical web platform developed to support real-time infectious disease outbreak investigations using WGS data. IRIDA empowers public health, regulatory and clinical microbiology laboratory personnel to better incorporate WGS technology into routine operations by shielding them from the computational and analytical complexities of big data genomics. IRIDA is now routinely used as part of a validated suite of tools to support outbreak investigations in Canada. While IRIDA was designed to serve the needs of the Canadian public health system, it is generally applicable to any public health and multi-jurisdictional environment. IRIDA enables localized analyses but provides mechanisms and standard outputs to enable data sharing. This approach can help overcome pervasive challenges in real-time global infectious disease surveillance, investigation and control, resulting in faster responses, and ultimately, better public health outcomes.nnDATA SUMMARYO_LIData used to generate some of the figures in this manuscript can be found in the NCBI BioProject PRJNA305824.nC_LI
]]></description>
<dc:creator>Matthews, T. C.</dc:creator>
<dc:creator>Bristow, F. R.</dc:creator>
<dc:creator>Griffiths, E. J.</dc:creator>
<dc:creator>Petkau, A.</dc:creator>
<dc:creator>Adam, J.</dc:creator>
<dc:creator>Dooley, D.</dc:creator>
<dc:creator>Kruczkiewicz, P.</dc:creator>
<dc:creator>Curatcha, J.</dc:creator>
<dc:creator>Cabral, J.</dc:creator>
<dc:creator>Fornika, D.</dc:creator>
<dc:creator>Winsor, G. L.</dc:creator>
<dc:creator>Courtot, M.</dc:creator>
<dc:creator>Bertelli, C.</dc:creator>
<dc:creator>Roudgar, A.</dc:creator>
<dc:creator>Feijao, P.</dc:creator>
<dc:creator>Mabon, P.</dc:creator>
<dc:creator>Enns, E.</dc:creator>
<dc:creator>Thiessen, J.</dc:creator>
<dc:creator>Keddy, A.</dc:creator>
<dc:creator>Isaac-Renton, J.</dc:creator>
<dc:creator>Gardy, J. L.</dc:creator>
<dc:creator>Tang, P.</dc:creator>
<dc:creator>The IRIDA Consortium,</dc:creator>
<dc:creator>Carrico, J. A.</dc:creator>
<dc:creator>Chindelevitch, L.</dc:creator>
<dc:creator>Chauve, C.</dc:creator>
<dc:creator>Graham, M. R.</dc:creator>
<dc:creator>McArthur, A. G.</dc:creator>
<dc:creator>Taboada, E. N.</dc:creator>
<dc:creator>Beiko, R. G.</dc:creator>
<dc:creator>Brinkman, F. S.</dc:creator>
<dc:creator>Hsiao, W. W.</dc:creator>
<dc:creator>Van Domselaar, G.</dc:creator>
<dc:date>2018-07-31</dc:date>
<dc:identifier>doi:10.1101/381830</dc:identifier>
<dc:title><![CDATA[The Integrated Rapid Infectious Disease Analysis (IRIDA) Platform]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/266312v1?rss=1">
<title>
<![CDATA[
pyseer: a comprehensive tool for microbial pangenome-wide association studies 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/266312v1?rss=1"
</link>
<description><![CDATA[
SummaryGenome-wide association studies (GWAS) in microbes face different challenges to eukaryotes and have been addressed by a number of different methods. pyseer brings these techniques together in one package tailored to microbial GWAS, allows greater flexibility of the input data used, and adds new methods to interpret the association results.nnAvailability and Implementationpyseer is written in python and is freely available at https://github.com/mgalardini/pyseer, or can be installed through pip. Documentation and a tutorial are available at http://pyseer.readthedocs.io.nnContactjohn.lees@nyumc.org and marco@ebi.ac.uknnSupplementary informationSupplementary data are available online.
]]></description>
<dc:creator>Lees, J.</dc:creator>
<dc:creator>Galardini, M.</dc:creator>
<dc:creator>Bentley, S. D.</dc:creator>
<dc:creator>Weiser, J. N.</dc:creator>
<dc:creator>Corander, J.</dc:creator>
<dc:date>2018-02-15</dc:date>
<dc:identifier>doi:10.1101/266312</dc:identifier>
<dc:title><![CDATA[pyseer: a comprehensive tool for microbial pangenome-wide association studies]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/437459v1?rss=1">
<title>
<![CDATA[
Condensin II inactivation in interphase does not affect chromatin folding or gene expression 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/437459v1?rss=1"
</link>
<description><![CDATA[
Condensin complexes have been proposed to play a prominent role in interphase chromatin organization and control of gene expression. Here, we report that the deletion of the central condensin II kleisin subunit Ncaph2 in differentiated mouse hepatocytes does not lead to significant changes in chromosome organization or in gene expression. Both observations challenge current views that implicate condensin in interphase chromosomal domain formation and in enhancer-promoter interactions. Instead, we suggest that the previously reported effects of condensin perturbation may result from their structural role during mitosis, which might indirectly impact the re-establishment of interphase chromosomal architecture after cell division.
]]></description>
<dc:creator>Abdennur, N.</dc:creator>
<dc:creator>Schwarzer, W.</dc:creator>
<dc:creator>Pekowska, A.</dc:creator>
<dc:creator>Shaltiel, I. A.</dc:creator>
<dc:creator>Huber, W.</dc:creator>
<dc:creator>Haering, C. H.</dc:creator>
<dc:creator>Mirny, L.</dc:creator>
<dc:creator>Spitz, F.</dc:creator>
<dc:date>2018-10-07</dc:date>
<dc:identifier>doi:10.1101/437459</dc:identifier>
<dc:title><![CDATA[Condensin II inactivation in interphase does not affect chromatin folding or gene expression]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/195115v1?rss=1">
<title>
<![CDATA[
Global analysis of specificity determinants in eukaryotic protein kinases 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/195115v1?rss=1"
</link>
<description><![CDATA[
Protein kinases lie at the heart of cell signalling processes, constitute one of the largest human domain families and are often mutated in disease. Kinase target recognition at the active site is in part determined by a few amino acids around the phosphoacceptor residue. These preferences vary across kinases and despite the increased knowledge of target substrates little is known about how most preferences are encoded in the kinase sequence and how these preferences evolve. Here, we used alignment-based approaches to identify 30 putative specificity determinant residues (SDRs) for 16 preferences. These were studied using structural models and were validated by activity assays of mutant kinases. Mutation data from patient cancer samples revealed that kinase specificity is often targeted in cancer to a greater extent than catalytic residues. Throughout evolution we observed that kinase specificity is strongly conserved across orthologs but can diverge after gene duplication as illustrated by the evolution of the G-protein coupled receptor kinase family. The identified SDRs can be used to predict kinase specificity from sequence and aid in the interpretation of evolutionary or disease-related genomic variants.
]]></description>
<dc:creator>Bradley, D.</dc:creator>
<dc:creator>Vieitez, C.</dc:creator>
<dc:creator>Rajeeve, V.</dc:creator>
<dc:creator>Cutillas, P. R.</dc:creator>
<dc:creator>Beltrao, P.</dc:creator>
<dc:date>2017-09-27</dc:date>
<dc:identifier>doi:10.1101/195115</dc:identifier>
<dc:title><![CDATA[Global analysis of specificity determinants in eukaryotic protein kinases]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/076331v1?rss=1">
<title>
<![CDATA[
Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/076331v1?rss=1"
</link>
<description><![CDATA[
Orthology assignment is ideally suited for functional inference. However, because predicting orthology is computationally intensive at large scale, and most pipelines relatively in accessible, less precise homology-based functional transfer is still the default for (meta-)genome annotation. We therefore developed eggNOG-mapper, a tool for functional annotation of large sets of sequences based on fast orthology assignments using precomputed clusters and phylogenies from eggNOG. To validate our method, we benchmarked Gene Ontology predictions against two widely used homology-based approaches: BLAST and InterProScan. Compared to BLAST, eggNOG-mapper reduced by 7% the rate of false positive assignments, and increased by 19% the ratio of curated terms recovered over all terms assigned per protein. Compared to InterProScan, eggNOG-mapper achieved similar proteome coverage and precision, while predicting on average 32 more terms per protein and increasing by 26% the rate of curated terms recovered over total term assignments per protein. Through strict orthology assignments, eggNOG-mapper further renders more specific annotations than possible from domain similarity only (e.g. predicting gene family names). eggNOG-mapper runs ~15x than BLAST and at least 2.5x faster than InterProScan. The tool is available standalone or as an online service at http://eggnog-mapper.embl.de.
]]></description>
<dc:creator>Jaime Huerta-Cepas</dc:creator>
<dc:creator>Kristoffer Forslund</dc:creator>
<dc:creator>Damian Szklarczyk</dc:creator>
<dc:creator>Lars Juhl Jensen</dc:creator>
<dc:creator>Christian von Mering</dc:creator>
<dc:creator>Peer Bork</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-09-22</dc:date>
<dc:identifier>doi:10.1101/076331</dc:identifier>
<dc:title><![CDATA[Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-09-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/350991v1?rss=1">
<title>
<![CDATA[
Memote: A community-driven effort towards a standardized genome-scale metabolic model test suite 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/350991v1?rss=1"
</link>
<description><![CDATA[
Several studies have shown that neither the formal representation nor the functional requirements of genome-scale metabolic models (GEMs) are precisely defined. Without a consistent standard, comparability, reproducibility, and interoperability of models across groups and software tools cannot be guaranteed.nnHere, we present memote (https://github.com/opencobra/memote) an open-source software containing a community-maintained, standardized set of metabolic model tests. The tests cover a range of aspects from annotations to conceptual integrity and can be extended to include experimental datasets for automatic model validation. In addition to testing a model once, memote can be configured to do so automatically, i.e., while building a GEM. A comprehensive report displays the models performance parameters, which supports informed model development and facilitates error detection.nnMemote provides a measure for model quality that is consistent across reconstruction platforms and analysis software and simplifies collaboration within the community by establishing workflows for publicly hosted and version controlled models.
]]></description>
<dc:creator>Lieven, C.</dc:creator>
<dc:creator>Beber, M. E.</dc:creator>
<dc:creator>Olivier, B. G.</dc:creator>
<dc:creator>Bergmann, F. T.</dc:creator>
<dc:creator>Babaei, P.</dc:creator>
<dc:creator>Bartell, J. A.</dc:creator>
<dc:creator>Blank, L. M.</dc:creator>
<dc:creator>Chauhan, S.</dc:creator>
<dc:creator>Correia, K.</dc:creator>
<dc:creator>Diener, C.</dc:creator>
<dc:creator>Dräger, A.</dc:creator>
<dc:creator>Ebert, B. E.</dc:creator>
<dc:creator>Edirisinghe, J. N.</dc:creator>
<dc:creator>Fleming, R. M. T.</dc:creator>
<dc:creator>Garcia-Jimenez, B.</dc:creator>
<dc:creator>van Helvoirt, W.</dc:creator>
<dc:creator>Henry, C.</dc:creator>
<dc:creator>Hermjakob, H.</dc:creator>
<dc:creator>Herrgard, M. J.</dc:creator>
<dc:creator>Kim, H. U.</dc:creator>
<dc:creator>King, Z.</dc:creator>
<dc:creator>Koehorst, J. J.</dc:creator>
<dc:creator>Klamt, S.</dc:creator>
<dc:creator>Klipp, E.</dc:creator>
<dc:creator>Lakshmanan, M.</dc:creator>
<dc:creator>Le Novere, N.</dc:creator>
<dc:creator>Lee, D.-Y.</dc:creator>
<dc:creator>Lee, S. Y.</dc:creator>
<dc:creator>Lee, S.</dc:creator>
<dc:creator>Lewis, N. E.</dc:creator>
<dc:creator>Ma, H.</dc:creator>
<dc:creator>Machado, D.</dc:creator>
<dc:creator>Mahadevan, R.</dc:creator>
<dc:creator>Maia, P.</dc:creator>
<dc:creator>Mardinoglu, A.</dc:creator>
<dc:creator>Medlock, G. L.</dc:creator>
<dc:creator>Monk, J.</dc:creator>
<dc:creator>Nielsen, J.</dc:creator>
<dc:creator>Nielsen, L. K.</dc:creator>
<dc:creator>Nogales, J.</dc:creator>
<dc:creator>Nookaew, I.</dc:creator>
<dc:creator>Resendis, O.</dc:creator>
<dc:creator>Palsson, B.</dc:creator>
<dc:date>2018-06-21</dc:date>
<dc:identifier>doi:10.1101/350991</dc:identifier>
<dc:title><![CDATA[Memote: A community-driven effort towards a standardized genome-scale metabolic model test suite]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/080978v1?rss=1">
<title>
<![CDATA[
Benchmarking substrate-based kinase activity inference using phosphoproteomic data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/080978v1?rss=1"
</link>
<description><![CDATA[
MotivationPhosphoproteomic experiments are increasingly used to study the changes in signalling occurring across different conditions. It has been proposed that changes in phosphorylation of kinase target sites can be used to infer when a kinase activity is under regulation. However, these approaches have not yet been benchmarked due to a lack of appropriate benchmarking strategies.nnResultsWe curated public phosphoproteomic experiments to identify a gold standard dataset containing a total of 184 kinase-condition pairs where regulation is expected to occur. A list of kinase substrates was compiled and used to estimate changes in kinase activities using the following methods: Z-test, Kolmogorov Smirnov test, Wilcoxon rank sum test, gene set enrichment analysis (GSEA), and a multiple linear regression model (MLR). We also tested weighted variants of the Z-test, and GSEA that include information on kinase sequence specificity as proxy for affinity. Finally, we tested how the number of known substrates and the type of evidence (in vivo, in vitro or in silico) supporting these influence the predictions.nnConclusionsMost models performed well with the Z-test and the GSEA performing best as determined by the area under the ROc curve (Mean AUC=0.722). Weighting kinase targets by the kinase target sequence preference improves the results only marginally. However, the number of known substrates and the evidence supporting the interactions has a strong effect on the predictions.
]]></description>
<dc:creator>Hernandez-Armenta, C.</dc:creator>
<dc:creator>Ochoa, D.</dc:creator>
<dc:creator>Goncalves, E.</dc:creator>
<dc:creator>Saez-Rodriguez, J.</dc:creator>
<dc:creator>Beltrao, P.</dc:creator>
<dc:date>2016-10-14</dc:date>
<dc:identifier>doi:10.1101/080978</dc:identifier>
<dc:title><![CDATA[Benchmarking substrate-based kinase activity inference using phosphoproteomic data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-10-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/346833v1?rss=1">
<title>
<![CDATA[
Capturing variation impact on molecular interactions: the IMEx Consortium mutations data set 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/346833v1?rss=1"
</link>
<description><![CDATA[
The current wealth of genomic variation data identified at the nucleotide level has provided us with the challenge of understanding by which mechanisms amino acid variation affects cellular processes. These effects may manifest as distinct phenotypic differences between individuals or result in the development of disease. Physical interactions between molecules are the linking steps underlying most, if not all, cellular processes. Understanding the effects that amino acid variation of a molecules sequence has on its molecular interactions is a key step towards connecting a full mechanistic characterization of nonsynonymous variation to cellular phenotype. Here we present an open access resource created by IMEx database curators over 14 years, featuring 28,000 annotations fully describing the effect of individual point sequence changes on physical protein interactions. We describe how this resource was built, the formats in which the data content is provided and offer a descriptive analysis of the data set. The data set is publicly available through the IntAct website at www.ebi.ac.uk/intact/resources/datasets#mutationDs and is being enhanced with every monthly release.
]]></description>
<dc:creator>The IMEx Consortium curators,</dc:creator>
<dc:creator>del-Toro, N.</dc:creator>
<dc:creator>Duesbury, M.</dc:creator>
<dc:creator>Koch, M.</dc:creator>
<dc:creator>Perfetto, L.</dc:creator>
<dc:creator>Shrivastava, A.</dc:creator>
<dc:creator>Ochoa, D.</dc:creator>
<dc:creator>Wagih, O.</dc:creator>
<dc:creator>Pinero, J.</dc:creator>
<dc:creator>Kotlyar, M.</dc:creator>
<dc:creator>Chiara, P.</dc:creator>
<dc:creator>Beltrao, P.</dc:creator>
<dc:creator>Furlong, L. I.</dc:creator>
<dc:creator>Jurisica, I.</dc:creator>
<dc:creator>Hermjakob, H.</dc:creator>
<dc:creator>Orchard, S.</dc:creator>
<dc:creator>Porras Millan, P.</dc:creator>
<dc:date>2018-06-14</dc:date>
<dc:identifier>doi:10.1101/346833</dc:identifier>
<dc:title><![CDATA[Capturing variation impact on molecular interactions: the IMEx Consortium mutations data set]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/250803v1?rss=1">
<title>
<![CDATA[
Structural variability of EspG chaperones from mycobacterial ESX-1, ESX-3 and ESX-5 type VII secretion systems 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/250803v1?rss=1"
</link>
<description><![CDATA[
Type VII secretion systems (ESX) are responsible for transport of multiple proteins in mycobacteria. How different ESX systems achieve specific secretion of cognate substrates remains elusive. In the ESX systems, the cytoplasmic chaperone EspG forms complexes with heterodimeric PE-PPE substrates that are secreted from the cells or remain associated with the cell surface. Here we report the crystal structure of the EspG1 chaperone from the ESX-1 system determined using a fusion strategy with T4 lysozyme. EspG1 adopts a quasi 2-fold symmetric structure that consists of a central {beta}-sheet and two -helical bundles. Additionally, we describe the structures of EspG3 chaperones from four different crystal forms. Alternate conformations of the putative PE-PPE binding site are revealed by comparison of the available EspG3 structures. Analysis of EspG1, EspG3 and EspG5 chaperones using small-angle X-ray scattering (SAXS) reveals that EspG1 and EspG3 chaperones form dimers in solution, which we observed in several of our crystal forms. Finally, we propose a model of the ESX-3 specific EspG3-PE5-PPE4 complex based on the SAXS analysis.nnHighlightsO_LIThe crystal structure of EspG1 reveals the common architecture of the type VII secretion system chaperonesnC_LIO_LIStructures of EspG3 chaperones display a number of conformations that could reflect alternative substrate binding modesnC_LIO_LIEspG3 chaperones dimerize in solutionnC_LIO_LIA model of EspG3 in complex with its substrate PE-PPE dimer is proposed based on SAXS datanC_LI
]]></description>
<dc:creator>Tuukkanen, A. T.</dc:creator>
<dc:creator>Freire, D.</dc:creator>
<dc:creator>Chan, S.</dc:creator>
<dc:creator>Arbing, M. A.</dc:creator>
<dc:creator>Reed, R. W.</dc:creator>
<dc:creator>Evans, T. J.</dc:creator>
<dc:creator>Zenkeviciute, G.</dc:creator>
<dc:creator>Kim, J.</dc:creator>
<dc:creator>Kahng, S.</dc:creator>
<dc:creator>Sawaya, M. R.</dc:creator>
<dc:creator>Wilmanns, M.</dc:creator>
<dc:creator>Eisenberg, D.</dc:creator>
<dc:creator>Parret, A. H. A.</dc:creator>
<dc:creator>Korotkov, K. V.</dc:creator>
<dc:date>2018-01-24</dc:date>
<dc:identifier>doi:10.1101/250803</dc:identifier>
<dc:title><![CDATA[Structural variability of EspG chaperones from mycobacterial ESX-1, ESX-3 and ESX-5 type VII secretion systems]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/368498v1?rss=1">
<title>
<![CDATA[
Quantification of differential transcription factor activity and multiomic-based classification into activators and repressors: diffTF 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/368498v1?rss=1"
</link>
<description><![CDATA[
Transcription factor (TF) activity is an important read-out of cellular signalling pathways and thus to assess regulatory differences across conditions. However, current technologies lack the ability to simultaneously assess activity changes for multiple TFs and in particular to determine whether a specific TF acts globally as transcriptional repressor or activator. To this end, we introduce a widely applicable genome-wide method diffTF to assess differential TF activity and to classify TFs as activator or repressor (available at https://git.embl.de/grp-zaugg/diffTF). This is done by integrating any type of genome-wide chromatin accessibility data with RNA-Seq data and in-silico predicted TF binding sites. We corroborated the classification of TFs into repressors and activators by three independent analyses based on enrichments of active/repressive chromatin states, correlation of TF activity with gene expression, and activator-and repressor-specific chromatin footprints. To show the power of diffTF, we present two case studies: First, we applied diffTF in to a large ATAC-Seq/RNA-Seq dataset comparing mutated and unmutated chronic lymphocytic leukemia samples, where we identified dozens of known (40%) and potentially novel (60%) TFs that are differentially active. We were also able to classify almost half of them as either repressor and activator. Second, we applied diffTF to a small ATAC-Seq/RNA-Seq data set comparing two cell types along the hematopoietic differentiation trajectory (multipotent progenitors - MPP - versus granulocyte-macrophage progenitors - GMP). Here we identified the known drivers of differentiation and found that the majority of the differentially active TFs are transcriptional activators. Overall, diffTF was able to recover the known TFs in both case studies, additionally identified TFs that have been less well characterized in the given condition, and provides a classification of the TFs into transcriptional activators and repressors.
]]></description>
<dc:creator>Berest, I.</dc:creator>
<dc:creator>Arnold, C.</dc:creator>
<dc:creator>Reyes-Palomares, A.</dc:creator>
<dc:creator>Palla, G.</dc:creator>
<dc:creator>Rasmussen, K. D.</dc:creator>
<dc:creator>Helin, K.</dc:creator>
<dc:creator>Zaugg, J.</dc:creator>
<dc:date>2018-07-13</dc:date>
<dc:identifier>doi:10.1101/368498</dc:identifier>
<dc:title><![CDATA[Quantification of differential transcription factor activity and multiomic-based classification into activators and repressors: diffTF]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/388538v1?rss=1">
<title>
<![CDATA[
Three-dimensional nanostructure of an intact microglia cell 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/388538v1?rss=1"
</link>
<description><![CDATA[
Microglia are non-neuronal cells of the myeloid lineage that invade and take up long-term residence in the brain during development (Ginhoux et al. 2010) and are increasingly implicated in neuronal maturation, homeostasis, and pathology (Bessis et al. 2007; Paolicelli et al. 2011; Li et al. 2012; Aguzzi et al. 2013, Cunningham 2013, Cunningham et al. 2013). Since the early twentieth century several methods for staining and visualizing microglia have been developed. Scientists in Ramon y Cajals group (Achucarro 1913, Rio-Hortega 1919) pioneered these methods and their work led to the christening of microglia as the third element of the nervous system, distinct from astrocytes and neurons. More recently, a combination of imaging, genetic, and immunological tools has been used to visualize microglia in living brain (Davalos et al. 2005; Nimmerjahn et al. 2005). It was found that microglia are highly motile under resting conditions and rapidly respond to injuries (Kettenmann et al. 2011) suggesting a role for microglia in both brain homeostasis and pathology. Transmission Electron microscopy (TEM) has provided crucial complementary information on microglia morphology and physiology but until recently EM analyses have been limited to single or limited serial section studies (Tremblay et al. 2010; Paolicelli et al. 2011; Schafer et al. 2012; Tremblay et al. 2012; Sipe et al. 2016). TEM studies were successful in defining a set of morphological criteria for microglia: a polygonal nucleus with peripheral condensed chromatin, a relatively small cytoplasm with abundant presence of rough endoplasmic reticulum (RER), and a large volume of lysosomes and inclusions in the perikaryon. Recent advances in volumetric electron microscopy techniques allow for 3D reconstruction of large samples at nanometer-resolution, thus opening up new avenues for the understanding of cell biology and architecture in intact tissues. At the same time, correlative light and electron microscopy (CLEM) techniques have been extended to 3D brain samples to help navigate and identify critical molecular landmarks within large EM volumes (Briggman and Denk 2006; Maco et al. 2013; Blazquez-Llorca et al. 2015, Bosch et al. 2015). Here we present the first volumetric ultrastructural reconstruction of an entire mouse hippocampal microglia using serial block face scanning electron microscopy (SBEM). Using CLEM we have ensured the inclusion of both large, small, and filopodial microglia processes. Segmentation of the dataset allowed us to carry out a comprehensive inventory of microglia cell structures, including vesicles, organelles, membrane protrusions, and processes. This study provides a reference that can serve as a data mining resource for investigating microglia cell biology.
]]></description>
<dc:creator>Bolasco, G.</dc:creator>
<dc:creator>Weinhard, L.</dc:creator>
<dc:creator>Boissonnet, T.</dc:creator>
<dc:creator>Neujahr, R.</dc:creator>
<dc:creator>Gross, C. T.</dc:creator>
<dc:date>2018-08-09</dc:date>
<dc:identifier>doi:10.1101/388538</dc:identifier>
<dc:title><![CDATA[Three-dimensional nanostructure of an intact microglia cell]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/101279v1?rss=1">
<title>
<![CDATA[
Uniform Resolution of Compact Identifiers for Biomedical Data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/101279v1?rss=1"
</link>
<description><![CDATA[
Most biomedical data repositories issue locally-unique accessions numbers, but do not provide globally unique, machine-resolvable, persistent identifiers for their datasets, as required by publishers wishing to implement data citation in accordance with widely accepted principles. Local accessions may however be prefixed with a namespace identifier, providing global uniqueness. Such "compact identifiers" have been widely used in biomedical informatics to support global resource identification with local identifier assignment.nnWe report here on our project to provide robust support for machine-resolvable, persistent compact identifiers in biomedical data citation, by harmonizing the Identifiers.org and N2T.net (Name-To-Thing) meta-resolvers and extending their capabilities. Identifiers.org services hosted at the European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), and N2T.net services hosted at the California Digital Library (CDL), can now resolve any given identifier from over 600 source databases to its original source on the Web, using a common registry of prefix-based redirection rules.nnWe believe these services will be of significant help to publishers and others implementing persistent, machine-resolvable citation of research data.
]]></description>
<dc:creator>Wimalaratne, S.</dc:creator>
<dc:creator>Juty, N.</dc:creator>
<dc:creator>Kunze, J.</dc:creator>
<dc:creator>Janee, G.</dc:creator>
<dc:creator>McMurry, J. A.</dc:creator>
<dc:creator>Beard, N.</dc:creator>
<dc:creator>Jimenez, R.</dc:creator>
<dc:creator>Grethe, J.</dc:creator>
<dc:creator>Hermjakob, H.</dc:creator>
<dc:creator>Clark, T.</dc:creator>
<dc:date>2017-01-18</dc:date>
<dc:identifier>doi:10.1101/101279</dc:identifier>
<dc:title><![CDATA[Uniform Resolution of Compact Identifiers for Biomedical Data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-01-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/420638v1?rss=1">
<title>
<![CDATA[
Bleaching-independent, whole-cell, 3D and multi-color STED imaging with exchangeable fluorophores 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/420638v1?rss=1"
</link>
<description><![CDATA[
We demonstrate bleaching-independent STED microscopy using fluorogenic labels that reversibly bind to their target structure. A constant exchange of labels guarantees the removal of photobleached fluorophores and their replacement by intact fluorophores, thereby circumventing bleaching-related limitations of STED super-resolution imaging in fixed and living cells. Foremost, we achieve a constant labeling density and demonstrate a fluorescence signal for long and theoretically unlimited acquisition times. Using this concept, we demonstrate whole-cell, 3D, multi-color and live cell STED microscopy with up to 100 min acquisition time.
]]></description>
<dc:creator>Spahn, C.</dc:creator>
<dc:creator>Grimm, J. B.</dc:creator>
<dc:creator>Lavis, L. D.</dc:creator>
<dc:creator>Lampe, M.</dc:creator>
<dc:creator>Heilemann, M.</dc:creator>
<dc:date>2018-09-18</dc:date>
<dc:identifier>doi:10.1101/420638</dc:identifier>
<dc:title><![CDATA[Bleaching-independent, whole-cell, 3D and multi-color STED imaging with exchangeable fluorophores]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/459354v1?rss=1">
<title>
<![CDATA[
The transcriptome-wide landscape and modalities of EJC binding in adult Drosophila 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/459354v1?rss=1"
</link>
<description><![CDATA[
Splicing-dependent assembly of the exon junction complex (EJC) at canonical sites -20 to -24 nucleotides upstream of exon-exon junctions in mRNAs occurs in all higher eukaryotes and affects most major regulatory events in the life of a transcript. In mammalian cell cytoplasm, EJC is essential for efficient RNA surveillance, while in Drosophila the most essential cytoplasmic EJC function is in localization of oskar mRNA. Here we developed a method for isolation of protein complexes and associated RNA-targets (ipaRt), which provides a transcriptome-wide view of RNA binding sites of the fully assembled EJC in adult Drosophila. We find that EJC binds at canonical positions, with highest occupancy on mRNAs from genes comprising multiple splice sites and long introns. Moreover, the occupancy is highest at junctions adjacent to strong splice sites, CG-rich hexamers and RNA structures. These modalities have not been identified by previous studies in mammals, where more binding was seen at non-canonical positions. The most highly occupied transcripts in Drosophila have increased tendency to be maternally localized, and are more likely to derive from genes involved in differentiation or development. Taken together, we identify the RNA modalities that specify EJC assembly in Drosophila on a biologically coherent set of transcripts.
]]></description>
<dc:creator>Obrdlik, A.</dc:creator>
<dc:creator>Lin, G.</dc:creator>
<dc:creator>Haberman, N.</dc:creator>
<dc:creator>Ule, J.</dc:creator>
<dc:creator>Ephrussi, A.</dc:creator>
<dc:date>2018-11-04</dc:date>
<dc:identifier>doi:10.1101/459354</dc:identifier>
<dc:title><![CDATA[The transcriptome-wide landscape and modalities of EJC binding in adult Drosophila]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-11-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/462978v1?rss=1">
<title>
<![CDATA[
Iron deficiency affects early stages of embryonic hematopoiesis but not the endothelial to hematopoietic transition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/462978v1?rss=1"
</link>
<description><![CDATA[
Iron is an essential micronutrient for hematopoiesis and previous research suggested that iron deficiency in the pregnant female could cause anemia in the offspring. Since the development of all embryonic and adult blood cells begins in the embryo, we aimed to resolve the role of iron in embryonic hematopoiesis. For this purpose, we used an experimental system of mouse embryonic stem cells differentiation into embryonic hematopoietic progenitors. We modulated the iron status in cultures by adding either an iron chelator DFO for iron deficiency, or ferric ammonium citrate for iron excess, and followed the emergence of developing hematopoietic progenitors by flow cytometry. We found interestingly that iron deficiency by DFO did not block the endothelial to hematopoietic transition, the first step of hematopoiesis. However, it had a differential effect on the proliferation, survival and clonogenic capacity of hematopoietic progenitors. Surprisingly, iron deficiency affected erythro-myeloid Kitpos CD41+ progenitors significantly more than the primitive erythroid Kitneg CD41+. The Kitpos progenitors paradoxically died more, proliferated less and had more reduction in colony formation than Kitneg after 24 hours of DFO treatment. Kitpos progenitors expressed less transferrin-receptor on the cell surface and had less labile iron compared to Kitneg, which could reduce their capacity to compete for scarce iron and survive iron deficiency. We suggest that iron deficiency could disturb hematopoiesis already at an early embryonic stage by compromising survival, proliferation and differentiation of definitive hematopoietic progenitors.
]]></description>
<dc:creator>Shvartsman, M.</dc:creator>
<dc:creator>Bilican, S.</dc:creator>
<dc:creator>Lancrin, C.</dc:creator>
<dc:date>2018-11-05</dc:date>
<dc:identifier>doi:10.1101/462978</dc:identifier>
<dc:title><![CDATA[Iron deficiency affects early stages of embryonic hematopoiesis but not the endothelial to hematopoietic transition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-11-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/575282v1?rss=1">
<title>
<![CDATA[
Lumen expansion facilitates epiblast-primitive endoderm fate specification in the mouse blastocyst formation. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/575282v1?rss=1"
</link>
<description><![CDATA[
Mouse blastocyst formation involves lumen formation and cell fate specification. While many studies have investigated how the blastocyst cell lineages are specified through genetics and signaling, studies into the potential role of the fluid lumen have yet to be conducted. We discover that blastocyst fluid emerges by secretion of cytoplasmic vesicles to intercellular space in addition to trans-epithelial flow. We observe that the beginning of epiblast and primitive endoderm spatial segregation directly follows lumen coalescence. Notably, we show that perturbing lumen expansion by pharmacological and biophysical means impair the specification and spatial segregation of primitive endoderm cells within the blastocyst. Combined, our results suggest that blastocyst lumen expansion plays a critical role in guiding cell fate specification and positioning. As epithelial tissues typically form lumina, lumen expansion may provide a general mechanism of cell fate control in many tissues.
]]></description>
<dc:creator>Ryan, A. Q.</dc:creator>
<dc:creator>Chan, C. J.</dc:creator>
<dc:creator>Graner, F.</dc:creator>
<dc:creator>Hiiragi, T.</dc:creator>
<dc:date>2019-03-12</dc:date>
<dc:identifier>doi:10.1101/575282</dc:identifier>
<dc:title><![CDATA[Lumen expansion facilitates epiblast-primitive endoderm fate specification in the mouse blastocyst formation.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-12</prism:publicationDate>
<prism:section></prism:section>
</item>
</rdf:RDF>
