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	<title>bioRxiv Channel: Simons Foundation Autism Research Initiative (SFARI)</title>
	<link>https://biorxiv.org</link>
	<description>
	This feed contains articles for bioRxiv Channel "Simons Foundation Autism Research Initiative (SFARI)"
	</description>

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	<title>bioRxiv</title>
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	<link>https://biorxiv.org</link>
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	<item rdf:about="https://biorxiv.org/cgi/content/short/027771v1?rss=1">
<title>
<![CDATA[
Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/027771v1?rss=1"
</link>
<description><![CDATA[
Almost all genetic risk factors for autism spectrum disorders (ASDs) can be found in the general population, but the effects of that risk are unclear in people not ascertained for neuropsychiatric symptoms. Using several large ASD consortia and population based resources, we find genetic links between ASDs and typical variation in social behavior and adaptive functioning. This finding is evidenced through both inherited and de novo variation, indicating that multiple types of genetic risk for ASDs influence a continuum of behavioral and developmental traits, the severe tail of which can result in an ASD or other neuropsychiatric disorder diagnosis. A continuum model should inform the design and interpretation of studies of neuropsychiatric disease biology.
]]></description>
<dc:creator>Elise B Robinson</dc:creator>
<dc:creator>Beate St Pourcain</dc:creator>
<dc:creator>Verneri Anttila</dc:creator>
<dc:creator>Jack Kosmicki</dc:creator>
<dc:creator>Brendan Bulik-Sullivan</dc:creator>
<dc:creator>Jakob Grove</dc:creator>
<dc:creator>Julian Maller</dc:creator>
<dc:creator>Kaitlin E Samocha</dc:creator>
<dc:creator>Stephan Sanders</dc:creator>
<dc:creator>Stephan Ripke</dc:creator>
<dc:creator>Joanna Martin</dc:creator>
<dc:creator>Mads V Hollegaard</dc:creator>
<dc:creator>Thomas Werge</dc:creator>
<dc:creator>David M Hougaard</dc:creator>
<dc:creator>Benjamin M Neale</dc:creator>
<dc:creator>David Evans</dc:creator>
<dc:creator>David Skuse</dc:creator>
<dc:creator>Preben Bo Mortensen</dc:creator>
<dc:creator>Anders Borglum</dc:creator>
<dc:creator>Angelica Ronald</dc:creator>
<dc:creator>George Davey Smith</dc:creator>
<dc:creator>Mark J Daly</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-09-29</dc:date>
<dc:identifier>doi:10.1101/027771</dc:identifier>
<dc:title><![CDATA[Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-09-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/127043v1?rss=1">
<title>
<![CDATA[
Limited contribution of rare, noncoding variation to autism spectrum disorder from sequencing of 2,076 genomes in quartet families 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/127043v1?rss=1"
</link>
<description><![CDATA[
Genomic studies to date in autism spectrum disorder (ASD) have largely focused on newly arising mutations that disrupt protein coding sequence and strongly influence risk. We evaluate the contribution of noncoding regulatory variation across the size and frequency spectrum through whole genome sequencing of 519 ASD cases, their unaffected sibling controls, and parents. Cases carry a small excess of de novo (1.02-fold) noncoding variants, which is not significant after correcting for paternal age. Assessing 51,801 regulatory classes, no category is significantly associated with ASD after correction for multiple testing. The strongest signals are observed in coding regions, including structural variation not detected by previous technologies and missense variation. While rare noncoding variation likely contributes to risk in neurodevelopmental disorders, no category of variation has impact equivalent to loss-of-function mutations. Average effect sizes are likely to be smaller than that for coding variation, requiring substantially larger samples to quantify this risk.
]]></description>
<dc:creator>Werling, D. M.</dc:creator>
<dc:creator>Brand, H.</dc:creator>
<dc:creator>An, J.-Y.</dc:creator>
<dc:creator>Stone, M. R.</dc:creator>
<dc:creator>Glessner, J. T.</dc:creator>
<dc:creator>Zhu, L.</dc:creator>
<dc:creator>Collins, R. L.</dc:creator>
<dc:creator>Dong, S.</dc:creator>
<dc:creator>Layer, R. M.</dc:creator>
<dc:creator>Markenscoff-Papadimitriou, E.-C.</dc:creator>
<dc:creator>Farrell, A.</dc:creator>
<dc:creator>Schwartz, G. B.</dc:creator>
<dc:creator>Currall, B. B.</dc:creator>
<dc:creator>Dea, J.</dc:creator>
<dc:creator>Duhn, C.</dc:creator>
<dc:creator>Erdman, C.</dc:creator>
<dc:creator>Gilson, M.</dc:creator>
<dc:creator>Handsaker, R. E.</dc:creator>
<dc:creator>Kashin, S.</dc:creator>
<dc:creator>Klei, L.</dc:creator>
<dc:creator>Mandell, J. D.</dc:creator>
<dc:creator>Nowakowski, T. J.</dc:creator>
<dc:creator>Liu, Y.</dc:creator>
<dc:creator>Pochareddy, S.</dc:creator>
<dc:creator>Smith, L.</dc:creator>
<dc:creator>Walker, M. F.</dc:creator>
<dc:creator>Wang, H. Z.</dc:creator>
<dc:creator>Waterman, M. J.</dc:creator>
<dc:creator>He, X.</dc:creator>
<dc:creator>Kriegstein, A. R.</dc:creator>
<dc:creator>Rubenstein, J. L.</dc:creator>
<dc:creator>Sestan, N.</dc:creator>
<dc:creator>McCarroll, S. A.</dc:creator>
<dc:creator>Neale, B. M.</dc:creator>
<dc:creator>Coon, H.</dc:creator>
<dc:creator>Willsey, A. J.</dc:creator>
<dc:creator>Buxbaum, J. D.</dc:creator>
<dc:creator>Daly, M. J.</dc:creator>
<dc:creator>State, M. W.</dc:creator>
<dc:creator>Quinlan, A.</dc:creator>
<dc:creator>Marth, G. T.</dc:creator>
<dc:creator>Roeder, K.</dc:creator>
<dc:creator>Devli</dc:creator>
<dc:date>2017-04-13</dc:date>
<dc:identifier>doi:10.1101/127043</dc:identifier>
<dc:title><![CDATA[Limited contribution of rare, noncoding variation to autism spectrum disorder from sequencing of 2,076 genomes in quartet families]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/060335v1?rss=1">
<title>
<![CDATA[
Homozygous loss of autism-risk gene CNTNAP2 results in reduced local and long-range prefrontal functional connectivity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/060335v1?rss=1"
</link>
<description><![CDATA[
Functional connectivity aberrancies, as measured with resting-state fMRI (rsfMRI), have been consistently observed in the brain of autism spectrum disorders (ASD) patients. However, the genetic and neurobiological underpinnings of these findings remain unclear. Homozygous mutations in Contactin Associated Protein-like 2 (CNTNAP2), a neurexin-related cell-adhesion protein, are strongly linked to autism and epilepsy. Here we used rsfMRI to show that homozygous mice lacking Cntnap2 exhibit reduced long-range and local functional connectivity in prefrontal and midline brain "connectivity hubs". Long-range rsfMRI connectivity impairments affected heteromodal cortical regions and were prominent between fronto-posterior components of the mouse default-mode network (DMN), an effect that was associated with reduced social investigation, a core "autism trait" in mice. Notably, viral tracing revealed reduced frequency of prefrontal-projecting neural clusters in the cingulate cortex of Cntnap2-/- mutants, suggesting a possible contribution of defective mesoscale axonal wiring to the observed functional impairments. Macroscale cortico-cortical white matter organization appeared to be otherwise preserved in these animals. These findings reveal a key contribution of ASD-associated gene CNTNAP2 in modulating macroscale functional connectivity, and suggest that homozygous loss-of-function mutations in this gene may predispose to neurodevelopmental disorders and autism through a selective dysregulation of connectivity in integrative prefrontal areas.
]]></description>
<dc:creator>Adam Liska</dc:creator>
<dc:creator>Ryszard Gomolka</dc:creator>
<dc:creator>Mara Sabbioni</dc:creator>
<dc:creator>Alberto Galbusera</dc:creator>
<dc:creator>Stefano Panzeri</dc:creator>
<dc:creator>Maria Luisa Scattoni</dc:creator>
<dc:creator>Alessandro Gozzi</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-06-29</dc:date>
<dc:identifier>doi:10.1101/060335</dc:identifier>
<dc:title><![CDATA[Homozygous loss of autism-risk gene CNTNAP2 results in reduced local and long-range prefrontal functional connectivity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-06-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/122770v1?rss=1">
<title>
<![CDATA[
Brainwide Mapping Of Endogenous Serotonergic Transmission Via Chemogenetic-fMRI 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/122770v1?rss=1"
</link>
<description><![CDATA[
Serotonergic transmission affects behaviours and neuro-physiological functions via the orchestrated recruitment of distributed neural systems. It is however unclear whether serotonins modulatory effect entails a global regulation of brainwide neural activity, or is relayed and encoded by a set of primary functional substrates. Here we combine DREADD-based chemogenetics and mouse fMRI, an approach we term "chemo-fMRI", to causally probe the brainwide substrates modulated by phasic serotonergic activity. We describe the generation of a conditional knock-in mouse line that, crossed with serotonin-specific Cre-recombinase mice, allowed us to remotely stimulate serotonergic neurons during fMRI scans. We show that chemogenetic stimulation of the serotonin system does not affect global brain activity, but results in region-specific activation of a set of primary target regions encompassing parieto-cortical, hippocampal, and midbrain structures, as well as ventro-striatal components of the mesolimbic reward systems. Many of the activated regions also exhibit increased c-Fos immunostaining upon chemogenetic stimulation in freely-behaving mice, corroborating a neural origin for the observed functional signals. These results identify a set of regional substrates that act as primary functional targets of endogenous serotonergic stimulation, and establish causation between phasic activation of serotonergic neurons and regional fMRI signals. They further highlight a functional cross-talk between serotonin and mesolimbic dopamine systems hence providing a novel framework for understanding serotonin dependent functions and interpreting data obtained from human fMRI studies of serotonin modulating agents.
]]></description>
<dc:creator>Giorgi, A.</dc:creator>
<dc:creator>Migliarini, S.</dc:creator>
<dc:creator>Gritti, M.</dc:creator>
<dc:creator>Galbusera, A.</dc:creator>
<dc:creator>Maddaloni, G.</dc:creator>
<dc:creator>De Luca, M. A.</dc:creator>
<dc:creator>Tonini, R.</dc:creator>
<dc:creator>Gozzi, A.</dc:creator>
<dc:creator>Pasqualetti, M.</dc:creator>
<dc:date>2017-04-03</dc:date>
<dc:identifier>doi:10.1101/122770</dc:identifier>
<dc:title><![CDATA[Brainwide Mapping Of Endogenous Serotonergic Transmission Via Chemogenetic-fMRI]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/068866v1?rss=1">
<title>
<![CDATA[
Comprehensive Analysis of Two Shank3 and the Cacna1c Mouse Models of Autism Spectrum Disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/068866v1?rss=1"
</link>
<description><![CDATA[
To expand, analyze and extend published behavioral phenotypes relevant to autism spectrum disorder (ASD), we present a study of three ASD genetic mouse models: Fengs Shank3tm2Gfng model, hereafter Shank3/F, Jiangs Shank3tm1Yhj model, hereafter Shank3/J, and the Cacna1c deletion model. The Shank3/F and Shank3/J models mimick gene mutations associated with Phelan-Mcdermid syndrome and the Cacna1c model recapitulates the deletion underlying Timothy syndrome. The current study utilizes both standard and novel, computer-vision based behavioral tests, the same methdology used in our previously published companion report on the Cntnap2 null and 16p11.2 deletion models. Overall, some but not all behaviors replicated published findings. Those that replicated, such as social behavior and overgrooming in Shank3 models, also tended to be milder than previous reports. The Shank3/F model, and to a much lesser extent, the Shank3/J and Cacna1c models, showed hypoactivity and a general anxiety-like behavior triggered by external stimuli which pervaded social interactions. We did not detect deficits in a cognitive procedural learning test nor did we observe perseverative behavior in these models. We did, however, find differences in exploratory patterns of Cacna1c mutant mice suggestive of a behavioral effect in a social setting. In addition, Shank3/F but not Shank3/J KO or Cacna1c HET showed differences in sensory-gating. Discrepancies in our current results from previous reports may be dependent on subtle differences in testing conditions, housing enrichment, or background strain. Both positive and negative results from this study will be useful in identifying the most robust and replicable behavioral signatures within and across mouse models of autism. Understanding these phenotypes may shed light of which features to study when screening compounds for potential therapeutic interventions.
]]></description>
<dc:creator>Patricia A Kabitzke</dc:creator>
<dc:creator>Daniela Brunner</dc:creator>
<dc:creator>Dansha He</dc:creator>
<dc:creator>Pamela A Fazio</dc:creator>
<dc:creator>Kimberly Cox</dc:creator>
<dc:creator>Jane Sutphen</dc:creator>
<dc:creator>Lucinda Thiede</dc:creator>
<dc:creator>Emily Sabath</dc:creator>
<dc:creator>Taleen Hanania</dc:creator>
<dc:creator>Vadim Alexandrov</dc:creator>
<dc:creator>Randall Rasmusson</dc:creator>
<dc:creator>Will Spooren</dc:creator>
<dc:creator>Anirvan Ghosh</dc:creator>
<dc:creator>Pamela Feliciano</dc:creator>
<dc:creator>Barbara Biemans</dc:creator>
<dc:creator>Marta Benedetti</dc:creator>
<dc:creator>Alice Luo Clayton</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-09-02</dc:date>
<dc:identifier>doi:10.1101/068866</dc:identifier>
<dc:title><![CDATA[Comprehensive Analysis of Two Shank3 and the Cacna1c Mouse Models of Autism Spectrum Disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-09-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/100875v1?rss=1">
<title>
<![CDATA[
Excessive ERK-dependent synaptic clustering with enhanced motor learning in the MECP2 duplication syndrome mouse model of autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/100875v1?rss=1"
</link>
<description><![CDATA[
Autism-associated genetic mutations may produce altered learning abilities by perturbing the balance between stability and plasticity of synaptic connections in the brain. Here we report an increase in the stabilization of dendritic spines formed during repetitive motor learning in the mouse model of MECP2-duplication syndrome, a high-penetrance form of syndromic autism. This increased stabilization is mediated entirely by spines that form cooperatively in clusters. The number of clusters formed and stabilized predicts the mutants enhanced motor learning and memory phenotype, reminiscent of savant-like behaviors occasionally associated with autism.nnThe ERK signaling pathway, which promotes cooperative plasticity between spines, was found to be hyperactive in MECP2-duplication motor cortex specifically after training. Inhibition of ERK signaling normalizes clustered spine stabilization and rescues motor learning behavior in mutants. We conclude that learning-associated dendritic spine clustering stabilized by hyperactive ERK signaling drives abnormal motor learning and memory consolidation in this model of syndromic autism.
]]></description>
<dc:creator>Ash, R. T.</dc:creator>
<dc:creator>Buffington, S. A.</dc:creator>
<dc:creator>Park, J.</dc:creator>
<dc:creator>Costa-Mattioli, M.</dc:creator>
<dc:creator>Zoghbi, H. Y.</dc:creator>
<dc:creator>Smirnakis, S. M.</dc:creator>
<dc:date>2017-01-16</dc:date>
<dc:identifier>doi:10.1101/100875</dc:identifier>
<dc:title><![CDATA[Excessive ERK-dependent synaptic clustering with enhanced motor learning in the MECP2 duplication syndrome mouse model of autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-01-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/030270v1?rss=1">
<title>
<![CDATA[
Frequency and complexity of de novo structural mutation in autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/030270v1?rss=1"
</link>
<description><![CDATA[
Genetic studies of Autism Spectrum Disorder (ASD) have established that de novo duplications and deletions contribute to risk. However, ascertainment of structural variation (SV) has been restricted by the coarse resolution of current approaches. By applying a custom pipeline for SV discovery, genotyping and de novo assembly to genome sequencing of 235 subjects, 71 cases, 26 sibling controls and their parents, we present an atlas of 1.2 million SVs (5,213/genome), comprising 11 different classes. We demonstrate a high diversity of de novo mutations, a majority of which were undetectable by previous methods. In addition, we observe complex mutation clusters where combinations of de novo SVs, nucleotide substitutions and indels occurred as a single event. We estimate a high rate of structural mutation in humans (20%). Genetic risk for ASD is attributable to an elevated frequency of gene-disrupting de novo SVs but not an elevated rate of genome rearrangement.
]]></description>
<dc:creator>William M Brandler</dc:creator>
<dc:creator>Danny Antaki</dc:creator>
<dc:creator>Madhusudan Gujral</dc:creator>
<dc:creator>Amina Noor</dc:creator>
<dc:creator>Gabriel Rosanio</dc:creator>
<dc:creator>Timothy R Chapman</dc:creator>
<dc:creator>Daniel J Barrera</dc:creator>
<dc:creator>Guan Ning Lin</dc:creator>
<dc:creator>Dheeraj Malhotra</dc:creator>
<dc:creator>Amanda C Watts</dc:creator>
<dc:creator>Lawrence C Wong</dc:creator>
<dc:creator>Jasper A Estabillo</dc:creator>
<dc:creator>Therese E Gadomski</dc:creator>
<dc:creator>Oanh Hong</dc:creator>
<dc:creator>Karin V Fuentes Fajardo</dc:creator>
<dc:creator>Abhishek Bhandari</dc:creator>
<dc:creator>Renius Owen</dc:creator>
<dc:creator>Michael Baughn</dc:creator>
<dc:creator>Jeffrey Yuan</dc:creator>
<dc:creator>Terry Solomon</dc:creator>
<dc:creator>Alexandra G Moyzis</dc:creator>
<dc:creator>Stephan J Sanders</dc:creator>
<dc:creator>Gail E Reiner</dc:creator>
<dc:creator>Keith K Vaux</dc:creator>
<dc:creator>Charles M Strom</dc:creator>
<dc:creator>Kang Zhang</dc:creator>
<dc:creator>Alysson R Muotri</dc:creator>
<dc:creator>Natacha Akshoomoff</dc:creator>
<dc:creator>Suzanne M Leal</dc:creator>
<dc:creator>Karen Pierce</dc:creator>
<dc:creator>Eric Courchesne</dc:creator>
<dc:creator>Lilia M Iakoucheva</dc:creator>
<dc:creator>Christina Corsello</dc:creator>
<dc:creator>Jonathan Sebat</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-10-30</dc:date>
<dc:identifier>doi:10.1101/030270</dc:identifier>
<dc:title><![CDATA[Frequency and complexity of de novo structural mutation in autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-10-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/102327v1?rss=1">
<title>
<![CDATA[
Paternally inherited noncoding structural variants contribute to autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/102327v1?rss=1"
</link>
<description><![CDATA[
The genetic architecture of autism spectrum disorder (ASD) is known to consist of contributions from gene-disrupting de novo mutations and common variants of modest effect. We hypothesize that the unexplained heritability of ASD also includes rare inherited variants with intermediate effects. We investigated the genome-wide distribution and functional impact of structural variants (SVs) through whole genome analysis ([&ge;]30X coverage) of 3,169 subjects from 829 families affected by ASD. Genes that are intolerant to inactivating variants in the exome aggregation consortium (ExAC) were depleted for SVs in parents, specifically within fetal-brain promoters, UTRs and exons. Rare paternally-inherited SVs that disrupt promoters or UTRs were over-transmitted to probands (P = 0.0013) and not to their typically-developing siblings. Recurrent functional noncoding deletions implicate the gene LEO1 in ASD. Protein-coding SVs were also associated with ASD (P = 0.0025). Our results establish that rare inherited SVs predispose children to ASD, with differing contributions from each parent.
]]></description>
<dc:creator>Brandler, W. M.</dc:creator>
<dc:creator>Antaki, D.</dc:creator>
<dc:creator>Gujral, M.</dc:creator>
<dc:creator>Kleiber, M. L.</dc:creator>
<dc:creator>Maile, M. S.</dc:creator>
<dc:creator>Hong, O.</dc:creator>
<dc:creator>Chapman, T. R.</dc:creator>
<dc:creator>Tan, S.</dc:creator>
<dc:creator>Tandon, P.</dc:creator>
<dc:creator>Pang, T.</dc:creator>
<dc:creator>Tang, S. C.</dc:creator>
<dc:creator>Vaux, K. K.</dc:creator>
<dc:creator>Yang, Y.</dc:creator>
<dc:creator>Harrington, E.</dc:creator>
<dc:creator>Juul, S.</dc:creator>
<dc:creator>Turner, D. J.</dc:creator>
<dc:creator>Kingsmore, S. F.</dc:creator>
<dc:creator>Gleeson, J. G.</dc:creator>
<dc:creator>Kakaradov, B.</dc:creator>
<dc:creator>Telenti, A.</dc:creator>
<dc:creator>Venter, J. C.</dc:creator>
<dc:creator>Corominas, R.</dc:creator>
<dc:creator>Cormand, B.</dc:creator>
<dc:creator>Rueda, I.</dc:creator>
<dc:creator>Messer, K. S.</dc:creator>
<dc:creator>Nievergelt, C. M.</dc:creator>
<dc:creator>Arranz, M. J.</dc:creator>
<dc:creator>Courchesne, E.</dc:creator>
<dc:creator>Pierce, K.</dc:creator>
<dc:creator>Muotri, A. R.</dc:creator>
<dc:creator>Iakoucheva, L. M.</dc:creator>
<dc:creator>Hervas, A.</dc:creator>
<dc:creator>Corsello, C.</dc:creator>
<dc:creator>Sebat, J.</dc:creator>
<dc:date>2017-03-29</dc:date>
<dc:identifier>doi:10.1101/102327</dc:identifier>
<dc:title><![CDATA[Paternally inherited noncoding structural variants contribute to autism]]></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/083428v1?rss=1">
<title>
<![CDATA[
Exonic somatic mutations contribute risk for autism spectrum disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/083428v1?rss=1"
</link>
<description><![CDATA[
Genetic risk factors for autism spectrum disorder (ASD) have yet to be fully elucidated. Somatic mosaic mutations (SMMs) have been implicated in several neurodevelopmental disorders and overgrowth syndromes. Here, we systematically evaluate SMMs by leveraging whole-exome sequencing (WES) data on a large family-based ASD cohort, the Simons Simplex Collection (SSC). We find evidence that ~10% of previously published de novo mutations are potentially SMMs. When using a custom somatic calling pipeline, we recalled all SSC WES data. We validated high and low confidence mutation predictions for a subset of families with single molecule molecular inversion probes. With these validation data, we iteratively developed a high confidence calling approach integrating logistic regression modeling and additional heuristics and applied it to the full cohort. Surprisingly, we found evidence of significant synonymous SMM burden in probands, with mutations more likely to be close to splicing sites. Overall, we observe no strong evidence of missense SMM burden. However, we do observe nominally significant signal for missense SMMs in those families without germline mutations, which strengthens specifically in genes intolerant to mutations. In contrast to missense germline mutations, missense SMMs show potential enrichment for chromatin modifiers. We observe 7-10% of parental mosaics are transmitted germline to a child as occult de novo mutations, which has important implications for recurrence risk for families and potential subclinical ASD features. Finally, we find SMMs in previously implicated high-confidence ASD risk genes, including CHD2, CTNNB1, KMT2C, SYNGAP1, and RELN, further suggesting that this class of mutations contribute to population risk.
]]></description>
<dc:creator>Krupp, D. R.</dc:creator>
<dc:creator>Barnard, R. A.</dc:creator>
<dc:creator>Duffourd, Y.</dc:creator>
<dc:creator>Evans, S.</dc:creator>
<dc:creator>Bernier, R.</dc:creator>
<dc:creator>Riviere, J.-B.</dc:creator>
<dc:creator>Fombonne, E.</dc:creator>
<dc:creator>O'Roak, B. J.</dc:creator>
<dc:date>2016-10-26</dc:date>
<dc:identifier>doi:10.1101/083428</dc:identifier>
<dc:title><![CDATA[Exonic somatic mutations contribute risk for autism spectrum disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-10-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/089342v1?rss=1">
<title>
<![CDATA[
Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/089342v1?rss=1"
</link>
<description><![CDATA[
Autism spectrum disorder (ASD) risk is influenced by both common polygenic and de novo variation. The purpose of this analysis was to clarify the influence of common polygenic risk for ASDs and to identify subgroups of cases, including those with strong acting de novo variants, in which different types of polygenic risk are relevant. To do so, we extend the transmission disequilibrium approach to encompass polygenic risk scores, and introduce the polygenic transmission disequilibrium test. Using data from more than 6,400 children with ASDs and 15,000 of their family members, we show that polygenic risk for ASDs, schizophrenia, and greater educational attainment is over transmitted to children with ASDs in two independent samples, but not to their unaffected siblings. These findings hold independent of proband IQ. We find that common polygenic variation contributes additively to risk in ASD cases that carry a very strong acting de novo variant. Lastly, we find evide ...
]]></description>
<dc:creator>Weiner, D. J.</dc:creator>
<dc:creator>Wigdor, E. M.</dc:creator>
<dc:creator>Ripke, S.</dc:creator>
<dc:creator>Walters, R. K.</dc:creator>
<dc:creator>Kosmicki, J. A.</dc:creator>
<dc:creator>Grove, J.</dc:creator>
<dc:creator>Samocha, K. E.</dc:creator>
<dc:creator>Goldstein, J.</dc:creator>
<dc:creator>Okbay, A.</dc:creator>
<dc:creator>Bybjerg-Gauholm, J.</dc:creator>
<dc:creator>Werge, T.</dc:creator>
<dc:creator>Hougaard, D. M.</dc:creator>
<dc:creator>Taylor, J.</dc:creator>
<dc:creator>Skuse, D.</dc:creator>
<dc:creator>Devlin, B.</dc:creator>
<dc:creator>Anney, R.</dc:creator>
<dc:creator>Sanders, S.</dc:creator>
<dc:creator>Bishop, S.</dc:creator>
<dc:creator>Bo Mortensen, P.</dc:creator>
<dc:creator>Borglum, A.</dc:creator>
<dc:creator>Davey Smith, G.</dc:creator>
<dc:creator>Daly, M. J.</dc:creator>
<dc:creator>Robinson, E. B.</dc:creator>
<dc:date>2016-11-23</dc:date>
<dc:identifier>doi:10.1101/089342</dc:identifier>
<dc:title><![CDATA[Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-11-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/077578v1?rss=1">
<title>
<![CDATA[
Contribution of de novo non-coding mutations to autism and identification of risk genes from whole-genome sequencing of affected families 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/077578v1?rss=1"
</link>
<description><![CDATA[
Analysis of de novo mutations (DNMs) from sequencing data of nuclear families has identified risk genes for many complex diseases, including multiple neurodevelopmental and psychiatric disorders. Most of these efforts have focused on mutations in protein-coding sequences. Evidence from genome-wide association studies (GWAS) strongly suggests that variants important to human diseases often lie in non-coding regions. Extending DNM-based approaches to non-coding sequences is, however, challenging because the functional significance of non-coding mutations is difficult to predict. We propose a new statistical framework for analyzing DNMs from whole-genome sequencing (WGS) data. This method, TADA-Annotations (TADA-A), is a major advance of the TADA method we developed earlier for DNM analysis in coding regions. TADA-A is able to incorporate many functional annotations such as conservation and enhancer marks, learn from data which annotations are informative of pathogenic mutations and combine both coding and non-coding mutations at the gene level to detect risk genes. It also supports meta-analysis of multiple DNM studies, while adjusting for study-specific technical effects. We applied TADA-A to WGS data of [~]300 autism family trios across five studies, and discovered several new autism risk genes. The software is freely available for all research uses.
]]></description>
<dc:creator>Yuwen Liu</dc:creator>
<dc:creator>A. Ercument Cicek</dc:creator>
<dc:creator>Yanyu Liang</dc:creator>
<dc:creator>Jinchen Li</dc:creator>
<dc:creator>Rebecca A Muhle</dc:creator>
<dc:creator>Nicholas Knoblauch</dc:creator>
<dc:creator>Martina Krenzer</dc:creator>
<dc:creator>Yue Mei</dc:creator>
<dc:creator>Yan Wang</dc:creator>
<dc:creator>Yi Jiang</dc:creator>
<dc:creator>Even Geller</dc:creator>
<dc:creator>Zhongshan Li</dc:creator>
<dc:creator>Iuliana Ionita-Laza</dc:creator>
<dc:creator>Jinyu Wu</dc:creator>
<dc:creator>Kun Xia</dc:creator>
<dc:creator>James P Noonan</dc:creator>
<dc:creator>Zhong Sheng Sun</dc:creator>
<dc:creator>Xin He</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-09-26</dc:date>
<dc:identifier>doi:10.1101/077578</dc:identifier>
<dc:title><![CDATA[Contribution of de novo non-coding mutations to autism and identification of risk genes from whole-genome sequencing of affected families]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-09-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/058826v1?rss=1">
<title>
<![CDATA[
A cell type-specific expression signature predicts haploinsufficient autism-susceptibility genes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/058826v1?rss=1"
</link>
<description><![CDATA[
Recent studies have identified many genes with rare de novo mutations in autism, but a limited number of these have been conclusively established as disease-susceptibility genes due to lack of recurrence and confounding background mutations. Such extreme genetic heterogeneity severely limits recurrence-based statistical power even in studies with a large sample size. In addition, the cellular contexts in which these genomic lesions confer disease risks remain poorly understood. Here we investigate the use of cell-type specific expression profiles to differentiate mutations in autism patients or unaffected siblings. Using 24 distinct cell types isolated from the mouse central nervous system, we identified an expression signature shared by genes with likely gene disrupting (LGD) mutations detected by exome-sequencing in autism cases. The signature reflects haploinsufficiency of risk genes enriched in transcriptional and post-transcriptional regulators, with the strongest positive associations with specific types of neurons in different brain regions, including cortical neurons, cerebellar granule cells, and striatal medium spiny neurons. Based on this signature, we assigned a D score to all human genes to prioritize candidate autism-susceptibility genes. When applied to genes with only a single LGD mutation in cases, the D score achieved a precision of 40% as compared to the 15% baseline with a minimal loss in sensitivity. Further improvement was made by combining D score and mutation intolerance metrics from ExAC which were derived from orthogonal data sources. The ensemble model achieved precision of 60% and predicted 117 high-priority candidates. These prioritized lists can facilitate identification of additional autism-susceptibility genes.
]]></description>
<dc:creator>Chaolin Zhang</dc:creator>
<dc:creator>Yufeng Shen</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-06-14</dc:date>
<dc:identifier>doi:10.1101/058826</dc:identifier>
<dc:title><![CDATA[A cell type-specific expression signature predicts haploinsufficient autism-susceptibility genes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-06-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/069120v1?rss=1">
<title>
<![CDATA[
Exaggerated CpH Methylation in the Autism-Affected Brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/069120v1?rss=1"
</link>
<description><![CDATA[
The etiology of autism, a complex neurodevelopmental disorder, remains largely unexplained. Here, we explore the role of CpG and CpH (H=A, C, or T) methylation within autism-affected cortical brain tissue. While no individual site of methylation was significantly associated with autism after multi-test correction, methylated CpH di-nucleotides were markedly enriched in autism-affected brains (~2-fold enrichment at p <0.05 cut-off, p=0.002). These results further implicate epigenetic alterations in pathobiological mechanisms that underlie autism.
]]></description>
<dc:creator>Shannon E Ellis</dc:creator>
<dc:creator>Simone Gupta</dc:creator>
<dc:creator>Anna Moes</dc:creator>
<dc:creator>Andrew B West</dc:creator>
<dc:creator>Dan E Arking</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-08-11</dc:date>
<dc:identifier>doi:10.1101/069120</dc:identifier>
<dc:title><![CDATA[Exaggerated CpH Methylation in the Autism-Affected Brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-08-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/029132v1?rss=1">
<title>
<![CDATA[
Transcriptome Analysis of Cortical Tissue Reveals Shared Sets of Down-Regulated Genes in Autism and Schizophrenia 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/029132v1?rss=1"
</link>
<description><![CDATA[
Autism (AUT), Schizophrenia (SCZ), and bipolar disorder (BPD) are three highly heritable neuropsychiatric conditions. Clinical similarities and genetic overlap between the three disorders have been reported; however, the causes and the downstream effects of this overlap remain elusive. By analyzing transcriptomic RNA-Sequencing data generated from post-mortem cortical brain tissues from AUT, SCZ, BPD and control subjects, we have begun to characterize the extent of gene expression overlap between these disorders. We report that the AUT and SCZ transcriptomes are significantly correlated (p<0.001), while the other two cross disorder comparisons (AUT-BPD, SCZ-BPD) are not. Among AUT and SCZ, we find that the genes differentially expressed across disorders are involved in neurotransmission and synapse regulation. Despite lack of global transcriptomic overlap across all three disorders, we highlight two genes, IQSEC3 and COPS7A, which are significantly down-regulated compared to controls across all three disorders, suggesting either shared etiology or compensatory changes across these neuropsychiatric conditions. Finally, we tested for enrichment of genes differentially expressed across disorders in genetic association signals in AUT, SCZ or BPD, reporting lack of signal in any of the previously published GWAS. Together, these studies highlight the importance of examining gene expression from the primary tissue involved in neuropsychiatric conditions, cortical brain. We identify a shared role for altered neurotransmission and synapse regulation in AUT and SCZ, in addition to two genes that may more generally contribute to neurodevelopmental and neuropsychiatric conditions.
]]></description>
<dc:creator>Shannon E Ellis</dc:creator>
<dc:creator>Rebecca Panitch</dc:creator>
<dc:creator>Andrew West</dc:creator>
<dc:creator>Dan E Arking</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-10-14</dc:date>
<dc:identifier>doi:10.1101/029132</dc:identifier>
<dc:title><![CDATA[Transcriptome Analysis of Cortical Tissue Reveals Shared Sets of Down-Regulated Genes in Autism and Schizophrenia]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-10-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/049536v1?rss=1">
<title>
<![CDATA[
CNView: a visualization and annotation tool for copy number variation from whole-genome sequencing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/049536v1?rss=1"
</link>
<description><![CDATA[
SummaryCopy number variation (CNV) is a major component of structural differences between individual genomes. The recent emergence of population-scale whole-genome sequencing (WGS) datasets has enabled genome-wide CNV delineation. However, molecular validation at this scale is impractical, so visualization is an invaluable preliminary screening approach when evaluating CNVs. Standardized tools for visualization of CNVs in large WGS datasets are therefore in wide demand.nnMethods & ResultsTo address this demand, we developed a software tool, CNView, for normalized visualization, statistical scoring, and annotation of CNVs from population-scale WGS datasets. CNView surmounts challenges of sequencing depth variability between individual libraries by locally adapting to cohort-wide variance in sequencing uniformity at any locus. Importantly, CNView is broadly extensible to any reference genome assembly and most current WGS data types.nnAvailability and ImplementationCNView is written in R, is supported on OS X, MS Windows, and Linux, and is freely distributed under the MIT license. Source code and documentation are available from https://github.com/RCollins13/CNViewnnContacttalkowski@chgr.mgh.harvard.edu
]]></description>
<dc:creator>Ryan L Collins</dc:creator>
<dc:creator>Matthew R Stone</dc:creator>
<dc:creator>Harrison Brand</dc:creator>
<dc:creator>Joseph T Glessner</dc:creator>
<dc:creator>Michael E Talkowski</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-04-20</dc:date>
<dc:identifier>doi:10.1101/049536</dc:identifier>
<dc:title><![CDATA[CNView: a visualization and annotation tool for copy number variation from whole-genome sequencing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-04-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/134957v1?rss=1">
<title>
<![CDATA[
High-risk Autism Spectrum Disorder Utah pedigrees: a novel Shared Genomic Segments analysis. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/134957v1?rss=1"
</link>
<description><![CDATA[
Progress in gene discovery for Autism Spectrum Disorder (ASD) has been rapid over the past decade, with major successes in validation of risk of predominantly rare, penetrant, de novo and inherited mutations in over 100 genes (de Rubies et al., 2015; Sanders et al., 2015). However, the majority of individuals with ASD diagnoses do not carry a rare, penetrant genetic risk factor. In fact, recent estimates suggest that most of the genetic liability of ASD is due to as yet undiscovered common, less penetrant inherited variation (Gaugler et al., 2014) which is much more difficult to detect. The study of extended, high-risk families adds significant information in our search for these common inherited risk factors. Here, we present results of a new, powerful pedigree analysis method (Shared Genomic Segments--SGS) on three large families from the Utah Autism Research Program. The method improves upon previous methods by allowing for within-family heterogeneity, and identifying exact region boundaries and subsets of cases who share for targeted follow-up analyses. Our SGS analyses identified one genome-wide significant shared segment on chromosome 17 (q21.32, p=1.47x10-8). Additional regions with suggestive evidence were identified on chromosomes 3, 4, 6, 8, 11, 13, 14, 15, and 18. Several of these segments showed evidence of sharing across families. Genes of interest in these regions include ATP8A1, DOCK3, CACNA2D2, ITGB3, AMBRA1, FOLH1, DGKZ, MTHFS, ARNT2, BTN2A2, BTN3A1, BTN3A3, BTN2A1, and BTN1A1. We are exploring multiple other lines of evidence to follow up these implicated regions and genes.
]]></description>
<dc:creator>Darlington, T.</dc:creator>
<dc:creator>Bilder, D.</dc:creator>
<dc:creator>Morgan, J.</dc:creator>
<dc:creator>Jerominski, L.</dc:creator>
<dc:creator>Rajamanickam, V.</dc:creator>
<dc:creator>Sargent, R.</dc:creator>
<dc:creator>Camp, N. J.</dc:creator>
<dc:creator>Coon, H. H.</dc:creator>
<dc:date>2017-05-09</dc:date>
<dc:identifier>doi:10.1101/134957</dc:identifier>
<dc:title><![CDATA[High-risk Autism Spectrum Disorder Utah pedigrees: a novel Shared Genomic Segments analysis.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/141200v1?rss=1">
<title>
<![CDATA[
Damaging Mutations are Associated with Diminished Motor Skills and IQ in Children on the Autism Spectrum 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/141200v1?rss=1"
</link>
<description><![CDATA[
In individuals with Autism Spectrum Disorder (ASD), de novo mutations have previously been shown to be significantly correlated with lower IQ, but not with the core characteristics of ASD: deficits in social communication and interaction, and restricted interests and repetitive patterns of behavior. We extend these findings by demonstrating in the Simons Simplex Collection that damaging de novo mutations in ASD individuals are also significantly and convincingly correlated with measures of impaired motor skills. This correlation is not explained by a correlation between IQ and motor skills. We find that IQ and motor skills are distinctly associated with damaging mutations and, in particular, that motor skills are a more sensitive indicator of mutational severity, as judged by the type and its gene target. We use this finding to propose a combined classification of phenotypic severity: mild (little impairment of both), moderate (impairment mainly to motor skills) and severe (impairment of both).
]]></description>
<dc:creator>Buja, A.</dc:creator>
<dc:creator>Volfovsky, N.</dc:creator>
<dc:creator>Krieger, A.</dc:creator>
<dc:creator>Lord, C.</dc:creator>
<dc:creator>Lash, A.</dc:creator>
<dc:creator>Wigler, M.</dc:creator>
<dc:creator>Iossifov, I.</dc:creator>
<dc:date>2017-05-23</dc:date>
<dc:identifier>doi:10.1101/141200</dc:identifier>
<dc:title><![CDATA[Damaging Mutations are Associated with Diminished Motor Skills and IQ in Children on the Autism Spectrum]]></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/137471v1?rss=1">
<title>
<![CDATA[
De novo indels within introns contribute to ASD incidence 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/137471v1?rss=1"
</link>
<description><![CDATA[
Copy number profiling and whole-exome sequencing has allowed us to make remarkable progress in our understanding of the genetics of autism over the past ten years, but there are major aspects of the genetics that are unresolved. Through whole-genome sequencing, additional types of genetic variants can be observed. These variants are abundant and to know which are functional is challenging. We have analyzed whole-genome sequencing data from 510 of the Simons Simplex Collections quad families and focused our attention on intronic variants. Within the introns of 546 high-quality autism target genes, we identified 63 de novo indels in the affected and only 37 in the unaffected siblings. The difference of 26 events is significantly larger than expected (p-val = 0.01) and using reasonable extrapolation shows that de novo intronic indels can contribute to at least 10% of simplex autism. The significance increases if we restrict to the half of the autism targets that are intolerant to damaging variants in the normal human population, which half we expect to be even more enriched for autism genes. For these 273 targets we observe 43 and 20 events in affected and unaffected siblings, respectively (p-value of 0.005). There was no significant signal in the number of de novo intronic indels in any of the control sets of genes analyzed. We see no signal from de novo substitutions in the introns of target genes.
]]></description>
<dc:creator>Munoz, A.</dc:creator>
<dc:creator>Yamrom, B.</dc:creator>
<dc:creator>Lee, Y.-h.</dc:creator>
<dc:creator>Andrews, P.</dc:creator>
<dc:creator>Marks, S.</dc:creator>
<dc:creator>Lin, K.-T.</dc:creator>
<dc:creator>Wang, Z.</dc:creator>
<dc:creator>Krainer, A. R.</dc:creator>
<dc:creator>Darnell, R. B.</dc:creator>
<dc:creator>Wigler, M.</dc:creator>
<dc:creator>Iossifov, I.</dc:creator>
<dc:date>2017-05-24</dc:date>
<dc:identifier>doi:10.1101/137471</dc:identifier>
<dc:title><![CDATA[De novo indels within introns contribute to ASD incidence]]></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/142265v1?rss=1">
<title>
<![CDATA[
Native KCC2 Interactome Reveals PACSIN1 As A Critical Regulator Of Synaptic Inhibition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/142265v1?rss=1"
</link>
<description><![CDATA[
KCC2 is a neuron-specific K+-Cl- cotransporter essential for establishing the Cl- gradient required for hyperpolarizing inhibition. KCC2 is highly localized to excitatory synapses where it regulates spine morphogenesis and AMPA receptor confinement. Aberrant KCC2 function contributes to numerous human neurological disorders including epilepsy and neuropathic pain. Using unbiased functional proteomics, we identified the KCC2-interactome in the mouse brain to determine KCC2-protein interactions that regulate KCC2 function. Our analysis revealed that KCC2 interacts with a diverse set of proteins, and its most predominant interactors play important roles in postsynaptic receptor recycling. The most abundant KCC2 interactor is a neuronal endocytic regulatory protein termed PACSIN1 (SYNDAPIN1). We verified the PACSIN1-KCC2 interaction biochemically and demonstrated that shRNA knockdown of PACSIN1 in hippocampal neurons significantly increases KCC2 expression and hyperpolarizes the reversal potential for Cl-. Overall, our global native-KCC2 interactome and subsequent characterization revealed PACSIN1 as a novel and potent negative regulator of KCC2.
]]></description>
<dc:creator>Mahadevan, V.</dc:creator>
<dc:creator>Khademullah, C. S.</dc:creator>
<dc:creator>Dargaei, Z.</dc:creator>
<dc:creator>Chevrier, J.</dc:creator>
<dc:creator>Uvarov, P.</dc:creator>
<dc:creator>Kwan, J.</dc:creator>
<dc:creator>Bagshaw, R. D.</dc:creator>
<dc:creator>Pawson, T.</dc:creator>
<dc:creator>Emili, A.</dc:creator>
<dc:creator>De Koninck, Y.</dc:creator>
<dc:creator>Anggono, V.</dc:creator>
<dc:creator>Airaksinen, M.</dc:creator>
<dc:creator>Woodin, M. A.</dc:creator>
<dc:date>2017-05-25</dc:date>
<dc:identifier>doi:10.1101/142265</dc:identifier>
<dc:title><![CDATA[Native KCC2 Interactome Reveals PACSIN1 As A Critical Regulator Of Synaptic Inhibition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/143552v1?rss=1">
<title>
<![CDATA[
Distinctive Behavioural Anomalies, Structural Brain Phenotypes And Cortical Hyper-Connectivity In Chd8-Deficient Mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/143552v1?rss=1"
</link>
<description><![CDATA[
Truncating CHD8 mutations are amongst the highest confidence risk factors for autism spectrum disorders (ASD) identified to date. To investigate how reduced Chd8 gene dosage may disrupt brain development and predispose individuals to ASD, we generated a Chd8 heterozygous mouse model. In line with clinical observations, we found that Chd8 heterozygous mice displayed subtle brain hyperplasia and hypertelorism, coupled with increased postnatal brain weight. Chd8 heterozygous mice displayed anomalous behaviours, but autism-like social deficits, repetitive and restricted behaviours were not present. Only minor gene expression changes were observed in the embryonic neocortex at E12.5, with more pronounced gene expression changes in postnatal cortex at P5. Differentially expressed genes showed highly significant enrichment for known autism candidates. Amongst the down-regulated transcripts, genes involved in cell adhesion and axon guidance were particularly prominent, implicating impaired connectivity as a potential mechanism underlying the ASD phenotype. To probe this further, we performed resting state functional fMRI and found increased synchronised activity in cortico-hippocampal and auditory-parietal networks, hinting at impaired sensory processing. Together, these data show that Chd8 heterozygous mice recapitulate key clinical features found in patients with CHD8 mutations and show a unique combination of behavioural phenotypes, which may be underpinned by a distinctive disruption of brain connectivity and sensory processing.
]]></description>
<dc:creator>Suetterlin, P.</dc:creator>
<dc:creator>Hurley, S.</dc:creator>
<dc:creator>Mohan, C.</dc:creator>
<dc:creator>Riegman, K. L. H.</dc:creator>
<dc:creator>Caruso, A.</dc:creator>
<dc:creator>Pagani, M.</dc:creator>
<dc:creator>Ellegood, J.</dc:creator>
<dc:creator>Galbusera, A.</dc:creator>
<dc:creator>Crespo-Enriquez, I.</dc:creator>
<dc:creator>Michetti, C.</dc:creator>
<dc:creator>Ellingford, R.</dc:creator>
<dc:creator>Brock, O.</dc:creator>
<dc:creator>Delogu, A.</dc:creator>
<dc:creator>Francis-West, P.</dc:creator>
<dc:creator>Lerch, J. P.</dc:creator>
<dc:creator>Scattoni, M. L.</dc:creator>
<dc:creator>Gozzi, A.</dc:creator>
<dc:creator>Fernandes, C.</dc:creator>
<dc:creator>Basson, A.</dc:creator>
<dc:date>2017-05-29</dc:date>
<dc:identifier>doi:10.1101/143552</dc:identifier>
<dc:title><![CDATA[Distinctive Behavioural Anomalies, Structural Brain Phenotypes And Cortical Hyper-Connectivity In Chd8-Deficient Mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/148296v1?rss=1">
<title>
<![CDATA[
Indexcov: fast coverage quality control for whole-genome sequencing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/148296v1?rss=1"
</link>
<description><![CDATA[
The BAM1 and CRAM2 formats provide a supplementary linear index that facilitates rapid access to sequence alignments in arbitrary genomic regions. Comparing consecutive entries in a BAM or CRAM index allows one to infer the number of alignment records per genomic region for use as an effective proxy of sequence depth in each genomic region. Based on these properties, we have developed indexcov, an efficient estimator of whole-genome sequencing coverage to rapidly identify samples with aberrant coverage profiles, reveal large scale chromosomal anomalies, recognize potential batch effects, and infer the sex of a sample. Indexcov is available at: https://github.com/brentp/goleft under the MIT license.
]]></description>
<dc:creator>Pedersen, B. S.</dc:creator>
<dc:creator>Collins, R. L.</dc:creator>
<dc:creator>Talkwoski, M. E.</dc:creator>
<dc:creator>Quinlan, A. R.</dc:creator>
<dc:date>2017-06-09</dc:date>
<dc:identifier>doi:10.1101/148296</dc:identifier>
<dc:title><![CDATA[Indexcov: fast coverage quality control for whole-genome sequencing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/149740v1?rss=1">
<title>
<![CDATA[
Mutational sequencing for accurate count and long-range assembly 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/149740v1?rss=1"
</link>
<description><![CDATA[
We introduce a new protocol, mutational sequencing or muSeq, which randomly deaminates unmethylated cytosines at a fixed and tunable rate. The muSeq protocol marks each initial template molecule with a unique mutation signature that is present in every copy of the template, and in every fragmented copy of a copy. In the sequenced read data, this signature is observed as a unique pattern of C-to-T or G-to-A nucleotide conversions. Clustering reads with the same conversion pattern enables accurate count and long-range assembly of initial template molecules from short-read sequence data. We explore count and low-error sequencing by profiling a 135,000 fragment PstI representation, demonstrating that muSeq improves copy number inference and significantly reduces sporadic sequencer error. We explore long-range assembly in the context of cDNA, generating contiguous transcript clusters greater than 3,000 bp in length. The muSeq assemblies reveal transcriptional diversity not observable from short-read data alone.
]]></description>
<dc:creator>Kumar, V.</dc:creator>
<dc:creator>Rosenbaum, J.</dc:creator>
<dc:creator>Wang, Z.</dc:creator>
<dc:creator>Forcier, T.</dc:creator>
<dc:creator>Ronemus, M.</dc:creator>
<dc:creator>Wigler, M.</dc:creator>
<dc:creator>Levy, D.</dc:creator>
<dc:date>2017-06-13</dc:date>
<dc:identifier>doi:10.1101/149740</dc:identifier>
<dc:title><![CDATA[Mutational sequencing for accurate count and long-range assembly]]></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/152462v1?rss=1">
<title>
<![CDATA[
Normal CA1 place fields but discoordinated network discharge in a Fmr1-null mouse model of fragile X syndrome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/152462v1?rss=1"
</link>
<description><![CDATA[
Silence of FMR1 causes loss of fragile X mental retardation protein (FMRP) and dysregulated translation at synapses, resulting in the intellectual disability and autistic symptoms of Fragile X Syndrome (FXS). Synaptic dysfunction hypotheses for how intellectual disabilities like cognitive inflexibility arise in FXS, predict impaired neural coding in the absence of FMRP. We tested the prediction by comparing hippocampus place cells in wild-type and FXS-model mice. Experience-driven CA1 synaptic function and synaptic plasticity changes are excessive in Fmr1-null mice, but CA1 place fields are normal. However, Fmr1-null discharge relationships to local field potential oscillations are abnormally weak, stereotyped, and homogeneous; also discharge coordination within Fmr1-null place cell networks is weaker and less reliable than wild-type. Rather than disruption of single-cell neural codes, these findings point to invariant tuning of single-cell responses and inadequate discharge coordination within neural ensembles as a pathophysiological basis of cognitive inflexibility in FXS.
]]></description>
<dc:creator>Sparks, F. T.</dc:creator>
<dc:creator>Talbot, Z. N.</dc:creator>
<dc:creator>Dvorak, D.</dc:creator>
<dc:creator>Curran, B. M.</dc:creator>
<dc:creator>Alarcon, J. M.</dc:creator>
<dc:creator>Fenton, A. A.</dc:creator>
<dc:date>2017-06-20</dc:date>
<dc:identifier>doi:10.1101/152462</dc:identifier>
<dc:title><![CDATA[Normal CA1 place fields but discoordinated network discharge in a Fmr1-null mouse model of fragile X syndrome]]></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/152488v1?rss=1">
<title>
<![CDATA[
Control of recollection by slow gamma dominating medium gamma in hippocampus CA1 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/152488v1?rss=1"
</link>
<description><![CDATA[
Behavior is used to assess memory and cognitive deficits in animals like Fmrl-null mice that model Fragile X Syndrome, but behavior is a proxy for unknown neural events that define cognitive variables like recollection. We identified an electrophysiological signature of recollection in mouse dorsal CA1 hippocampus. During a shocked-place avoidance task, slow gamma (SG: 30-50 Hz) dominates mid-frequency gamma (MG: 70-90 Hz) oscillations 2-3 seconds before successful avoidance, but not failures. Wild-type but not Fmrl-null mice rapidly adapt to relocating the shock; concurrently, SG/MG maxima (SGdominance) decrease in wild-type but not in cognitively inflexible Fmrl-null mice. During SGdominance, putative pyramidal cell ensembles represent distant locations; during place avoidance, these are avoided places. During shock relocation, wild-type ensembles represent distant locations near the currently-correct shock zone but Fmrl-null ensembles represent the formerly-correct zone. These findings indicate that recollection occurs when CA1 slow gamma dominates mid-frequency gamma, and that accurate recollection of inappropriate memories explains Fmrl-null cognitive inflexibility.
]]></description>
<dc:creator>Dvorak, D.</dc:creator>
<dc:creator>Radwan, B.</dc:creator>
<dc:creator>Sparks, F. T.</dc:creator>
<dc:creator>Talbot, Z. N.</dc:creator>
<dc:creator>Fenton, A. A.</dc:creator>
<dc:date>2017-06-20</dc:date>
<dc:identifier>doi:10.1101/152488</dc:identifier>
<dc:title><![CDATA[Control of recollection by slow gamma dominating medium gamma in hippocampus CA1]]></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/155382v1?rss=1">
<title>
<![CDATA[
Distinct contributions of three GABAergic interneuron populations to a mouse model of Rett Syndrome. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/155382v1?rss=1"
</link>
<description><![CDATA[
BackgroundRett Syndrome is a devastating neurodevelopmental disorder resulting from mutations in the gene MeCP2. MeCP2 is a transcriptional regulator active in many cell types throughout the brain. However, mutations of MeCP2 restricted to GABAergic cell types largely replicate the behavioral phenotypes associated with mouse models of Rett Syndrome, suggesting a key role for inhibitory interneurons in the pathophysiology underlying this disorder.nnMethodsWe generated conditional deletions of MeCP2 from each of three major classes of GABAergic interneurons, the parvalbumin (PV), somatostatin (SOM), and vasoactive intestinal peptide (VIP)-expressing cells, along with a pan-interneuron deletion from all three GABAergic populations. We examined seizure incidence, mortality, and performance on several key behavioral assays.nnResultsWe find that each interneuron class makes a contribution to the seizure phenotype associated with Rett Syndrome. PV, SOM, and VIP interneurons made partially overlapping contributions to deficits in motor behaviors. We find little evidence for elevated anxiety associated with any of the conditional deletions. However, MeCP2 deletion from VIP interneurons causes a unique deficit in marble burying. Furthermore, VIP interneurons make a distinct contribution to deficits in social behavior.nnConclusionsWe find an unanticipated contribution of VIP interneuron dysfunction to the MeCP2 loss-of-function model of Rett Syndrome. Together, our findings suggest a complex interaction between GABAergic dysfunction and behavioral phenotypes in this neurodevelopmental disorder.
]]></description>
<dc:creator>Mossner, J.</dc:creator>
<dc:creator>Batista-Brito, R.</dc:creator>
<dc:creator>Pant, R.</dc:creator>
<dc:creator>Cardin, J.</dc:creator>
<dc:date>2017-06-25</dc:date>
<dc:identifier>doi:10.1101/155382</dc:identifier>
<dc:title><![CDATA[Distinct contributions of three GABAergic interneuron populations to a mouse model of Rett Syndrome.]]></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/156216v1?rss=1">
<title>
<![CDATA[
An insula-central amygdala circuit for behavioral inhibition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/156216v1?rss=1"
</link>
<description><![CDATA[
Predicting which substances are suitable for consumption during foraging is critical for animals to survive. While food-seeking behavior is extensively studied, the neural circuit mechanisms underlying avoidance of potentially poisonous substances remain poorly understood. Here we examined the role of the insular cortex (IC) to central amygdala (CeA) circuit in the establishment of such avoidance behavior. Using anatomic tracing approaches combined with optogenetics-assisted circuit mapping, we found that the gustatory region of the IC sends direct excitatory projections to the lateral division of the CeA (CeL), making monosynaptic excitatory connections with distinct populations of CeL neurons. Specific inhibition of neurotransmitter release from the CeL-projecting IC neurons prevented mice from acquiring the "no-go" response, while leaving the "go" response largely unaffected in a tastant (sucrose/quinine)-reinforced "go/no-go" task. Furthermore, selective activation of the IC-CeL pathway with optogenetics drove unconditioned lick suppression in thirsty animals, induced aversive responses, and was sufficient to instruct conditioned action suppression in response to a cue predicting the optogenetic activation. These results indicate that activity in the IC-CeL circuit is necessary for establishing anticipatory avoidance responses to an aversive tastant, and is also sufficient to drive learning of such anticipatory avoidance. This function of the IC-CeL circuit is likely important for guiding avoidance of substances with unpleasant tastes during foraging in order to minimize the chance of being poisoned.nnSignificance StatementThe ability to predict which substances are suitable for consumption is critical for survival. Here we found that activity in the insular cortex (IC) to central amygdala (CeA) circuit is necessary for establishing avoidance responses to an unpleasant tastant, and is also sufficient to drive learning of such avoidance responses. These results suggest that the IC-CeA circuit is critical for behavioral inhibition in anticipation of potentially poisonous substances during foraging.
]]></description>
<dc:creator>Schiff, H. C.</dc:creator>
<dc:creator>Bouhuis, A. L.</dc:creator>
<dc:creator>Yu, K.</dc:creator>
<dc:creator>Penzo, M. A.</dc:creator>
<dc:creator>Li, H.</dc:creator>
<dc:creator>He, M.</dc:creator>
<dc:creator>Li, B.</dc:creator>
<dc:date>2017-06-26</dc:date>
<dc:identifier>doi:10.1101/156216</dc:identifier>
<dc:title><![CDATA[An insula-central amygdala circuit for behavioral inhibition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/160499v1?rss=1">
<title>
<![CDATA[
Whole Genome Sequencing in Psychiatric Disorders: the WGSPD Consortium 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/160499v1?rss=1"
</link>
<description><![CDATA[
As technology advances, whole genome sequencing (WGS) is likely to supersede other genotyping technologies. The rate of this change depends on its relative cost and utility. Variants identified uniquely through WGS may reveal novel biological pathways underlying complex disorders and provide high-resolution insight into when, where, and in which cell type these pathways are affected. Alternatively, cheaper and less computationally intensive approaches may yield equivalent insights. Understanding the role of rare variants in the noncoding gene-regulating genome, through pilot WGS projects, will be critical to determine which of these two extremes best represents reality. With large cohorts, well-defined risk loci, and a compelling need to understand the underlying biology, psychiatric disorders have a role to play in this preliminary WGS assessment. The WGSPD consortium will integrate data for 18,000 individuals with psychiatric disorders, beginning with autism spectrum disorder, schizophrenia, bipolar disorder, and major depressive disorder, along with over 150,000 controls.
]]></description>
<dc:creator>Sanders, S. J.</dc:creator>
<dc:creator>Neale, B. M.</dc:creator>
<dc:creator>Huang, H.</dc:creator>
<dc:creator>Werling, D. M.</dc:creator>
<dc:creator>An, J.-Y.</dc:creator>
<dc:creator>Dong, S.</dc:creator>
<dc:creator>- Whole Genome Sequencing for Psychiatric Disorders,</dc:creator>
<dc:creator>Abecasis, G.</dc:creator>
<dc:creator>Arguello, P. A.</dc:creator>
<dc:creator>Blangero, J.</dc:creator>
<dc:creator>Boehnke, M.</dc:creator>
<dc:creator>Daly, M.</dc:creator>
<dc:creator>Eggan, K.</dc:creator>
<dc:creator>Geschwind, D. H.</dc:creator>
<dc:creator>Glahn, D.</dc:creator>
<dc:creator>Goldstein, D. B.</dc:creator>
<dc:creator>Gur, R. E.</dc:creator>
<dc:creator>Handsaker, R. E.</dc:creator>
<dc:creator>McCarroll, S. A.</dc:creator>
<dc:creator>Ophoff, R. A.</dc:creator>
<dc:creator>Palotie, A.</dc:creator>
<dc:creator>Pato, C.</dc:creator>
<dc:creator>Sabatti, C.</dc:creator>
<dc:creator>State, M. W.</dc:creator>
<dc:creator>Willsey, A. J.</dc:creator>
<dc:creator>Hyman, S. E.</dc:creator>
<dc:creator>Addington, A.</dc:creator>
<dc:creator>Lehner, T.</dc:creator>
<dc:creator>Freimer, N. B.</dc:creator>
<dc:date>2017-07-07</dc:date>
<dc:identifier>doi:10.1101/160499</dc:identifier>
<dc:title><![CDATA[Whole Genome Sequencing in Psychiatric Disorders: the WGSPD Consortium]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/165316v1?rss=1">
<title>
<![CDATA[
Abnormal Speech Motor Control in Individuals with 16p11.2 Deletions 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/165316v1?rss=1"
</link>
<description><![CDATA[
Speech and motor deficits are highly prevalent (>70%) in individuals with the 600 kb BP4-BP5 16p11.2 deletion; however, the mechanisms that drive these deficits are unclear, limiting our ability to target interventions and advance treatment. This study examined fundamental aspects of speech motor control in participants with the 16p11.2 deletion. To assess capacity for control of voice, we examined how accurately and quickly subjects changed the pitch of their voice within a trial to correct for a transient perturbation of the pitch of their auditory feedback. When compared to sibling controls, 16p11.2 deletion carriers show an over-exaggerated pitch compensation response to unpredictable mid-vocalization pitch perturbations. We also examined sensorimotor adaptation of speech by assessing how subjects learned to adapt their sustained productions of formants (speech spectral peak frequencies important for vowel identity), in response to consistent changes in their auditory feedback during vowel production. Deletion carriers show reduced sensorimotor adaptation to sustained vowel identity changes in auditory feedback. These results together suggest that 16p11.2 deletion carriers have fundamental impairments in the basic mechanisms of speech motor control and these impairments may partially explain the deficits in speech and language in these individuals.
]]></description>
<dc:creator>Demopoulos, C.</dc:creator>
<dc:creator>Kothare, H.</dc:creator>
<dc:creator>Mizuiri, D.</dc:creator>
<dc:creator>Henderson-Sabes, J.</dc:creator>
<dc:creator>Fregeau, B.</dc:creator>
<dc:creator>Tjernagel, J.</dc:creator>
<dc:creator>Houde, J.</dc:creator>
<dc:creator>Sherr, E.</dc:creator>
<dc:creator>Nagarajan, S. S.</dc:creator>
<dc:date>2017-07-18</dc:date>
<dc:identifier>doi:10.1101/165316</dc:identifier>
<dc:title><![CDATA[Abnormal Speech Motor Control in Individuals with 16p11.2 Deletions]]></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/186239v1?rss=1">
<title>
<![CDATA[
Increased axonal bouton stability during learning in the mouse model of MECP2 duplication syndrome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/186239v1?rss=1"
</link>
<description><![CDATA[
MECP2-duplication syndrome is an X-linked form of syndromic autism caused by genomic duplication of the region encoding Methyl-CpG-binding protein 2. Mice overexpressing MECP2 demonstrate altered patterns of learning and memory, including enhanced motor learning. Previous work associated this enhanced motor learning to abnormally increased stability of dendritic spine clusters formed in the apical tuft of corticospinal, area M1, neurons during rotarod training. In the current study, we measure the structural plasticity of axonal boutons in Layer 5 (L5) pyramidal neuron projections to layer 1 of area M1 during motor learning. In wild-type mice we find that during rotarod training, bouton formation rate changes minimally, if at all, while bouton elimination rate doubles. Notably, the observed upregulation in bouton elimination with learning is absent in MECP2-duplication mice. This result provides further evidence of imbalance between structural stability and plasticity in this form of syndromic autism. Furthermore, the observation that axonal bouton elimination doubles with motor learning in wild-type animals contrasts with the increase of dendritic spine consolidation observed in corticospinal neurons at the same layer. This dissociation suggests that different area M1 microcircuits may manifest different patterns of structural synaptic plasticity during motor learning.nnSIGNIFICANCE STATEMENTAbnormal balance between synaptic stability and plasticity is a feature of several autism spectrum disorders, often corroborated by in vivo studies of dendritic spine turnover. Here we provide the first evidence that abnormally increased stability of axonal boutons, the presynaptic component of excitatory synapses, occurs during motor learning in the MECP2 duplication syndrome mouse model of autism. In contrast, in normal controls, axonal bouton elimination in L5 pyramidal neuron projections to layer 1 of area M1 doubles with motor learning. The fact that axonal projection boutons get eliminated, while corticospinal dendritic spines get consolidated with motor learning in layer 1 of area M1, suggests that structural plasticity manifestations differ across different M1 microcircuits.
]]></description>
<dc:creator>Ash, R. T.</dc:creator>
<dc:creator>Fahey, P. G.</dc:creator>
<dc:creator>Park, J.</dc:creator>
<dc:creator>Zoghbi, H. Y.</dc:creator>
<dc:creator>Smirnakis, S. M.</dc:creator>
<dc:date>2017-09-08</dc:date>
<dc:identifier>doi:10.1101/186239</dc:identifier>
<dc:title><![CDATA[Increased axonal bouton stability during learning in the mouse model of MECP2 duplication syndrome]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/185900v1?rss=1">
<title>
<![CDATA[
Genetic analysis of very obese children with autism spectrum disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/185900v1?rss=1"
</link>
<description><![CDATA[
Autism spectrum disorder (ASD) is defined by the triad of deficits in social interactions, deficits in communication, and repetitive behaviors. Common co-morbidities in syndromic forms of ASD include intellectual disability, seizures, and obesity. We asked whether very obese children with ASD had different behavioral, physical and genetic characteristics compared to children with ASD who were not obese. We found that very obese children with ASD had significantly poorer scores on standardized behavioral tests. Very obese boys with ASD had lower full scale IQ and increased impairments with respect to stereotypies, communication and social skills. Very obese girls with ASD had increased impairments with respect to irritability and oppositional defiant behavior. We identified genetic lesions in a subset of the children with ASD and obesity and attempted to identify enriched biological pathways. Our study demonstrates the value of identifying co-morbidities in children with ASD as we move forward towards understanding the biological processes that contribute to this complex disorder and prepare to design customized treatments that target the diverse genetic lesions present in individuals with ASD.
]]></description>
<dc:creator>Cortes, H. D.</dc:creator>
<dc:creator>Wevrick, R.</dc:creator>
<dc:date>2017-09-12</dc:date>
<dc:identifier>doi:10.1101/185900</dc:identifier>
<dc:title><![CDATA[Genetic analysis of very obese children with autism spectrum disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/105312v1?rss=1">
<title>
<![CDATA[
Inhibitory neuron diversity originates from cardinal classes shared across germinal zones. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/105312v1?rss=1"
</link>
<description><![CDATA[
Diverse subsets of cortical interneurons play a particularly important role in the stability of the neural circuits underlying cognitive and higher order brain functions, yet our understanding of how this diversity is generated is far from complete. We applied massively parallel single-cell RNA-seq to profile a developmental time course of interneuron development, measuring the transcriptomes of over 60,000 progenitors during their maturation in the ganglionic eminences and embryonic migration into the cortex. While diversity within mitotic progenitors is largely driven by cell cycle and differentiation state, we observed sparse eminence-specific transcription factor expression, which seeds the emergence of later cell diversity. Upon becoming postmitotic, cells from all eminences pass through one of three precursor states, one of which represents a cortical interneuron ground state. By integrating datasets across developmental timepoints, we identified transcriptomic heterogeneity in interneuron precursors representing the emergence of four cardinal classes (Pvalb, Sst, Id2 and Vip), which further separate into subtypes at different timepoints during development. Our analysis revealed that the ASD-associated transcription factor Mef2c discriminates early Pvalb-precursors in E13.5 cells, and removal of Mef2c confirms its essential role for Pvalb interneuron development. These findings shed new light on the molecular diversification of early inhibitory precursors, and suggest gene modules that may link developmental specification with the etiology of neuropsychiatric disorders.
]]></description>
<dc:creator>Mayer, C.</dc:creator>
<dc:creator>Hafemeister, C.</dc:creator>
<dc:creator>Bandler, R. C.</dc:creator>
<dc:creator>Machold, R.</dc:creator>
<dc:creator>Fishell, G.</dc:creator>
<dc:creator>Satija, R.</dc:creator>
<dc:date>2017-02-02</dc:date>
<dc:identifier>doi:10.1101/105312</dc:identifier>
<dc:title><![CDATA[Inhibitory neuron diversity originates from cardinal classes shared across germinal zones.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-02-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/141408v1?rss=1">
<title>
<![CDATA[
TiSAn: Tissue Specific Variant Annotation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/141408v1?rss=1"
</link>
<description><![CDATA[
Measures of general deleteriousness, like CADD or PolyPhen, have become indispensable tools in the interpretation of genetic variants. However, these measures say little about where in the organism these deleterious effects will be most apparent. An additional, complementary measure is needed to link deleterious variants (as determined by e.g., CADD) to tissues in which their effect will be most meaningful. Here, we introduce TiSAn (Tissue Specific Annotation), a tool that predicts how related a genomic position is to a given tissue (http://github.com/kevinVervier/TiSAn). TiSAn uses machine learning on genome-scale, tissue-specific data to discriminate variants relevant to a tissue from those having no bearing on the development or function of that tissue. Predictions are then made genome-wide, and these scores can then be used to contextualize and filter variants of interest in whole genome sequencing or genome wide association studies (GWAS). We demonstrate the accuracy and versatility of TiSAn by introducing predictive models for human heart and human brain, and detecting tissue-relevant variations in large cohorts for autism spectrum disorder (TiSAn-brain) and coronary artery disease (TiSAn-heart). We find that TiSAn is better able to prioritize genetic variants according to their tissue-specific action than the current state of the art method, GenoSkyLine.
]]></description>
<dc:creator>Vervier, K.</dc:creator>
<dc:creator>Michaelson, J. J.</dc:creator>
<dc:date>2017-05-24</dc:date>
<dc:identifier>doi:10.1101/141408</dc:identifier>
<dc:title><![CDATA[TiSAn: Tissue Specific Variant Annotation]]></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/127712v1?rss=1">
<title>
<![CDATA[
De novo damaging coding mutations are strongly associated with obsessive-compulsive disorder and overlap with autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/127712v1?rss=1"
</link>
<description><![CDATA[
Obsessive-compulsive disorder (OCD) is a debilitating developmental neuropsychiatric disorder with a genetic risk component, yet identification of high-confidence risk genes has been challenging. We performed whole-exome sequencing in 222 OCD parent-child trios (184 trios after quality control), finding strong evidence that de novo likely gene disrupting and predicted damaging missense variants contribute to OCD risk. Together, these de novo damaging variants are enriched in OCD probands (RR 1.52, p=0.0005). We identified two high-confidence risk genes, each containing two de novo damaging variants in unrelated probands: CHD8 (Chromodomain Helicase DNA Binding Protein 8) and SCUBE1 (Signal Peptide, CUB Domain And EGF Like Domain Containing 1). Based on our data, we estimate that 34% of de novo damaging variants seen in OCD contribute to risk, and that de novo damaging variants in approximately 335 genes contribute to risk in 22% of OCD cases. Furthermore, genes harboring de novo damaging variants in OCD are enriched for those reported in neurodevelopmental disorders, particularly autism spectrum disorders. An exploratory network analysis reveals significant functional connectivity and enrichment in canonical pathways related to immune response.nnSIGNIFICANCE STATEMENTDecades of genetic studies in obsessive-compulsive disorder (OCD) have yet to provide reproducible, statistically significant findings. Following an approach that has led to tremendous success in gene discovery for several neuropsychiatric disorders, here we report findings from DNA whole-exome sequencing of patients with OCD and their parents. We find strong evidence for the contribution of spontaneous, or de novo, predicted-damaging genetic variants to OCD risk, identify two high-confidence risk genes, and detect significant overlap with genes previously identified in autism. These results change the status quo of OCD genetics by identifying novel OCD risk genes, clarifying the genetic landscape of OCD with respect to de novo variation, and suggesting underlying biological pathways that will improve our understanding of OCD biology.
]]></description>
<dc:creator>Cappi, C.</dc:creator>
<dc:creator>Oliphant, M. E.</dc:creator>
<dc:creator>Peter, Z.</dc:creator>
<dc:creator>Zai, G.</dc:creator>
<dc:creator>Sullivan, C. A.</dc:creator>
<dc:creator>Gupta, A. R.</dc:creator>
<dc:creator>Hoffman, E. J.</dc:creator>
<dc:creator>Virdee, M.</dc:creator>
<dc:creator>Willsey, A. J.</dc:creator>
<dc:creator>Shavitt, R. G.</dc:creator>
<dc:creator>Miguel, E. C.</dc:creator>
<dc:creator>Kennedy, J. L.</dc:creator>
<dc:creator>Richter, M. A.</dc:creator>
<dc:creator>Fernandez, T. V.</dc:creator>
<dc:date>2017-09-21</dc:date>
<dc:identifier>doi:10.1101/127712</dc:identifier>
<dc:title><![CDATA[De novo damaging coding mutations are strongly associated with obsessive-compulsive disorder and overlap with autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/192740v1?rss=1">
<title>
<![CDATA[
Paternal-age-related de novo mutations and risk for five disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/192740v1?rss=1"
</link>
<description><![CDATA[
BackgroundThere are well-established epidemiologic associations between advanced paternal age and increased offspring risk for several psychiatric and developmental disorders. These associations are commonly attributed to age-related de novo mutations. However, the actual magnitude of risk conferred by age-related de novo mutations in the male germline is unknown. Quantifying this risk would clarify the clinical and public health significance of delayed paternity.nnMethodsUsing results from large, parent-child trio whole-exome-sequencing studies, we estimated the relationship between paternal-age-related de novo single nucleotide variants (dnSNVs) and offspring risk for five disorders: autism spectrum disorders (ASD), congenital heart disease (CHD), neurodevelopmental disorders with epilepsy (EPI), intellectual disability (ID), and schizophrenia (SCZ). Using Danish national registry data, we then investigated the degree to which the epidemiologic association between each disorder and advanced paternal age was consistent with the estimated role of de novo mutations.nnResultsIncidence rate ratios comparing dnSNV-based risk to offspring of 45 versus 25-year-old fathers ranged from 1.05 (95% confidence interval 1.01-1.13) for SCZ to 1.29 (95% CI 1.13-1.68) for ID. Epidemiologic estimates of paternal age risk for CHD, ID and EPI were consistent with the dnSNV effect. However, epidemiologic effects for ASDs and SCZ significantly exceeded the risk that could be explained by dnSNVs alone (p<2e-4 for both comparisons).nnConclusionIncreasing dnSNVs due to advanced paternal age confer a small amount of offspring risk for psychiatric and developmental disorders. For ASD and SCZ, epidemiologic associations with delayed paternity largely reflect factors that cannot be assumed to increase with age.
]]></description>
<dc:creator>Taylor, J.</dc:creator>
<dc:creator>Debost, J.-C. P. G.</dc:creator>
<dc:creator>Morton, S. U.</dc:creator>
<dc:creator>Wigdor, E. M.</dc:creator>
<dc:creator>Heyne, H. O.</dc:creator>
<dc:creator>Lal, D.</dc:creator>
<dc:creator>Howrigan, D. P.</dc:creator>
<dc:creator>Bloemendal, A.</dc:creator>
<dc:creator>Larsen, J. T.</dc:creator>
<dc:creator>Kosmicki, J. A.</dc:creator>
<dc:creator>Weiner, D. J.</dc:creator>
<dc:creator>Pediatric Cardiac Genomics Consortium,</dc:creator>
<dc:creator>Homsy, J.</dc:creator>
<dc:creator>Seidman, J. G.</dc:creator>
<dc:creator>Seidman, C. E.</dc:creator>
<dc:creator>Agerbo, E.</dc:creator>
<dc:creator>McGrath, J. J.</dc:creator>
<dc:creator>Mortensen, P. B.</dc:creator>
<dc:creator>Petersen, L.</dc:creator>
<dc:creator>Daly, M. J.</dc:creator>
<dc:creator>Robinson, E. B.</dc:creator>
<dc:date>2017-09-22</dc:date>
<dc:identifier>doi:10.1101/192740</dc:identifier>
<dc:title><![CDATA[Paternal-age-related de novo mutations and risk for five disorders]]></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/208165v1?rss=1">
<title>
<![CDATA[
Quantification of autism recurrence risk by direct assessment of paternal sperm mosaicism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/208165v1?rss=1"
</link>
<description><![CDATA[
De novo genetic mutations represent a major contributor to pediatric disease, including autism spectrum disorders (ASD), congenital heart disease, and muscular dystrophies1,2, but there are currently no methods to prevent or predict them. These mutations are classically thought to occur either at low levels in progenitor cells or at the time of fertilization1,3 and are often assigned a low risk of recurrence in siblings4,5. Here, we directly assess the presence of de novo mutations in paternal sperm and discover abundant, germline-restricted mosaicism. From a cohort of ASD cases, employing single molecule genotyping, we found that four out of 14 fathers were germline mosaic for a putatively causative mutation transmitted to the affected child. Three of these were enriched or exclusively present in sperm at high allelic fractions (AF; 7-15%); and one was recurrently transmitted to two additional affected children, representing clinically actionable information. Germline mosaicism was further assessed by deep (>90x) whole genome sequencing of four paternal sperm samples, which detected 12/355 transmitted de novo single nucleotide variants that were mosaic above 2% AF, and more than two dozen additional, non-transmitted mosaic variants in paternal sperm. Our results demonstrate that germline mosaicism is an underestimated phenomenon, which has important implications for clinical practice and in understanding the basis of human disease. Genetic analysis of sperm can assess individualized recurrence risk following the birth of a child with a de novo disease, as well as the risk in any male planning to have children.
]]></description>
<dc:creator>Breuss, M.</dc:creator>
<dc:creator>Kleiber, M.</dc:creator>
<dc:creator>George, R. D.</dc:creator>
<dc:creator>Antaki, D.</dc:creator>
<dc:creator>James, K. N.</dc:creator>
<dc:creator>Ball, L. L.</dc:creator>
<dc:creator>Hong, O.</dc:creator>
<dc:creator>Garcia, C. A. B.</dc:creator>
<dc:creator>Musaev, D.</dc:creator>
<dc:creator>Nguyen, A.</dc:creator>
<dc:creator>McEvoy-Venneri, J.</dc:creator>
<dc:creator>Knox, R.</dc:creator>
<dc:creator>Sticca, E.</dc:creator>
<dc:creator>Devinsky, O.</dc:creator>
<dc:creator>Gymrek, M.</dc:creator>
<dc:creator>Sebat, J.</dc:creator>
<dc:creator>Gleeson, J. G.</dc:creator>
<dc:date>2017-10-24</dc:date>
<dc:identifier>doi:10.1101/208165</dc:identifier>
<dc:title><![CDATA[Quantification of autism recurrence risk by direct assessment of paternal sperm mosaicism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/208744v1?rss=1">
<title>
<![CDATA[
Single-cell transcriptomic catalog of mouse cortical development 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/208744v1?rss=1"
</link>
<description><![CDATA[
We generated a single-cell transcriptomic catalog of the developing mouse cerebral cortex that includes numerous classes of neurons, progenitors, and glia, their proliferation, migration, and activation states, and their relatedness within and across timepoints. Cell expression profiles stratified neurological disease-associated genes into distinct subtypes. Complex neurodevelopmental processes can be reconstructed with single-cell transcriptomics data, permitting a deeper understanding of cortical development and the cellular origins of brain diseases.
]]></description>
<dc:creator>Loo, L.</dc:creator>
<dc:creator>Simon, J. M.</dc:creator>
<dc:creator>McCoy, E. S.</dc:creator>
<dc:creator>Niehaus, J. K.</dc:creator>
<dc:creator>Zylka, M. J.</dc:creator>
<dc:date>2017-10-25</dc:date>
<dc:identifier>doi:10.1101/208744</dc:identifier>
<dc:title><![CDATA[Single-cell transcriptomic catalog of mouse cortical development]]></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/210120v1?rss=1">
<title>
<![CDATA[
Prediction and interpretation of deleterious coding variants in terms of protein structural stability 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/210120v1?rss=1"
</link>
<description><![CDATA[
The classification of human genetic variants into deleterious and neutral is a challenging issue, whose complexity is rooted in the large variety of biophysical mechanisms that can be responsible for disease conditions. For non-synonymous mutations in structured proteins, one of these is the protein stability change, which can lead to functionality loss. We developed a stability-driven knowledge-based classifier that uses protein structure, artificial neural networks and solvent accessibility-dependent combinations of statistical potentials to predict whether destabilizing or stabilizing mutations are disease-causing. Our predictor yields a balanced accuracy of 71% in cross validation. As expected, it has a very high positive predictive value of 89%: it predicts with high accuracy the subset of mutations that are deleterious because of stability issues, but is by construction unable of classifying variants that are deleterious for other reasons. Its combination with an evolutionary-based predictor increases the balanced accuracy up to 75%, and allowed predicting more than 1/4 of the deleterious variants with 95% positive predictive value. Our method, called SNPMuSiC, can be used with both experimental and structural models and compares favorably with other prediction tools on several independent test sets. It constitutes a step towards interpreting variant effects at the molecular scale.
]]></description>
<dc:creator>Ancien, F.</dc:creator>
<dc:creator>Pucci, F.</dc:creator>
<dc:creator>Godfroid, M.</dc:creator>
<dc:creator>Rooman, M.</dc:creator>
<dc:date>2017-10-27</dc:date>
<dc:identifier>doi:10.1101/210120</dc:identifier>
<dc:title><![CDATA[Prediction and interpretation of deleterious coding variants in terms of protein structural stability]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/217414v1?rss=1">
<title>
<![CDATA[
Impaired perceptual learning in Fragile X syndrome is mediated by parvalbumin neuron dysfunction in V1 and is reversible. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/217414v1?rss=1"
</link>
<description><![CDATA[
Atypical sensory processing is a core characteristic in autism spectrum disorders1 that negatively impacts virtually all activities of daily living. Sensory symptoms are predictive of the subsequent appearance of impaired social behavior and other autistic traits2, 3. Thus, a better understanding of the changes in neural circuitry that disrupt perceptual learning in autism could shed light into the mechanistic basis and potential therapeutic avenues for a range of autistic symptoms2. Likewise, the lack of directly comparable behavioral paradigms in both humans and animal models currently limits the translational potential of discoveries in the latter. We adopted a symptom-to-circuit approach to uncover the circuit-level alterations in the Fmr1-/- mouse model of Fragile X syndrome (FXS) that underlie atypical visual discrimination in this disorder4, 5. Using a go/no-go task and in vivo 2-photon calcium imaging in primary visual cortex (V1), we find that impaired discrimination in Fmr1-/- mice correlates with marked deficits in orientation tuning of principal neurons, and a decrease in the activity of parvalbumin (PV) interneurons in V1. Restoring visually evoked activity in PV cells in Fmr1-/- mice with a chemogenetic (DREADD) strategy was sufficient to rescue their behavioral performance. Finally, we found that human subjects with FXS exhibit strikingly similar impairments in visual discrimination as Fmr1-/- mice. We conclude that manipulating orientation tuning in autism could improve visually guided behaviors that are critical for playing sports, driving or judging emotions.
]]></description>
<dc:creator>Goel, A.</dc:creator>
<dc:creator>Cantu, D.</dc:creator>
<dc:creator>Guilfoyle, J.</dc:creator>
<dc:creator>Chaudhari, G. R.</dc:creator>
<dc:creator>Newadkar, A.</dc:creator>
<dc:creator>Todisco, B.</dc:creator>
<dc:creator>Alba, D. d.</dc:creator>
<dc:creator>Kourdougli, N.</dc:creator>
<dc:creator>Schmitt, L. M.</dc:creator>
<dc:creator>Pedapati, E.</dc:creator>
<dc:creator>Erickson, C. A.</dc:creator>
<dc:creator>Portera-Cailliau, C.</dc:creator>
<dc:date>2017-11-13</dc:date>
<dc:identifier>doi:10.1101/217414</dc:identifier>
<dc:title><![CDATA[Impaired perceptual learning in Fragile X syndrome is mediated by parvalbumin neuron dysfunction in V1 and is reversible.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/233197v1?rss=1">
<title>
<![CDATA[
Structural disruption of genomic regions containing ultraconserved elements is associated with neurodevelopmental phenotypes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/233197v1?rss=1"
</link>
<description><![CDATA[
The development of the human brain and nervous system can be affected by genetic or environmental factors. Here we focus on characterizing the genetic perturbations that accompany and may contribute to neurodevelopmental phenotypes. Specifically, we examine two types of structural variants, namely, copy number variation and balanced chromosome rearrangements, discovered in subjects with neurodevelopmental disorders and related phenotypes. We find that a feature uniting these types of genetic aberrations is a proximity to ultraconserved elements (UCEs), which are sequences that are perfectly conserved between the reference genomes of distantly related species. In particular, while UCEs are generally depleted from copy number variant regions in healthy individuals, they are, on the whole, enriched in genomic regions disrupted by copy number variants or breakpoints of balanced rearrangements in affected individuals. Additionally, while genes associated with neurodevelopmental disorders are enriched in UCEs, this does not account for the excess of UCEs either in copy number variants or close to the breakpoints of balanced rearrangements in affected individuals. Indeed, our data are consistent with some manifestations of neurodevelopmental disorders resulting from a disruption of genome integrity in the vicinity of UCEs.
]]></description>
<dc:creator>McCole, R. B.</dc:creator>
<dc:creator>Saylor, W.</dc:creator>
<dc:creator>Redin, C.</dc:creator>
<dc:creator>Fonseka, C. Y.</dc:creator>
<dc:creator>Brand, H.</dc:creator>
<dc:creator>Erceg, J.</dc:creator>
<dc:creator>Talkowski, M. E.</dc:creator>
<dc:creator>Wu, C.- t.</dc:creator>
<dc:date>2017-12-13</dc:date>
<dc:identifier>doi:10.1101/233197</dc:identifier>
<dc:title><![CDATA[Structural disruption of genomic regions containing ultraconserved elements is associated with neurodevelopmental phenotypes]]></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/244905v1?rss=1">
<title>
<![CDATA[
Neuron-specific cTag-CLIP reveals cell-specific diversity of functional RNA regulation in the brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/244905v1?rss=1"
</link>
<description><![CDATA[
RNA-binding proteins (RBPs) regulate genetic diversity, but the degree to which they do so in individual cell-types in vivo is unknown. We employed NOVA2 cTag-CLIP to generate functional RBP-RNA maps from single neuronal populations in the mouse brain. Combining cell-type specific data from Nova2-cTag and Nova2 conditional knock-out mice revealed differential NOVA2 regulatory actions (e.g. alternative splicing) on the same transcripts in different neurons, including in cerebellar Purkinje cells, where NOVA2 acts as an essential factor for proper motor coordination and synapse formation. This also led to the discovery of a mechanism by which NOVA2 action leads to different outcomes in different cells on the same transcripts: NOVA2 is able to regulate retained introns, which subsequently serve as scaffolds for another trans-acting splicing factor, PTBP2. Our results describe differential roles and mechanisms by which RBPs mediate RNA diversity in different neurons and consequent functional outcomes within the brain.
]]></description>
<dc:creator>Saito, Y.</dc:creator>
<dc:creator>Yuan, Y.</dc:creator>
<dc:creator>Zucker-Scharff, I.</dc:creator>
<dc:creator>Fak, J. J.</dc:creator>
<dc:creator>Tajima, Y.</dc:creator>
<dc:creator>Licatalosi, D. D.</dc:creator>
<dc:creator>Darnell, R. B.</dc:creator>
<dc:date>2018-01-08</dc:date>
<dc:identifier>doi:10.1101/244905</dc:identifier>
<dc:title><![CDATA[Neuron-specific cTag-CLIP reveals cell-specific diversity of functional RNA regulation in the brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/245928v1?rss=1">
<title>
<![CDATA[
A master regulatory network restoring brain glutamate homeostasis is coordinately activated in stroke 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/245928v1?rss=1"
</link>
<description><![CDATA[
Post-transcriptional regulation by miRNAs is essential for complex molecular responses to physiological insult and disease. Although many disease-associated miRNAs are known, their global targets and culminating network effects on pathophysiology remain poorly understood. We applied AGO CLIP to systematically elucidate altered miRNA-target interactions in brain following ischemia/reperfusion (I/R) injury. Among 1,190 identified, most prominent was the cumulative loss of target regulation by miR-29 family members. Integration of translational and time-course RNA profiles revealed a dynamic mode of miR-29 target de-regulation, led by acute translational activation and later increase in RNA levels, allowing rapid proteomic changes to take effect. These functional regulatory events rely on canonical and non-canonical miR-29 binding and engage glutamate reuptake signals to control local glutamate levels. These results uncover a miRNA target network that acts acutely to maintain brain homeostasis after ischemic stroke.
]]></description>
<dc:creator>Kobayashi, M.</dc:creator>
<dc:creator>Anderson, C.</dc:creator>
<dc:creator>Benakis, C.</dc:creator>
<dc:creator>Moore, M. J.</dc:creator>
<dc:creator>Mele, A.</dc:creator>
<dc:creator>Fak, J. J.</dc:creator>
<dc:creator>Park, C. Y.</dc:creator>
<dc:creator>Zhou, P.</dc:creator>
<dc:creator>Anrather, J.</dc:creator>
<dc:creator>Iadecola, C.</dc:creator>
<dc:creator>Darnell, R. B.</dc:creator>
<dc:date>2018-01-10</dc:date>
<dc:identifier>doi:10.1101/245928</dc:identifier>
<dc:title><![CDATA[A master regulatory network restoring brain glutamate homeostasis is coordinately activated in stroke]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/209478v1?rss=1">
<title>
<![CDATA[
Robust identification of deletions in exome and genome sequence data based on clustering of Mendelian errors 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/209478v1?rss=1"
</link>
<description><![CDATA[
Multiple tools have been developed to identify copy number variants (CNVs) from whole exome (WES) and whole genome sequencing (WGS) data. Current tools such as XHMM for WES and CNVnator for WGS identify CNVs based on changes in read depth. For WGS, other methods to identify CNVs include utilizing discordant read pairs and split reads and genome-wide local assembly with tools such as Lumpy and SvABA, respectively. Here, we introduce a new method to identify deletion CNVs from WES and WGS trio data based on the clustering of Mendelian errors (MEs). Using our Mendelian Error Method (MEM), we identified 127 deletions (inherited and de novo) in 2,601 WES trios from the Pediatric Cardiac Genomics Consortium, with a validation rate of 88% by digital droplet PCR. MEM identified additional de novo deletions compared to XHMM, and also identified sample switches, DNA contamination, a significant enrichment of 15q11.2 deletions compared to controls and eight cases of uniparental disomy. We applied MEM to WGS data from the Genome In A Bottle Ashkenazi trio and identified deletions with 97% specificity. MEM provides a robust, computationally inexpensive method for identifying deletions, and an orthogonal approach for verifying deletions called by other tools.
]]></description>
<dc:creator>Manheimer, K. B.</dc:creator>
<dc:creator>Patel, N.</dc:creator>
<dc:creator>Richter, F.</dc:creator>
<dc:creator>Gorham, J.</dc:creator>
<dc:creator>Tai, A. C.</dc:creator>
<dc:creator>Homsy, J.</dc:creator>
<dc:creator>Boskovski, M. T.</dc:creator>
<dc:creator>Parfenov, M.</dc:creator>
<dc:creator>Goldmuntz, E.</dc:creator>
<dc:creator>Chung, W. K.</dc:creator>
<dc:creator>Brueckner, M.</dc:creator>
<dc:creator>Tristani-Firouzi, M.</dc:creator>
<dc:creator>Srivastava, D.</dc:creator>
<dc:creator>Seidman, J. G.</dc:creator>
<dc:creator>Seidman, C. E.</dc:creator>
<dc:creator>Gelb, B. D.</dc:creator>
<dc:creator>Sharp, A. J.</dc:creator>
<dc:date>2017-10-26</dc:date>
<dc:identifier>doi:10.1101/209478</dc:identifier>
<dc:title><![CDATA[Robust identification of deletions in exome and genome sequence data based on clustering of Mendelian errors]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/199497v1?rss=1">
<title>
<![CDATA[
Two-Photon Imaging of Striatum Demonstrates Distinct Functions for Striosomes and Matrix in Reinforcement Learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/199497v1?rss=1"
</link>
<description><![CDATA[
Despite the discovery of striosomes several decades ago, technical difficulties have hampered the study of their functions. Here we used 2-photon calcium imaging in neuronal birthdate-labeled Mash1-CreER mice to image simultaneously the activity of striosomal and matrix neurons in vivo. We report that with this method we can visually identify circumscribed zones of neuropil that correspond to striosomes as verified in immunostained sections. We find that striosomal neurons, relative to matrix neurons, preferentially encode reward-predicting cues, and that their activity contains more information about expected outcome. These characteristics emerge during training and further strengthen during overtraining. Both striatal compartments are active similarly after reward delivery, firing at neuron-specific times during or after consummatory licking. Finally, we find that immediate reward history strongly modulates neuronal activation in the next trial, especially in matrix neurons. These results suggest that striosomes and matrix have distinct functions in relation to reinforcement learning.
]]></description>
<dc:creator>Bloem, B.</dc:creator>
<dc:creator>Huda, R.</dc:creator>
<dc:creator>Sur, M.</dc:creator>
<dc:creator>Graybiel, A. M.</dc:creator>
<dc:date>2017-11-24</dc:date>
<dc:identifier>doi:10.1101/199497</dc:identifier>
<dc:title><![CDATA[Two-Photon Imaging of Striatum Demonstrates Distinct Functions for Striosomes and Matrix in Reinforcement Learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/225193v1?rss=1">
<title>
<![CDATA[
Elevated polygenic burden for autism is associated with differential DNA methylation at birth. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/225193v1?rss=1"
</link>
<description><![CDATA[
BackgroundAutism spectrum disorder (ASD) is a severe neurodevelopmental disorder characterized by deficits in social communication and restricted, repetitive behaviors, interests, or activities. The etiology of ASD involves both inherited and environmental risk factors, with epigenetic processes hypothesized as one mechanism by which both genetic and non-genetic variation influence gene regulation and pathogenesis.nnMethodsWe quantified neonatal methylomic variation in 1,263 infants - of whom ~50% went on to subsequently develop ASD - using DNA isolated from a unique collection of archived blood spots taken shortly after birth. We used matched genetic data from the same individuals to examine the molecular consequences of ASD genetic risk variants, identifying methylomic variation associated with elevated polygenic burden for ASD. In addition, we performed DNA methylation quantitative trait loci (mQTL) mapping to prioritize target genes from ASD GWAS findings.nnResultsAlthough we did not identify specific loci showing consistent changes in neonatal DNA methylation associated with later ASD, we found a significant association between increased polygenic burden for autism and methylomic variation at two CpG sites located proximal to a robust GWAS signal for ASD on chromosome 8.nnConclusionsThis study is the largest analysis of DNA methylation in ASD yet undertaken and the first to integrate both genetic and epigenetic variation at birth in ASD. We demonstrate the utility of using a polygenic risk score to identify molecular variation associated with disease, and of using mQTL to refine the functional and regulatory variation associated with ASD risk variants.
]]></description>
<dc:creator>Hannon, E.</dc:creator>
<dc:creator>Schendel, D.</dc:creator>
<dc:creator>Ladd-Acosta, C.</dc:creator>
<dc:creator>Grove, J.</dc:creator>
<dc:creator>iPSYCH-Broad ASD Group,</dc:creator>
<dc:creator>Hansen, C. S.</dc:creator>
<dc:creator>Andrews, S. V.</dc:creator>
<dc:creator>Hougaard, D.</dc:creator>
<dc:creator>Bresnahan, M.</dc:creator>
<dc:creator>Mors, O.</dc:creator>
<dc:creator>Hollegaard, M. V.</dc:creator>
<dc:creator>Baekvad-Hansen, M.</dc:creator>
<dc:creator>Hornig, M.</dc:creator>
<dc:creator>Mortensen, P. B.</dc:creator>
<dc:creator>Borglum, A.</dc:creator>
<dc:creator>Werge, T.</dc:creator>
<dc:creator>Pedersen, M. G.</dc:creator>
<dc:creator>Nordentoft, M.</dc:creator>
<dc:creator>Buxbaum, J.</dc:creator>
<dc:creator>Fallin, D.</dc:creator>
<dc:creator>Bybjerg-Grauholm, J.</dc:creator>
<dc:creator>Reichenberg, A.</dc:creator>
<dc:creator>Mill, J.</dc:creator>
<dc:date>2017-11-26</dc:date>
<dc:identifier>doi:10.1101/225193</dc:identifier>
<dc:title><![CDATA[Elevated polygenic burden for autism is associated with differential DNA methylation at birth.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/247601v1?rss=1">
<title>
<![CDATA[
Precise temporal regulation of alternative splicing during neural development 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/247601v1?rss=1"
</link>
<description><![CDATA[
Alternative splicing (AS) is a crucial step of gene expression that must be tightly controlled, but the precise timing of dynamic splicing switches during neural development and the underlying regulatory mechanisms are poorly understood. Here we systematically analyzed the temporal regulation of AS in a large number of transcriptome profiles of developing mouse cortices, in vivo purified neuronal subtypes, and neurons differentiated in vitro. Our analysis revealed early- and late-switch exons in genes with distinct functions, and these switches accurately define neuronal maturation stages. Integrative modeling suggests that these switches are under direct and combinatorial regulation by distinct sets of neuronal RNA-binding proteins including Nova, Rbfox, Mbnl and Ptbp. Surprisingly, various neuronal subtypes in the sensory systems lack Nova and/or Rbfox expression. These neurons retain the "immature" splicing program in early-switch exons, affecting numerous synaptic genes. These results provide new insights into the organization and regulation of the neurodevelopmental transcriptome.
]]></description>
<dc:creator>Weyn-Vanhentenryck, S. M.</dc:creator>
<dc:creator>Feng, H.</dc:creator>
<dc:creator>Ustianenko, D.</dc:creator>
<dc:creator>Duffie, R.</dc:creator>
<dc:creator>Yan, Q.</dc:creator>
<dc:creator>Jacko, M.</dc:creator>
<dc:creator>Martinez, J. C.</dc:creator>
<dc:creator>Goodwin, M.</dc:creator>
<dc:creator>Zhang, X.</dc:creator>
<dc:creator>Hengst, U.</dc:creator>
<dc:creator>Lomvardas, S.</dc:creator>
<dc:creator>Swanson, M. S.</dc:creator>
<dc:creator>Zhang, C.</dc:creator>
<dc:date>2018-01-14</dc:date>
<dc:identifier>doi:10.1101/247601</dc:identifier>
<dc:title><![CDATA[Precise temporal regulation of alternative splicing during neural development]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/256693v1?rss=1">
<title>
<![CDATA[
Spatio-Temporal Gene Discovery For Autism Spectrum Disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/256693v1?rss=1"
</link>
<description><![CDATA[
Whole exome sequencing (WES) studies for Autism Spectrum Disorder (ASD) could identify only around six dozen risk genes to date because the genetic architecture of the disorder is highly complex. To speed the gene discovery process up, a few network-based ASD gene discovery algorithms were proposed. Although these methods use static gene interaction networks, functional clustering of genes is bound to evolve during neurodevelopment and disruptions are likely to have a cascading effect on the future associations. Thus, approaches that disregard the dynamic nature of neurodevelopment are limited in power. Here, we present a spatio-temporal gene discovery algorithm for ASD, which leverages information from evolving gene coexpression networks of neurodevelopment. The algorithm solves a variant of prize-collecting Steiner forest-based problem on coexpression networks to model neurodevelopment and transfer information from precursor neurodevelopmental windows. The decisions made by the algorithm can be traced back, adding interpretability to the results. We apply the algorithm on WES data of 3,871 samples and identify risk clusters using BrainSpan coexpression networks of earlyand mid-fetal periods. On an independent dataset, we show that incorporation of the temporal dimension increases the prediction power: Predicted clusters are hit more and show higher enrichment in ASD-related functions compared to the state-of-the-art. Code is available at http://ciceklab.cs.bilkent.edu.tr/ST-Steiner/.
]]></description>
<dc:creator>Norman, U.</dc:creator>
<dc:creator>Cicek, A. E.</dc:creator>
<dc:date>2018-01-30</dc:date>
<dc:identifier>doi:10.1101/256693</dc:identifier>
<dc:title><![CDATA[Spatio-Temporal Gene Discovery For Autism Spectrum Disorder]]></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/256321v1?rss=1">
<title>
<![CDATA[
Nucleosome turnover is sufficient to establish varied histone methylation states 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/256321v1?rss=1"
</link>
<description><![CDATA[
Transcription-dependent methylation of histone H3 at lysine 79 (H3K79) is evolutionarily conserved from yeast to mammals, critical for normal development and frequently deregulated by genetic recombination in Mixed Lineage Leukemia. Although this histone modification is associated with gene activity, little is known about the cellular mechanisms of H3K79 methylation regulation. Because no H3K79 demethylase has been discovered, the mechanism of its removal remains unclear. Utilizing chemical-induced-proximity to control histone methylation in vivo we show that the dynamics of methylation state (mono, di, tri-methylation) is genome-context specific. Further, Monte Carlo simulations coupling systems of kinetic reactions with histone turnover rates, suggest that nucleo-some turnover is sufficient to establish varied genome-wide methylation states without active demethylation.
]]></description>
<dc:creator>Chory, E. J.</dc:creator>
<dc:creator>Calarco, J. P.</dc:creator>
<dc:creator>Hathaway, N. A.</dc:creator>
<dc:creator>Bell, O.</dc:creator>
<dc:creator>Neel, D.</dc:creator>
<dc:creator>Crabtree, G. R.</dc:creator>
<dc:date>2018-01-31</dc:date>
<dc:identifier>doi:10.1101/256321</dc:identifier>
<dc:title><![CDATA[Nucleosome turnover is sufficient to establish varied histone methylation states]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/257758v1?rss=1">
<title>
<![CDATA[
Rare variants in the genetic background modulate the expressivity of neurodevelopmental disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/257758v1?rss=1"
</link>
<description><![CDATA[
PurposeTo assess the contribution of rare variants in the genetic background towards variability of neurodevelopmental phenotypes in individuals with rare copy-number variants (CNVs) and gene-disruptive mutations.nnMethodsWe analyzed quantitative clinical information, exome-sequencing, and microarray data from 757 probands and 233 parents and siblings who carry disease-associated mutations.nnResultsThe number of rare secondary mutations in functionally intolerant genes (second-hits) correlated with the expressivity of neurodevelopmental phenotypes in probands with 16p12.1 deletion (n=23, p=0.004) and in probands with autism carrying gene-disruptive mutations (n=184, p=0.03) compared to their carrier family members. Probands with 16p12.1 deletion and a strong family history presented more severe clinical features (p=0.04) and higher burden of second-hits compared to those with mild/no family history (p=0.001). The number of secondary variants also correlated with the severity of cognitive impairment in probands carrying pathogenic rare CNVs (n=53) or de novo mutations in disease genes (n=290), and negatively correlated with head size among 80 probands with 16p11.2 deletion. These second-hits involved known disease-associated genes such as SETD5, AUTS2, and NRXN1, and were enriched for genes affecting cellular and developmental processes.nnConclusionAccurate genetic diagnosis of complex disorders will require complete evaluation of the genetic background even after a candidate gene mutation is identified.
]]></description>
<dc:creator>Pizzo, L.</dc:creator>
<dc:creator>Jensen, M.</dc:creator>
<dc:creator>Polyak, A.</dc:creator>
<dc:creator>Rosenfeld, J. A.</dc:creator>
<dc:creator>Mannik, K.</dc:creator>
<dc:creator>Krishnan, A.</dc:creator>
<dc:creator>McCready, E.</dc:creator>
<dc:creator>Pichon, O.</dc:creator>
<dc:creator>Le Caignec, C.</dc:creator>
<dc:creator>Van Dijck, A.</dc:creator>
<dc:creator>Pope, K.</dc:creator>
<dc:creator>Voorhoeve, E.</dc:creator>
<dc:creator>Yoon, J.</dc:creator>
<dc:creator>Stankiewicz, P.</dc:creator>
<dc:creator>Cheung, S. W.</dc:creator>
<dc:creator>Pazuchanics, D.</dc:creator>
<dc:creator>Huber, E.</dc:creator>
<dc:creator>Kumar, V.</dc:creator>
<dc:creator>Kember, R.</dc:creator>
<dc:creator>Mari, F.</dc:creator>
<dc:creator>Curro, A.</dc:creator>
<dc:creator>Castiglia, L.</dc:creator>
<dc:creator>Galesi, O.</dc:creator>
<dc:creator>Avola, E.</dc:creator>
<dc:creator>Mattina, T.</dc:creator>
<dc:creator>Fichera, M.</dc:creator>
<dc:creator>Mandara, L.</dc:creator>
<dc:creator>Vincent, M.</dc:creator>
<dc:creator>Nizon, M.</dc:creator>
<dc:creator>Mercier, S.</dc:creator>
<dc:creator>Beneteau, C.</dc:creator>
<dc:creator>Blesson, S.</dc:creator>
<dc:creator>Martin-Coignard, D.</dc:creator>
<dc:creator>Mosca-Boidron, A.-L.</dc:creator>
<dc:creator>Caberg, J. H.</dc:creator>
<dc:creator>Bucan, M.</dc:creator>
<dc:creator>Zeesman, S.</dc:creator>
<dc:creator>Nowaczyk, M. J. M.</dc:creator>
<dc:creator>Lefebvre, M.</dc:creator>
<dc:creator>Faivre, L.</dc:creator>
<dc:creator>Callier, P.</dc:creator>
<dc:creator>Skinner, C.</dc:creator>
<dc:creator>Keren, B.</dc:creator>
<dc:creator>Perrine, C.</dc:creator>
<dc:creator>Pronte</dc:creator>
<dc:date>2018-02-01</dc:date>
<dc:identifier>doi:10.1101/257758</dc:identifier>
<dc:title><![CDATA[Rare variants in the genetic background modulate the expressivity of neurodevelopmental disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/259390v1?rss=1">
<title>
<![CDATA[
MVP: predicting pathogenicity of missense variants by deep neural networks 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/259390v1?rss=1"
</link>
<description><![CDATA[
Accurate pathogenicity prediction of missense variants is critical to improve power in genetic studies and accurate interpretation in clinical genetic testing. Here we describe a new prediction method, MVP, which uses a deep learning approach to leverage large training data sets and many correlated predictors. Using cancer mutation hotspots and de novo germline mutations from developmental disorders for benchmarking, MVP achieved better performance in prioritizing pathogenic missense variants than previous methods.
]]></description>
<dc:creator>Qi, H.</dc:creator>
<dc:creator>Chen, C.</dc:creator>
<dc:creator>Zhang, H.</dc:creator>
<dc:creator>Long, J. J.</dc:creator>
<dc:creator>Chung, W. K.</dc:creator>
<dc:creator>Guan, Y.</dc:creator>
<dc:creator>Shen, Y.</dc:creator>
<dc:date>2018-02-02</dc:date>
<dc:identifier>doi:10.1101/259390</dc:identifier>
<dc:title><![CDATA[MVP: predicting pathogenicity of missense variants by deep neural networks]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/224774v1?rss=1">
<title>
<![CDATA[
Common risk variants identified in autism spectrum disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/224774v1?rss=1"
</link>
<description><![CDATA[
Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 ASD cases and 27,969 controls that identifies five genome-wide significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), seven additional loci shared with other traits are identified at equally strict significance levels. Dissecting the polygenic architecture we find both quantitative and qualitative polygenic heterogeneity across ASD subtypes, in contrast to what is typically seen in other complex disorders. These results highlight biological insights, particularly relating to neuronal function and corticogenesis and establish that GWAS performed at scale will be much more productive in the near term in ASD, just as it has been in a broad range of important psychiatric and diverse medical phenotypes.
]]></description>
<dc:creator>Grove, J.</dc:creator>
<dc:creator>Ripke, S.</dc:creator>
<dc:creator>Als, T. D.</dc:creator>
<dc:creator>Mattheisen, M.</dc:creator>
<dc:creator>Walters, R.</dc:creator>
<dc:creator>Won, H.</dc:creator>
<dc:creator>Pallesen, J.</dc:creator>
<dc:creator>Agerbo, E.</dc:creator>
<dc:creator>Andreassen, O. A.</dc:creator>
<dc:creator>Anney, R.</dc:creator>
<dc:creator>Belliveau, R.</dc:creator>
<dc:creator>Bettella, F.</dc:creator>
<dc:creator>Buxbaum, J. D.</dc:creator>
<dc:creator>Bybjerg-Grauholm, J.</dc:creator>
<dc:creator>Baekved-Hansen, M.</dc:creator>
<dc:creator>Cerrato, F.</dc:creator>
<dc:creator>Chambert, K.</dc:creator>
<dc:creator>Christensen, J. H.</dc:creator>
<dc:creator>Churchhouse, C.</dc:creator>
<dc:creator>Dellenvall, K.</dc:creator>
<dc:creator>Demontis, D.</dc:creator>
<dc:creator>De Rubeis, S.</dc:creator>
<dc:creator>Devlin, B.</dc:creator>
<dc:creator>Djurovic, S.</dc:creator>
<dc:creator>Dumont, A.</dc:creator>
<dc:creator>Goldstein, J.</dc:creator>
<dc:creator>Hansen, C. S.</dc:creator>
<dc:creator>Hauberg, M. E.</dc:creator>
<dc:creator>Hollegaard, M. V.</dc:creator>
<dc:creator>Hope, S.</dc:creator>
<dc:creator>Howrigan, D. P.</dc:creator>
<dc:creator>Huang, H.</dc:creator>
<dc:creator>Hultman, C.</dc:creator>
<dc:creator>Klei, L.</dc:creator>
<dc:creator>Maller, J.</dc:creator>
<dc:creator>Martin, J.</dc:creator>
<dc:creator>Martin, A. R.</dc:creator>
<dc:creator>Moran, J.</dc:creator>
<dc:creator>Nyegaard, M.</dc:creator>
<dc:creator>Naerland, T.</dc:creator>
<dc:creator>Palmer, D. S.</dc:creator>
<dc:creator>Palotie, A.</dc:creator>
<dc:creator>Peders</dc:creator>
<dc:date>2017-11-25</dc:date>
<dc:identifier>doi:10.1101/224774</dc:identifier>
<dc:title><![CDATA[Common risk variants identified in autism spectrum disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/017301v1?rss=1">
<title>
<![CDATA[
Simple genetic models for autism spectrum disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/017301v1?rss=1"
</link>
<description><![CDATA[
To explore the interplay between new mutation, transmission, and gender bias in genetic disease requires formal quantitative modeling. Autism spectrum disorders offer an ideal case: they are genetic in origin, complex, and show a gender bias. The high reproductive costs of autism ensure that most strongly associated genetic mutations are short-lived, and indeed the disease exhibits both transmitted and de novo components. There is a large body of both epidemiologic and genomic data that greatly constrain the genetic mechanisms that may contribute to the disorder. We develop a computational framework that assumes classes of additive variants, each member of a class having equal effect. We restrict our initial exploration to single class models, each having three parameters. Only one model matches epidemiological data. It also independently matches the incidence of de novo mutation in simplex families, the gender bias in unaffected siblings in simplex populations, and rates of mutation in target genes. This model makes strong and as yet not fully tested predictions, namely that females are the primary carriers in cases of genetic transmission, and that the incidence of de novo mutation in target genes for families at high risk for autism are not especially elevated. In its simplicity, this model does not account for MZ twin concordance or the distorted gender bias of high functioning children with ASD, and does not accommodate all the known mechanisms contributing to ASD. We point to the next steps in applying the same computational framework to explore more complex models.nnAuthor summaryFor understanding complex genetic diseases one needs both data and molecular/genetic models. In the absence of any model, it is impossible to do more than summarize observations. A good model will be consistent with much or all of the existing data and puts the data in the context of known genetic principles. Ideally the model will make testable predictions. Where the good models fail often shows the directions that require more thought about mechanisms. In this paper we describe a new computational framework that we use to explore a complex genetic disorder with many gene targets, with both de novo and transmitted variants, and with gender bias. The disorder we consider is autism spectrum disorder (ASD), and our framework rules out some previous models that make unsustainable predictions. We identify a formal model that satisfies diverse epidemiologic and genomic observations. This model makes strong and untested predictions and thereby suggests new studies that would resolve outstanding aspects of autism genetics.
]]></description>
<dc:creator>Swagatam Mukhopadhyay</dc:creator>
<dc:creator>Michael Wigler</dc:creator>
<dc:creator>Dan Levy</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-03-30</dc:date>
<dc:identifier>doi:10.1101/017301</dc:identifier>
<dc:title><![CDATA[Simple genetic models for autism spectrum disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-03-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/264416v1?rss=1">
<title>
<![CDATA[
Maturation Trajectories of Cortical Resting-State Networks Depend on the Mediating Frequency Band 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/264416v1?rss=1"
</link>
<description><![CDATA[
The functional significance of resting state networks and their abnormal manifestations in psychiatric disorders are firmly established, as is the importance of the cortical rhythms in mediating these networks. Resting state networks are known to undergo substantial reorganization from childhood to adulthood, but whether distinct cortical rhythms, which are generated by separable neural mechanisms and are often manifested abnormally in psychiatric conditions, mediate maturation differentially, remains unknown. Using magnetoencephalography (MEG) to map frequency band specific maturation of resting state networks from age 7 to 29 in 162 participants (31 independent), we found significant changes with age in networks mediated by the beta (13-30Hz) and gamma (31-80Hz) bands. More specifically, gamma band mediated networks followed an expected asymptotic trajectory, but beta band mediated networks followed a linear trajectory. Network integration increased with age in gamma band mediated networks, while local segregation increased with age in beta band mediated networks. Spatially, the hubs that changed in importance with age in the beta band mediated networks had relatively little overlap with those that showed the greatest changes in the gamma band mediated networks. These findings are relevant for our understanding of the neural mechanisms of cortical maturation, in both typical and atypical development.
]]></description>
<dc:creator>Khan, S.</dc:creator>
<dc:creator>Hashmi, J.</dc:creator>
<dc:creator>Mamashli, F.</dc:creator>
<dc:creator>Michmizos, K.</dc:creator>
<dc:creator>Kitzbichler, M.</dc:creator>
<dc:creator>Bharadwaj, H.</dc:creator>
<dc:creator>Bekhti, Y.</dc:creator>
<dc:creator>Ganesan, S.</dc:creator>
<dc:creator>Garel, K. A.</dc:creator>
<dc:creator>Whitfield-Gabrieli, S.</dc:creator>
<dc:creator>Gollub, R.</dc:creator>
<dc:creator>Kong, J.</dc:creator>
<dc:creator>Vaina, L. M.</dc:creator>
<dc:creator>Rana, K.</dc:creator>
<dc:creator>Stufflebeam, S.</dc:creator>
<dc:creator>Hamalainen, M.</dc:creator>
<dc:creator>Kenet, T.</dc:creator>
<dc:date>2018-02-13</dc:date>
<dc:identifier>doi:10.1101/264416</dc:identifier>
<dc:title><![CDATA[Maturation Trajectories of Cortical Resting-State Networks Depend on the Mediating Frequency Band]]></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/277707v1?rss=1">
<title>
<![CDATA[
ASD and ADHD have a similar burden of rare protein-truncating variants 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/277707v1?rss=1"
</link>
<description><![CDATA[
Main Text
]]></description>
<dc:creator>Satterstrom, F. K.</dc:creator>
<dc:creator>Walters, R. K.</dc:creator>
<dc:creator>Singh, T.</dc:creator>
<dc:creator>Wigdor, E. M.</dc:creator>
<dc:creator>Lescai, F.</dc:creator>
<dc:creator>Demontis, D.</dc:creator>
<dc:creator>Kosmicki, J. A.</dc:creator>
<dc:creator>Grove, J.</dc:creator>
<dc:creator>Stevens, C.</dc:creator>
<dc:creator>Bybjerg-Grauholm, J.</dc:creator>
<dc:creator>Baekvad-Hansen, M.</dc:creator>
<dc:creator>Palmer, D. S.</dc:creator>
<dc:creator>Maller, J. B.</dc:creator>
<dc:creator>iPSYCH-Broad Consortium,</dc:creator>
<dc:creator>Nordentoft, M.</dc:creator>
<dc:creator>Mors, O.</dc:creator>
<dc:creator>Robinson, E. B.</dc:creator>
<dc:creator>Hougaard, D. M.</dc:creator>
<dc:creator>Werge, T. M.</dc:creator>
<dc:creator>Bo Mortensen, P.</dc:creator>
<dc:creator>Neale, B. M.</dc:creator>
<dc:creator>Borglum, A. D.</dc:creator>
<dc:creator>Daly, M. J.</dc:creator>
<dc:date>2018-03-06</dc:date>
<dc:identifier>doi:10.1101/277707</dc:identifier>
<dc:title><![CDATA[ASD and ADHD have a similar burden of rare protein-truncating variants]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/277673v1?rss=1">
<title>
<![CDATA[
A reference haplotype panel for genome-wide imputation of short tandem repeats 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/277673v1?rss=1"
</link>
<description><![CDATA[
Short tandem repeats (STRs) are involved in dozens of Mendelian disorders and have been implicated in a variety of complex traits. However, existing technologies focusing on single nucleotide polymorphisms (SNPs) have not allowed for systematic STR association studies. Here, we leverage next-generation sequencing data from 479 families to create a SNP+STR reference haplotype panel for genome-wide imputation of STRs into SNP data. Imputation achieved an average of 97% concordance between genotyped and imputed STR genotypes in an external dataset compared to 63% expected under a random model. Performance varied widely across STRs, with near perfect concordance at bi-allelic STRs vs. 70% at highly polymorphic forensics markers. We demonstrate that imputation increases power over individual SNPs to detect STR associations using simulated phenotypes and gene expression data. This resource will enable the first large-scale STR association studies using existing SNP datasets, and will likely yield new insights into complex traits.
]]></description>
<dc:creator>Saini, S.</dc:creator>
<dc:creator>Mitra, I.</dc:creator>
<dc:creator>Gymrek, M.</dc:creator>
<dc:date>2018-03-06</dc:date>
<dc:identifier>doi:10.1101/277673</dc:identifier>
<dc:title><![CDATA[A reference haplotype panel for genome-wide imputation of short tandem repeats]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/276527v1?rss=1">
<title>
<![CDATA[
Disentangling genetic overlap between Attention-Deficit/Hyperactivity Disorder, literacy and language 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/276527v1?rss=1"
</link>
<description><![CDATA[
Interpreting polygenic overlap between ADHD and both literacy- and language-related impairments is challenging as genetic confounding can bias associations. Here, we investigate evidence for links between polygenic ADHD risk and multiple literacy- and language-related abilities (LRAs), assessed in UK children (N[&le;]5,919), conditional on genetic effects shared with educational attainment (EA). Genome-wide summary statistics on clinical ADHD and years-of-schooling were obtained from large consortia (N[&le;]326,041). ADHD-polygenic scores (ADHD-PGS) were inversely associated with LRAs in ALSPAC, most consistently with reading-related abilities, and explained [&le;]1.6% phenotypic variation. Polygenic links were then dissected into both genetic effects shared with and independent of EA using multivariable regressions (MVR), analogous to Mendelian Randomization approaches accounting for mediating effects. Conditional on EA, polygenic ADHD risk remained associated with multiple literacy-related skills, phonemic awareness and verbal intelligence, but not language-related skills such as listening comprehension and non-word repetition. Pooled reading performance showed the strongest overlap with ADHD independent of EA. Using conservative ADHD-instruments (P-threshold<5x10-8) this corresponded to a 0.35 decrease in Z-scores per log-odds in ADHD-liability (P=9.2x10-5). Using subthreshold ADHD-instruments (P-threshold<0.0015), these associations had lower magnitude, but higher predictive accuracy, with a 0.03 decrease in Z-scores (P=1.4x10-6). Polygenic ADHD-effects shared with EA were of equal strength and at least equal magnitude compared to those independent of EA, for all LRAs studied, and only detectable using subthreshold instruments. Thus, ADHD-related polygenic links are highly susceptible to genetic confounding, concealing an ADHD-specific association profile that primarily involves reading-related impairments, but few language-related problems.
]]></description>
<dc:creator>Verhoef, E.</dc:creator>
<dc:creator>Demontis, D.</dc:creator>
<dc:creator>Burgess, S.</dc:creator>
<dc:creator>Shapland, C. Y.</dc:creator>
<dc:creator>Dale, P. S.</dc:creator>
<dc:creator>Okbay, A.</dc:creator>
<dc:creator>Neale, B. M.</dc:creator>
<dc:creator>Faraone, S. V.</dc:creator>
<dc:creator>iPSYCH-Broad-PGC ADHD Consortium,</dc:creator>
<dc:creator>Stergiakouli, E.</dc:creator>
<dc:creator>Davey Smith, G.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Borglum, A.</dc:creator>
<dc:creator>St Pourcain, B.</dc:creator>
<dc:date>2018-03-05</dc:date>
<dc:identifier>doi:10.1101/276527</dc:identifier>
<dc:title><![CDATA[Disentangling genetic overlap between Attention-Deficit/Hyperactivity Disorder, literacy and language]]></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/270850v1?rss=1">
<title>
<![CDATA[
Intellectual phenotypes in autism strongly correlate with gene dosage changes and exon locations of truncating mutations 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/270850v1?rss=1"
</link>
<description><![CDATA[
Autism spectrum disorders (ASD) are a group of related neurodevelopmental diseases displaying significant genetic and phenotypic heterogeneity1-4. Despite recent progress in understanding ASD genetics, the nature of phenotypic heterogeneity across probands remains unclear5, 6. Notably, likely gene-disrupting (LGD) de novo mutations affecting the same gene often result in substantially different ASD phenotypes. Nevertheless, we find that truncating mutations that affect the same exon frequently lead to strikingly similar intellectual phenotypes in unrelated ASD probands. Analogous patterns are observed for two independent proband cohorts and several other important ASD-associated phenotypes. We find that exons biased towards prenatal and postnatal expression preferentially contribute to ASD cases with lower and higher IQ phenotypes, respectively. These results suggest that exons, rather than genes, often represent a unit of effective phenotypic impact for truncating mutations in autism. The observed phenotypic effects are likely mediated by nonsense-mediated decay (NMD) of splicing isoforms, with autism phenotypes usually triggered by relatively mild (15-30%) decreases in overall gene dosage. We find that each gene with recurrent ASD mutations can be described by a parameter, phenotype dosage sensitivity (PDS), which characterizes the quantitative relationship between changes in a genes dosage and changes in a given disease phenotype. We further demonstrate analogous relationships between LGD mutations and changes in gene expression across human tissues. Therefore, similar phenotypic patterns may be also observed in multiple other systems and genetic disorders.
]]></description>
<dc:creator>Chiang, A. H.</dc:creator>
<dc:creator>Chang, J.</dc:creator>
<dc:creator>Vitkup, D.</dc:creator>
<dc:date>2018-04-17</dc:date>
<dc:identifier>doi:10.1101/270850</dc:identifier>
<dc:title><![CDATA[Intellectual phenotypes in autism strongly correlate with gene dosage changes and exon locations of truncating mutations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/305904v1?rss=1">
<title>
<![CDATA[
Rbfox1 mediates cell-type-specific splicing in cortical interneurons 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/305904v1?rss=1"
</link>
<description><![CDATA[
Cortical interneurons display a remarkable diversity in their morphology, physiological properties and connectivity. Elucidating the molecular determinants underlying this heterogeneity is essential for understanding interneuron development and function. We discovered that alternative splicing differentially regulates the integration of somatostatin- and parvalbumin-expressing interneurons into nascent cortical circuits through the cell-type specific tailoring of mRNAs. Specifically, we identified a role for the activity-dependent splicing regulator Rbfox1 in the development of cortical interneuron subtype specific efferent connectivity. Our work demonstrates that Rbfox1 mediates largely non-overlapping alternative splicing programs within two distinct but related classes of interneurons.
]]></description>
<dc:creator>Jaglin, X. H.</dc:creator>
<dc:creator>Wamsley, B.</dc:creator>
<dc:creator>Favuzzi, E.</dc:creator>
<dc:creator>Quattracolo, G.</dc:creator>
<dc:creator>Negro, M.</dc:creator>
<dc:creator>Yusef, N.</dc:creator>
<dc:creator>Khodadadi-Jamayran, A.</dc:creator>
<dc:creator>Rudy, B.</dc:creator>
<dc:creator>Fishell, G.</dc:creator>
<dc:date>2018-04-21</dc:date>
<dc:identifier>doi:10.1101/305904</dc:identifier>
<dc:title><![CDATA[Rbfox1 mediates cell-type-specific splicing in cortical interneurons]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/317693v1?rss=1">
<title>
<![CDATA[
Increased excitation-inhibition ratio stabilizes synapse and circuit excitability in four autism mouse models. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/317693v1?rss=1"
</link>
<description><![CDATA[
Distinct genetic forms of autism are hypothesized to share a common increase in excitation-inhibition (E-I) ratio in cerebral cortex, causing hyperexcitability and excess spiking. We provide the first systematic test of this hypothesis across 4 mouse models (Fmr1-/y, Cntnap2-/-, 16p11.2del/+, Tsc2+/-), focusing on somatosensory cortex. All autism mutants showed reduced feedforward inhibition in layer 2/3 coupled with more modest, variable reductions in feedforward excitation, driving a common increase in E-I conductance ratio. Despite this, feedforward spiking, synaptic depolarization and spontaneous spiking were essentially normal. Modeling revealed that E and I conductance changes in each mutant were quantitatively matched to yield stable, not increased, synaptic depolarization for cells near spike threshold. Correspondingly, whisker-evoked spiking was not increased in vivo, despite detectably reduced inhibition. Thus, elevated E-I ratio is a common circuit phenotype, but appears to reflect homeostatic stabilization of synaptic drive, rather than driving network hyperexcitability in autism.
]]></description>
<dc:creator>Antoine, M. W.</dc:creator>
<dc:creator>Schnepel, P.</dc:creator>
<dc:creator>Langberg, T.</dc:creator>
<dc:creator>Feldman, D. E.</dc:creator>
<dc:date>2018-05-09</dc:date>
<dc:identifier>doi:10.1101/317693</dc:identifier>
<dc:title><![CDATA[Increased excitation-inhibition ratio stabilizes synapse and circuit excitability in four autism mouse models.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/319368v1?rss=1">
<title>
<![CDATA[
Widespread Alterations in Translation Elongation in the Brain of Juvenile Fmr1 Knock-Out Mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/319368v1?rss=1"
</link>
<description><![CDATA[
FMRP is a polysome-associated RNA-binding protein encoded by Fmr1 that is lost in Fragile X syndrome. Increasing evidence suggests that FMRP regulates both translation initiation and elongation, but the gene-specificity of these effects is unclear. To elucidate the impact of Fmr1 loss on translation, we used ribosome profiling for genome-wide measurements of ribosomal occupancy and positioning in the cortex of 24 day-old Fmr1 knock-out mice. We found a remarkably coherent reduction in ribosome footprint abundance per mRNA for previously identified, high-affinity mRNA binding partners of FMRP, and an increase for terminal oligo-pyrimidine (TOP) motif-containing genes canonically controlled by mTOR-4EBP-eIF4E signaling. Amino acid motif- and gene-level analyses both showed a widespread reduction of translational pausing in Fmr1 knock-out mice. Our findings are consistent with a model of FMRP-mediated regulation of both translation initiation through eIF4E and elongation that is disrupted in Fragile X syndrome.
]]></description>
<dc:creator>Das Sharma, S.</dc:creator>
<dc:creator>Metz, J. B.</dc:creator>
<dc:creator>Li, H.</dc:creator>
<dc:creator>Hobson, B. D.</dc:creator>
<dc:creator>Hornstein, N.</dc:creator>
<dc:creator>Sulzer, D.</dc:creator>
<dc:creator>Tang, G.</dc:creator>
<dc:creator>Sims, P. A.</dc:creator>
<dc:date>2018-05-10</dc:date>
<dc:identifier>doi:10.1101/319368</dc:identifier>
<dc:title><![CDATA[Widespread Alterations in Translation Elongation in the Brain of Juvenile Fmr1 Knock-Out Mice]]></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/319681v1?rss=1">
<title>
<![CDATA[
Whole-genome deep learning analysis reveals causal role of noncoding mutations in autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/319681v1?rss=1"
</link>
<description><![CDATA[
We address the challenge of detecting the contribution of noncoding mutations to disease with a deep-learning-based framework that predicts specific regulatory effects and deleterious disease impact of genetic variants. Applying this framework to 1,790 Autism Spectrum Disorder (ASD) simplex families reveals autism disease causality of noncoding mutations by demonstrating that ASD probands harbor transcriptional (TRDs) and post-transcriptional (RRDs) regulation-disrupting mutations of significantly higher functional impact than unaffected siblings. Importantly, we detect this significant noncoding contribution at each level, transcriptional and post-transcriptional, independently and after multiple hypothesis correction. Further analysis suggests involvement of noncoding mutations in synaptic transmission and neuronal development, and reveals a convergent genetic landscape of coding and noncoding (TRD and RRD) de novo mutations in ASD. We demonstrate that sequences carrying prioritized proband de novo mutations possess transcriptional regulatory activity and drive expression differentially, and highlight a link between noncoding mutations and IQ heterogeneity in ASD probands. Our predictive genomics framework illuminates the role of noncoding mutations in ASD, prioritizes high impact transcriptional and post-transcriptional regulatory mutations for further study, and is broadly applicable to complex human diseases.
]]></description>
<dc:creator>Zhou, J.</dc:creator>
<dc:creator>Park, C.</dc:creator>
<dc:creator>Theesfeld, C.</dc:creator>
<dc:creator>Yuan, Y.</dc:creator>
<dc:creator>Sawicka, K.</dc:creator>
<dc:creator>Darnell, J.</dc:creator>
<dc:creator>Scheckel, C.</dc:creator>
<dc:creator>Fak, J.</dc:creator>
<dc:creator>Tajima, Y.</dc:creator>
<dc:creator>Darnell, R.</dc:creator>
<dc:creator>Troyanskaya, O.</dc:creator>
<dc:date>2018-05-11</dc:date>
<dc:identifier>doi:10.1101/319681</dc:identifier>
<dc:title><![CDATA[Whole-genome deep learning analysis reveals causal role of noncoding mutations in autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/321182v1?rss=1">
<title>
<![CDATA[
Dynamics of social representation in the mouse prefrontal cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/321182v1?rss=1"
</link>
<description><![CDATA[
The prefrontal cortex (PFC) plays an important role in regulating social functions in mammals, and impairments in this region have been linked with social dysfunction in psychiatric disorders. Yet little is known of how the PFC encodes social information and of how social representations may be altered in such disorders. Here, we show that neurons in the medial PFC (mPFC) of freely behaving mice preferentially respond to socially-relevant sensory cues. Population activity patterns in the mPFC differed considerably between social and nonsocial stimuli and underwent experience-dependent refinement. In Cntnap2 knockout mice, a genetic model of autism, both the categorization of sensory stimuli and the refinement of social representations were impaired. Noise levels in spontaneous population activity were higher in Cntnap2 mice, and correlated strongly with the degree to which social representations were disrupted. Our findings elucidate the encoding of social sensory cues in the mPFC, and provide an important link between altered prefrontal dynamics and autism-associated social dysfunction.
]]></description>
<dc:creator>Levy, D. R.</dc:creator>
<dc:creator>Tamir, T.</dc:creator>
<dc:creator>Kaufman, M.</dc:creator>
<dc:creator>Weissbrod, A.</dc:creator>
<dc:creator>Schneidman, E.</dc:creator>
<dc:creator>Yizhar, O.</dc:creator>
<dc:date>2018-05-14</dc:date>
<dc:identifier>doi:10.1101/321182</dc:identifier>
<dc:title><![CDATA[Dynamics of social representation in the mouse prefrontal cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/358622v1?rss=1">
<title>
<![CDATA[
Nested oscillatory dynamics in cortical organoids model early human brain network development 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/358622v1?rss=1"
</link>
<description><![CDATA[
Structural and transcriptional changes during early brain maturation follow fixed developmental programs defined by genetics. However, whether this is true for functional network activity remains unknown, primarily due to experimental inaccessibility of the initial stages of the living human brain. Here, we developed cortical organoids that spontaneously display periodic and regular oscillatory network events that are dependent on glutamatergic and GABAergic signaling. These nested oscillations exhibit cross-frequency coupling, proposed to coordinate neuronal computation and communication. As evidence of potential network maturation, oscillatory activity subsequently transitioned to more spatiotemporally irregular patterns, capturing features observed in preterm human electroencephalography (EEG). These results show that the development of structured network activity in the human neocortex may follow stable genetic programming, even in the absence of external or subcortical inputs. Our approach provides novel opportunities for investigating and manipulating the role of network activity in the developing human cortex.nnHIGHLIGHTSO_LIEarly development of human functional neural networks and oscillatory activity can be modeled in vitro.nC_LIO_LICortical organoids exhibit phase-amplitude coupling between delta oscillation (2 Hz) and high-frequency activity (100-400 Hz) during network-synchronous events.nC_LIO_LIDifferential role of glutamate and GABA in initiating and maintaining oscillatory network activity.nC_LIO_LIDevelopmental impairment of MECP2-KO cortical organoids impacts the emergence of oscillatory activity.nC_LIO_LICortical organoid network electrophysiological signatures correlate with human preterm neonatal EEG features.nC_LInneTOCBrain oscillations are a candidate mechanism for how neural populations are temporally organized to instantiate cognition and behavior. Cortical organoids initially exhibit periodic and highly regular nested oscillatory network events that eventually transition to more spatiotemporally complex activity, capturing features of late-stage preterm infant electroencephalography. Functional neural circuitry in cortical organoids exhibits emergence and development of oscillatory network dynamics similar to those found in the developing human brain.
]]></description>
<dc:creator>Trujillo, C. A.</dc:creator>
<dc:creator>Gao, R.</dc:creator>
<dc:creator>Negraes, P. D.</dc:creator>
<dc:creator>Chaim, I. A.</dc:creator>
<dc:creator>Domissy, A.</dc:creator>
<dc:creator>Vandenberghe, M.</dc:creator>
<dc:creator>Devor, A.</dc:creator>
<dc:creator>Yeo, G. W.</dc:creator>
<dc:creator>Voytek, B.</dc:creator>
<dc:creator>Muotri, A. R.</dc:creator>
<dc:date>2018-06-29</dc:date>
<dc:identifier>doi:10.1101/358622</dc:identifier>
<dc:title><![CDATA[Nested oscillatory dynamics in cortical organoids model early human brain network development]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/366781v1?rss=1">
<title>
<![CDATA[
The autism-associated gene Scn2a plays an essential role in synaptic stability and learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/366781v1?rss=1"
</link>
<description><![CDATA[
Autism spectrum disorder (ASD) is strongly associated with de novo gene mutations. One of the most commonly affected genes is SCN2A. ASD-associated SCN2A mutations impair the encoded protein NaV1.2, a sodium channel important for action potential initiation and propagation in developing excitatory cortical neurons. The link between an axonal sodium channel and ASD, a disorder typically attributed to synaptic or transcriptional dysfunction, is unclear. Here, we show NaV1.2 is unexpectedly critical for dendritic excitability and synaptic function in mature pyramidal neurons, in addition to regulating early developmental axonal excitability. NaV1.2 loss reduced action potential backpropagation into dendrites, impairing synaptic plasticity and synaptic stability, even when NaV1.2 expression was disrupted late in development. Furthermore, we identified behavioral impairments in learning and sociability, paralleling observations in children with SCN2A loss. These results reveal a novel dendritic function for NaV1.2, providing insight into cellular mechanisms likely underlying circuit and behavioral dysfunction in ASD.
]]></description>
<dc:creator>Spratt, P.</dc:creator>
<dc:creator>Ben-Shalom, R.</dc:creator>
<dc:creator>Keeshen, C.</dc:creator>
<dc:creator>Burke, K.</dc:creator>
<dc:creator>Clarkson, R.</dc:creator>
<dc:creator>Sanders, S.</dc:creator>
<dc:creator>Bender, K.</dc:creator>
<dc:date>2018-07-10</dc:date>
<dc:identifier>doi:10.1101/366781</dc:identifier>
<dc:title><![CDATA[The autism-associated gene Scn2a plays an essential role in synaptic stability and learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/307009v1?rss=1">
<title>
<![CDATA[
Bidirectional control of orienting behavior by distinct prefrontal circuits 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/307009v1?rss=1"
</link>
<description><![CDATA[
Sensorimotor behaviors require processing of behaviorally relevant sensory cues and the ability to select appropriate responses from a vast behavioral repertoire. Top-down modulation by the prefrontal cortex (PFC) is thought to be key for both processes but the precise role of specific circuits remains unclear. We examined the sensorimotor function of anatomically distinct outputs from a subdivision of the mouse PFC, the anterior cingulate cortex (ACC). Using a visually guided two-choice behavioral paradigm with multiple cue-response mappings, we dissociated the sensory and motor response components of sensorimotor control. Projection-specific two-photon calcium imaging and optogenetic manipulations show that ACC outputs to the superior colliculus, a key midbrain structure for response selection, principally coordinate specific motor responses. Importantly, ACC outputs exert top-down control by reducing the innate response bias of the superior colliculus. In contrast, ACC outputs to the visual cortex facilitate sensory processing of visual cues. Our results ascribe motor and sensory roles to ACC projections to the superior colliculus and the visual cortex and demonstrate for the first time a circuit motif for PFC function wherein anatomically non-overlapping output pathways coordinate complementary but distinct aspects of visual sensorimotor behavior.
]]></description>
<dc:creator>Huda, R.</dc:creator>
<dc:creator>Sipe, G. O.</dc:creator>
<dc:creator>Adam, E.</dc:creator>
<dc:creator>Breton-Provencher, V.</dc:creator>
<dc:creator>Pho, G.</dc:creator>
<dc:creator>Gunter, L.</dc:creator>
<dc:creator>Wickersham, I. R.</dc:creator>
<dc:creator>Sur, M.</dc:creator>
<dc:date>2018-04-25</dc:date>
<dc:identifier>doi:10.1101/307009</dc:identifier>
<dc:title><![CDATA[Bidirectional control of orienting behavior by distinct prefrontal circuits]]></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/365445v1?rss=1">
<title>
<![CDATA[
Autism-associated Shank3 is essential for homeostatic plasticity and neuronal circuit stability 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/365445v1?rss=1"
</link>
<description><![CDATA[
Mutations in Shank3 are strongly associated with autism spectrum disorders and circuit disfunction, but a unified view of how Shank3 loss disrupts circuit function and excitability is lacking. Stabilizing, homeostatic forms of synaptic and intrinsic plasticity are critical for preventing circuit hyper- or hypo-excitability, leading us to ask whether Shank3 loss perturbs circuits by disrupting homeostatic plasticity. We show that Shank3 loss abolishes synaptic and intrinsic homeostatic plasticity, which can be rescued by lithium(Li), a drug with therapeutic potential in human Shankopathies. Further, Shank3 loss in vivo severely compromises the ability of visual cortical circuits to recover from perturbations to sensory drive. Our findings suggest that the loss of homeostatic compensation is a critical endophenotype that can explain a range of circuit disfunctions in Shankopathies.
]]></description>
<dc:creator>Tatavarty, V.</dc:creator>
<dc:creator>Torrado Pacheco, A.</dc:creator>
<dc:creator>Lin, H.</dc:creator>
<dc:creator>Miska, N. J.</dc:creator>
<dc:creator>Hengen, K. B.</dc:creator>
<dc:creator>Wagner, F. F.</dc:creator>
<dc:creator>Turrigiano, G. G.</dc:creator>
<dc:date>2018-07-09</dc:date>
<dc:identifier>doi:10.1101/365445</dc:identifier>
<dc:title><![CDATA[Autism-associated Shank3 is essential for homeostatic plasticity and neuronal circuit stability]]></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/260083v1?rss=1">
<title>
<![CDATA[
The critical role of ASD-related gene CNTNAP3 in regulating synaptic development and social behavior in mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/260083v1?rss=1"
</link>
<description><![CDATA[
Accumulated genetic evidences indicate that the contactin associated protein-like (CNTNAP) family is implicated in autism spectrum disorders (ASD). In this study, we identified genetic mutations in the CNTNAP3 gene from Chinese Han ASD cohorts and Simons Simplex Collections. We found that CNTNAP3 interacted with synaptic adhesion proteins Neuroligin1 and Neuroligin2, as well as scaffolding proteins PSD95 and Gephyrin. Significantly, we found that CNTNAP3 played an opposite role in controlling the development of excitatory and inhibitory synapses in vitro and in vivo, in which ASD mutants exhibited loss-of-function effects. In this study, we showed that Cntnap3-null mice exhibited deficits in social interaction, spatial learning and prominent repetitive behaviors. These evidences elucidate the pivotal role of CNTNAP3 in synapse development and social behaviors, providing the mechanistic insights for ASD.
]]></description>
<dc:creator>Tong, D.</dc:creator>
<dc:creator>Chen, R.</dc:creator>
<dc:creator>Lu, Y.</dc:creator>
<dc:creator>Li, W.</dc:creator>
<dc:creator>Zhang, Y.</dc:creator>
<dc:creator>Lin, J.</dc:creator>
<dc:creator>He, L.</dc:creator>
<dc:creator>Dang, T.</dc:creator>
<dc:creator>Shan, S.</dc:creator>
<dc:creator>Xu, X.</dc:creator>
<dc:creator>Zhang, Y.</dc:creator>
<dc:creator>Zhang, C.</dc:creator>
<dc:creator>Du, Y.</dc:creator>
<dc:creator>Zhou, W.-H.</dc:creator>
<dc:creator>Wang, X.</dc:creator>
<dc:creator>Qiu, Z.</dc:creator>
<dc:date>2018-02-05</dc:date>
<dc:identifier>doi:10.1101/260083</dc:identifier>
<dc:title><![CDATA[The critical role of ASD-related gene CNTNAP3 in regulating synaptic development and social behavior in mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/401604v1?rss=1">
<title>
<![CDATA[
CLIP-Seq and massively parallel functional analysis of the CELF6 RNA binding protein reveals a role in destabilizing synaptic gene mRNAs through interaction with 3’UTR elements in vivo 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/401604v1?rss=1"
</link>
<description><![CDATA[
CELF6 is a RNA-binding protein in a family of proteins with roles in human health and disease, however little is known about the mRNA targets or in vivo function of this protein. We utilized CLIP-Seq to identify, for the first time, in vivo targets of CELF6 and identify hundreds of transcripts bound by CELF6 in the brain. We found these are disproportionately mRNAs coding for synaptic proteins. We then conducted functional validation of these targets, testing greater than 400 CELF6 bound sequence elements for their activity, applying a massively parallel reporter assay framework to evaluation of the CLIP data. We also mutated potential binding motifs within these elements and tested their impact. This comprehensive analysis led us to ascribe a previously unknown function to CELF6: we found bound elements were generally repressive of translation, that CELF6 further enhances this repression via decreasing RNA abundance, and this process was dependent on UGU-rich sequence motifs. This greatly extends the known role for CELF6, which had previously been defined only as a splicing factor. We further extend these findings by demonstrating the same function for CELF3, CELF4, and CELF5. Finally, we demonstrate that the CELF6 targets are derepressed in CELF6 mutant mice in vivo, confirming this new role in the brain. Thus, our study demonstrates that CELF6 and other sub-family members are repressive CNS RNA-binding proteins, and CELF6 downregulates specific mRNAs in vivo.
]]></description>
<dc:creator>Rieger, M. A.</dc:creator>
<dc:creator>King, D. M.</dc:creator>
<dc:creator>Cohen, B. A.</dc:creator>
<dc:creator>Dougherty, J. D.</dc:creator>
<dc:date>2018-08-27</dc:date>
<dc:identifier>doi:10.1101/401604</dc:identifier>
<dc:title><![CDATA[CLIP-Seq and massively parallel functional analysis of the CELF6 RNA binding protein reveals a role in destabilizing synaptic gene mRNAs through interaction with 3’UTR elements in vivo]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/285981v1?rss=1">
<title>
<![CDATA[
Integrative cross-species analyses identify deficits in habituation learning as a widely affected mechanism in Autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/285981v1?rss=1"
</link>
<description><![CDATA[
BackgroundAlthough habituation is one of the most ancient and fundamental forms of learning, its regulators and relevance for human disease are poorly understood.nnMethodsWe manipulated the orthologs of 286 genes implicated in intellectual disability (ID) with or without comorbid autism spectrum disorder (ASD) specifically in Drosophila neurons, and tested these models in light-off jump habituation. We dissected neuronal substrates underlying the identified habituation deficits and integrated genotype-phenotype annotations, gene ontologies and interaction networks to determine the clinical features and molecular processes that are associated with habituation deficits.nnResultsWe identified more than 100 genes required for habituation learning. For the vast majority of these, 93 genes, a role in habituation learning was previously unknown. These genes characterize ID disorders with overgrowth/macrocephaly and comorbid ASD. Moreover, ASD individuals from the Simons Simplex Collection carrying disruptive de novo mutations in these genes exhibit increased rates of specific aberrant behaviors including stereotypic speech, hyperactivity and irritability. At the molecular level, ID genes required for normal habituation are enriched in synaptic function and converge on Ras-MAPK signaling. Both increased Ras-MAPK signaling in GABAergic and decreased Ras-MAPK signaling in cholinergic neurons specifically inhibit the adaptive habituation response.nnConclusionsOur work demonstrates the relevance of habituation learning to autism, identifies an unprecedented number of novel habituation players, supports an emerging role for inhibitory neurons in habituation and reveals an opposing, circuit-level-based mechanism for Ras-MAPK signaling. This establishes habituation as a possible, widely applicable target for pharmacologic intervention in ID/ASD.
]]></description>
<dc:creator>Fenckova, M.</dc:creator>
<dc:creator>Asztalos, L.</dc:creator>
<dc:creator>Cizek, P.</dc:creator>
<dc:creator>Singgih, E. L.</dc:creator>
<dc:creator>Blok, L. E. R.</dc:creator>
<dc:creator>Glennon, J. C.</dc:creator>
<dc:creator>IntHout, J.</dc:creator>
<dc:creator>Zweier, C.</dc:creator>
<dc:creator>Eichler, E. E.</dc:creator>
<dc:creator>Bernier, R.</dc:creator>
<dc:creator>Asztalos, Z.</dc:creator>
<dc:creator>Schenck, A.</dc:creator>
<dc:date>2018-03-20</dc:date>
<dc:identifier>doi:10.1101/285981</dc:identifier>
<dc:title><![CDATA[Integrative cross-species analyses identify deficits in habituation learning as a widely affected mechanism in Autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/396986v1?rss=1">
<title>
<![CDATA[
Altered dendritic spine function and integration in a mouse model of Fragile X Syndrome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/396986v1?rss=1"
</link>
<description><![CDATA[
Cellular and circuit hyperexcitability are core features of Fragile X Syndrome and related autism spectrum disorder models. However, a synaptic basis for this hyperexcitability has proved elusive. We show in a mouse model of Fragile X Syndrome, glutamate uncaging onto individual dendritic spines yields stronger single-spine excitation than wild-type, with more silent spines. Furthermore, near-simultaneous uncaging at multiple spines revealed fewer spines are required to trigger an action potential. This arose, in part, from increased dendritic gain due to increased intrinsic excitability, resulting from reduced hyperpolarization-activated currents. Super-resolution microscopy revealed no change in dendritic spine morphology, pointing to an absence of a structure-function relationship. However, ultrastructural analysis revealed a 3-fold increase in multiply-innervated spines, accounting for the increased single-spine excitatory currents following glutamate uncaging. Thus, loss of FMRP causes abnormal synaptogenesis, leading to large numbers of poly-synaptic spines despite normal spine morphology, thus explaining the synaptic perturbations underlying circuit hyperexcitability.
]]></description>
<dc:creator>Booker, S. A.</dc:creator>
<dc:creator>Domanski, A. P.</dc:creator>
<dc:creator>Dando, O. R.</dc:creator>
<dc:creator>Jackson, A. D.</dc:creator>
<dc:creator>Isaac, J. T.</dc:creator>
<dc:creator>Hardingham, G. E.</dc:creator>
<dc:creator>Wyllie, D. J.</dc:creator>
<dc:creator>Kind, P. C.</dc:creator>
<dc:date>2018-08-21</dc:date>
<dc:identifier>doi:10.1101/396986</dc:identifier>
<dc:title><![CDATA[Altered dendritic spine function and integration in a mouse model of Fragile X Syndrome]]></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/379099v1?rss=1">
<title>
<![CDATA[
Using multiple measurements of tissue to estimate individual- and cell-type-specific gene expression via deconvolution 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/379099v1?rss=1"
</link>
<description><![CDATA[
MotivationPatterns of gene expression, quantified at the level of tissue or cells, can inform on etiology of disease. There are now rich resources for tissue-level (bulk) gene expression data, which have been collected from thousands of subjects, and resources involving single-cell RNA-sequencing (scRNA-seq) data are expanding rapidly. The latter yields cell type information, although the data can be noisy and typically are derived from a small number of subjects.nnResultsComplementing these approaches, we develop a method to estimate subject- and cell-type-specific (CTS) gene expression from tissue using an empirical Bayes method that borrows information across multiple measurements of the same tissue per subject (e.g., multiple regions of the brain). Analyzing expression data from multiple brain regions from the Genotype-Tissue Expression project (GTEx) reveals CTS expression, which then permits downstream analyses, such as identification of CTS expression Quantitative Trait Loci (eQTL).nnAvailability and implementationWe implement this method as an R package MIND, hosted on https://github.com/randel/MIND.
]]></description>
<dc:creator>Wang, J.</dc:creator>
<dc:creator>Devlin, B.</dc:creator>
<dc:creator>Roeder, K.</dc:creator>
<dc:date>2018-07-27</dc:date>
<dc:identifier>doi:10.1101/379099</dc:identifier>
<dc:title><![CDATA[Using multiple measurements of tissue to estimate individual- and cell-type-specific gene expression via deconvolution]]></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/338855v1?rss=1">
<title>
<![CDATA[
Whole genome sequencing in multiplex families reveals novel inherited and de novo genetic risk in autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/338855v1?rss=1"
</link>
<description><![CDATA[
Genetic studies of autism spectrum disorder (ASD) have revealed a complex, heterogeneous architecture, in which the contribution of rare inherited variation remains relatively un-explored. We performed whole-genome sequencing (WGS) in 2,308 individuals from families containing multiple affected children, including analysis of single nucleotide variants (SNV) and structural variants (SV). We identified 16 new ASD-risk genes, including many supported by inherited variation, and provide statistical support for 69 genes in total, including previously implicated genes. These risk genes are enriched in pathways involving negative regulation of synaptic transmission and organelle organization. We identify a significant protein-protein interaction (PPI) network seeded by inherited, predicted damaging variants disrupting highly constrained genes, including members of the BAF complex and established ASD risk genes. Analysis of WGS also identified SVs effecting non-coding regulatory regions in developing human brain, implicating NR3C2 and a recurrent 2.5Kb deletion within the promoter of DLG2. These data lend support to studying multiplex families for identifying inherited risk for ASD. We provide these data through the Hartwell Autism Research and Technology Initiative (iHART), an open access cloud-computing repository for ASD genetics research.
]]></description>
<dc:creator>Ruzzo, E. K.</dc:creator>
<dc:creator>Perez-Cano, L.</dc:creator>
<dc:creator>Jung, J.-Y.</dc:creator>
<dc:creator>Wang, L.-k.</dc:creator>
<dc:creator>Kashef-Haghighi, D.</dc:creator>
<dc:creator>Hartl, C.</dc:creator>
<dc:creator>Hoekstra, J.</dc:creator>
<dc:creator>Leventhal, O.</dc:creator>
<dc:creator>Gandal, M. J.</dc:creator>
<dc:creator>Paskov, K.</dc:creator>
<dc:creator>Stockham, N.</dc:creator>
<dc:creator>Polioudakis, D.</dc:creator>
<dc:creator>Lowe, J. K.</dc:creator>
<dc:creator>Geschwind, D. H.</dc:creator>
<dc:creator>Wall, D. P.</dc:creator>
<dc:date>2018-06-06</dc:date>
<dc:identifier>doi:10.1101/338855</dc:identifier>
<dc:title><![CDATA[Whole genome sequencing in multiplex families reveals novel inherited and de novo genetic risk in autism]]></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/484113v1?rss=1">
<title>
<![CDATA[
Novel genes for autism implicate both excitatory and inhibitory cell lineages in risk 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/484113v1?rss=1"
</link>
<description><![CDATA[
We present the largest exome sequencing study to date focused on rare variation in autism spectrum disorder (ASD) (n=35,584). Integrating de novo and case-control variation with an enhanced Bayesian framework incorporating evolutionary constraint against mutation, we implicate 99 genes in ASD risk at a false discovery rate (FDR) [&le;] 0.1. Of these 99 risk genes, 46 show higher frequencies of disruptive de novo variants in individuals ascertained for severe neurodevelopmental delay, while 50 show higher frequencies in individuals ascertained for ASD, and comparing ASD cases with disruptive mutations in the two groups shows differences in phenotypic presentation. Expressed early in brain development, most of the risk genes have roles in neuronal communication or regulation of gene expression, and 12 fall within recurrent copy number variant loci. In human cortex single-cell gene expression data, expression of the 99 risk genes is also enriched in both excitatory and inhibitory neuronal lineages, implying that disruption of these genes alters the development of both neuron types. Together, these insights broaden our understanding of the neurobiology of ASD.
]]></description>
<dc:creator>Satterstrom, F. K.</dc:creator>
<dc:creator>Kosmicki, J. A.</dc:creator>
<dc:creator>Wang, J.</dc:creator>
<dc:creator>Breen, M.</dc:creator>
<dc:creator>De Rubeis, S.</dc:creator>
<dc:creator>An, J.-Y.</dc:creator>
<dc:creator>Peng, M.</dc:creator>
<dc:creator>Collins, R. L.</dc:creator>
<dc:creator>Grove, J.</dc:creator>
<dc:creator>Klei, L.</dc:creator>
<dc:creator>Stevens, C.</dc:creator>
<dc:creator>Reichert, J.</dc:creator>
<dc:creator>Mulhern, M.</dc:creator>
<dc:creator>Artomov, M.</dc:creator>
<dc:creator>Gerges, S.</dc:creator>
<dc:creator>Sheppard, B.</dc:creator>
<dc:creator>Xu, X.</dc:creator>
<dc:creator>Bhaduri, A.</dc:creator>
<dc:creator>Norman, U.</dc:creator>
<dc:creator>Brand, H.</dc:creator>
<dc:creator>Schwartz, G.</dc:creator>
<dc:creator>Nguyen, R.</dc:creator>
<dc:creator>Guerrero, E.</dc:creator>
<dc:creator>Dias, C.</dc:creator>
<dc:creator>Aleksic, B.</dc:creator>
<dc:creator>Anney, R. J.</dc:creator>
<dc:creator>Barbosa, M.</dc:creator>
<dc:creator>Bishop, S.</dc:creator>
<dc:creator>Brusco, A.</dc:creator>
<dc:creator>Bybjerg-Grauholm, J.</dc:creator>
<dc:creator>Carracedo, A.</dc:creator>
<dc:creator>Chan, M. C. Y.</dc:creator>
<dc:creator>Chiocchetti, A.</dc:creator>
<dc:creator>Chung, B.</dc:creator>
<dc:creator>Coon, H.</dc:creator>
<dc:creator>Cuccaro, M.</dc:creator>
<dc:creator>Curro, A.</dc:creator>
<dc:creator>Dalla Bernardina, B.</dc:creator>
<dc:creator>Doan, R.</dc:creator>
<dc:creator>Domenici, E.</dc:creator>
<dc:creator>Dong, S.</dc:creator>
<dc:creator>Fallerini, C.</dc:creator>
<dc:creator>Fernandez-Prieto, M.</dc:creator>
<dc:creator>Ferrero, G. B.</dc:creator>
<dc:creator>Freitag,</dc:creator>
<dc:date>2018-11-30</dc:date>
<dc:identifier>doi:10.1101/484113</dc:identifier>
<dc:title><![CDATA[Novel genes for autism implicate both excitatory and inhibitory cell lineages in risk]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-11-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/409284v1?rss=1">
<title>
<![CDATA[
Deletion of autism risk gene Shank3 disrupts prefrontal connectivity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/409284v1?rss=1"
</link>
<description><![CDATA[
Mutations in the synaptic scaffolding protein Shank3 are a major cause of autism, and are associated with prominent intellectual and language deficits. However, the neural mechanisms whereby SHANK3 deficiency affects higher order socio-communicative functions remain unclear. Using high-resolution functional and structural MRI in mice, here we show that loss of Shank3 (Shank3B-/-) results in disrupted local and long-range prefrontal functional connectivity, as well as fronto-striatal decoupling. We document that prefrontal hypo-connectivity is associated with reduced short-range cortical projections density, and reduced gray matter volume. Finally, we show that prefrontal disconnectivity is predictive of social communication deficits, as assessed with ultrasound vocalization recordings. Collectively, our results reveal a critical role of SHANK3 in the development of prefrontal anatomy and function, and suggest that SHANK3 deficiency may predispose to intellectual disability and socio-communicative impairments via dysregulation of higher-order cortical connectivity.
]]></description>
<dc:creator>Pagani, M.</dc:creator>
<dc:creator>Bertero, A.</dc:creator>
<dc:creator>Liska, A.</dc:creator>
<dc:creator>Galbusera, A.</dc:creator>
<dc:creator>Sabbioni, M.</dc:creator>
<dc:creator>Scattoni, M. L.</dc:creator>
<dc:creator>Pasqualetti, M.</dc:creator>
<dc:creator>Gozzi, A.</dc:creator>
<dc:date>2018-09-06</dc:date>
<dc:identifier>doi:10.1101/409284</dc:identifier>
<dc:title><![CDATA[Deletion of autism risk gene Shank3 disrupts prefrontal connectivity]]></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/469031v1?rss=1">
<title>
<![CDATA[
Non-monotonic regulation of gene expression, neural progenitor fate and brain growth by the chromatin remodeller CHD8 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/469031v1?rss=1"
</link>
<description><![CDATA[
Heterozygous CHD8 mutations are associated with autism and macrocephaly with high penetrance in the human population. The reported mutations may have loss-of-function (haploinsufficient), hypomorphic or dominant negative effects on protein function. To determine the effects of reducing CHD8 protein function below haploinsufficient levels on brain development, we established a Chd8 allelic series in the mouse. Chd8 heterozygous mice exhibited relatively subtle brain overgrowth and little gene expression changes in the embryonic neocortex. In comparison, mild Chd8 hypomorphs displayed significant postnatal lethality, with surviving animals exhibiting more pronounced brain hyperplasia, and significantly altered expression of over 2000 genes. Autism-associated genes were downregulated and neural progenitor proliferation genes upregulated. Severe Chd8 hypomorphs displayed even greater transcriptional dysregulation, affecting genes and pathways that largely overlapped with those dysregulated in the mild hypomorphs. By contrast, homozygous, conditional deletion of Chd8 in early neuronal progenitors resulted in the induction of p53 target genes, cell cycle exit, apoptosis and pronounced brain hypoplasia. Intriguingly, increased progenitor proliferation in hypomorphs was primarily restricted to TBR2+ intermediate progenitors, suggesting critical roles for CHD8 in regulating the expansion of this population. Given the importance of these progenitors in human cortical growth, this observation suggests that human brain development might be more sensitive to CHD8 deficiency than the mouse. We conclude that brain development is acutely sensitive to CHD8 dosage and that the varying sensitivities of different progenitor populations and cellular processes to CHD8 dosage can result in non-linear effects on gene transcription and brain growth.
]]></description>
<dc:creator>Hurley, S.</dc:creator>
<dc:creator>Mohan, C.</dc:creator>
<dc:creator>Suetterlin, P.</dc:creator>
<dc:creator>Ellegood, J.</dc:creator>
<dc:creator>Rudari, F.</dc:creator>
<dc:creator>Lerch, J. P.</dc:creator>
<dc:creator>Fernandes, C.</dc:creator>
<dc:creator>Basson, M. A.</dc:creator>
<dc:date>2018-11-12</dc:date>
<dc:identifier>doi:10.1101/469031</dc:identifier>
<dc:title><![CDATA[Non-monotonic regulation of gene expression, neural progenitor fate and brain growth by the chromatin remodeller CHD8]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-11-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/460931v1?rss=1">
<title>
<![CDATA[
A machine-learning approach for accurate detection of copy-number variants from exome sequencing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/460931v1?rss=1"
</link>
<description><![CDATA[
Copy-number variants (CNVs) are a major cause of several genetic disorders, making their detection an essential component of genetic analysis pipelines. Current methods for detecting CNVs from exome sequencing data are limited by high false positive rates and low concordance due to the inherent biases of individual algorithms. To overcome these issues, calls generated by two or more algorithms are often intersected using Venn-diagram approaches to identify "high-confidence" CNVs. However, this approach is inadequate, as it misses potentially true calls that do not have consensus from multiple callers. Here, we present CN-Learn, a machine-learning framework (https://github.com/girirajanlab/CN_Learn) that integrates calls from multiple CNV detection algorithms and learns to accurately identify true CNVs using caller-specific and genomic features from a small subset of validated CNVs. Using CNVs predicted by four exome-based CNV callers (CANOES, CODEX, XHMM and CLAMMS) from 503 samples, we demonstrate that CN-Learn identifies true CNVs at higher precision (~90%) and recall (~85%) rates while maintaining robust performance even when trained with minimal data (~30 samples). CN-Learn recovers twice as many CNVs compared to individual callers or Venn diagram-based approaches, with features such as exome capture probe count, caller concordance and GC content providing the most discriminatory power. In fact, about 58% of all true CNVs recovered by CN-Learn were either singletons or calls that lacked support from at least one caller. Our study underscores the limitations of current approaches for CNV identification and provides an effective method that yields high-quality CNVs for application in clinical diagnostics.
]]></description>
<dc:creator>Kumar, V.</dc:creator>
<dc:creator>Jensen, M.</dc:creator>
<dc:creator>Jayakar, G.</dc:creator>
<dc:creator>Kelkar, N.</dc:creator>
<dc:creator>Girirajan, S.</dc:creator>
<dc:date>2018-11-02</dc:date>
<dc:identifier>doi:10.1101/460931</dc:identifier>
<dc:title><![CDATA[A machine-learning approach for accurate detection of copy-number variants from exome sequencing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-11-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/459958v1?rss=1">
<title>
<![CDATA[
An interaction-based model for neuropsychiatric features of copy-number variants 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/459958v1?rss=1"
</link>
<description><![CDATA[
Variably expressive copy-number variants (CNVs) are characterized by extensive phenotypic heterogeneity of neuropsychiatric phenotypes. Approaches to identify single causative genes for these phenotypes within each CNV have not been successful. Here, we posit using multiple lines of evidence, including pathogenicity metrics, functional assays of model organisms, and gene expression data, that multiple genes within each CNV region are likely responsible for the observed phenotypes. We propose that candidate genes within each region likely interact with each other through shared pathways to modulate the individual gene phenotypes, emphasizing the genetic complexity of CNV-associated neuropsychiatric features.
]]></description>
<dc:creator>Jensen, M.</dc:creator>
<dc:creator>Girirajan, S.</dc:creator>
<dc:date>2018-11-02</dc:date>
<dc:identifier>doi:10.1101/459958</dc:identifier>
<dc:title><![CDATA[An interaction-based model for neuropsychiatric features of copy-number variants]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-11-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/449819v1?rss=1">
<title>
<![CDATA[
Calculating the Effects of Autism Risk Gene Variants on Dysfunction of Biological Processes Identifies Clinically-Useful Information 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/449819v1?rss=1"
</link>
<description><![CDATA[
Autism spectrum disorders (ASD) are neurodevelopmental conditions that are influenced by genetic factors and encompass a wide-range and severity of symptoms. The details of how genetic variation contributes to variable symptomatology are unclear, creating a major challenge for translating vast amounts of data into clinically-useful information. To determine if variation in ASD risk genes correlates with symptomatology differences among individuals with ASD, thus informing treatment, we developed an approach to calculate the likelihood of genetic dysfunction in Gene Ontology-defined biological processes that have significant overrepresentation of known risk genes. Using whole-exome sequence data from 2,381 individuals with ASD included in the Simons Simplex Collection, we identified likely damaging variants and conducted a clustering analysis to define subgroups based on scores reflecting genetic dysfunction in each process of interest to ASD etiology. Dysfunction in cognition-related genes distinguished a distinct subset of individuals with increased social deficits, lower IQs, and reduced adaptive behaviors when compared to individuals with no evidence of cognition-related gene dysfunction. In particular, a stop-gain variant in the pharmacogene encoding cycloxygenase-2 was associated with having an IQ<70 (i.e. intellectual disability), a key comorbidity in ASD. We expect that screening genes involved in cognition for deleterious variants in ASD cases may be useful for identifying clinically-informative factors that should be prioritized for functional follow-up. This has implications in designing more comprehensive genetic testing panels and may help provide the basis for more informed treatment in ASD.
]]></description>
<dc:creator>Veatch, O. J.</dc:creator>
<dc:creator>Mazzotti, D. R.</dc:creator>
<dc:creator>Sutcliffe, J. S.</dc:creator>
<dc:creator>Schultz, R. T.</dc:creator>
<dc:creator>Abel, T.</dc:creator>
<dc:creator>Tunc, B.</dc:creator>
<dc:creator>Assouline, S. G.</dc:creator>
<dc:creator>Brodkin, E. S.</dc:creator>
<dc:creator>Michaelson, J. J.</dc:creator>
<dc:creator>Nickl-Jockschat, T.</dc:creator>
<dc:creator>Warren, Z. E.</dc:creator>
<dc:creator>Malow, B. A.</dc:creator>
<dc:creator>Pack, A. I.</dc:creator>
<dc:date>2018-10-22</dc:date>
<dc:identifier>doi:10.1101/449819</dc:identifier>
<dc:title><![CDATA[Calculating the Effects of Autism Risk Gene Variants on Dysfunction of Biological Processes Identifies Clinically-Useful Information]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/370601v1?rss=1">
<title>
<![CDATA[
Forecasting autism gene discovery with machine learning and genome-scale data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/370601v1?rss=1"
</link>
<description><![CDATA[
BackgroundGenes are one of the most powerful windows into the biology of autism, and it has been estimated that perhaps a thousand or more genes may confer risk. However, less than 100 genes are currently viewed as having robust enough evidence to be considered true "autism genes". Massive genetic studies are underway to produce data to implicate additional genes, but this approach, although necessary, is costly and slow-moving.nnMethodsWe approach autism gene discovery as a machine learning problem, rather than a genetic association problem, and use genome-scale data as predictors for identifying further genes that have similar properties in the feature space compared to established autism risk genes. This approach, which we call forecASD, integrates spatiotemporal gene expression, heterogeneous network data, and previous gene-level predictors of autism association into an ensemble classifier that yields a single score that indexes each genes evidence for being involved in the etiology of autism.nnResultsWe demonstrate that forecASD has substantially increased sensitivity and specificity compared to previous gene-level predictors of autism association, including genetic measures such as TADA. On an independent test set, consisting of newly-released pilot data from the SPARK Genomics Consortium, we show that forecASD best predicts which genes will have an excess of likely gene disrupting (LGD) de novo mutations. We further use independent data from a recent post mortem study of case/control gene expression to show that forecASD is also a significant predictor of genes implicated in ASD through differential expression. Using forecASD results, we show which molecular pathways are currently under-represented in the autism literature and likely represent under-appreciated biological mechanisms of autism. Finally, forecASD correctly predicted 12 of 16 genes implicated at FDR=0.2 by the latest ASD gene discovery study, while also identifying the most likely false positives among the candidate genes.nnConclusionsThese results demonstrate that forecASD bridges the gap between genetic- and expression-based ASD gene discovery, and provides a data-driven replacement to much of the manual filtering and curation that is a critical step in ensuring the robustness of gene discovery studies.
]]></description>
<dc:creator>Brueggeman, L.</dc:creator>
<dc:creator>Koomar, T.</dc:creator>
<dc:creator>Michaelson, J.</dc:creator>
<dc:date>2018-07-16</dc:date>
<dc:identifier>doi:10.1101/370601</dc:identifier>
<dc:title><![CDATA[Forecasting autism gene discovery with machine learning and genome-scale data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/430421v1?rss=1">
<title>
<![CDATA[
Reduced frontal gamma power at 24 months is associated with better expressive language in toddlers at risk for autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/430421v1?rss=1"
</link>
<description><![CDATA[
Gamma oscillations have been associated with early language development in typically developing toddlers, and gamma band abnormalities have been observed in individuals with ASD, as well high-risk infant siblings (those having an older sibling with autism), as early as 6-months of age. The current study investigated differences in baseline frontal gamma power and its association with language development in toddlers at high versus low familial risk for autism. EEG recordings as well as cognitive and behavioral assessments were acquired at 24-months as part of prospective, longitudinal study of infant siblings of children with and without autism. Diagnosis of autism was determined at 24-36 months, and data was analyzed across three outcome groups - low risk without ASD (n=43), high-risk without ASD (n=42), and high-risk with ASD (n=16). High-risk toddlers without ASD had reduced baseline frontal gamma power (30-50Hz) compared to low-risk toddlers. Among high-risk toddlers increased frontal gamma was only marginally associated with ASD diagnosis (p=0.06), but significantly associated with reduced expressive language ability (p=0.007). No association between gamma power and language was present in the low-risk group. These findings suggest that differences in gamma oscillations in high-risk toddlers may represent compensatory mechanisms associated with improved developmental outcomes.
]]></description>
<dc:creator>Wilkinson, C. L.</dc:creator>
<dc:creator>Levin, A. R.</dc:creator>
<dc:creator>Gabard-Durnam, L. J.</dc:creator>
<dc:creator>Tager-Flusberg, H.</dc:creator>
<dc:creator>Nelson, C. A.</dc:creator>
<dc:date>2018-09-29</dc:date>
<dc:identifier>doi:10.1101/430421</dc:identifier>
<dc:title><![CDATA[Reduced frontal gamma power at 24 months is associated with better expressive language in toddlers at risk for autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/500934v1?rss=1">
<title>
<![CDATA[
Establishing Cerebral Organoids as Models of Human-Specific Brain Evolution 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/500934v1?rss=1"
</link>
<description><![CDATA[
Direct comparisons of human and non-human primate brain tissue have the potential to reveal molecular pathways underlying remarkable specializations of the human brain. However, chimpanzee tissue is largely inaccessible during neocortical neurogenesis when differences in brain size first appear. To identify human-specific features of cortical development, we leveraged recent innovations that permit generating pluripotent stem cell-derived cerebral organoids from chimpanzee. First, we systematically evaluated the fidelity of organoid models to primary human and macaque cortex, finding organoid models preserve gene regulatory networks related to cell types and developmental processes but exhibit increased metabolic stress. Second, we identified 261 genes differentially expressed in human compared to chimpanzee organoids and macaque cortex. Many of these genes overlap with human-specific segmental duplications and a subset suggest increased PI3K/AKT/mTOR activation in human outer radial glia. Together, our findings establish a platform for systematic analysis of molecular changes contributing to human brain development and evolution.
]]></description>
<dc:creator>Pollen, A. A.</dc:creator>
<dc:creator>Bhaduri, A.</dc:creator>
<dc:creator>Andrews, M. G.</dc:creator>
<dc:creator>Nowakowski, T. J.</dc:creator>
<dc:creator>Meyerson, O. S.</dc:creator>
<dc:creator>Mostajo-Radji, M. A.</dc:creator>
<dc:creator>Di Lullo, E.</dc:creator>
<dc:creator>Alvarado, B.</dc:creator>
<dc:creator>Bedolli, M.</dc:creator>
<dc:creator>Dougherty, M. L.</dc:creator>
<dc:creator>Fiddes, I. T.</dc:creator>
<dc:creator>Kronenberg, Z. N.</dc:creator>
<dc:creator>Shuga, J.</dc:creator>
<dc:creator>Leyrat, A. A.</dc:creator>
<dc:creator>West, J. A.</dc:creator>
<dc:creator>Bershteyn, M.</dc:creator>
<dc:creator>Lowe, C. B.</dc:creator>
<dc:creator>Pavolvic, B. J.</dc:creator>
<dc:creator>Salama, S. R.</dc:creator>
<dc:creator>Haussler, D.</dc:creator>
<dc:creator>Eichler, E.</dc:creator>
<dc:creator>Kriegstein, A. A.</dc:creator>
<dc:date>2018-12-19</dc:date>
<dc:identifier>doi:10.1101/500934</dc:identifier>
<dc:title><![CDATA[Establishing Cerebral Organoids as Models of Human-Specific Brain Evolution]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-12-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/516625v1?rss=1">
<title>
<![CDATA[
Exome sequencing of 457 autism families recruited online provides evidence for novel ASD genes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/516625v1?rss=1"
</link>
<description><![CDATA[
Autism spectrum disorder (ASD) is a genetically heterogeneous condition, caused by a combination of rare de novo and inherited variants as well as common variants in at least several hundred genes. However, significantly larger sample sizes are needed to identify the complete set of genetic risk factors. We conducted a pilot study for SPARK (SPARKForAutism.org) of 457 families with ASD, all consented online. Whole exome sequencing (WES) and genotyping data were generated for each family using DNA from saliva. We identified variants in genes and loci that are clinically recognized causes or significant contributors to ASD in 10.4% of families without previous genetic findings. Additionally, we identified variants that are possibly associated with autism in an additional 3.4% of families. A meta-analysis using the TADA framework at a false discovery rate (FDR) of 0.2 provides statistical support for 34 ASD risk genes with at least one damaging variant identified in SPARK. Nine of these genes (BRSK2, DPP6, EGR3, FEZF2, ITSN1, KDM1B, NR4A2, PAX5 and RALGAPB) are newly emerging genes in autism, of which BRSK2 has the strongest statistical support as a risk gene for autism (TADA q-value = 0.0015). Future studies leveraging the thousands of individuals with ASD that have enrolled in SPARK are likely to further clarify the genetic risk factors associated with ASD as well as allow accelerate autism research that incorporates genetic etiology.
]]></description>
<dc:creator>Feliciano, P.</dc:creator>
<dc:creator>Zhou, X.</dc:creator>
<dc:creator>Astrovskaya, I.</dc:creator>
<dc:creator>Turner, T.</dc:creator>
<dc:creator>Wang, T.</dc:creator>
<dc:creator>Brueggeman, L.</dc:creator>
<dc:creator>Barnard, R.</dc:creator>
<dc:creator>Hsieh, A.</dc:creator>
<dc:creator>Snyder, L. G.</dc:creator>
<dc:creator>Muzny, D.</dc:creator>
<dc:creator>Sabo, A.</dc:creator>
<dc:creator>The SPARK Consortium,</dc:creator>
<dc:creator>Gibbs, R.</dc:creator>
<dc:creator>Eichler, E.</dc:creator>
<dc:creator>O'Roak, B.</dc:creator>
<dc:creator>Michaelson, J.</dc:creator>
<dc:creator>Volfovsky, N.</dc:creator>
<dc:creator>Shen, Y.</dc:creator>
<dc:creator>Chung, W.</dc:creator>
<dc:date>2019-01-09</dc:date>
<dc:identifier>doi:10.1101/516625</dc:identifier>
<dc:title><![CDATA[Exome sequencing of 457 autism families recruited online provides evidence for novel ASD genes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/363853v1?rss=1">
<title>
<![CDATA[
Both rare and common genetic variants contribute to autism in the Faroe Islands 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/363853v1?rss=1"
</link>
<description><![CDATA[
The number of genes associated with autism is increasing, but few studies have been performed on epidemiological cohorts and in isolated populations. Here, we investigated 357 individuals from the Faroe Islands including 36 individuals with autism, 136 of their relatives and 185 non-autism controls. Data from SNP array and whole exome sequencing revealed that individuals with autism compared to controls had a higher burden of copy-number variants (p < 0.05), higher inbreeding status (p < 0.005) and higher load of homozygous deleterious variants (p < 0.01). Our analysis supports the role of several genes/loci associated with autism (e.g. NRXN1, ADNP, 22q11 deletion) and identified new truncating (e.g. GRIK2, ROBO1, NINL and IMMP2L) or recessive deleterious variants (e.g. KIRELL3 and CNTNAP2) affecting autism-risk genes. It also revealed three genes involved in synaptic plasticity, RIMS4, KALRN and PLA2G4A, carrying de novo deleterious variants in individuals with autism without intellectual disability. In summary, our analysis provides a better understanding of the genetic architecture of autism in isolated populations by highlighting the role of both common and rare gene variants and pointing at new autism-risk genes. It also indicates that more knowledge about how multiple genetic hits affect neuronal function will be necessary to fully understand the genetic architecture of autism.
]]></description>
<dc:creator>Leblond, C.</dc:creator>
<dc:creator>Cliquet, F.</dc:creator>
<dc:creator>Carton, C.</dc:creator>
<dc:creator>Huguet, G.</dc:creator>
<dc:creator>Mathieu, A.</dc:creator>
<dc:creator>Kergrohen, T.</dc:creator>
<dc:creator>Buratti, J.</dc:creator>
<dc:creator>Lemiere, N.</dc:creator>
<dc:creator>Cuisset, L.</dc:creator>
<dc:creator>Bienvenu, T.</dc:creator>
<dc:creator>Boland, A.</dc:creator>
<dc:creator>Deleuze, J.-F.</dc:creator>
<dc:creator>Stora, T.</dc:creator>
<dc:creator>Biskupstoe, R.</dc:creator>
<dc:creator>Halling, J.</dc:creator>
<dc:creator>Andorsdottir, G.</dc:creator>
<dc:creator>Billstedt, E.</dc:creator>
<dc:creator>Gillberg, C.</dc:creator>
<dc:creator>Bourgeron, T.</dc:creator>
<dc:date>2018-07-06</dc:date>
<dc:identifier>doi:10.1101/363853</dc:identifier>
<dc:title><![CDATA[Both rare and common genetic variants contribute to autism in the Faroe Islands]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/536680v1?rss=1">
<title>
<![CDATA[
mTOR suppresses macroautophagy during postnatal development of the striatum. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/536680v1?rss=1"
</link>
<description><![CDATA[
Macroautophagy (hereafter referred to as autophagy) plays a critical role in neuronal function related to development and degeneration. Here, we investigated whether autophagy is developmentally regulated in the striatum, a brain region implicated in neurodevelopmental disease. We demonstrate that autophagic flux is suppressed during striatal postnatal development, reaching adult levels around postnatal day 28 (P28). We also find that mTOR signaling, a key regulator of autophagy, increases during the same developmental period. We further show that mTOR signaling is responsible for suppressing autophagy, via regulation of Beclin-1 and VPS34 activity. These results demonstrate that neurons coopt metabolic signaling cascades to developmentally regulate autophagy and establish mTOR as a central node in the regulation of neuronal autophagy.
]]></description>
<dc:creator>Lieberman, O.</dc:creator>
<dc:creator>Pigulevskiy, I.</dc:creator>
<dc:creator>Post, M.</dc:creator>
<dc:creator>Sulzer, D.</dc:creator>
<dc:creator>Santini, E.</dc:creator>
<dc:date>2019-01-31</dc:date>
<dc:identifier>doi:10.1101/536680</dc:identifier>
<dc:title><![CDATA[mTOR suppresses macroautophagy during postnatal development of the striatum.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/429852v1?rss=1">
<title>
<![CDATA[
Enhanced population coding for rewarded choices in the medial frontal cortex of the mouse 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/429852v1?rss=1"
</link>
<description><![CDATA[
Instrumental behavior is characterized by the selection of actions based on the degree to which they lead to a desired outcome. However, we lack a detailed understanding of how rewarded actions are reinforced and preferentially implemented. In rodents, the medial frontal cortex is hypothesized to play an important role in this process, based in part on its capacity to encode chosen actions and their outcomes. We therefore asked how neural representations of choice and outcome might interact to facilitate instrumental behavior. To investigate this question, we imaged neural ensemble activity in layer 2/3 of the secondary motor region (M2) while mice engaged in a two-choice auditory discrimination task with probabilistic outcomes. Correct choices could result in one of three reward amounts (single-, double-, or omitted-reward), which allowed us to measure neural and behavioral effects of reward magnitude, as well as its categorical presence or absence. Single-unit and population decoding analyses revealed a consistent influence of outcome on choice signals in M2. Specifically, rewarded choices were more robustly encoded relative to unrewarded choices, with little dependence on the exact magnitude of reinforcement. Our results provide insight into the integration of past choices and outcomes in the rodent brain during instrumental behavior.
]]></description>
<dc:creator>Siniscalchi, M. J.</dc:creator>
<dc:creator>Wang, H.</dc:creator>
<dc:creator>Kwan, A. C.</dc:creator>
<dc:date>2018-09-28</dc:date>
<dc:identifier>doi:10.1101/429852</dc:identifier>
<dc:title><![CDATA[Enhanced population coding for rewarded choices in the medial frontal cortex of the mouse]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/540732v1?rss=1">
<title>
<![CDATA[
Oligogenic effects of 16p11.2 copy number variation on craniofacial development 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/540732v1?rss=1"
</link>
<description><![CDATA[
A copy number variant (CNV) of 16p11.2, which encompasses 30 genes, is associated with developmental and psychiatric disorders, head size and body mass. The genetic mechanisms that underlie these associations are not understood. To elucidate the effects of genes on development, we exploited the quantitative effects of CNV on craniofacial structure in humans and model organisms. We show that reciprocal deletion and duplication of 16p11.2 have characteristic "mirror" effects on craniofacial features that are conserved in human, rat and mouse. By testing gene dosage effects on the shape of the mandible in zebrafish, we show that the distribution of effects for all individual genes is consistent with that of the CNV, and some combinations have non-additive effects. Our results suggest that, at minimum, one third of genes within the 16p11.2 region influence craniofacial development, and the facial gestalt of each CNV represents a product of 30 dosage effects.

HighlightsO_LIReciprocal CNVs of 16p11.2 have mirror effects on craniofacial structure. Copy number is associated with a positive effect on nasal and mandibular regions and a negative effect on frontal regions of the face.
C_LIO_LIEffects of CNV on craniofacial development in human are well conserved in rat and mouse models of 16p11.2 deletion and duplication.
C_LIO_LI7/30 genes each independently have significant effects on the shape of the mandible in zebrafish; these include SPN, C16orf54, SEZ6L2, ASPHD1, TAOK2, INO80E and FAM57B. Others (MAPK3, MVP, KCTD13) have detectable effects only in combination.
C_LIO_LIOverexpression of 30 genes individually showed a distribution of effects that was skewed in the same direction as that of the full duplication, suggesting that specific facial features represent the net of all individual effects combined.
C_LI
]]></description>
<dc:creator>Qiu, Y.</dc:creator>
<dc:creator>Arbogast, T.</dc:creator>
<dc:creator>Martin Lorenzo, S.</dc:creator>
<dc:creator>Li, H.</dc:creator>
<dc:creator>Shih, T.</dc:creator>
<dc:creator>Ellen, R.</dc:creator>
<dc:creator>Hong, O.</dc:creator>
<dc:creator>Cho, S.</dc:creator>
<dc:creator>Shanta, O.</dc:creator>
<dc:creator>Timothy, P.</dc:creator>
<dc:creator>Corsello, C.</dc:creator>
<dc:creator>Deutsch, C. K.</dc:creator>
<dc:creator>Chevalier, C.</dc:creator>
<dc:creator>Davis, E. E.</dc:creator>
<dc:creator>Iakoucheva, L. M.</dc:creator>
<dc:creator>Herault, Y.</dc:creator>
<dc:creator>Katasanis, N.</dc:creator>
<dc:creator>Messer, K.</dc:creator>
<dc:creator>Sebat, J.</dc:creator>
<dc:date>2019-02-05</dc:date>
<dc:identifier>doi:10.1101/540732</dc:identifier>
<dc:title><![CDATA[Oligogenic effects of 16p11.2 copy number variation on craniofacial development]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/580365v1?rss=1">
<title>
<![CDATA[
Shared polygenetic variation between ASD and ADHD exerts opposite association patterns with educational attainment 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/580365v1?rss=1"
</link>
<description><![CDATA[
Insight into shared polygenetic architectures affects our understanding of neurodevelopmental disorders. Here, we investigate evidence for pleiotropic mechanisms that may explain the comorbidity between Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD). These complex neurodevelopmental conditions often co-occur, but differ in their polygenetic association patterns, especially with educational attainment (EA), showing discordant association effects. Using multivariable regression analyses and existing genome-wide summary statistics based on 10,610 to 766,345 individuals, we demonstrate that EA-related polygenic variation is shared between ASD and ADHD. We show that different combinations of the same ASD and ADHD risk-increasing alleles can simultaneously re-capture known ASD-related positive and ADHD-related negative associations with EA. Such patterns, although to a lesser degree, were also present for combinations of other psychiatric disorders. These findings suggest pleiotropic mechanisms, where the same polygenic sites can encode multiple independent, even discordant, association patterns without involving distinct loci, and have implications for cross-disorder investigations.
]]></description>
<dc:creator>Verhoef, E.</dc:creator>
<dc:creator>Grove, J.</dc:creator>
<dc:creator>Shapland, C. Y.</dc:creator>
<dc:creator>Demontis, D.</dc:creator>
<dc:creator>Burgess, S.</dc:creator>
<dc:creator>Rai, D.</dc:creator>
<dc:creator>Borglum, A. D.</dc:creator>
<dc:creator>St Pourcain, B.</dc:creator>
<dc:date>2019-03-17</dc:date>
<dc:identifier>doi:10.1101/580365</dc:identifier>
<dc:title><![CDATA[Shared polygenetic variation between ASD and ADHD exerts opposite association patterns with educational attainment]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/601500v1?rss=1">
<title>
<![CDATA[
Robust and replicable measurement for prepulse inhibition of the acoustic startle response 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/601500v1?rss=1"
</link>
<description><![CDATA[
Measuring animal behavior in the context of experimental manipulation is critical for modeling and understanding neuro-psychiatric disease. Prepulse inhibition of the acoustic startle response (PPI) is a behavioral paradigm used extensively for this purpose, but the results of PPI studies are often inconsistent. As a result, the utility of this metric remains uncertain. Here we deconstruct the phenomenon of PPI. We first confirm several limitations of the traditional PPI metric, including that the underlying startle response has a non-Gaussian distribution and that the traditional PPI metric changes with different stimulus condition. We then develop a novel model that reveals PPI to be a combination of the previously appreciated scaling of the startle response, as well as a scaling of sound perception. Using our model, we find no evidence for differences in PPI in a rat model of Fragile-X Syndrome (FXS) compared to wild-type controls. These results in the rat provide a reliable methodology that could be used to clarify inconsistent PPI results in mice and humans. In addition, we find robust differences between wild-type male and female rats. Our model allows us to understand the nature of these differences, and we find that both the startle-scaling and sound-scaling components of PPI are a function of the baseline startle response. Males and females differ specifically in the startle-scaling, but not the sound-scaling, component of PPI. These findings establish a robust experimental and analytical approach that has the potential to provide a consistent biomarker of brain function.
]]></description>
<dc:creator>Miller, E. A.</dc:creator>
<dc:creator>Kastner, D. B.</dc:creator>
<dc:creator>Grzybowski, M. N.</dc:creator>
<dc:creator>Dwinell, M. R.</dc:creator>
<dc:creator>Geurts, A. M.</dc:creator>
<dc:creator>Frank, L. M.</dc:creator>
<dc:date>2019-04-07</dc:date>
<dc:identifier>doi:10.1101/601500</dc:identifier>
<dc:title><![CDATA[Robust and replicable measurement for prepulse inhibition of the acoustic startle response]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/606566v1?rss=1">
<title>
<![CDATA[
Impaired KCC2 phosphorylation leads to neuronal network dysfunction and neurodevelopmental pathogenesis. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/606566v1?rss=1"
</link>
<description><![CDATA[
KCC2 is a vital neuronal K+/Cl- co-transporter that is implicated in the etiology of numerous neurological diseases. It is subject to developmental dephosphorylation at threonine 906 and 1007, the functional importance of which remains unclear. We engineered mice with heterozygous phospho-mimetic mutations T906E and T1007E (KCC2E/+) to prevent the normal developmental dephosphorylation of these sites. Immature (P15) but not juvenile (P30) KCC2E/+ mice exhibited altered GABAergic inhibition, an increased glutamate/GABA synaptic ratio, and higher seizure susceptibility. KCC2E/+ mice also had abnormal ultra-sonic vocalizations at P10-P12 and impaired social behavior at P60. Post-natal bumetanide treatment restored network activity at P15 but not social behavior at P60. Our data show that post-translational KCC2 regulation controls the GABAergic developmental sequence in vivo. The post-translational deregulation of KCC2 could be a risk factor for the emergence of neurological pathology and the presence of depolarizing GABA is not essential for manifestation of behavioral changes.
]]></description>
<dc:creator>Pisella, L.</dc:creator>
<dc:creator>Gaiarsa, J.-L.</dc:creator>
<dc:creator>Diabira, D.</dc:creator>
<dc:creator>Zhang, J.</dc:creator>
<dc:creator>Khalilov, I.</dc:creator>
<dc:creator>Duan, J.</dc:creator>
<dc:creator>Kahle, K.</dc:creator>
<dc:creator>Medyna, I.</dc:creator>
<dc:date>2019-04-12</dc:date>
<dc:identifier>doi:10.1101/606566</dc:identifier>
<dc:title><![CDATA[Impaired KCC2 phosphorylation leads to neuronal network dysfunction and neurodevelopmental pathogenesis.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/611780v1?rss=1">
<title>
<![CDATA[
Single-cell analysis of Foxp1-driven mechanisms essential for striatal development 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/611780v1?rss=1"
</link>
<description><![CDATA[
The striatum is a critical forebrain structure for integrating cognitive, sensory, and motor information from diverse brain regions into meaningful behavioral output. However, the transcriptional mechanisms that underlie striatal development and organization at single-cell resolution remain unknown. Here, we show that Foxp1, a transcription factor strongly linked to autism and intellectual disability, regulates organizational features of striatal circuitry in a cell-type-dependent fashion. Using single-cell RNA-sequencing, we examine the cellular diversity of the early postnatal striatum and find that cell-type-specific deletion of Foxp1 in striatal projection neurons alters the cellular composition and neurochemical architecture of the striatum. Importantly, using this approach, we identify the non-cell autonomous effects produced by disrupting Foxp1 in one cell-type and the molecular compensation that occurs in other populations. Finally, we identify Foxp1-regulated target genes within distinct cell-types and connect these molecular changes to functional and behavioral deficits relevant to phenotypes described in patients with FOXP1 loss-of-function mutations. These data reveal cell-type-specific transcriptional mechanisms underlying distinct features of striatal circuitry and identify Foxp1 as a key regulator of striatal development.
]]></description>
<dc:creator>Anderson, A. G.</dc:creator>
<dc:creator>Kulkarni, A.</dc:creator>
<dc:creator>Harper, M.</dc:creator>
<dc:creator>Konopka, G.</dc:creator>
<dc:date>2019-04-18</dc:date>
<dc:identifier>doi:10.1101/611780</dc:identifier>
<dc:title><![CDATA[Single-cell analysis of Foxp1-driven mechanisms essential for striatal development]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/624973v1?rss=1">
<title>
<![CDATA[
Cortical Foxp2 supports behavioral flexibility and developmental dopamine D1 receptor expression 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/624973v1?rss=1"
</link>
<description><![CDATA[
Genetic studies have associated FOXP2 variation with speech and language disorders and other neurodevelopmental disorders involving pathology of the cortex. In this brain region, FoxP2 is expressed from development into adulthood, but little is known about its downstream molecular and behavioral functions. Here, we characterized cortex-specific Foxp2 conditional knockout mice and found a major deficit in reversal learning, a form of behavioral flexibility. In contrast, they showed normal activity levels, anxiety, and vocalizations, save for a slight decrease in neonatal call loudness. These behavioral phenotypes were accompanied by decreased cortical dopamine D1 receptor (D1R) expression at neonatal and adult stages, while general cortical development remained unaffected. Finally, using single-cell transcriptomics, we identified at least five excitatory and three inhibitory D1R-expressing cell types in neonatal frontal cortex, and we found changes in D1R cell type composition and gene expression upon cortical Foxp2 deletion. Strikingly, these alterations included non-cell-autonomous changes in upper-layer neurons and interneurons. Together these data support a role for Foxp2 in the development of dopamine-modulated cortical circuits and behaviors relevant to neurodevelopmental disorders.
]]></description>
<dc:creator>Co, M.</dc:creator>
<dc:creator>Hickey, S. L.</dc:creator>
<dc:creator>Kulkarni, A.</dc:creator>
<dc:creator>Harper, M.</dc:creator>
<dc:creator>Konopka, G.</dc:creator>
<dc:date>2019-05-02</dc:date>
<dc:identifier>doi:10.1101/624973</dc:identifier>
<dc:title><![CDATA[Cortical Foxp2 supports behavioral flexibility and developmental dopamine D1 receptor expression]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-05-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/621250v1?rss=1">
<title>
<![CDATA[
Psychotic symptoms in 16p11.2 copy number variant carriers 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/621250v1?rss=1"
</link>
<description><![CDATA[
16p11.2 copy number variation (CNV) is implicated in neurodevelopmental disorders, with the duplication and deletion associated with autism spectrum disorder (ASD) and the duplication associated with schizophrenia (SCZ). The 16p11.2 CNV may therefore provide insight into the relationship between ASD and SCZ, distinct disorders that co-occur at an elevated rate and are difficult to distinguish from each other and from common co-occurring diagnoses such as obsessive compulsive disorder (OCD), itself a potential risk factor for SCZ. As psychotic symptoms are core to SCZ but distinct from ASD, we sought to examine their predictors in a population (n = 546) of 16p11.2 CNV carriers and their noncarrier siblings recruited by the Simons Variation in Individuals Project. We hypothesized that psychotic symptoms would be most common in duplication carriers followed by deletion carriers and noncarriers, that an ASD diagnosis would predict psychotic symptoms among CNV carriers, and that OCD symptoms would predict psychotic symptoms among all participants. Using data collected across multiple measures, we identified 19 participants with psychotic symptoms. Logistic regression models adjusting for biological sex, age, and IQ found that 16p11.2 duplication and ASD diagnosis predicted psychotic symptom presence. Our findings suggest that the association between 16p11.2 duplication and psychotic symptoms is independent of ASD diagnosis and that ASD diagnosis and psychotic symptoms may be associated in 16p11.2 CNV carriers.nnLay SummaryEither deletion or duplication at chromosome 16p11.2 raises the risk of autism spectrum disorder, and duplication, but not deletion, has been reported in schizophrenia. In a sample of 16p11.2 deletion and duplication carriers, we found that having the duplication or having an autism diagnosis may increase the risk of psychosis, a key feature of schizophrenia.
]]></description>
<dc:creator>Jutla, A.</dc:creator>
<dc:creator>Turner, J. B.</dc:creator>
<dc:creator>Green Snyder, L.</dc:creator>
<dc:creator>Chung, W. K.</dc:creator>
<dc:creator>Veenstra-VanderWeele, J.</dc:creator>
<dc:date>2019-05-05</dc:date>
<dc:identifier>doi:10.1101/621250</dc:identifier>
<dc:title><![CDATA[Psychotic symptoms in 16p11.2 copy number variant carriers]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/655035v1?rss=1">
<title>
<![CDATA[
Maternal experience-dependent cortical plasticity in mice is circuit- and stimulus-specific and requires Mecp2 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/655035v1?rss=1"
</link>
<description><![CDATA[
The neurodevelopmental disorder Rett syndrome is caused by mutations in the gene Mecp2. Misexpression of the protein MECP2 is thought to contribute to neuropathology by causing dysregulation of plasticity. Female heterozygous Mecp2 mutants (Mecp2het) failed to acquire a learned maternal retrieval behavior when exposed to pups, an effect linked to disruption of parvalbumin-expressing inhibitory interneurons (PV+) in the auditory cortex. However, the consequences of dysregulated PV+ networks during early maternal experience for auditory cortical sensory activity are unknown. Here we show that maternal experience in wild-type adult female mice (Mecp2wt) triggers suppression of PV+ auditory responses. We also observe concomitant disinhibition of auditory responses in deep-layer pyramidal neurons that is selective for behaviorally-relevant pup vocalizations. These neurons also exhibit sharpened tuning for pup vocalizations following maternal experience. All of these neuronal changes are abolished in Mecp2het, yet a genetic manipulation of GABAergic networks that restores accurate retrieval behavior in Mecp2het also restores maternal experience-dependent plasticity of PV+. Our data are consistent with a growing body of evidence that cortical networks are particularly vulnerable to mutations of Mecp2 in PV+ neurons.
]]></description>
<dc:creator>Lau, B. Y. B.</dc:creator>
<dc:creator>Krishnan, K.</dc:creator>
<dc:creator>Huang, Z. J.</dc:creator>
<dc:creator>Shea, S. D.</dc:creator>
<dc:date>2019-05-30</dc:date>
<dc:identifier>doi:10.1101/655035</dc:identifier>
<dc:title><![CDATA[Maternal experience-dependent cortical plasticity in mice is circuit- and stimulus-specific and requires Mecp2]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-05-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/653527v1?rss=1">
<title>
<![CDATA[
Mutually exclusive autism mutations point to the circadian clock and PI3K signaling pathways 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/653527v1?rss=1"
</link>
<description><![CDATA[
Mutual exclusivity analysis of genomic mutations has proven useful for detecting driver alterations in cancer patient cohorts. Here we demonstrate, for the first time, that this pattern is also present among de novo mutations in autism spectrum disorder. We analyzed three large whole genome sequencing studies and identified mutual exclusivity patterns within the most confident set of autism-related genes, as well as in the circadian clock and PI3K/AKT signaling pathways.
]]></description>
<dc:creator>Manning, H.</dc:creator>
<dc:creator>O'Roak, B. J.</dc:creator>
<dc:creator>Babur, O.</dc:creator>
<dc:date>2019-05-30</dc:date>
<dc:identifier>doi:10.1101/653527</dc:identifier>
<dc:title><![CDATA[Mutually exclusive autism mutations point to the circadian clock and PI3K signaling pathways]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-05-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/657189v1?rss=1">
<title>
<![CDATA[
Diminished cortical excitation during perceptual impairments in a mouse model of autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/657189v1?rss=1"
</link>
<description><![CDATA[
Sensory impairments are a core feature of autism spectrum disorder (ASD). These impairments affect visual perception (Robertson and Baron-Cohen, 2017), and have been hypothesized to arise from imbalances in cortical excitatory and inhibitory activity (Rubenstein and Merzenich, 2003; Nelson and Valakh, 2015; Sohal and Rubenstein, 2019); however, there is little direct evidence testing this hypothesis in identified excitatory and inhibitory neurons during impairments of sensory perception. Several recent studies have examined cortical activity in transgenic mouse models of ASD (Goel et al., 2018; Antoine et al., 2019; Lazaro et al., 2019), but have provided conflicting evidence for excitatory versus inhibitory activity deficits. Here, we utilized a genetically relevant mouse model of ASD (CNTNAP2-/- knockout, KO; Arking et al., 2008; Penagarikano et al., 2011) and directly recorded putative excitatory and inhibitory population spiking in primary visual cortex (V1) while measuring visual perceptual behavior (Speed et al., 2019). We found quantitative impairments in the speed, accuracy, and contrast sensitivity of visual perception in KO mice. These impairments were simultaneously associated with elevated inhibitory and diminished excitatory neuron activity evoked by visual stimuli during behavior, along with aberrant 3 - 10 Hz oscillations in superficial cortical layers 2/3 (L2/3). These results establish that perceptual deficits relevant for ASD can arise from diminished sensory activity of excitatory neurons in feedforward layers of cortical circuits.
]]></description>
<dc:creator>Del Rosario, J.</dc:creator>
<dc:creator>Speed, A.</dc:creator>
<dc:creator>Arrowood, H.</dc:creator>
<dc:creator>Motz, C.</dc:creator>
<dc:creator>Pardue, M.</dc:creator>
<dc:creator>Haider, B.</dc:creator>
<dc:date>2019-06-03</dc:date>
<dc:identifier>doi:10.1101/657189</dc:identifier>
<dc:title><![CDATA[Diminished cortical excitation during perceptual impairments in a mouse model of autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/659292v1?rss=1">
<title>
<![CDATA[
Ketamine disinhibits dendrites and enhances calcium signals in prefrontal dendritic spines 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/659292v1?rss=1"
</link>
<description><![CDATA[
A subanesthetic dose of ketamine causes acute psychotomimetic symptoms and then more sustained antidepressant effects. A key targeted brain region is the prefrontal cortex, and the prevailing disinhibition hypothesis posits that N-methyl-d-aspartate receptor (NMDAR) antagonists such as ketamine may act preferentially on GABAergic neurons. However, cortical GABAergic neurons are heterogeneous. In particular, somatostatin-expressing (SST) interneurons selectively inhibit dendrites and regulate synaptic inputs, yet their response to systemic NMDAR antagonism is unknown. Here, we report that administration of ketamine acutely suppresses the activity of SST interneurons in the medial prefrontal cortex of the awake mouse. The deficient dendritic inhibition leads to greater synaptically evoked calcium transients in the apical dendritic spines of pyramidal neurons. By manipulating NMDAR signaling via GluN2B knockdown, we show that ketamines actions on the dendritic inhibitory mechanism has ramifications for frontal cortex-dependent behaviors and cortico-cortical connectivity. Collectively, these results demonstrate dendritic disinhibition and elevated calcium levels in dendritic spines as important local-circuit alterations driven by the administration of subanesthetic ketamine.
]]></description>
<dc:creator>Ali, F.</dc:creator>
<dc:creator>Gerhard, D. M.</dc:creator>
<dc:creator>Sweasy, K.</dc:creator>
<dc:creator>Pothula, S.</dc:creator>
<dc:creator>Pittenger, C.</dc:creator>
<dc:creator>Duman, R. S.</dc:creator>
<dc:creator>Kwan, A. C.</dc:creator>
<dc:date>2019-06-03</dc:date>
<dc:identifier>doi:10.1101/659292</dc:identifier>
<dc:title><![CDATA[Ketamine disinhibits dendrites and enhances calcium signals in prefrontal dendritic spines]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/671453v1?rss=1">
<title>
<![CDATA[
Predicting Functional Effects of Missense Variants in Voltage-Gated Sodium and Calcium Channels 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/671453v1?rss=1"
</link>
<description><![CDATA[
Malfunctions of voltage-gated sodium and calcium channels (SCN and CACNA1 genes) have been associated with severe neurologic, psychiatric, cardiac and other diseases. Altered channel activity is frequently grouped into gain or loss of ion channel function (GOF or LOF, respectively) which is not only corresponding to clinical disease manifestations, but also to differences in drug response. Experimental studies of channel function are therefore important, but laborious and usually focus only on a few variants at a time. Based on known gene-disease-mechanisms, we here infer LOF (518 variants) and GOF (309 variants) of likely pathogenic variants from disease phenotypes of variant carriers. We show regional clustering of inferred GOF and LOF variants, respectively, across the alignment of the entire gene family, suggesting shared pathomechanisms in the SCN/CACNA1 genes. By training a machine learning model on sequence- and structure-based features we predict LOF- or GOF- associated disease phenotypes (ROC = 0.85) of likely pathogenic missense variants. We then successfully validate the GOF versus LOF prediction on 87 functionally tested variants in SCN1/2/8A and CACNA1I (ROC = 0.73) and in exome-wide data from > 100.000 cases and controls. Ultimately, functional prediction of missense variants in clinically relevant genes will facilitate precision medicine in clinical practice.
]]></description>
<dc:creator>Heyne, H.</dc:creator>
<dc:creator>Palmer, D.</dc:creator>
<dc:creator>Iqbal, S.</dc:creator>
<dc:creator>Baez-Nieto, D.</dc:creator>
<dc:creator>Brunklaus, A.</dc:creator>
<dc:creator>the Epi25 Collaborative,</dc:creator>
<dc:creator>Johannesen, K.</dc:creator>
<dc:creator>Lauxmann, S.</dc:creator>
<dc:creator>Lemke, J.</dc:creator>
<dc:creator>Moller, R.</dc:creator>
<dc:creator>Perez-Palma, E.</dc:creator>
<dc:creator>Scholl, U.</dc:creator>
<dc:creator>Syrbe, S.</dc:creator>
<dc:creator>Lerche, H.</dc:creator>
<dc:creator>May, P.</dc:creator>
<dc:creator>Lal, D.</dc:creator>
<dc:creator>Campbell, A.</dc:creator>
<dc:creator>Pan, J.</dc:creator>
<dc:creator>Wang, H.-R.</dc:creator>
<dc:creator>Daly, M.</dc:creator>
<dc:date>2019-06-14</dc:date>
<dc:identifier>doi:10.1101/671453</dc:identifier>
<dc:title><![CDATA[Predicting Functional Effects of Missense Variants in Voltage-Gated Sodium and Calcium Channels]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/693952v1?rss=1">
<title>
<![CDATA[
The human-specific BOLA2 duplication modifies iron homeostasis and anemia predisposition in chromosome 16p11.2 autism patients 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/693952v1?rss=1"
</link>
<description><![CDATA[
Human-specific duplications at chromosome 16p11.2 mediate recurrent pathogenic 600 kbp BP4-BP5 copy number variations, one of the most common genetic causes of autism. These copy number polymorphic duplications are under positive selection and include 3-8 copies of BOLA2, a gene involved in the maturation of cytosolic iron-sulfur proteins. To investigate the potential advantage provided by the rapid expansion of BOLA2, we assessed hematological traits and anemia prevalence in 379,385 controls and individuals who have lost or gained copies of BOLA2: 89 chromosome 16p11.2 BP4-BP5 deletion and 56 reciprocal duplication carriers in the UK Biobank. We found that the 16p11.2 deletion is associated with anemia (18/89 carriers, 20%, P=4e-7, OR=5), particularly iron-deficiency anemia. We observed similar enrichments in two clinical 16p11.2 deletion cohorts, with 6/63 (10%) and 7/20 (35%) unrelated individuals with anemia, microcytosis, low serum iron, or low blood hemoglobin. Upon stratification by BOLA2 copy number, we found an association between low BOLA2 dosage and the above phenotypes (8/15 individuals with three copies, 53%, P=1e-4). In parallel, we analyzed hematological traits in mice carrying the 16p11.2 orthologous deletion or duplication, as well as Bola2+/- and Bola2-/- animals. The deletion and Bola2-deficient mice showed early evidence of iron deficiency, including a mild decrease in hemoglobin, lower plasma iron, microcytosis, and an increased red blood cell zinc protoporphyrin to heme ratio. Our results indicate that BOLA2 participates in iron homeostasis in vivo and its expansion has a potential adaptive role in protecting against iron deficiency.
]]></description>
<dc:creator>Giannuzzi, G.</dc:creator>
<dc:creator>Schmidt, P. J.</dc:creator>
<dc:creator>Porcu, E.</dc:creator>
<dc:creator>Willemin, G.</dc:creator>
<dc:creator>Munson, K. M.</dc:creator>
<dc:creator>Nuttle, X.</dc:creator>
<dc:creator>Earl, R.</dc:creator>
<dc:creator>Chrast, J.</dc:creator>
<dc:creator>Hoekzema, K.</dc:creator>
<dc:creator>Risso, D.</dc:creator>
<dc:creator>Mannik, K.</dc:creator>
<dc:creator>De Nittis, P.</dc:creator>
<dc:creator>Baratz, E. D.</dc:creator>
<dc:creator>16p11.2 Consortium,</dc:creator>
<dc:creator>Herault, Y.</dc:creator>
<dc:creator>Gao, X.</dc:creator>
<dc:creator>Philpott, C. C.</dc:creator>
<dc:creator>Bernier, R. A.</dc:creator>
<dc:creator>Kutalik, Z.</dc:creator>
<dc:creator>Fleming, M. D.</dc:creator>
<dc:creator>Eichler, E. E.</dc:creator>
<dc:creator>Reymond, A.</dc:creator>
<dc:date>2019-07-05</dc:date>
<dc:identifier>doi:10.1101/693952</dc:identifier>
<dc:title><![CDATA[The human-specific BOLA2 duplication modifies iron homeostasis and anemia predisposition in chromosome 16p11.2 autism patients]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/693937v1?rss=1">
<title>
<![CDATA[
Variants in the degron of AFF3 cause a multi-system disorder with mesomelic dysplasia, horseshoe kidney and developmental and epileptic encephalopathy 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/693937v1?rss=1"
</link>
<description><![CDATA[
The ALF transcription factor paralogs, AFF1, AFF2, AFF3 and AFF4, are components of the transcriptional super elongation complex that regulates expression of genes involved in neurogenesis and development. We describe a new autosomal dominant disorder associated with de novo missense variants in the degron of AFF3, a nine amino acid sequence important for its degradation. Consistent with a causative role of AFF3 variants, the mutated AFF3 proteins show reduced clearance. Ten affected individuals were identified, and present with a recognizable pattern of anomalies, which we named KINSSHIP syndrome (KI for horseshoe KIdney, NS for Nievergelt/Savarirayan type of mesomelic dysplasia, S for Seizures, H for Hypertrichosis, I for Intellectual disability and P for Pulmonary involvement), partially overlapping the AFF4 associated CHOPS syndrome. An eleventh individual with a microdeletion encompassing only the transactivation domain and degron motif of AFF3 exhibited overlapping clinical features. A zebrafish overexpression model that shows body axis anomalies provides further support for the pathological effect of increased amount of AFF3 protein.nnWhereas homozygous Aff3 knockout mice display skeletal anomalies, kidney defects, brain malformation and neurological anomalies, knock-in animals modeling the microdeletion and the missense variants identified in affected individuals presented with lower mesomelic limb deformities and early lethality, respectively.nnTranscriptome analyses as well as the partial phenotypic overlap of syndromes associated with AFF3 and AFF4 variants suggest that ALF transcription factors are not redundant in contrast to what was previously suggested
]]></description>
<dc:creator>Voisin, N.</dc:creator>
<dc:creator>Schnur, R. E.</dc:creator>
<dc:creator>Douzgou, S.</dc:creator>
<dc:creator>Hiatt, S. M.</dc:creator>
<dc:creator>Rustad, C. F.</dc:creator>
<dc:creator>Brown, N. J.</dc:creator>
<dc:creator>Earl, D. L.</dc:creator>
<dc:creator>Keren, B.</dc:creator>
<dc:creator>Levchenko, O.</dc:creator>
<dc:creator>Geuer, S.</dc:creator>
<dc:creator>Amor, D.</dc:creator>
<dc:creator>Brusco, A.</dc:creator>
<dc:creator>Bebin, E. M.</dc:creator>
<dc:creator>Cappuccio, G.</dc:creator>
<dc:creator>Charrow, J.</dc:creator>
<dc:creator>Chatron, N.</dc:creator>
<dc:creator>Cooper, G. M.</dc:creator>
<dc:creator>Dadali, E.</dc:creator>
<dc:creator>Delafontaine, J.</dc:creator>
<dc:creator>Del Giudice, E.</dc:creator>
<dc:creator>Douglas, G.</dc:creator>
<dc:creator>Funari, T.</dc:creator>
<dc:creator>Giannuzzi, G.</dc:creator>
<dc:creator>Guex, N.</dc:creator>
<dc:creator>Heron, D.</dc:creator>
<dc:creator>Holla, O. L.</dc:creator>
<dc:creator>Hurst, A. C. E.</dc:creator>
<dc:creator>Juusola, J.</dc:creator>
<dc:creator>Kronn, D.</dc:creator>
<dc:creator>Lavrov, A.</dc:creator>
<dc:creator>Lee, C.</dc:creator>
<dc:creator>Merckoll, E.</dc:creator>
<dc:creator>Mikhaleva, A.</dc:creator>
<dc:creator>Norman, J.</dc:creator>
<dc:creator>Pradervand, S.</dc:creator>
<dc:creator>Sanders, V.</dc:creator>
<dc:creator>Sirchia, F.</dc:creator>
<dc:creator>Takenouchi, T.</dc:creator>
<dc:creator>Tanaka, A. J.</dc:creator>
<dc:creator>Taska-Tench, H.</dc:creator>
<dc:creator>Tonne, E.</dc:creator>
<dc:creator>Tveten, K.</dc:creator>
<dc:creator>Vitiello, G.</dc:creator>
<dc:creator>Uehara, T.</dc:creator>
<dc:creator>Nava, C.</dc:creator>
<dc:creator>Y</dc:creator>
<dc:date>2019-07-17</dc:date>
<dc:identifier>doi:10.1101/693937</dc:identifier>
<dc:title><![CDATA[Variants in the degron of AFF3 cause a multi-system disorder with mesomelic dysplasia, horseshoe kidney and developmental and epileptic encephalopathy]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/228254v1?rss=1">
<title>
<![CDATA[
Systemizing is genetically correlated with autism and is genetically distinct from social autistic traits 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/228254v1?rss=1"
</link>
<description><![CDATA[
The core diagnostic criteria for autism comprise two symptom domains - social and communication difficulties, and unusually repetitive and restricted behaviour, interests and activities. There is some evidence to suggest that these two domains are dissociable, yet, this hypothesis has not been tested using molecular genetics. We test this using a GWAS of a non-social autistic trait, systemizing (N = 51,564), defined as the drive to analyse and build systems. We demonstrate that systemizing is heritable and genetically correlated with autism. In contrast, we do not identify significant genetic correlations between social autistic traits and systemizing. Supporting this, polygenic scores for systemizing are significantly positively associated with restricted and repetitive behaviour but not with social difficulties in autistic individuals. These findings strongly suggest that the two core domains of autism are genetically dissociable, and point at how to fractionate the genetics of autism.
]]></description>
<dc:creator>Warrier, V.</dc:creator>
<dc:creator>Toro, R.</dc:creator>
<dc:creator>Chakrabarti, B.</dc:creator>
<dc:creator>iPSYCH-Broad Autism Group,</dc:creator>
<dc:creator>Borglum, A.</dc:creator>
<dc:creator>Grove, J.</dc:creator>
<dc:creator>the 23andMe Research Team,</dc:creator>
<dc:creator>Hinds, D.</dc:creator>
<dc:creator>Bourgeron, T.</dc:creator>
<dc:creator>Baron-Cohen, S.</dc:creator>
<dc:date>2017-12-03</dc:date>
<dc:identifier>doi:10.1101/228254</dc:identifier>
<dc:title><![CDATA[Systemizing is genetically correlated with autism and is genetically distinct from social autistic traits]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/706135v1?rss=1">
<title>
<![CDATA[
Reduced sleep pressure in young children with autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/706135v1?rss=1"
</link>
<description><![CDATA[
Study ObjectivesSleep disturbances and insomnia are highly prevalent in children with Autism Spectrum Disorder (ASD). Sleep homeostasis, a fundamental mechanism of sleep regulation that generates pressure to sleep as a function of wakefulness, has not been studied in children with ASD so far, and its potential contribution to their sleep disturbances remains unknown. Here, we examined whether slow wave activity (SWA), a measure that is indicative of sleep pressure, differs in children with ASD.

MethodsIn this case-control study, we compared overnight electroencephalogram (EEG) recordings that were performed during Polysomnography (PSG) evaluations of 29 children with ASD and 23 typically developing children.

ResultsChildren with ASD exhibited significantly weaker SWA power, shallower SWA slopes, and a decreased proportion of slow wave sleep in comparison to controls. This difference was largest during the first two hours following sleep onset and decreased gradually thereafter. Furthermore, SWA power of children with ASD was significantly, negatively correlated with the time of their sleep onset in the lab and at home, as reported by parents.

ConclusionsThese results suggest that children with ASD may have a dysregulation of sleep homeostasis that is manifested in reduced sleep pressure. The extent of this dysregulation in individual children was apparent in the amplitude of their SWA power, which was indicative of the severity of their individual sleep disturbances. We, therefore, suggest that disrupted homeostatic sleep regulation may contribute to sleep disturbances in children with ASD.

Statement of significanceSleep disturbances are apparent in 40-80% of children with autism. Homeostatic sleep regulation, a mechanism that increases the pressure to sleep as a function of prior wakefulness, has not been studied in children with autism. Here, we compared Polysomnography exams of 29 children with autism and 23 matched controls. We found that children with autism exhibited reduced slow-wave-activity power and shallower slopes, particularly during the first two hours of sleep. This suggests that they develop less pressure to sleep. Furthermore, the reduction in slow-wave-activity was associated with the severity of sleep disturbances as observed in the laboratory and as reported by parents. We, therefore, suggest that disrupted homeostatic sleep regulation may contribute to sleep disturbances of children with autism.
]]></description>
<dc:creator>Arazi, A.</dc:creator>
<dc:creator>Meiri, G.</dc:creator>
<dc:creator>Danan, D.</dc:creator>
<dc:creator>Michaelovski, A.</dc:creator>
<dc:creator>Flusser, H.</dc:creator>
<dc:creator>Menashe, I.</dc:creator>
<dc:creator>Tarasiuk, A.</dc:creator>
<dc:creator>Dinstein, I.</dc:creator>
<dc:date>2019-07-22</dc:date>
<dc:identifier>doi:10.1101/706135</dc:identifier>
<dc:title><![CDATA[Reduced sleep pressure in young children with autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/687194v1?rss=1">
<title>
<![CDATA[
Systematic phenomics analysis of ASD-associated genes reveals shared functions and parallel networks underlying reversible impairments in habituation learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/687194v1?rss=1"
</link>
<description><![CDATA[
A major challenge facing the genetics of Autism Spectrum Disorders (ASD) is the large and growing number of candidate risk genes and gene variants of unknown functional significance. Here, we used Caenorhabditis elegans to systematically functionally characterize ASD-associated genes in vivo. Using our custom machine vision system we quantified 26 phenotypes spanning morphology, locomotion, tactile sensitivity, and habituation learning in 87 strains each carrying a mutation in an ortholog of an ASD-associated gene. We identified hundreds of novel genotype-phenotype relationships ranging from severe developmental delays and uncoordinated movement to subtle deficits in sensory and learning behaviors. We clustered genes by similarity in phenomic profiles and used epistasis analysis to discover parallel networks centered on CHD8*chd-7 and NLGN3*nlg-1 that underlie mechanosensory hyper-responsivity and impaired habituation learning. We then leveraged our data for in vivo functional assays to gauge missense variant effect. Expression of wild-type NLG-1 in nlg-1 mutant C. elegans rescued their sensory and learning impairments. Testing the rescuing ability of all conserved ASD-associated neuroligin variants revealed varied partial loss-of-function despite proper subcellular localization. Finally, we used CRISPR-Cas9 auxin inducible degradation to determine that phenotypic abnormalities caused by developmental loss of NLG-1 can be reversed by adult expression. This work charts the phenotypic landscape of ASD-associated genes, offers novel in vivo variant functional assays, and potential therapeutic targets for ASD.
]]></description>
<dc:creator>McDiarmid, T. A.</dc:creator>
<dc:creator>Belmadani, M.</dc:creator>
<dc:creator>Liang, j.</dc:creator>
<dc:creator>Meili, F.</dc:creator>
<dc:creator>Mathews, E. A.</dc:creator>
<dc:creator>Mullen, G. P.</dc:creator>
<dc:creator>Rand, J. B.</dc:creator>
<dc:creator>Mizumoto, K.</dc:creator>
<dc:creator>Haas, K.</dc:creator>
<dc:creator>Pavlidis, P.</dc:creator>
<dc:creator>Rankin, C. H.</dc:creator>
<dc:date>2019-06-30</dc:date>
<dc:identifier>doi:10.1101/687194</dc:identifier>
<dc:title><![CDATA[Systematic phenomics analysis of ASD-associated genes reveals shared functions and parallel networks underlying reversible impairments in habituation learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/715755v1?rss=1">
<title>
<![CDATA[
Gene discoveries in autism are biased towards comorbidity with intellectual disability 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/715755v1?rss=1"
</link>
<description><![CDATA[
Autism typically presents with a highly heterogeneous set of features, including frequent comorbidity with intellectual disability (ID). The overlap between these two phenotypes has confounded the accurate diagnosis and discovery of genetic factors associated with autism. We analyzed genetic variants in 2,290 individuals with autism from the Simons Simplex Collection (SSC) who have either ID or normal cognitive function to determine whether genes associated with autism also contribute towards ID comorbidity. We found that individuals who carried variants in a set of 173 reported autism-associated genes showed decreased IQ (p=5.49x10-6) and increased autism severity (p=0.013) compared with individuals without such variants. A subset of autism-associated genes also showed strong evidence for ID comorbidity in published case reports. We also found that individuals with high-functioning autism (IQ>100) had lower frequencies of CNVs (p=0.065) and LGD variants (p=0.021) compared with individuals who manifested both autism and ID (IQ<70). These data indicated that de novo LGD variants conferred a 1.53-fold higher risk (p=0.035) towards comorbid ID, while LGD mutations specifically disrupting autism-associated genes conferred a 4.85-fold increased risk (p=0.011) for comorbid ID. Furthermore, de novo LGD variants in individuals with high-functioning autism were more likely to disrupt genes with little functional relevance towards neurodevelopment, as demonstrated by evidence from pathogenicity metrics, expression patterns in the developing brain, and mouse model phenotypes. Overall, our data suggest that de novo pathogenic variants disrupting genes associated with autism contribute towards autism and ID comorbidity, while other genetic factors are likely to be causal for high-functioning autism.
]]></description>
<dc:creator>Jensen, M.</dc:creator>
<dc:creator>Smolen, C.</dc:creator>
<dc:creator>Girirajan, S.</dc:creator>
<dc:date>2019-07-26</dc:date>
<dc:identifier>doi:10.1101/715755</dc:identifier>
<dc:title><![CDATA[Gene discoveries in autism are biased towards comorbidity with intellectual disability]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/716415v1?rss=1">
<title>
<![CDATA[
Leveraging biobank-scale rare and common variant analyses to identify ASPHD1 as the main driver of reproductive traits in the 16p11.2 locus 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/716415v1?rss=1"
</link>
<description><![CDATA[
Whereas genome-wide association studies (GWAS) allowed identifying thousands of associations between variants and traits, their success rate in pinpointing causal genes has been disproportionately low. Here, we integrate biobank-scale phenotype data from carriers of a rare copy-number variant (CNV), Mendelian randomization and animal modeling to identify causative genes in a GWAS locus for age at menarche (AaM). We show that the dosage of the 16p11.2 BP4-BP5 interval is correlated positively with AaM in the UK and Estonian biobanks and 16p11.2 clinical cohorts, with a directionally consistent trend for pubertal onset in males. These correlations parallel an increase in reproductive tract disorders in both sexes. In support of these observations, 16p11.2 mouse models display perturbed pubertal onset and structurally altered reproductive organs that track with CNV dose. Further, we report a negative correlation between the 16p11.2 dosage and relative hypothalamic volume in both humans and mice, intimating a perturbation in the gonadotropin-releasing hormone (GnRH) axis. Two independent lines of evidence identified candidate causal genes for AaM; Mendelian randomization and agnostic dosage modulation of each 16p11.2 gene in zebrafish gnrh3:egfp models. ASPHD1, expressed predominantly in brain and pituitary gland, emerged as a major phenotype driver; and it is subject to modulation by KCTD13 to exacerbate GnRH neuron phenotype. Together, our data highlight the power of an interdisciplinary approach to elucidate disease etiologies underlying complex traits.
]]></description>
<dc:creator>Männik, K.</dc:creator>
<dc:creator>Arbogast, T.</dc:creator>
<dc:creator>Lepamets, M.</dc:creator>
<dc:creator>Lepik, K.</dc:creator>
<dc:creator>Pellaz, A.</dc:creator>
<dc:creator>Ademi, H.</dc:creator>
<dc:creator>Kupchinsky, Z. A.</dc:creator>
<dc:creator>Ellegood, J.</dc:creator>
<dc:creator>Attanasio, C.</dc:creator>
<dc:creator>Messina, A.</dc:creator>
<dc:creator>Rotman, S.</dc:creator>
<dc:creator>Martin-Brevet, S.</dc:creator>
<dc:creator>Dubruc, E.</dc:creator>
<dc:creator>Chrast, J.</dc:creator>
<dc:creator>Lerch, J. P.</dc:creator>
<dc:creator>Qiu, L. R.</dc:creator>
<dc:creator>Laisk, T.</dc:creator>
<dc:creator>The 16p11.2 European Consortium,</dc:creator>
<dc:creator>The Simons VIP Consortium,</dc:creator>
<dc:creator>The eQTLGen Consortium,</dc:creator>
<dc:creator>Henkelman, M. R.</dc:creator>
<dc:creator>Jacquemont, S.</dc:creator>
<dc:creator>Herault, Y.</dc:creator>
<dc:creator>Lindgren, C. M.</dc:creator>
<dc:creator>Peterson, H.</dc:creator>
<dc:creator>Stehle, J. C.</dc:creator>
<dc:creator>Katsanis, N.</dc:creator>
<dc:creator>Kutalik, Z.</dc:creator>
<dc:creator>Nef, S.</dc:creator>
<dc:creator>Draganski, B.</dc:creator>
<dc:creator>Davis, E. E.</dc:creator>
<dc:creator>Mägi, R.</dc:creator>
<dc:creator>Reymond, A.</dc:creator>
<dc:date>2019-07-26</dc:date>
<dc:identifier>doi:10.1101/716415</dc:identifier>
<dc:title><![CDATA[Leveraging biobank-scale rare and common variant analyses to identify ASPHD1 as the main driver of reproductive traits in the 16p11.2 locus]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/722074v1?rss=1">
<title>
<![CDATA[
Brain-wide visual habituation networks in wild type and fmr1 zebrafish 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/722074v1?rss=1"
</link>
<description><![CDATA[
Habituation is a form of learning during which animals stop responding to repetitive stimuli, and deficits in habituation are characteristics of several psychiatric disorders. Due to the technical challenges of measuring brain activity comprehensively and at cellular resolution, the brain-wide networks mediating habituation are poorly understood. Here we report brain-wide calcium imaging during visual learning in larval zebrafish as they habituate to repeated threatening loom stimuli. We show that different functional categories of loom-sensitive neurons are located in characteristic locations throughout the brain, and that both the functional properties of their networks and the resulting behavior can be modulated by stimulus saliency and timing. Using graph theory, we identify a principally visual circuit that habituates minimally, a moderately habituating midbrain population proposed to mediate the sensorimotor transformation, and downstream circuit elements responsible for higher order representations and the delivery of behavior. Zebrafish larvae carrying a mutation in the fmr1 gene have a systematic shift towards sustained premotor activity in this network, and show slower behavioral habituation. This represents the first description of a visual learning network across the brain at cellular resolution, and provides insights into the circuit-level changes that may occur in people with Fragile X syndrome and related psychiatric conditions.
]]></description>
<dc:creator>Marquez-Legorreta, E.</dc:creator>
<dc:creator>Constantin, L.</dc:creator>
<dc:creator>Piber, M.</dc:creator>
<dc:creator>Favre-Bulle, I. A.</dc:creator>
<dc:creator>Taylor, M.</dc:creator>
<dc:creator>Vanwalleghem, G.</dc:creator>
<dc:creator>Scott, E.</dc:creator>
<dc:date>2019-08-06</dc:date>
<dc:identifier>doi:10.1101/722074</dc:identifier>
<dc:title><![CDATA[Brain-wide visual habituation networks in wild type and fmr1 zebrafish]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/722082v1?rss=1">
<title>
<![CDATA[
Altered brain-wide auditory networks in fmr1-mutant larval zebrafish 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/722082v1?rss=1"
</link>
<description><![CDATA[
Altered sensory processing is characteristic of several psychiatric conditions, including autism and fragile X syndrome (FXS). Here, we use whole-brain calcium imaging at cellular resolution to map sensory processing in wild type larval zebrafish and mutants for fmr1, which causes FXS in humans. Using functional analyses and graph theory, we describe increased transmission and reduced filtering of auditory information, resulting in network-wide hypersensitivity analogous to the auditory phenotypes seen in FXS.
]]></description>
<dc:creator>Constantin, L.</dc:creator>
<dc:creator>Poulsen, R.</dc:creator>
<dc:creator>Favre-Bulle, I. A.</dc:creator>
<dc:creator>Taylor, M.</dc:creator>
<dc:creator>Sun, B.</dc:creator>
<dc:creator>Goodhill, G.</dc:creator>
<dc:creator>Vanwalleghem, G.</dc:creator>
<dc:creator>Scott, E.</dc:creator>
<dc:date>2019-08-05</dc:date>
<dc:identifier>doi:10.1101/722082</dc:identifier>
<dc:title><![CDATA[Altered brain-wide auditory networks in fmr1-mutant larval zebrafish]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/730952v1?rss=1">
<title>
<![CDATA[
Primary complex motor stereotypies are associated with de novo damaging DNA coding mutations that identify candidate risk genes and biological pathways 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/730952v1?rss=1"
</link>
<description><![CDATA[
Motor stereotypies are common in children with autism spectrum disorder (ASD), intellectual disability, or sensory deprivation, as well as in typically developing children ("primary" stereotypies, CMS). The precise pathophysiological mechanism for motor stereotypies is unknown, although genetic etiologies have been suggested. In this study, we perform whole-exome DNA sequencing in 129 parent-child trios with CMS and 853 control trios (118 cases and 750 controls after quality control). We report an increased rate of de novo predicted-damaging variants in CMS versus controls, identifying KDM5B as a high-confidence risk gene and estimating 184 genes conferring risk. Genes harboring de novo damaging variants in CMS probands show significant overlap with those in Tourette syndrome, ASD candidate genes, and those in ASD probands with high stereotypy scores. Furthermore, exploratory biological pathway and gene ontology analysis highlight histone demethylation, organism development, cell motility, glucocorticoid receptor pathway, and ion channel transport. Continued sequencing of CMS trios will identify more risk genes and allow greater insights into biological mechanisms of stereotypies across diagnostic boundaries.
]]></description>
<dc:creator>Fernandez, T. V.</dc:creator>
<dc:creator>Williams, Z. P.</dc:creator>
<dc:creator>Kline, T.</dc:creator>
<dc:creator>Rajendran, S.</dc:creator>
<dc:creator>Augustine, F.</dc:creator>
<dc:creator>Wright, N.</dc:creator>
<dc:creator>Sullivan, C. A. W.</dc:creator>
<dc:creator>Olfson, E.</dc:creator>
<dc:creator>Abdallah, S. B.</dc:creator>
<dc:creator>Liu, W.</dc:creator>
<dc:creator>Hoffman, E. J.</dc:creator>
<dc:creator>Gupta, A. R.</dc:creator>
<dc:creator>Singer, H. S.</dc:creator>
<dc:date>2019-08-13</dc:date>
<dc:identifier>doi:10.1101/730952</dc:identifier>
<dc:title><![CDATA[Primary complex motor stereotypies are associated with de novo damaging DNA coding mutations that identify candidate risk genes and biological pathways]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/730150v1?rss=1">
<title>
<![CDATA[
Placental neurosteroids shape cerebellar development and social behaviour 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/730150v1?rss=1"
</link>
<description><![CDATA[
Compromised placental function or premature loss has been linked to diverse neurodevelopmental disorders 1,2. The placenta is the first functional foetal endocrine organ, but the direct impact of placental hormone loss on foetal brain in late gestation has not been empirically tested. Allopregnanolone (ALLO) is a non-glucocorticoid, progesterone derivative that acts as a positive modulator of GABA-A receptor activity3 with the potential to alter critical GABA-mediated developmental processes 4,5. To directly test the role of placental ALLO, we generated a novel mouse model in which the gene encoding the synthetic enzyme for ALLO (Akr1c14) is specifically deleted in trophoblasts using a tissue-specific Cre-Lox strategy. ALLO concentrations are significantly decreased in late gestation in placenta and brain when placental Akr1c14 is removed, indicating placenta as the primary gestational ALLO source. We now demonstrate that targeted placental ALLO loss leads to permanent changes in brain development in a sex- and regionally-specific manner. Placental ALLO insufficiency led to male-specific cerebellar white matter (WM) abnormalities characterized by excess myelination with increased myelin protein expression, similar to changes reported in boys with autism spectrum disorders (ASD)6,7. Behavioural testing of these mice revealed increased repetitive behaviour and sociability deficits, two hallmarks of ASD, only in male offspring with placental ALLO insufficiency. Notably, a strong positive correlation was seen between the cerebellar contents of myelin basic protein (MBP) and the severity of ASD-like behaviours. A single injection of ALLO during gestation was sufficient to rescue both cerebellar MBP levels and aberrant behaviours. This study reveals a new role for a placental hormone in shaping specific brain structures and behaviours, and suggests that identifying placental hormone insufficiency or preterm loss may offer novel therapeutic opportunities to prevent later neurobehavioural disorders.
]]></description>
<dc:creator>Vacher, C.-M.</dc:creator>
<dc:creator>O'Reilly, J. J.</dc:creator>
<dc:creator>Salzbank, J.</dc:creator>
<dc:creator>Lacaille, H.</dc:creator>
<dc:creator>Bakalar, D.</dc:creator>
<dc:creator>Sebaoui-Illoul, S.</dc:creator>
<dc:creator>Liere, P.</dc:creator>
<dc:creator>Clarkson-Paredes, C.</dc:creator>
<dc:creator>Sasaki, T.</dc:creator>
<dc:creator>Sathyanesan, A.</dc:creator>
<dc:creator>Imamura Kawasawa, Y.</dc:creator>
<dc:creator>Popratiloff, A.</dc:creator>
<dc:creator>Hashimoto-Torii, K.</dc:creator>
<dc:creator>Gallo, V.</dc:creator>
<dc:creator>Schumacher, M.</dc:creator>
<dc:creator>Penn, A. A.</dc:creator>
<dc:date>2019-08-13</dc:date>
<dc:identifier>doi:10.1101/730150</dc:identifier>
<dc:title><![CDATA[Placental neurosteroids shape cerebellar development and social behaviour]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/742213v1?rss=1">
<title>
<![CDATA[
Human cerebral organoids capture the spatiotemporal complexity and disease dynamics of UBE3A 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/742213v1?rss=1"
</link>
<description><![CDATA[
Human neurodevelopment and its associated diseases are complex and challenging to study. This has driven recent excitement for human cerebral organoids (hCOs) as research and screening tools. These models are steadily proving their utility; however, it remains unclear what limits they will face in recapitulating the complexities of neurodevelopment and disease. Here we show that their utility extends to key (epi)genetic and disease processes that are complex in space and time. Specifically, hCOs capture UBE3As dynamically imprinted expression and subcellular localization patterns. Furthermore, given UBE3As direct links to Angelman Syndrome and Autism Spectrum Disorder, we show that hCOs respond to candidate small molecule therapeutics. This work demonstrates that hCOs can provide important insights to focus the scope of mechanistic and therapeutic strategies including revealing difficult to access prenatal developmental time windows and cell types key to disease etiology.
]]></description>
<dc:creator>Sen, D.</dc:creator>
<dc:creator>Voulgaropoulos, A.</dc:creator>
<dc:creator>Drobna, Z.</dc:creator>
<dc:creator>Keung, A. J.</dc:creator>
<dc:date>2019-08-22</dc:date>
<dc:identifier>doi:10.1101/742213</dc:identifier>
<dc:title><![CDATA[Human cerebral organoids capture the spatiotemporal complexity and disease dynamics of UBE3A]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/744540v1?rss=1">
<title>
<![CDATA[
Robust Hi-C chromatin loop maps in human neurogenesis and brain tissues at high-resolution 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/744540v1?rss=1"
</link>
<description><![CDATA[
Genome-wide mapping of chromatin interactions at high resolution remains experimentally and computationally challenging. Here we used a low-input "easy Hi-C" (eHi-C) protocol to map the 3D genome architecture in neurogenesis and brain tissues, and also developed an improved Hi-C bias-correction pipeline (HiCorr) enabling better identification of enhancer loops or aggregates at sub-TAD level. We compared ultra-deep 3D genome maps from 10 human tissue- or cell types, with a focus on stem cells and neural development. We found several large loci in skin-derived human iPSC lines showing recurrent 3D compartmental memory of somatic heterochromatin. Chromatin loop interactions, but not genome compartments, are hallmarks of neural differentiation. Interestingly, we observed many cell type- or differentiation-specific enhancer aggregates spanning large neighborhoods, supporting a phase-separation mechanism that stabilizes enhancer contacts during development. Finally, we demonstrated that chromatin loop outperforms eQTL in explaining neurological GWAS results, revealing a unique value of high-resolution 3D genome maps in elucidating the disease etiology.nnHighlightsO_LILow input "easy Hi-C" protocol compatible with 50-100K cellsnC_LIO_LIImproved Hi-C bias correction allows direct observation and accurate identification of sub-TAD chromatin loops and enhancer aggregatesnC_LIO_LIRecurrent architectural memory of somatic heterochromatin at compartment level in skin-derived hiPSCsnC_LIO_LIChromatin loop, but not genome compartment, marks neural differentiationnC_LIO_LIChromatin loop outperforms eQTL in defining brain GWAS target genesnC_LI
]]></description>
<dc:creator>LU, L.</dc:creator>
<dc:creator>Liu, X.</dc:creator>
<dc:creator>Huang, W.-K.</dc:creator>
<dc:creator>Giusti-Rodriguez, P.</dc:creator>
<dc:creator>Cui, J.</dc:creator>
<dc:creator>Zhang, S.</dc:creator>
<dc:creator>Xu, W.</dc:creator>
<dc:creator>Wen, Z.</dc:creator>
<dc:creator>Ma, S.</dc:creator>
<dc:creator>Rosen, J. D.</dc:creator>
<dc:creator>Xu, Z.</dc:creator>
<dc:creator>Bartels, C.</dc:creator>
<dc:creator>Riki Kawaguchi, R.</dc:creator>
<dc:creator>Hu, M.</dc:creator>
<dc:creator>Scacheri, P.</dc:creator>
<dc:creator>Rong, Z.</dc:creator>
<dc:creator>Li, Y.</dc:creator>
<dc:creator>Sullivan, P. F.</dc:creator>
<dc:creator>Song, H.</dc:creator>
<dc:creator>Ming, G.-l.</dc:creator>
<dc:creator>Li, Y.</dc:creator>
<dc:creator>Jin, F.</dc:creator>
<dc:date>2019-08-22</dc:date>
<dc:identifier>doi:10.1101/744540</dc:identifier>
<dc:title><![CDATA[Robust Hi-C chromatin loop maps in human neurogenesis and brain tissues at high-resolution]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/762500v1?rss=1">
<title>
<![CDATA[
FMRP binding to a ranked subset of long genes is revealed by coupled CLIP and TRAP in specific neuronal cell types 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/762500v1?rss=1"
</link>
<description><![CDATA[
Loss of function of the Fragile X Mental Retardation Protein (FMRP) in human Fragile X Syndrome (FXS) and in model organisms results in phenotypes of abnormal neuronal structure and dynamics, synaptic function and connectivity which may contribute to a state of neuronal, circuit and organism hyperexcitability. Previous in vivo identification of FMRP association with specific mRNA targets in mouse brain revealed that FMRP regulates the translation of a large fraction of the synaptic proteome in both pre- and post-synaptic compartments as well as many transcription factors and chromatin modifying proteins. However, it was not previously possible to determine the ratio of FMRP binding to transcript abundance due to the complexity of different neuronal cell types in whole brain. Moreover, it has been difficult to link the translational regulation of specific targets to model phenotypes or human symptoms. For example, loss-of-function of FMRP in the Purkinje cells of the cerebellum results in three cell autonomous phenotypes related to learning and memory, including enhanced mGluR-LTD at parallel fiber synapses, altered dendritic spines and behavioral deficits in a eyeblink-conditioning learning paradigm shared by human FXS patients. The molecular basis for these and related human Fragile X phenotypes is unknown. To address these critical issues we have developed a new mouse model (the Fmr1 cTAG mouse) in which endogenous FMRP can be conditionally tagged for RNA:protein crosslinking and immunoprecipitation (CLIP) identification of the RNAs with which it interacts in vivo. We used the Fmr1 cTAG mouse to quantitatively evaluate FMRP-mRNA association in Purkinje and cerebellar granule neurons which together comprise the parallel-fiber synapse. We calculated a stoichiometrically ranked list of FMRP RNA binding events by normalizing to ribosome-associated transcript abundance determined by TRAP-seq, and now definitively find that FMRP associates with specific sets of mRNAs which differ between the two cell types. In Purkinje cells, many components of the mGluR signaling pathway are FMRP targets including the top-ranked Purkinje cell mRNA Itpr1, encoding the IP3 receptor, the function of which is critical to proper mGluR-dependent synaptic plasticity. In sum, this novel approach provides the first ranked list of FMRP target mRNAs and further reveals that FMRP regulates a specific set of long neural genes related to relevant cell autonomous phenotypes.nnHighlightsO_LIWe have created a mouse model in which endogenous FMRP can be conditionally tagged.nC_LIO_LIUsing tag-specific CLIP we describe ranked and specific sets of in vivo FMRP mRNA targets in two types of neurons.nC_LIO_LIThis ranking was used to reveal that FMRP regulates mRNAs with long coding sequences.nC_LIO_LIFMRP mRNA targets in Purkinje cells, including the top-ranked IP3 receptor, are related to cell-autonomous Fragile X phenotypes.nC_LIO_LIWe have updated our previous list of whole mouse brain FMRP mRNA targets with more replicates, deeper sequencing and improved analysisnC_LIO_LIThe use of tagged FMRP in less abundant cell populations allowed identification of novel mRNA targets missed in a whole brain analysisnC_LI
]]></description>
<dc:creator>Van Driesche, S. J.</dc:creator>
<dc:creator>Sawicka, K.</dc:creator>
<dc:creator>Zhang, C.</dc:creator>
<dc:creator>Hung, S. K. Y.</dc:creator>
<dc:creator>Park, C. Y.</dc:creator>
<dc:creator>Fak, J. J.</dc:creator>
<dc:creator>Yang, C.</dc:creator>
<dc:creator>Darnell, R. B.</dc:creator>
<dc:creator>Darnell, J. C.</dc:creator>
<dc:date>2019-09-09</dc:date>
<dc:identifier>doi:10.1101/762500</dc:identifier>
<dc:title><![CDATA[FMRP binding to a ranked subset of long genes is revealed by coupled CLIP and TRAP in specific neuronal cell types]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/766634v1?rss=1">
<title>
<![CDATA[
Deletion of a non-canonical promoter regulatory element causes loss of Scn1a expression and epileptic phenotypes in mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/766634v1?rss=1"
</link>
<description><![CDATA[
Genes with multiple co-active promoters appear common in brain, yet little is known about functional requirements for these potentially redundant genomic regulatory elements. SCN1A, which encodes the NaV1.1 sodium channel alpha subunit, is one such gene with two co-active promoters. Mutations in SCN1A are associated with epilepsy, including Dravet Syndrome (DS). The majority of DS patients harbor coding mutations causing SCN1A haploinsufficiency, however putative causal non-coding promoter mutations have been identified. To determine the functional role of one of these potentially redundant Scn1a promoters, we focused on the non-coding Scn1a 1b regulatory region, previously described as a non-canonical alternative transcriptional start site. Mice harboring a deletion of the extended evolutionarily-conserved 1b non-coding interval exhibited surprisingly severe reductions of Scn1a and NaV1.1 expression in brain with accompanying electroencephalographic seizures and behavioral deficits. This work identified the 1b region as a critical disease-relevant regulatory element and provides evidence that non-canonical and seemingly redundant promoters can have essential function.
]]></description>
<dc:creator>Haigh, J. L.</dc:creator>
<dc:creator>Adhikari, A.</dc:creator>
<dc:creator>Copping, N. A.</dc:creator>
<dc:creator>Stradleigh, T. W.</dc:creator>
<dc:creator>Wade, A. A.</dc:creator>
<dc:creator>Catta-Preta, R. F.</dc:creator>
<dc:creator>Su-Feher, L.</dc:creator>
<dc:creator>Zdilar, I.</dc:creator>
<dc:creator>Morse, S. J.</dc:creator>
<dc:creator>Fenton, T. A.</dc:creator>
<dc:creator>Nguyen, A. B.</dc:creator>
<dc:creator>Quintero, D. M.</dc:creator>
<dc:creator>Sramek, M.</dc:creator>
<dc:creator>Carter, J. L.</dc:creator>
<dc:creator>Gompers, A.</dc:creator>
<dc:creator>Lambert, J. T.</dc:creator>
<dc:creator>Canales, C. P.</dc:creator>
<dc:creator>Pennacchio, L.</dc:creator>
<dc:creator>Visel, A.</dc:creator>
<dc:creator>Dickel, D.</dc:creator>
<dc:creator>Silverman, J. L.</dc:creator>
<dc:creator>Nord, A. S.</dc:creator>
<dc:date>2019-09-12</dc:date>
<dc:identifier>doi:10.1101/766634</dc:identifier>
<dc:title><![CDATA[Deletion of a non-canonical promoter regulatory element causes loss of Scn1a expression and epileptic phenotypes in mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/802538v1?rss=1">
<title>
<![CDATA[
A sex difference in the composition of the rodent postsynaptic density 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/802538v1?rss=1"
</link>
<description><![CDATA[
SynGAP is a postsynaptic density (PSD) protein that binds to PDZ domains of the scaffold protein PSD-95. We previously reported that heterozygous deletion of synGAP in mice is correlated with increased steady-state levels of other key PSD proteins that bind PSD-95, although the level of PSD-95 remains constant (Walkup et al., 2016). For example, the ratio to PSD-95 of Transmembrane AMPA-Receptor-associated Proteins (TARPs), which mediate binding of AMPA-type glutamate receptors to PSD-95, was increased in young synGAP+/- mice. Here we show that a highly significant increase in TARP in the PSDs of young synGAP+/- rodents is present only in females and not in males. The data reveal a sex difference in the adaptation of the PSD scaffold to synGAP heterozygosity.
]]></description>
<dc:creator>Mastro, T. L.</dc:creator>
<dc:creator>Preza, A.</dc:creator>
<dc:creator>Basu, S.</dc:creator>
<dc:creator>Chattarji, S.</dc:creator>
<dc:creator>Till, S. M.</dc:creator>
<dc:creator>Kind, P. C.</dc:creator>
<dc:creator>Kennedy, M. B.</dc:creator>
<dc:date>2019-10-12</dc:date>
<dc:identifier>doi:10.1101/802538</dc:identifier>
<dc:title><![CDATA[A sex difference in the composition of the rodent postsynaptic density]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/800011v1?rss=1">
<title>
<![CDATA[
Multi-model functionalization of disease-associated PTEN missense mutations identifies multiple molecular mechanisms underlying protein dysfunction 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/800011v1?rss=1"
</link>
<description><![CDATA[
Functional variomics provides the foundation for personalized medicine by linking genetic variation to disease expression, outcome and treatment, yet its utility is dependent on appropriate assays to evaluate mutation impact on protein function. To fully assess the effects of 106 missense and nonsense variants of PTEN associated with autism spectrum disorder, somatic cancer and PHTS, we take a deep phenotypic profiling approach using 18 assays in 5 model systems spanning diverse cellular environments ranging from molecular function to neuronal morphogenesis and behavior. Variants inducing instability occurred across the protein, resulting in partial to complete loss of function (LoF), which was well correlated across models. However, assays were selectively sensitive to variants located in substrate binding and catalytic domains, which exhibited complete LoF or dominant negativity independent of effects on stability. Our results indicate that full characterization of variant impact requires assays sensitive to instability and a range of protein functions.
]]></description>
<dc:creator>Post, K. L.</dc:creator>
<dc:creator>Belmadani, M.</dc:creator>
<dc:creator>Ganguly, P.</dc:creator>
<dc:creator>Meili, F.</dc:creator>
<dc:creator>Dingwall, R.</dc:creator>
<dc:creator>McDiarmid, T. A.</dc:creator>
<dc:creator>Meyers, W. M.</dc:creator>
<dc:creator>Herrington, C.</dc:creator>
<dc:creator>Young, B. P.</dc:creator>
<dc:creator>Callaghan, D. B.</dc:creator>
<dc:creator>Rogic, S.</dc:creator>
<dc:creator>Edwards, M.</dc:creator>
<dc:creator>Niciforovic, A.</dc:creator>
<dc:creator>Cau, A.</dc:creator>
<dc:creator>Rankin, C.</dc:creator>
<dc:creator>OConnor, T. P.</dc:creator>
<dc:creator>Bamji, S. X.</dc:creator>
<dc:creator>Loewen, C. J.</dc:creator>
<dc:creator>Allan, D. W.</dc:creator>
<dc:creator>Pavlidis, P.</dc:creator>
<dc:creator>Haas, K.</dc:creator>
<dc:date>2019-10-10</dc:date>
<dc:identifier>doi:10.1101/800011</dc:identifier>
<dc:title><![CDATA[Multi-model functionalization of disease-associated PTEN missense mutations identifies multiple molecular mechanisms underlying protein dysfunction]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/798025v1?rss=1">
<title>
<![CDATA[
Acute and repeated intranasal oxytocin differentially modulate brain-wide functional connectivity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/798025v1?rss=1"
</link>
<description><![CDATA[
Central release of the neuropeptide oxytocin (OXT) modulates neural substrates involved in socio-affective behavior. This property has prompted research into the use of intranasal OXT administration as an adjunctive therapy for brain conditions characterized by social impairment, such as autism spectrum disorders (ASD). However, the neural circuitry and brain-wide functional networks recruited by intranasal OXT administration remain elusive. Moreover, little is known of the neuroadaptive cascade triggered by long-term administration of this peptide at the network level. To address these questions, we applied fMRI-based circuit mapping in adult mice upon acute and repeated (seven-day) intranasal dosing of OXT. We report that acute and chronic OXT administration elicit comparable fMRI activity as assessed with cerebral blood volume mapping, but entail largely different patterns of brain-wide functional connectivity. Specifically, acute OXT administration focally boosted connectivity within key limbic components of the rodent social brain, whereas repeated dosing led to a prominent and widespread increase in functional connectivity, involving a strong coupling between the amygdala and extended cortical territories. Importantly, this connectional reconfiguration was accompanied by a paradoxical reduction in social interaction and communication in wild-type mice. Our results identify the network substrates engaged by exogenous OXT administration, and show that repeated OXT dosing leads to a substantial reconfiguration of brain-wide connectivity, entailing an aberrant functional coupling between cortico-limbic structures involved in socio-communicative and affective functions. Such divergent patterns of network connectivity might contribute to discrepant clinical findings involving acute or long-term OXT dosing in clinical populations.
]]></description>
<dc:creator>Pagani, M.</dc:creator>
<dc:creator>De Felice, A.</dc:creator>
<dc:creator>Montani, C.</dc:creator>
<dc:creator>Galbusera, A.</dc:creator>
<dc:creator>Papaleo, F.</dc:creator>
<dc:creator>Gozzi, A.</dc:creator>
<dc:date>2019-10-09</dc:date>
<dc:identifier>doi:10.1101/798025</dc:identifier>
<dc:title><![CDATA[Acute and repeated intranasal oxytocin differentially modulate brain-wide functional connectivity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/801449v1?rss=1">
<title>
<![CDATA[
Genetic Rescue of Fragile X Syndrome Links FMRP Deficiency to Codon Optimality-Dependent RNA Destabilization 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/801449v1?rss=1"
</link>
<description><![CDATA[
Fragile X syndrome (FXS) is caused by inactivation of the FMR1 gene and loss of encoded FMRP, an RNA binding protein that represses translation of some of its target transcripts. Here we use ribosome profiling and RNA-seq to investigate the dysregulation of translation in the mouse brain cortex. We find that most changes in ribosome occupancy on hundreds of mRNAs are largely driven by dysregulation in transcript abundance. Many downregulated mRNAs, which are mostly responsible for neuronal and synaptic functions, are highly enriched for FMRP binding targets. RNA metabolic labeling demonstrates that in FMRP-deficient cortical neurons, mRNA downregulation is caused by elevated degradation, and is correlated with codon optimality. Moreover, FMRP preferentially binds mRNAs with optimal codons, suggesting that it stabilizes such transcripts through direct interactions via the translational machinery. Finally, we show that the paradigm of genetic rescue of FXS-like phenotypes in FMRP-deficient mice by deletion of the Cpeb1 gene is mediated by restoration of steady state RNA levels and consequent rebalancing of translational homeostasis. Our data establish an essential role of FMRP in codon optimality-dependent mRNA stability as an important factor in FXS.
]]></description>
<dc:creator>Shu, H. R.</dc:creator>
<dc:creator>Donnard, E.</dc:creator>
<dc:creator>Liu, B.</dc:creator>
<dc:creator>Richter, J.</dc:creator>
<dc:date>2019-10-10</dc:date>
<dc:identifier>doi:10.1101/801449</dc:identifier>
<dc:title><![CDATA[Genetic Rescue of Fragile X Syndrome Links FMRP Deficiency to Codon Optimality-Dependent RNA Destabilization]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/578674v1?rss=1">
<title>
<![CDATA[
An open resource of structural variation for medical and population genetics 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/578674v1?rss=1"
</link>
<description><![CDATA[
Structural variants (SVs) rearrange large segments of the genome and can have profound consequences for evolution and human diseases. As national biobanks, disease association studies, and clinical genetic testing grow increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD) have become integral for interpreting genetic variation. To date, no large-scale reference maps of SVs exist from high-coverage sequencing comparable to those available for point mutations in protein-coding genes. Here, we constructed a reference atlas of SVs across 14,891 genomes from diverse global populations (54% non-European) as a component of gnomAD. We discovered a rich landscape of 433,371 distinct SVs, including 5,295 multi-breakpoint complex SVs across 11 mutational subclasses, and examples of localized chromosome shattering, as in chromothripsis. The average individual harbored 7,439 SVs, which accounted for 25-29% of all rare protein-truncating events per genome. We found strong correlations between constraint against damaging point mutations and rare SVs that both disrupt and duplicate protein-coding sequence, suggesting intolerance to reciprocal dosage alterations for a subset of tightly regulated genes. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than any effect on noncoding SVs. Finally, we benchmarked carrier rates for medically relevant SVs, finding very large ([&ge;]1Mb) rare SVs in 3.8% of genomes (~1:26 individuals) and clinically reportable incidental SVs in 0.18% of genomes (~1:556 individuals). These data have been integrated directly into the gnomAD browser (https://gnomad.broadinstitute.org) and will have broad utility for population genetics, disease association, and diagnostic screening.
]]></description>
<dc:creator>Collins, R. L.</dc:creator>
<dc:creator>Brand, H.</dc:creator>
<dc:creator>Karczewski, K. J.</dc:creator>
<dc:creator>Zhao, X.</dc:creator>
<dc:creator>Alflödi, J.</dc:creator>
<dc:creator>Khera, A. V.</dc:creator>
<dc:creator>Francioli, L. C.</dc:creator>
<dc:creator>Gauthier, L. D.</dc:creator>
<dc:creator>Wang, H.</dc:creator>
<dc:creator>Watts, N. A.</dc:creator>
<dc:creator>Solomonson, M.</dc:creator>
<dc:creator>O'Donnell-Luria, A.</dc:creator>
<dc:creator>Baumann, A.</dc:creator>
<dc:creator>Munshi, R.</dc:creator>
<dc:creator>Lowther, C.</dc:creator>
<dc:creator>Walker, M.</dc:creator>
<dc:creator>Whelan, C.</dc:creator>
<dc:creator>Huang, Y.</dc:creator>
<dc:creator>Brookings, T.</dc:creator>
<dc:creator>Sharpe, T.</dc:creator>
<dc:creator>Stone, M. R.</dc:creator>
<dc:creator>Valkanas, E.</dc:creator>
<dc:creator>Fu, J.</dc:creator>
<dc:creator>Tiao, G.</dc:creator>
<dc:creator>Laricchia, K. M.</dc:creator>
<dc:creator>Stevens, C.</dc:creator>
<dc:creator>Gupta, N.</dc:creator>
<dc:creator>Margolin, L.</dc:creator>
<dc:creator>The Genome Aggregation Database (gnomAD) Productio,</dc:creator>
<dc:creator>The gnomAD Consortium,</dc:creator>
<dc:creator>Spertus, J. A.</dc:creator>
<dc:creator>Taylor, K. D.</dc:creator>
<dc:creator>Lin, H. J.</dc:creator>
<dc:creator>Rich, S. S.</dc:creator>
<dc:creator>Post, W.</dc:creator>
<dc:creator>Chen, Y.-D. I.</dc:creator>
<dc:creator>Rotter, J. I.</dc:creator>
<dc:creator>Nusbaum, C.</dc:creator>
<dc:creator>Philippakis, A.</dc:creator>
<dc:creator>Lander, E</dc:creator>
<dc:date>2019-03-14</dc:date>
<dc:identifier>doi:10.1101/578674</dc:identifier>
<dc:title><![CDATA[An open resource of structural variation for medical and population genetics]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/808006v1?rss=1">
<title>
<![CDATA[
Dynamic preferences account for inter-animal variability during the continual learning of a cognitive task 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/808006v1?rss=1"
</link>
<description><![CDATA[
Individual animals perform tasks in different ways, yet the nature and origin of that variability is poorly understood. In the context of spatial memory tasks, variability is often interpreted as resulting from differences in memory ability, but the validity of this interpretation is seldom tested since we lack a systematic approach for identifying and understanding factors that make one animals behavior different than another. Here we identify such factors in the context of spatial alternation in rats, a task often described as relying solely on memory of past choices. We combine hypothesis-driven behavioral design and reinforcement learning modeling to identify spatial preferences that, when combined with memory, support learning of a spatial alternation task. Identifying these preferences allows us to capture differences among animals, including differences in overall learning ability. Our results show that to understand the complexity of behavior requires quantitative accounts of the preferences of each animal.
]]></description>
<dc:creator>Kastner, D. B.</dc:creator>
<dc:creator>Miller, E. A.</dc:creator>
<dc:creator>Yang, Z.</dc:creator>
<dc:creator>Roumis, D. K.</dc:creator>
<dc:creator>Liu, D. F.</dc:creator>
<dc:creator>Frank, L. M.</dc:creator>
<dc:creator>Dayan, P.</dc:creator>
<dc:date>2019-10-17</dc:date>
<dc:identifier>doi:10.1101/808006</dc:identifier>
<dc:title><![CDATA[Dynamic preferences account for inter-animal variability during the continual learning of a cognitive task]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/824151v1?rss=1">
<title>
<![CDATA[
MEF2C hypofunction in neuronal and neuroimmune populations cooperate to produce MEF2C haploinsufficiency syndrome-like behaviors in mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/824151v1?rss=1"
</link>
<description><![CDATA[
Microdeletions of the MEF2C gene are linked to a syndromic form of autism termed MEF2C haploinsufficiency syndrome (MCHS). Here, we show that MCHS-associated missense mutations cluster in the conserved DNA binding domain and disrupt MEF2C DNA binding. DNA binding-deficient global Mef2c heterozygous mice (Mef2c-Het) display numerous MCHS-like behaviors, including autism-related behaviors, as well as deficits in cortical excitatory synaptic transmission. We find that hundreds of genes are dysregulated in Mef2c-Het cortex, including significant enrichments of autism risk and excitatory neuron genes. In addition, we observe an enrichment of upregulated microglial genes, but not due to neuroinflammation in the Mef2c-Het cortex. Importantly, conditional Mef2c heterozygosity in forebrain excitatory neurons reproduces a subset of the Mef2c-Het phenotypes, while conditional Mef2c heterozygosity in microglia reproduces social deficits and repetitive behavior. Together our findings suggest that MEF2C regulates typical brain development and function through multiple cell types, including excitatory neuronal and neuroimmune populations.
]]></description>
<dc:creator>Harrington, A. J.</dc:creator>
<dc:creator>Bridges, C. M.</dc:creator>
<dc:creator>Blankenship, K.</dc:creator>
<dc:creator>Assali, A.</dc:creator>
<dc:creator>Berto, S.</dc:creator>
<dc:creator>Siemsen, B. M.</dc:creator>
<dc:creator>Moore, H. W.</dc:creator>
<dc:creator>Cho, J. Y.</dc:creator>
<dc:creator>Tsvetkov, E.</dc:creator>
<dc:creator>Thielking, A.</dc:creator>
<dc:creator>Konopka, G.</dc:creator>
<dc:creator>Everman, D. B.</dc:creator>
<dc:creator>Scofield, M.</dc:creator>
<dc:creator>Skinner, S. A.</dc:creator>
<dc:creator>Cowan, C. W.</dc:creator>
<dc:date>2019-10-30</dc:date>
<dc:identifier>doi:10.1101/824151</dc:identifier>
<dc:title><![CDATA[MEF2C hypofunction in neuronal and neuroimmune populations cooperate to produce MEF2C haploinsufficiency syndrome-like behaviors in mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/835678v1?rss=1">
<title>
<![CDATA[
Transcriptome-wide transmission disequilibrium analysis identifies novel risk genes for autism spectrum disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/835678v1?rss=1"
</link>
<description><![CDATA[
Recent advances in consortium-scale genome-wide association studies (GWAS) have highlighted the involvement of common genetic variants in autism spectrum disorder (ASD), but our understanding of their etiologic roles, especially the interplay with rare variants, is incomplete. In this work, we introduce an analytical framework to quantify the transmission disequilibrium of genetically regulated gene expression from parents to offspring. We applied this framework to conduct a transcriptome-wide association study (TWAS) on 7,805 ASD proband-parent trios, and replicated our findings using 35,740 independent samples. We identified 31 associations at the transcriptome-wide significance level. In particular, we identified POU3F2 (p=2.1e-7), a transcription factor (TF) mainly expressed in developmental brain. TF targets regulated by POU3F2 showed a 2.1-fold enrichment for known ASD genes (p=4.6e-5) and a 2.7-fold enrichment for loss-of-function de novo mutations in ASD probands (p=7.1e-5). These results provide a clear example of the connection between ASD genes affected by very rare mutations and an unlinked key regulator affected by common genetic variations.
]]></description>
<dc:creator>Huang, K.</dc:creator>
<dc:creator>Wu, Y.</dc:creator>
<dc:creator>Shin, J.</dc:creator>
<dc:creator>Zheng, Y.</dc:creator>
<dc:creator>Fotuhi Siahpirani, A.</dc:creator>
<dc:creator>Lin, Y.</dc:creator>
<dc:creator>Ni, Z.</dc:creator>
<dc:creator>Chen, J.</dc:creator>
<dc:creator>You, J.</dc:creator>
<dc:creator>Keles, S.</dc:creator>
<dc:creator>Wang, D.</dc:creator>
<dc:creator>Roy, S.</dc:creator>
<dc:creator>Lu, Q.</dc:creator>
<dc:date>2019-11-08</dc:date>
<dc:identifier>doi:10.1101/835678</dc:identifier>
<dc:title><![CDATA[Transcriptome-wide transmission disequilibrium analysis identifies novel risk genes for autism spectrum disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/803015v1?rss=1">
<title>
<![CDATA[
G-Graph: An interactive genomic graph viewer 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/803015v1?rss=1"
</link>
<description><![CDATA[
MotivationEffective and efficient exploration of numeric data and annotations as a function of genomic position requires specialized software.

ResultsWe present G-Graph, an interactive genomic scatter plot viewer. G-Graph stacks or tiles multiple data series in one graph using different colors and markers. It displays gene annotation and other metadata, allows easy changes to the appearance of data series, implements stack-based undo functionality, and saves user-selected application views as image and pdf files. G-Graph delivers smooth and rapid scrolling and zooming even for datasets with millions of points and line segments. The primary target user is a researcher examining many copy number profiles to identify potentially deleterious variants. G-Graph runs under Linux, Mac OSX and Windows.

Availabilityhttps://github.com/docpaa/mumdex/ or https://mumdex.com/ggraph/

Contactandrewsp@cshl.edu (or paa@drpa.us)
]]></description>
<dc:creator>Andrews, P. A.</dc:creator>
<dc:creator>Alexander, J.</dc:creator>
<dc:creator>Kendall, J.</dc:creator>
<dc:creator>Wigler, M.</dc:creator>
<dc:date>2019-11-18</dc:date>
<dc:identifier>doi:10.1101/803015</dc:identifier>
<dc:title><![CDATA[G-Graph: An interactive genomic graph viewer]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/862680v1?rss=1">
<title>
<![CDATA[
Multiplexed single-cell autism modeling reveals convergent mechanisms altering neuronal differentiation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/862680v1?rss=1"
</link>
<description><![CDATA[
The overwhelming success of exome- and genome-wide association studies in discovering thousands of disease-associated genes necessitates novel high-throughput functional genomics approaches to elucidate the mechanisms of these genes. Here, we have coupled multiplexed repression of neurodevelopmental disease-associated genes to single-cell transcriptional profiling in differentiating human neurons to rapidly assay the functions of multiple genes in a disease-relevant context, assess potentially convergent mechanisms, and prioritize genes for specific functional assays. For a set of 13 autism spectrum disorder (ASD) associated genes, we demonstrate that this approach generated important mechanistic insights, revealing two functionally convergent modules of ASD genes: one that delays neuron differentiation and one that accelerates it. Five genes that delay neuron differentiation (ADNP, ARID1B, ASH1L, CHD2, and DYRK1A) mechanistically converge, as they all dysregulate genes involved in cell-cycle control and progenitor cell proliferation. Live-cell imaging after individual ASD gene repression validated this functional module, confirming that these genes reduce neural progenitor cell proliferation and neurite growth. Finally, these functionally convergent ASD gene modules predicted shared clinical phenotypes among individuals with mutations in these genes. Altogether these results demonstrate the utility of a novel and simple approach for the rapid functional elucidation of neurodevelopmental disease-associated genes.
]]></description>
<dc:creator>Lalli, M. A.</dc:creator>
<dc:creator>Avey, D.</dc:creator>
<dc:creator>Dougherty, J. D.</dc:creator>
<dc:creator>Milbrandt, J.</dc:creator>
<dc:creator>Mitra, R. D.</dc:creator>
<dc:date>2019-12-03</dc:date>
<dc:identifier>doi:10.1101/862680</dc:identifier>
<dc:title><![CDATA[Multiplexed single-cell autism modeling reveals convergent mechanisms altering neuronal differentiation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/852673v1?rss=1">
<title>
<![CDATA[
Massively parallel disruption of enhancers active during human corticogenesis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/852673v1?rss=1"
</link>
<description><![CDATA[
Changes in gene regulation have been linked to the expansion of the human cerebral cortex and to neurodevelopmental disorders. However, the biological effects of genetic variation within developmental regulatory elements on human corticogenesis are not well understood. We used sgRNA-Cas9 genetic screens in human neural stem cells (hNSCs) to disrupt 10,674 expressed genes and 2,227 enhancers active in the developing human cortex and determine the resulting effects on cellular proliferation. Gene disruptions affecting proliferation were enriched for genes associated with risk for human neurodevelopmental phenotypes including primary microcephaly and autism spectrum disorder. Although disruptions in enhancers had overall weaker effects on proliferation than gene disruptions, we identified enhancer disruptions that severely perturbed hNSC self-renewal. Disruptions in Human Accelerated Regions and Human Gain Enhancers, regulatory elements implicated in the evolution of the human brain, also perturbed hNSC proliferation, establishing a role for these elements in human neurodevelopment. Integrating proliferation phenotypes with chromatin interaction maps revealed regulatory relationships between enhancers and target genes that contribute to neurogenesis and potentially to human cortical evolution.
]]></description>
<dc:creator>Geller, E.</dc:creator>
<dc:creator>Gockley, J.</dc:creator>
<dc:creator>Emera, D.</dc:creator>
<dc:creator>Uebbing, S.</dc:creator>
<dc:creator>Cotney, J.</dc:creator>
<dc:creator>Noonan, J. P.</dc:creator>
<dc:date>2019-12-02</dc:date>
<dc:identifier>doi:10.1101/852673</dc:identifier>
<dc:title><![CDATA[Massively parallel disruption of enhancers active during human corticogenesis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/862615v1?rss=1">
<title>
<![CDATA[
Neuropsychiatric mutations delineate functional brain connectivity dimensions contributing to autism and schizophrenia 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/862615v1?rss=1"
</link>
<description><![CDATA[
16p11.2 and 22q11.2 Copy Number Variants (CNVs) confer high risk for Autism Spectrum Disorder (ASD), schizophrenia (SZ), and Attention-Deficit-Hyperactivity-Disorder (ADHD), but their impact on functional connectivity (FC) remains unclear.

We analyzed resting-state functional magnetic resonance imaging data from 101 CNV carriers, 755 individuals with idiopathic ASD, SZ, or ADHD and 1,072 controls. We used CNV FC-signatures to identify dimensions contributing to complex idiopathic conditions.

CNVs had large mirror effects on FC at the global and regional level. Thalamus, somatomotor, and posterior insula regions played a critical role in dysconnectivity shared across deletions, duplications, idiopathic ASD, SZ but not ADHD. Individuals with higher similarity to deletion FC-signatures exhibited worse cognitive and behavioral symptoms. Deletion similarities identified at the connectivity level could be related to the redundant associations observed genome-wide between gene expression spatial patterns and FC-signatures. Results may explain why many CNVs affect a similar range of neuropsychiatric symptoms.
]]></description>
<dc:creator>Moreau, C.</dc:creator>
<dc:creator>Urchs, S.</dc:creator>
<dc:creator>Orban, P.</dc:creator>
<dc:creator>Schramm, C.</dc:creator>
<dc:creator>Dumas, G.</dc:creator>
<dc:creator>Labbe, A.</dc:creator>
<dc:creator>Huguet, G.</dc:creator>
<dc:creator>Douard, E.</dc:creator>
<dc:creator>Quirion, P.-O.</dc:creator>
<dc:creator>Lin, A.</dc:creator>
<dc:creator>Kushan, L.</dc:creator>
<dc:creator>Grot, S.</dc:creator>
<dc:creator>Luck, D.</dc:creator>
<dc:creator>Mendrek, A.</dc:creator>
<dc:creator>Potvin, S.</dc:creator>
<dc:creator>Stip, E.</dc:creator>
<dc:creator>Bourgeron, T.</dc:creator>
<dc:creator>Evans, A. C.</dc:creator>
<dc:creator>SimonsVIP Consortium,</dc:creator>
<dc:creator>Bearden, C. E.</dc:creator>
<dc:creator>Bellec, P.</dc:creator>
<dc:creator>Jacquemont, S.</dc:creator>
<dc:date>2019-12-06</dc:date>
<dc:identifier>doi:10.1101/862615</dc:identifier>
<dc:title><![CDATA[Neuropsychiatric mutations delineate functional brain connectivity dimensions contributing to autism and schizophrenia]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2019.12.28.890004v1?rss=1">
<title>
<![CDATA[
Increased variability but intact integration during visual navigation in Autism Spectrum Disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2019.12.28.890004v1?rss=1"
</link>
<description><![CDATA[
Autism Spectrum Disorder (ASD) is a common neurodevelopmental disturbance afflicting a variety of functions from perception to cognition. The recent computational focus suggesting aberrant Bayesian inference in ASD has yielded promising but conflicting results in attempting to explain a wide variety of phenotypes by canonical computations. Here we used a naturalistic visual path integration task that combines continuous action with active sensing and allows tracking of subjects dynamic belief states. Both groups showed a previously documented bias pattern, by overshooting the radial distance and angular eccentricity of targets. For both control and ASD groups, these errors were driven by misestimated velocity signals due to a non-uniform speed prior, rather than imperfect integration. We tracked participants beliefs and found no difference in the speed prior, but heightened variability in the ASD group. Both end-point variance and trajectory irregularities correlated with ASD symptom severity. With feedback, variance was reduced and ASD performance approached that of controls. These findings highlight the need for both more naturalistic tasks and a broader computational perspective to understand the ASD phenotype and pathology.
]]></description>
<dc:creator>Noel, J.-P.</dc:creator>
<dc:creator>Lakshminarasimhan, K. J.</dc:creator>
<dc:creator>Park, H.</dc:creator>
<dc:creator>Angelaki, D.</dc:creator>
<dc:date>2019-12-28</dc:date>
<dc:identifier>doi:10.1101/2019.12.28.890004</dc:identifier>
<dc:title><![CDATA[Increased variability but intact integration during visual navigation in Autism Spectrum Disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2019.12.31.891036v1?rss=1">
<title>
<![CDATA[
Regulation of Prefrontal Patterning, Connectivity and Synaptogenesis by Retinoic Acid 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2019.12.31.891036v1?rss=1"
</link>
<description><![CDATA[
The prefrontal cortex (PFC) and its reciprocal connections with the mediodorsal thalamus (MD) are crucial for cognitive flexibility and working memory1-4 and are thought to be altered in several disorders such as autism spectrum disorder5, 6 and schizophrenia6-9. While developmental mechanisms governing regional patterning of the rodent cerebral cortex have been characterized10-15, the mechanisms underlying the development of PFC-MD connectivity and the lateral expansion of PFC with distinct granular layer 4 in anthropoid primates16-23 have not been elucidated. Here we report increased concentration of retinoic acid (RA), a signaling molecule involved in brain development and function24, 25 in the prospective PFC areas of human and macaque, compared to mouse, during mid-fetal development, a crucial period for cortical circuit assembly. In addition, we observed the lateral expansion of RA synthesizing enzyme, ALDH1A3, expression in mid-fetal macaque and human frontal cortex, compared to mouse. Furthermore, we found that enrichment of RA signaling is restricted to the prospective PFC by CYP26B1, a gene encoding an RA-catabolizing enzyme upregulated in the mid-fetal motor cortex. Gene deletion in mice revealed that RA signaling through anteriorly upregulated RA receptors, Rxrg and Rarb, and Cyp26b1-dependent catabolism is required for the proper molecular patterning of PFC and motor areas, the expression of the layer 4 marker RORB, intra-PFC synaptogenesis, and the development of reciprocal PFC-MD connectivity. Together, these findings reveal a critical role for RA signaling in PFC development and, potentially, its evolutionary expansion.
]]></description>
<dc:creator>Shibata, M.</dc:creator>
<dc:creator>Pattabiraman, K.</dc:creator>
<dc:creator>Lorente-Galdos, B.</dc:creator>
<dc:creator>Andreijevic, D.</dc:creator>
<dc:creator>Xing, X.</dc:creator>
<dc:creator>Sousa, A. M. M.</dc:creator>
<dc:creator>Santpere, G.</dc:creator>
<dc:creator>Sestan, N.</dc:creator>
<dc:date>2019-12-31</dc:date>
<dc:identifier>doi:10.1101/2019.12.31.891036</dc:identifier>
<dc:title><![CDATA[Regulation of Prefrontal Patterning, Connectivity and Synaptogenesis by Retinoic Acid]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.01.03.894014v1?rss=1">
<title>
<![CDATA[
The stability flexibility tradeoff and the dark side of detail 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.01.03.894014v1?rss=1"
</link>
<description><![CDATA[
Learning in dynamic environments requires integrating over stable fluctuations to minimize the impact of noise (stability) but rapidly responding in the face of fundamental changes (flexibility). Achieving one of these goals often requires sacrificing the other to some degree, producing a stability-flexibility tradeoff. Individuals navigate this tradeoff in different ways, with some people learning rapidly (emphasizing flexibility) and others relying more heavily on historical information (emphasizing stability). Despite the prominence of such individual differences in learning tasks, the degree to which they relate to broader characteristics of real-world behavior or pathologies has not been well explored. Here we relate individual differences in learning behavior to self-report measures thought to collectively capture characteristics of the Autism spectrum. We show that that young adults who learn most slowly tend to integrate more effective samples into their beliefs about the world making them more robust to noise (more stability), but are more likely to integrate information from previous contexts (less flexibility). We show that individuals who report paying more attention to detail tend to use high flexibility and low stability information processing strategies. We demonstrate the robustness of this inverse relationship between attention to detail and formation of stable beliefs in a heterogeneous population of children that includes a high proportion of Autism diagnoses. Together, our results highlight that attention to detail reflects an information processing policy that comes with a substantial downside, namely the ability to integrate data to overcome environmental noise.
]]></description>
<dc:creator>Nassar, M. R.</dc:creator>
<dc:creator>Troiani, V.</dc:creator>
<dc:date>2020-01-03</dc:date>
<dc:identifier>doi:10.1101/2020.01.03.894014</dc:identifier>
<dc:title><![CDATA[The stability flexibility tradeoff and the dark side of detail]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-01-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/801076v1?rss=1">
<title>
<![CDATA[
FMRP Control of Ribosome Translocation Promotes Chromatin Modifications and Alternative Splicing of Neuronal Genes Linked to Autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/801076v1?rss=1"
</link>
<description><![CDATA[
Silencing of FMR1 and loss of its gene product FMRP results in Fragile X Syndrome. FMRP binds brain mRNAs and inhibits polypeptide elongation. Using ribosome profiling of the hippocampus, we find that ribosome footprint levels in Fmr1-deficient tissue mostly reflect changes in RNA abundance. Profiling over a time course of ribosome runoff in wildtype tissue reveals a wide range of ribosome translocation rates; on many mRNAs, the ribosomes are stalled. Sucrose gradient ultracentrifugation of hippocampal slices after ribosome runoff reveals that FMRP co-sediments with stalled ribosomes; and its loss results in decline of ribosome stalling on specific mRNAs. One such mRNA encodes SETD2, a lysine methyltransferase that catalyzes H3K36me3. ChIP-Seq demonstrates that loss of FMRP alters the deployment of this epigenetic mark on chromatin. H3K36me3 is associated with alternative pre-RNA processing, which we find occurs in an FMRP-dependent manner on transcripts linked to neural function and autism spectrum disorders.

Highlights- Loss of FMRP results in decline of ribosome stalling on specific mRNAs (eg., SETD2)
- Increased SETD2 protein levels alter H3K36me3 marks in FMRP deficient hippocampus
- Genome-wide changes in mRNA alternative splicing occur in FMRP deficient hippocampus
- H3K36me3 marks and alternative splicing changes occur on transcripts linked to autism
]]></description>
<dc:creator>Richter, J.</dc:creator>
<dc:creator>Huber, K.</dc:creator>
<dc:creator>Shah, S.</dc:creator>
<dc:creator>Molinaro, G.</dc:creator>
<dc:creator>Liu, B.</dc:creator>
<dc:creator>Wang, R.</dc:creator>
<dc:date>2019-10-10</dc:date>
<dc:identifier>doi:10.1101/801076</dc:identifier>
<dc:title><![CDATA[FMRP Control of Ribosome Translocation Promotes Chromatin Modifications and Alternative Splicing of Neuronal Genes Linked to Autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.01.16.909531v1?rss=1">
<title>
<![CDATA[
Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.01.16.909531v1?rss=1"
</link>
<description><![CDATA[
Excitation-inhibition (E:I) imbalance is theorized as an important pathophysiological mechanism in autism. Autism affects males more frequently than females and sex-related mechanisms (e.g., X-linked genes, androgen hormones) can influence E:I balance. This suggests that E:I imbalance may affect autism differently in males versus females. With a combination of in-silico modeling and in-vivo chemogenetic manipulations in mice, we first show that a time-series metric estimated from fMRI BOLD signal, the Hurst exponent (H), can be an index for underlying change in the synaptic E:I ratio. In autism we find that H is reduced, indicating increased excitation, in the medial prefrontal cortex (MPFC) of autistic males but not females. Increasingly intact MPFC H is also associated with heightened ability to behaviorally camouflage social-communicative difficulties, but only in autistic females. This work suggests that H in BOLD can index synaptic E:I ratio and that E:I imbalance affects autistic males and females differently.
]]></description>
<dc:creator>Trakoshis, S.</dc:creator>
<dc:creator>Martinez-Canada, P.</dc:creator>
<dc:creator>Rocchi, F.</dc:creator>
<dc:creator>Canella, C.</dc:creator>
<dc:creator>You, W.</dc:creator>
<dc:creator>Chakrabarti, B.</dc:creator>
<dc:creator>Ruigrok, A. N.</dc:creator>
<dc:creator>Bullmore, E.</dc:creator>
<dc:creator>Suckling, J.</dc:creator>
<dc:creator>Markicevic, M.</dc:creator>
<dc:creator>Zerbi, V.</dc:creator>
<dc:creator>MRC AIMS Consortium,</dc:creator>
<dc:creator>Baron-Cohen, S.</dc:creator>
<dc:creator>Panzeri, S.</dc:creator>
<dc:creator>Gozzi, A.</dc:creator>
<dc:creator>Lai, M.-C.</dc:creator>
<dc:creator>Lombardo, M. V.</dc:creator>
<dc:date>2020-01-27</dc:date>
<dc:identifier>doi:10.1101/2020.01.16.909531</dc:identifier>
<dc:title><![CDATA[Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-01-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.01.31.927665v1?rss=1">
<title>
<![CDATA[
Homeostatic Plasticity Commonly Fails at the Intersection of Autism-Gene Mutations and a Novel Class of Common Phenotypic Modifier 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.01.31.927665v1?rss=1"
</link>
<description><![CDATA[
We identify a set of common phenotypic modifiers that interact with five independent autism gene orthologs (RIMS1, CHD8, CHD2, WDFY3, ASH1L) causing a common failure of presynaptic homeostatic plasticity (PHP). Heterozygous null mutations in each autism gene are demonstrated to have normal baseline neurotransmission and PHP. However, we find that PHP is sensitized and rendered prone to failure. A subsequent electrophysiology-based genetic screen identifies the first known heterozygous mutations that commonly genetically interact with multiple ASD gene orthologs, causing PHP to fail. Two phenotypic modifiers identified in the screen, PDPK1 and PPP2R5D, are characterized. Finally, transcriptomic, ultrastructural and electrophysiological analyses define one mechanism by which PHP fails; an unexpected, maladaptive up-regulation of CREG, a conserved, neuronally expressed, stress response gene and a novel repressor of PHP. Thus, we define a novel genetic landscape by which diverse, unrelated autism risk genes may converge to commonly affect the robustness of synaptic transmission.
]]></description>
<dc:creator>Genc, O.</dc:creator>
<dc:creator>An, J. Y.</dc:creator>
<dc:creator>Fetter, R. D.</dc:creator>
<dc:creator>Kulik, Y.</dc:creator>
<dc:creator>Zunino, G.</dc:creator>
<dc:creator>Sanders, S. J.</dc:creator>
<dc:creator>Davis, G. W.</dc:creator>
<dc:date>2020-01-31</dc:date>
<dc:identifier>doi:10.1101/2020.01.31.927665</dc:identifier>
<dc:title><![CDATA[Homeostatic Plasticity Commonly Fails at the Intersection of Autism-Gene Mutations and a Novel Class of Common Phenotypic Modifier]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-01-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.02.931337v1?rss=1">
<title>
<![CDATA[
The Oft-Overlooked Massively Parallel Reporter Assay: Where, When, and Which Psychiatric Genetic Variants are Functional? 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.02.931337v1?rss=1"
</link>
<description><![CDATA[
Neuropsychiatric phenotypes have been long known to be influenced by heritable risk factors. The past decade of genetic studies have confirmed this directly, revealing specific common and rare genetic variants enriched in disease cohorts. However, the early hope for these studies--that only a small set of genes would be responsible for a given disorder--proved false. The picture that has emerged is far more complex: a given disorder may be influenced by myriad coding and noncoding variants of small effect size, and/or by rare but severe variants of large effect size, many de novo. Noncoding genomic sequences harbor a large portion of these variants, the molecular functions of which cannot usually be inferred from sequence alone. This creates a substantial barrier to understanding the higher-order molecular and biological systems underlying disease risk. Fortunately, a proliferation of genetic technologies--namely, scalable oligonucleotide synthesis, high-throughput RNA sequencing, CRISPR, and CRISPR derivatives--have opened novel avenues to experimentally identify biologically significant variants en masse. These advances have yielded an especially versatile technique adaptable to large-scale functional assays of variation in both untranscribed and untranslated regulatory features: Massively Parallel Reporter Assays (MPRAs). MPRAs are powerful molecular genetic tools that can be used to screen tens of thousands of predefined sequences for functional effects in a single experiment. This approach has several ideal features for psychiatric genetics, but remains underutilized in the field to date. To emphasize the opportunities MPRA holds for dissecting psychiatric polygenicity, we review here its applications in the literature, discuss its ability to test several biological variables implicated in psychiatric disorders, illustrate this flexibility with a proof-of-principle, in vivo cell-type specific implementation of the assay, and envision future outcomes of applying MPRA to both computational and experimental neurogenetics.
]]></description>
<dc:creator>Mulvey, B.</dc:creator>
<dc:creator>Lagunas, T.</dc:creator>
<dc:creator>Dougherty, J. D.</dc:creator>
<dc:date>2020-02-03</dc:date>
<dc:identifier>doi:10.1101/2020.02.02.931337</dc:identifier>
<dc:title><![CDATA[The Oft-Overlooked Massively Parallel Reporter Assay: Where, When, and Which Psychiatric Genetic Variants are Functional?]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.10.932327v1?rss=1">
<title>
<![CDATA[
Recent ultra-rare inherited mutations identify novel autism candidate risk genes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.10.932327v1?rss=1"
</link>
<description><![CDATA[
Autism is a highly heritable, complex disorder where de novo mutation (DNM) variation contributes significantly to disease risk. Using whole-genome sequencing data from 3,474 families, we investigate another source of large-effect risk variation, ultra-rare mutations. We report and replicate a transmission disequilibrium of private likely-gene disruptive (LGD) mutations in probands but find that 95% of this burden resides outside of known DNM-enriched genes. This variant class more strongly affects multiplex family probands and supports a multi-hit model for autism. Candidate genes with private LGD variants preferentially transmitted to probands converge on the E3 ubiquitin-protein ligase complex, intracellular transport, and Erb signaling protein networks. We estimate these mutations are ~2.5 generations old and significantly younger than other mutations of similar type and frequency in siblings. Overall, private LGD variants are under strong purifying selection and act on a distinct set of genes not yet associated with autism.

One sentence summaryUltra-rare autism variants preferentially transmitted to probands are younger and identify distinct gene candidates and functional networks.
]]></description>
<dc:creator>Wilfert, A. B.</dc:creator>
<dc:creator>Turner, T. N.</dc:creator>
<dc:creator>Murali, S. C.</dc:creator>
<dc:creator>Hsieh, P.</dc:creator>
<dc:creator>Sulovari, A.</dc:creator>
<dc:creator>Wang, T.</dc:creator>
<dc:creator>Coe, B. P.</dc:creator>
<dc:creator>Guo, H.</dc:creator>
<dc:creator>Hoekzema, K.</dc:creator>
<dc:creator>Bakken, T. E.</dc:creator>
<dc:creator>Winterkorn, L. H.</dc:creator>
<dc:creator>Evani, U. S.</dc:creator>
<dc:creator>Byrska-Bishop, M.</dc:creator>
<dc:creator>Earl, R. K.</dc:creator>
<dc:creator>Bernier, R. A.</dc:creator>
<dc:creator>The SPARK Consortium,</dc:creator>
<dc:creator>Zody, M. C.</dc:creator>
<dc:creator>Eichler, E. E.</dc:creator>
<dc:date>2020-02-11</dc:date>
<dc:identifier>doi:10.1101/2020.02.10.932327</dc:identifier>
<dc:title><![CDATA[Recent ultra-rare inherited mutations identify novel autism candidate risk genes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.07.939256v1?rss=1">
<title>
<![CDATA[
Autism-linked Cullin3 germline haploinsufficiency impacts cytoskeletal dynamics and cortical neurogenesis through RhoA signaling 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.07.939256v1?rss=1"
</link>
<description><![CDATA[
E3-ubiquitin ligase Cullin3 (Cul3) is a high confidence risk gene for Autism Spectrum Disorder (ASD) and Developmental Delay (DD). To investigate how Cul3 mutations impact brain development, we generated haploinsufficient Cul3 mouse model using CRISPR/Cas9 genome engineering. Cul3 mutant mice exhibited social and cognitive deficits and hyperactive behavior. Brain MRI found decreased volume of cortical regions and changes in many other brain regions of Cul3 mutant mice starting from early postnatal development. Spatiotemporal transcriptomic and proteomic profiling of the brain implicated neurogenesis and cytoskeletal defects as key drivers of Cul3 functional impact. Specifically, dendritic growth, filamentous actin puncta, and spontaneous network activity were reduced in Cul3 mutant mice. Inhibition of small GTPase RhoA, a molecular substrate of Cul3 ligase, rescued dendrite length and network activity phenotypes. Our study identified neuronal cytoskeleton and Rho signaling as primary targets of Cul3 mutation during early brain development.
]]></description>
<dc:creator>Amar, M.</dc:creator>
<dc:creator>Pramod, A. B.</dc:creator>
<dc:creator>Herrera, V. M.</dc:creator>
<dc:creator>Yu, N.-K.</dc:creator>
<dc:creator>Qiu, L. R.</dc:creator>
<dc:creator>Zhang, P.</dc:creator>
<dc:creator>Moran-Losada, P.</dc:creator>
<dc:creator>Trujillo, C. A.</dc:creator>
<dc:creator>Ellegood, J.</dc:creator>
<dc:creator>Urresti, J.</dc:creator>
<dc:creator>Chau, K.</dc:creator>
<dc:creator>Diedrich, J.</dc:creator>
<dc:creator>Chen, J.</dc:creator>
<dc:creator>Gutierrez, J.</dc:creator>
<dc:creator>Sebat, J.</dc:creator>
<dc:creator>Ramanathan, D.</dc:creator>
<dc:creator>Lerch, J. P.</dc:creator>
<dc:creator>Yates, J. R.</dc:creator>
<dc:creator>Muotri, A. R.</dc:creator>
<dc:creator>Iakoucheva, L. M.</dc:creator>
<dc:date>2020-02-12</dc:date>
<dc:identifier>doi:10.1101/2020.02.07.939256</dc:identifier>
<dc:title><![CDATA[Autism-linked Cullin3 germline haploinsufficiency impacts cytoskeletal dynamics and cortical neurogenesis through RhoA signaling]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.26.966531v1?rss=1">
<title>
<![CDATA[
Natural selection influenced the genetic architecture of brain structure, behavioral and neuropsychiatric traits 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.26.966531v1?rss=1"
</link>
<description><![CDATA[
Natural selection has shaped the phenotypic characteristics of human populations. Genome-wide association studies (GWAS) have elucidated contributions of thousands of common variants with small effects on an individuals predisposition to complex traits (polygenicity), as well as wide-spread sharing of risk alleles across traits in the human phenome (pleiotropy). It remains unclear how the pervasive effects of natural selection influence polygenicity in brain-related traits. We investigate these effects by annotating the genome with measures of background (BGS) and positive selection, indications of Neanderthal introgression, measures of functional significance including loss-of-function (LoF) intolerant and genic regions, and genotype networks in 75 brain-related traits. Evidence of natural selection was determined using binary annotations of top 2%, 1%, and 0.5% of selection scores genome-wide. We detected enrichment (q<0.05) of SNP-heritability at loci with elevated BGS (7 phenotypes) and in genic (34 phenotypes) and LoF-intolerant regions (67 phenotypes). BGS (top 2%) significantly predicted effect size variance for trait-associated loci ({sigma}2 parameter) in 75 brain-related traits ({beta}=4.39x10-5, p=1.43x10-5, model r2=0.548). By including the number of DSM-5 diagnostic combinations per psychiatric disorder, we substantially improved model fit ({sigma}2 ~ BTop2% x Genic x diagnostic combinations; model r2=0.661). We show that GWAS with larger variance in risk locus effect sizes are collectively predicted by the effects of loci under strong BGS and in regulatory regions of the genome. We further show that diagnostic complexity exacerbates this relationship and perhaps dampens the ability to detect psychiatric risk loci.
]]></description>
<dc:creator>Wendt, F. R.</dc:creator>
<dc:creator>Pathak, G. A.</dc:creator>
<dc:creator>Overstreet, C.</dc:creator>
<dc:creator>Tylee, D. S.</dc:creator>
<dc:creator>Gelernter, J.</dc:creator>
<dc:creator>Atkinson, E. G.</dc:creator>
<dc:creator>Polimanti, R.</dc:creator>
<dc:date>2020-02-27</dc:date>
<dc:identifier>doi:10.1101/2020.02.26.966531</dc:identifier>
<dc:title><![CDATA[Natural selection influenced the genetic architecture of brain structure, behavioral and neuropsychiatric traits]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.04.974170v1?rss=1">
<title>
<![CDATA[
The contribution of de novo tandem repeat mutations to autism spectrum disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.04.974170v1?rss=1"
</link>
<description><![CDATA[
Autism Spectrum Disorder (ASD) is an early onset developmental disorder characterized by deficits in communication and social interaction and restrictive or repetitive behaviors1,2. Family studies demonstrate that ASD has a significant genetic basis3 with contributions both from inherited and de novo variants. While the majority of variance in liability to ASD is estimated to arise from common genetic variation4, it has been estimated that de novo mutations may contribute to 30% of all simplex cases, in which only a single child is affected per family5. Tandem repeats (TRs), consisting of approximately 1-20bp motifs repeated in tandem, comprise one of the largest sources of de novo mutations in humans6. Yet, largely due to technical challenges they present, de novo TR mutations have not yet been characterized on a genome-wide scale, and their contribution to ASD remains unexplored. Here, we develop novel bioinformatics tools for identifying and prioritizing de novo TR mutations from whole genome sequencing (WGS) data and use these to perform a genome-wide characterization of de novo TR mutations in ASD-affected probands and unaffected siblings. Compared to recent work on TRs in ASD7, we explicitly infer mutation events and their precise changes in repeat copy number, and primarily focus on more prevalent stepwise copy number changes rather than large or complex expansions. Our results demonstrate a significant genome-wide excess of TR mutations in ASD probands. TR mutations in probands tend to be larger, enriched in fetal brain regulatory regions, and predicted to be more evolutionarily deleterious compared to mutations observed in unaffected siblings. Overall, our results highlight the importance of considering repeat variants in future studies of de novo mutations.
]]></description>
<dc:creator>Mitra, I.</dc:creator>
<dc:creator>Mousavi, N.</dc:creator>
<dc:creator>Ma, N.</dc:creator>
<dc:creator>Lamkin, M.</dc:creator>
<dc:creator>Yanicky, R.</dc:creator>
<dc:creator>Shleizer-Burko, S.</dc:creator>
<dc:creator>Gymrek, M.</dc:creator>
<dc:date>2020-03-05</dc:date>
<dc:identifier>doi:10.1101/2020.03.04.974170</dc:identifier>
<dc:title><![CDATA[The contribution of de novo tandem repeat mutations to autism spectrum disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.04.976191v1?rss=1">
<title>
<![CDATA[
Aberrant Sensory Encoding in Patients with Autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.04.976191v1?rss=1"
</link>
<description><![CDATA[
Perceptual anomalies in patients with Autism Spectrum Disorder (ASD) have been attributed to irregularities in the Bayesian interpretation (i.e., decoding) of sensory information. Here we show that how sensory information is encoded and adapts to changing stimulus statistics also characteristically differs between healthy and ASD groups. In a visual estimation task, we extracted the accuracy of sensory encoding directly from psychophysical data, bypassing the decoding stage by using information theoretic measures. Initially, sensory representations in both groups reflected the statistics of visual orientations in natural scenes, but encoding capacity was overall lower in the ASD group. Exposure to an artificial statistical distribution of visual orientations altered the sensory representations of the control group toward the novel experimental statistics, while also increasing their total encoding resources. Neither total encoding resources nor their allocation changed significantly in the ASD group. Most interestingly, across both groups the adaptive re-allocation of encoding resources was correlated with subjects initial encoding capacity. These findings suggest that neural encoding resources are limited in ASD, and this limitation may explain their reduced perceptual flexibility.
]]></description>
<dc:creator>Noel, J.-P.</dc:creator>
<dc:creator>Zhang, L.-Q.</dc:creator>
<dc:creator>Stocker, A.</dc:creator>
<dc:creator>Angelaki, D.</dc:creator>
<dc:date>2020-03-05</dc:date>
<dc:identifier>doi:10.1101/2020.03.04.976191</dc:identifier>
<dc:title><![CDATA[Aberrant Sensory Encoding in Patients with Autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.14.992032v1?rss=1">
<title>
<![CDATA[
CHD8 Suppression Impacts on Histone H3 Lysine 36 Trimethylation and Alters RNA Alternative Splicing. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.14.992032v1?rss=1"
</link>
<description><![CDATA[
Disruptive mutations in the chromodomain helicase DNA binding protein 8 (CHD8) have been recurrently associated with Autism Spectrum Disorders (ASD). In normal cellular physiology, CHD8 co-purifies with MLL1 and MOF transcriptional activation complex, with elongating RNAPII and directly binds to DNA promoters and enhancers regions, thus a regulatory role in transcriptional initiation and elongation could be postulated.

Here we investigated how chromatin landscape reacts to CHD8 suppression by analyzing a panel of histone modifications in induced pluripotent stem cell-derived neural progenitors. We interrogated transcriptionally active and repressed regions, as well as active and poised enhancers.

CHD8 suppression led to significant reduction (47.82%) in histone H3K36me3 peaks at gene bodies, particularly impacting on transcriptional elongation chromatin states. H3K36me3 reduction specifically affects highly expressed, CHD8-bound genes. Histone H3K36me3 reduction associated to CHD8-suppression does not functionally impact on global transcriptional levels, but correlated with altered alternative splicing patterns of [~] 2000 protein coding genes implicated in "RNA splicing", "mitotic cell cycle phase transition" and "mRNA processing", especially affecting alternative first exon and exon skipping events.

In summary, our results point toward broad molecular consequences of CHD8 suppression, implicating altered histone deposition/maintenance and RNA processing regulation as important regulatory processes in ASD.
]]></description>
<dc:creator>Kerschbamer, E.</dc:creator>
<dc:creator>Tripathi, T.</dc:creator>
<dc:creator>Erdin, S.</dc:creator>
<dc:creator>Salviato, E.</dc:creator>
<dc:creator>Di Leva, F.</dc:creator>
<dc:creator>Sebestyen, E.</dc:creator>
<dc:creator>Arnoldi, M.</dc:creator>
<dc:creator>Benelli, M.</dc:creator>
<dc:creator>Gusella, J. F.</dc:creator>
<dc:creator>Piazza, S.</dc:creator>
<dc:creator>Demichelis, F.</dc:creator>
<dc:creator>Talkowski, M. E.</dc:creator>
<dc:creator>Ferrari, F.</dc:creator>
<dc:creator>Biagioli, M.</dc:creator>
<dc:date>2020-03-16</dc:date>
<dc:identifier>doi:10.1101/2020.03.14.992032</dc:identifier>
<dc:title><![CDATA[CHD8 Suppression Impacts on Histone H3 Lysine 36 Trimethylation and Alters RNA Alternative Splicing.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.21.053686v1?rss=1">
<title>
<![CDATA[
Multi-parametric analysis of 58 SYNGAP1 variants reveal impacts on GTPase signaling, localization and protein stability 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.21.053686v1?rss=1"
</link>
<description><![CDATA[
SYNGAP1 is a Ras and Rap GTPase with important roles in regulating excitatory synaptic plasticity. While many SYNGAP1 missense and nonsense mutations have been associated with intellectual disability, epilepsy, schizophrenia and autism spectrum disorder (ASD), there are many variants of unknown significance (VUS). In this report, we characterize 58 variants in nine assays that examine multiple aspects of SYNGAP1 function. Specifically, we used multiplex phospho-flow cytometry to measure the impact of variants on pERK, pGSK3{beta} and pCREB and high-content imaging to examine their subcellular localization. We find variants ranging from complete loss-of-function (LoF) to wildtype (WT)-like in their ability to regulate pERK and pGSK3{beta}, while all variants retain at least partial ability to regulate pCREB. Interestingly, our assays reveal that a high percentage of variants located within the disordered domain of unknown function that makes up the C-terminal half of SYNGAP1 exhibited LoF, compared to the more well studied catalytic domain. Moreover, we find protein instability to be a major contributor to dysfunction only for two missense variants both located within the catalytic domain. Using high-content imaging, we find variants with nuclear enrichment/exclusion and aberrant nuclear speckle localization. These variants are primarily located within the C2 domain known to mediate membrane lipid interactions. We find that mislocalization is distinct from altered catalytic activity, highlighting multiple independent molecular mechanisms underlying variant dysfunction. Our multidimensional dataset allows clustering of variants based on functional phenotypes and provides high-confidence pathogenicity classification.
]]></description>
<dc:creator>Meili, F.</dc:creator>
<dc:creator>Wei, W. J.</dc:creator>
<dc:creator>Sin, W.-C.</dc:creator>
<dc:creator>Dascalu, I.</dc:creator>
<dc:creator>Callaghan, D. B.</dc:creator>
<dc:creator>Rogic, S.</dc:creator>
<dc:creator>Meyers, W. M.</dc:creator>
<dc:creator>Pavlidis, P.</dc:creator>
<dc:creator>Haas, K.</dc:creator>
<dc:date>2020-04-22</dc:date>
<dc:identifier>doi:10.1101/2020.04.21.053686</dc:identifier>
<dc:title><![CDATA[Multi-parametric analysis of 58 SYNGAP1 variants reveal impacts on GTPase signaling, localization and protein stability]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-04-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.04.076034v1?rss=1">
<title>
<![CDATA[
Genoppi: an open-source software for robust and standardized integration of proteomic and genetic data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.04.076034v1?rss=1"
</link>
<description><![CDATA[
Combining genetic and cell-type-specific proteomic datasets can lead to new biological insights and therapeutic hypotheses, but a technical and statistical framework for such analyses is lacking. Here, we present an open-source computational tool called Genoppi that enables robust, standardized, and intuitive integration of quantitative proteomic results with genetic data. We used Genoppi to analyze sixteen cell-type-specific protein interaction datasets of four proteins (TDP-43, MDM2, PTEN, and BCL2) involved in cancer and neurological disease. Through systematic quality control of the data and integration with published protein interactions, we show a general pattern of both cell-type-independent and cell-type-specific interactions across three cancer and one human iPSC-derived neuronal type. Furthermore, through the integration of proteomic and genetic datasets in Genoppi, our results suggest that the neuron-specific interactions of these proteins are mediating their genetic involvement in neurodevelopmental and neurodegenerative diseases. Importantly, our analyses indicate that human iPSC-derived neurons are a relevant model system for studying the involvement of TDP-43 and BCL2 in amyotrophic lateral sclerosis.
]]></description>
<dc:creator>Pintacuda, G.</dc:creator>
<dc:creator>Lassen, F. H.</dc:creator>
<dc:creator>Hsu, Y.-H. H.</dc:creator>
<dc:creator>Kim, A.</dc:creator>
<dc:creator>Martin, J. M.</dc:creator>
<dc:creator>Malolepsza, E.</dc:creator>
<dc:creator>Lim, J. K.</dc:creator>
<dc:creator>Fornelos, N.</dc:creator>
<dc:creator>Eggan, K. C.</dc:creator>
<dc:creator>Lage, K.</dc:creator>
<dc:date>2020-05-05</dc:date>
<dc:identifier>doi:10.1101/2020.05.04.076034</dc:identifier>
<dc:title><![CDATA[Genoppi: an open-source software for robust and standardized integration of proteomic and genetic data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.14.093187v1?rss=1">
<title>
<![CDATA[
Cell-type-specific synaptic imbalance and disrupted homeostatic plasticity in cortical circuits of ASD-associated Chd8 haploinsufficient mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.14.093187v1?rss=1"
</link>
<description><![CDATA[
Heterozygous mutation of chromodomain helicase DNA binding protein 8 (CHD8) is strongly associated with autism spectrum disorder (ASD) and results in dysregulated expression of neurodevelopmental and synaptic genes during brain development. To reveal how these changes affect ASD-associated cortical circuits, we studied synaptic transmission in the prefrontal cortex of a haploinsufficient Chd8 mouse model. We report profound alterations to both excitatory and inhibitory synaptic transmission onto deep layer projection neurons, resulting in a reduced excitatory:inhibitory balance, which were found to vary dynamically across neurodevelopment and result from distinct effects of reduced Chd8 expression within individual neuronal subtypes. These changes were associated with disrupted regulation of homeostatic plasticity mechanisms operating via spontaneous neurotransmission. These findings therefore directly implicate CHD8 mutation in the disruption of ASD-relevant circuits in the cortex.
]]></description>
<dc:creator>Ellingford, R. A.</dc:creator>
<dc:creator>Rabeshala de Meritens, E.</dc:creator>
<dc:creator>Shaunak, R.</dc:creator>
<dc:creator>Naybour, L.</dc:creator>
<dc:creator>Basson, M. A.</dc:creator>
<dc:creator>Andreae, L. C.</dc:creator>
<dc:date>2020-05-14</dc:date>
<dc:identifier>doi:10.1101/2020.05.14.093187</dc:identifier>
<dc:title><![CDATA[Cell-type-specific synaptic imbalance and disrupted homeostatic plasticity in cortical circuits of ASD-associated Chd8 haploinsufficient mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.13.150201v1?rss=1">
<title>
<![CDATA[
Multitask learning on comorbid disorders improves gene risk prediction for Autism Spectrum Disorder and Intellectual Disability 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.13.150201v1?rss=1"
</link>
<description><![CDATA[
Autism Spectrum Disorder (ASD) and Intellectual Disability (ID) are comorbid neurodevelopmental disorders with complex genetic architectures. Despite large-scale sequencing studies only a fraction of the risk genes were identified for both. Here, we present a novel network-based gene risk prioritization algorithm named DeepND that performs cross-disorder analysis to improve prediction power by exploiting the comorbidity of ASD and ID via multitask learning. Our model leverages information from gene coexpression networks that model human brain development using graph convolutional neural networks and learns which spatio-temporal neurovelopmental windows are important for disorder etiologies. We show that our approach substantially improves the state-of-the-art prediction power in both single-disorder and cross-disorder settings. DeepND identifies prefrontal and primary motor-somatosensory cortex brain region, and periods from early fetal to mid fetal periods and from early childhood to young adulthood as the highest neurodevelopmental risk windows for both ASD and ID. Finally, we investigate frequent ASD and ID associated copy number variation regions and report our findings for several susceptibility gene candidates. DeepND can be generalized to analyze any combinations of comorbid disorders and is released at http://github.com/ciceklab/deepnd.
]]></description>
<dc:creator>Beyreli, I.</dc:creator>
<dc:creator>Karakahya, O.</dc:creator>
<dc:creator>Cicek, A. E.</dc:creator>
<dc:date>2020-06-15</dc:date>
<dc:identifier>doi:10.1101/2020.06.13.150201</dc:identifier>
<dc:title><![CDATA[Multitask learning on comorbid disorders improves gene risk prediction for Autism Spectrum Disorder and Intellectual Disability]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.15.153031v1?rss=1">
<title>
<![CDATA[
Dissecting Autism Genetic Risk Using Single-cell RNA-seq Data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.15.153031v1?rss=1"
</link>
<description><![CDATA[
Autism spectrum disorder (autism) is a condition with strong but heterogenous genetic contribution. Recent exome and genome sequencing studies have uncovered many new risk genes through de novo variants. However, a large fraction of enrichment of de novo variants observed in cases are not accounted for by known or candidate risk genes, suggesting that the majority of risk genes are still unknown. Here we hypothesize that autism risk genes share a few common cell-type specific gene expression patterns during brain development, and such information can be quantified to improve statistical power of detecting new risk genes. We obtained large-scale single-cell RNA-seq data from human fetal brain collected through a range of developmental stages, and developed a supervised machine-learning approach "A-risk" (Autism risk), to predict the plausibility of autism risk genes across the genome. Using data from recent exome sequencing studies of autism, A-risk achieves better performance in prioritizing de novo variants than other methods, especially for genes that are less intolerant of loss of function variants. We stratified genes based on A-risk and mutation intolerance metrics to improve estimation of priors in extTADA and identified 71 candidate risk genes. In particular, CLCN4, PRKAR1B, and NR2F1 are potentially new risk genes with further support from neurodevelopmental disorders. Expression patterns of both known and candidate risk genes reveals the important role of deep-layer excitatory neurons from adult human cortex in autism etiology. With the unprecedented revolution of single-cell transcriptomics and expanding autism cohorts with exome or genome sequencing, our method will facilitate systematic discovery of novel risk genes and understanding of biological pathogenesis in autism.
]]></description>
<dc:creator>Chen, S.</dc:creator>
<dc:creator>Zhou, X.</dc:creator>
<dc:creator>Byington, E.</dc:creator>
<dc:creator>Bruce, S. L.</dc:creator>
<dc:creator>Zhang, H.</dc:creator>
<dc:creator>Shen, Y.</dc:creator>
<dc:date>2020-06-16</dc:date>
<dc:identifier>doi:10.1101/2020.06.15.153031</dc:identifier>
<dc:title><![CDATA[Dissecting Autism Genetic Risk Using Single-cell RNA-seq Data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.25.172262v1?rss=1">
<title>
<![CDATA[
Cortical Organoids Model Early Brain Development Disrupted by 16p11.2 Copy Number Variants in Autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.25.172262v1?rss=1"
</link>
<description><![CDATA[
Reciprocal deletion and duplication of 16p11.2 region is the most common copy number variation (CNV) associated with Autism Spectrum Disorders. We generated cortical organoids from skin fibroblasts of patients with 16p11.2 CNV to investigate impacted neurodevelopmental processes. We show that organoid size recapitulates macrocephaly and microcephaly phenotypes observed in the patients with 16p11.2 deletions and duplications. The CNV has mirror-opposite effect on neuronal maturation, proliferation, and synapse number, in concordance with its effect on brain growth in humans. We demonstrate that 16p11.2 CNV alters the ratio of neurons to neural progenitors in organoids during early neurogenesis, with excess of neurons and depletion of neural progenitors observed in deletions, and mirror phenotypes in duplications. Transcriptomic and proteomic profiling revealed multiple dysregulated pathways, including defects in neuron migration. Inhibition of activity of the small GTPase RhoA rescued migration deficits. This study provides insights into potential neurobiological mechanisms behind the 16p11.2 CNV during neocortical development.
]]></description>
<dc:creator>Urresti, J.</dc:creator>
<dc:creator>Zhang, P.</dc:creator>
<dc:creator>Moran-Losada, P.</dc:creator>
<dc:creator>Yu, N.-K.</dc:creator>
<dc:creator>Negraes, P. D.</dc:creator>
<dc:creator>Trujillo, C. A.</dc:creator>
<dc:creator>Antaki, D.</dc:creator>
<dc:creator>Amar, M.</dc:creator>
<dc:creator>Chau, K.</dc:creator>
<dc:creator>Pramod, A. B.</dc:creator>
<dc:creator>Diedrich, J.</dc:creator>
<dc:creator>Tejwani, L.</dc:creator>
<dc:creator>Romero, S.</dc:creator>
<dc:creator>Sebat, J.</dc:creator>
<dc:creator>Yates, J. R.</dc:creator>
<dc:creator>Muotri, A. R.</dc:creator>
<dc:creator>Iakoucheva, L. M.</dc:creator>
<dc:date>2020-06-27</dc:date>
<dc:identifier>doi:10.1101/2020.06.25.172262</dc:identifier>
<dc:title><![CDATA[Cortical Organoids Model Early Brain Development Disrupted by 16p11.2 Copy Number Variants in Autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.27.175489v1?rss=1">
<title>
<![CDATA[
Isoform transcriptome of developing human brain provides new insights into autism risk variants 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.27.175489v1?rss=1"
</link>
<description><![CDATA[
Alternative splicing plays important role in brain development, however its global contribution to human neurodevelopmental diseases (NDD) has not been fully investigated. Here, we examined the relationships between full-length splicing isoforms expression in the brain and de novo loss-of-function mutations identified in the patients with NDDs. We analyzed the full-length isoform transcriptome of the developing human brain and observed differentially expressed isoforms and isoform co-expression modules undetectable by gene-level analyses. These isoforms were enriched in loss-of-function mutations and microexons, co-expressed with a unique set of partners, and had higher prenatal expression. We experimentally tested the impact of splice site mutations in five NDD risk genes, including SCN2A, DYRK1A and BTRC, and demonstrated exon skipping. Furthermore, our results suggest that the splice site mutation in BTRC reduces translational efficiency, likely impacting Wnt signaling through impaired degradation of {beta}-catenin. We propose that functional effect of mutations associated with human diseases should be investigated at the isoform-rather than the gene-level resolution.

HighlightsO_LIDifferential isoform expression analysis of the human brain transcriptome reveals neurodevelopmental processes and pathways undetectable by differential gene expression analyses.
C_LIO_LISplicing isoforms impacted by neurodevelopmental disease (NDD) risk mutations exhibit higher prenatal expression, are enriched in microexons and are involved in neuronal-related functions.
C_LIO_LIIsoform co-expression network analysis identifies modules with splicing and synaptic functions that are enriched in NDD mutations.
C_LIO_LISplice site mutations impacting NDD risk genes cause exon skipping and produce novel isoforms with altered biological properties.
C_LIO_LIFunctional impact of mutations should be investigated at the full-length isoform-level rather than the gene-level resolution
C_LI
]]></description>
<dc:creator>Chau, K.</dc:creator>
<dc:creator>Zhang, P.</dc:creator>
<dc:creator>Urresti, J.</dc:creator>
<dc:creator>Amar, M.</dc:creator>
<dc:creator>Pramod, A. B.</dc:creator>
<dc:creator>Thomas, A.</dc:creator>
<dc:creator>Corominas, R.</dc:creator>
<dc:creator>Lin, G. N.</dc:creator>
<dc:creator>Iakoucheva, L. M.</dc:creator>
<dc:date>2020-06-27</dc:date>
<dc:identifier>doi:10.1101/2020.06.27.175489</dc:identifier>
<dc:title><![CDATA[Isoform transcriptome of developing human brain provides new insights into autism risk variants]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.10.195859v1?rss=1">
<title>
<![CDATA[
DNMT3A haploinsufficiency results in behavioral deficits and global epigenomic dysregulation shared across neurodevelopment disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.10.195859v1?rss=1"
</link>
<description><![CDATA[
Mutations in DNA methyltransferase 3A (DNMT3A) have been detected in autism and related disorders, but how these mutations disrupt nervous system function is unknown. Here we define the effects of neurodevelopmental disease-associated DNMT3A mutations. We show that diverse mutations affect different aspects of protein activity yet lead to shared deficiencies in neuronal DNA methylation. Heterozygous DNMT3A knockout mice mimicking DNMT3A disruption in disease display growth and behavioral alterations consistent with human phenotypes. Strikingly, in these mice we detect global disruption of neuron-enriched non-CG DNA methylation, a binding site for the Rett syndrome protein MeCP2. Loss of this methylation leads to enhancer and gene dysregulation that overlaps with models of Rett syndrome and autism. These findings define effects of DNMT3A haploinsufficiency in the brain and uncover disruption of the non-CG methylation pathway as a convergence point across neurodevelopmental disorders.
]]></description>
<dc:creator>Christian, D. L.</dc:creator>
<dc:creator>Wu, D. Y.</dc:creator>
<dc:creator>Martin, J. R.</dc:creator>
<dc:creator>Moore, J. R.</dc:creator>
<dc:creator>Liu, Y. R.</dc:creator>
<dc:creator>Clemens, A. W.</dc:creator>
<dc:creator>Nettles, S. A.</dc:creator>
<dc:creator>Kirkland, N. M.</dc:creator>
<dc:creator>Hill, C. A.</dc:creator>
<dc:creator>Wozniak, D. F.</dc:creator>
<dc:creator>Dougherty, J. D.</dc:creator>
<dc:creator>Gabel, H. W.</dc:creator>
<dc:date>2020-07-13</dc:date>
<dc:identifier>doi:10.1101/2020.07.10.195859</dc:identifier>
<dc:title><![CDATA[DNMT3A haploinsufficiency results in behavioral deficits and global epigenomic dysregulation shared across neurodevelopment disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.21.213173v1?rss=1">
<title>
<![CDATA[
FOXP1 negatively regulates intrinsic excitability in D2 striatal projection neurons by promoting inwardly rectifying and leak potassium currents 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.21.213173v1?rss=1"
</link>
<description><![CDATA[
Heterozygous loss-of-function mutations in the transcription factor FOXP1 are strongly associated with autism. Dopamine receptor 2 expressing (D2) striatal projection neurons (SPNs) in heterozygous Foxp1 (Foxp1+/-) mice have higher intrinsic excitability. To understand the mechanisms underlying this alteration, we examined SPNs with cell-type specific homozygous Foxp1 deletion to study cell-autonomous regulation by Foxp1. As in Foxp1+/- mice, D2 SPNs had increased intrinsic excitability with homozygous Foxp1 deletion. This effect involved postnatal mechanisms. The hyperexcitability was mainly due to down-regulation of two classes of potassium currents: inwardly rectifying (KIR) and leak (KLeak). Single-cell RNA sequencing data from D2 SPNs with Foxp1 deletion indicated the down-regulation of transcripts of candidate ion channels that may underlie these currents: Kcnj2 and Kcnj4 for KIR and Kcnk2 for KLeak. This Foxp1-dependent regulation was neuron-type specific since these same currents and transcripts were either unchanged, or very little changed, in D1 SPNs with cell-specific Foxp1 deletion. Our data are consistent with a model where FOXP1 negatively regulates the excitability of D2 SPNs through KIR and KLeak by transcriptionally activating their corresponding transcripts. This, in turn, provides a novel example of how a transcription factor may regulate multiple genes to impact neuronal electrophysiological function that depends on the integration of multiple current types - and do this in a cell-specific fashion. Our findings provide initial clues to altered neuronal function and possible therapeutic strategies not only for FOXP1-associated autism but also for other autism forms associated with transcription factor dysfunction.
]]></description>
<dc:creator>Khandelwal, N.</dc:creator>
<dc:creator>Cavalier, S.</dc:creator>
<dc:creator>Rybalchenko, V.</dc:creator>
<dc:creator>Kulkarni, A.</dc:creator>
<dc:creator>Anderson, A. G.</dc:creator>
<dc:creator>Konopka, G.</dc:creator>
<dc:creator>Gibson, J. R.</dc:creator>
<dc:date>2020-07-21</dc:date>
<dc:identifier>doi:10.1101/2020.07.21.213173</dc:identifier>
<dc:title><![CDATA[FOXP1 negatively regulates intrinsic excitability in D2 striatal projection neurons by promoting inwardly rectifying and leak potassium currents]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.05.238949v1?rss=1">
<title>
<![CDATA[
Bayesian estimation of cell-type-specific gene expression per bulk sample with prior derived from single-cell data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.05.238949v1?rss=1"
</link>
<description><![CDATA[
When assessed over a large number of samples, bulk RNA sequencing provides reliable data for gene expression at the tissue level. Single-cell RNA sequencing (scRNA-seq) deepens those analyses by evaluating gene expression at the cellular level. Both data types lend insights into disease etiology. With current technologies, however, scRNA-seq data are known to be noisy. Moreover, constrained by costs, scRNA-seq data are typically generated from a relatively small number of subjects, which limits their utility for some analyses, such as identification of gene expression quantitative trait loci (eQTLs). To address these issues while maintaining the unique advantages of each data type, we develop a Bayesian method (bMIND) to integrate bulk and scRNA-seq data. With a prior derived from scRNA-seq data, we propose to estimate sample-level cell-type-specific (CTS) expression from bulk expression data. The CTS expression enables large-scale sample-level downstream analyses, such as detecting CTS differentially expressed genes (DEGs) and eQTLs. Through simulations, we demonstrate that bMIND improves the accuracy of sample-level CTS expression estimates and power to discover CTS-DEGs when compared to existing methods. To further our understanding of two complex phenotypes, autism spectrum disorder and Alzheimers disease, we apply bMIND to gene expression data of relevant brain tissue to identify CTS-DEGs. Our results complement findings for CTS-DEGs obtained from snRNA-seq studies, replicating certain DEGs in specific cell types while nominating other novel genes in those cell types. Finally, we calculate CTS-eQTLs for eleven brain regions by analyzing GTEx V8 data, creating a new resource for biological insights.
]]></description>
<dc:creator>Wang, J.</dc:creator>
<dc:creator>Roeder, K.</dc:creator>
<dc:creator>Devlin, B.</dc:creator>
<dc:date>2020-08-06</dc:date>
<dc:identifier>doi:10.1101/2020.08.05.238949</dc:identifier>
<dc:title><![CDATA[Bayesian estimation of cell-type-specific gene expression per bulk sample with prior derived from single-cell data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.12.248526v1?rss=1">
<title>
<![CDATA[
Systematic evaluation of genome sequencing as a first-tier diagnostic test for prenatal and pediatric disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.12.248526v1?rss=1"
</link>
<description><![CDATA[
Current clinical guidelines recommend three genetic tests for the assessment of fetal structural anomalies: karyotype to detect microscopically-visible balanced and unbalanced chromosomal rearrangements, chromosomal microarray (CMA) to detect sub-microscopic copy number variants (CNVs), and exome sequencing (ES) to identify individual nucleotide changes in coding sequence. Advances in genome sequencing (GS) analysis suggest that it is poised to displace the sequential application of all three conventional tests to become a single diagnostic approach for the assessment of fetal structural anomalies. However, systematic benchmarking is required to assure that GS can capture the full mutational spectrum associated with fetal structural anomalies and to accurately quantify the added diagnostic yield of GS. We applied a novel GS analytic framework that included the discovery, filtration, and interpretation of nine classes of genomic variation to 7,195 individuals. We assessed the sensitivity of GS to detect diagnostic variants (pathogenic or likely pathogenic) from three standard-of-care tests using 1,612 autism spectrum disorder quartet families (ASD; n=6,448) with matched GS, ES, and CMA data, and validated these findings in 46 fetuses with a clinically reportable variant originally identified by karyotype, CMA, or ES. We then assessed the added diagnostic yield of GS in 249 trios (n=747) comprising a fetus with a structural anomaly detected by ultrasound and two unaffected parents that were pre-screened with a combination of all three standard-of-care tests. Across both cohorts, our GS analytic framework identified 98.2% of all diagnostic variants detected by standard-of-care tests, including 100% of those originally detected by CMA (n=88) and ES (n=61), as well as 78.6% (n=11/14) of the chromosomal rearrangements identified by karyotype. The diagnostic yield from GS was 7.8% across all 1,612 ASD probands, almost two-fold more than CMA (4.4%) and three-fold more than ES (3.0%). We also demonstrated that the yield of ES can approach that of GS when CNVs are captured with high sensitivity from exome data (7.4% vs. 7.8%, respectively). In 249 pre-screened fetuses with structural anomalies, GS provided an additional diagnostic yield of 0.4% beyond the combination of all three tests (karyotype, CMA, and ES). Applying our benchmarking results to existing data indicates that GS can achieve an overall diagnostic yield of 46.1% in unselected fetuses with fetal structural anomalies, providing an estimated 17.2% increase in diagnostic yield over karyotype, 14.1% over CMA, and 36.1% over ES when sequence variants are assessed, and 4.1% when CNVs are also identified from exome data. In this study we demonstrate that GS is sensitive to the detection of almost all pathogenic variation captured by karyotype, CMA, and ES, provides a superior diagnostic yield than any individual test by a wide margin, and contributes a modest increase in diagnostic yield beyond the combination of all three tests. We also outline several strategies to aid the interpretation of GS variants that are cryptic to conventional technologies, which we anticipate will be increasingly encountered as comprehensive variant identification from GS is performed. Taken together, these data suggest GS warrants consideration as a first-tier diagnostic approach for fetal structural anomalies.
]]></description>
<dc:creator>Lowther, C.</dc:creator>
<dc:creator>Valkanas, E.</dc:creator>
<dc:creator>Giordano, J. L.</dc:creator>
<dc:creator>Wang, H. Z.</dc:creator>
<dc:creator>Currall, B. B.</dc:creator>
<dc:creator>O'Keefe, K.</dc:creator>
<dc:creator>Collins, R. L.</dc:creator>
<dc:creator>Zhao, X.</dc:creator>
<dc:creator>Austin-Tse, C. A.</dc:creator>
<dc:creator>Evangelista, E.</dc:creator>
<dc:creator>Aggarwal, V.</dc:creator>
<dc:creator>Lucente, D.</dc:creator>
<dc:creator>Gauthier, L. D.</dc:creator>
<dc:creator>Tolonen, C.</dc:creator>
<dc:creator>Sahakian, N.</dc:creator>
<dc:creator>An, J.-Y.</dc:creator>
<dc:creator>Dong, S.</dc:creator>
<dc:creator>Norton, M. E.</dc:creator>
<dc:creator>MacKenzie, T.</dc:creator>
<dc:creator>Devlin, B.</dc:creator>
<dc:creator>Gilmore, K.</dc:creator>
<dc:creator>Powell, B.</dc:creator>
<dc:creator>Brandt, A.</dc:creator>
<dc:creator>Vetrini, F.</dc:creator>
<dc:creator>DiVito, M.</dc:creator>
<dc:creator>Goldstein, D. B.</dc:creator>
<dc:creator>Sanders, S. J.</dc:creator>
<dc:creator>MacArthur, D. G.</dc:creator>
<dc:creator>Hodge, J. C.</dc:creator>
<dc:creator>O'Donnell-Luria, A.</dc:creator>
<dc:creator>Rehm, H.</dc:creator>
<dc:creator>Vora, N.</dc:creator>
<dc:creator>Levy, B.</dc:creator>
<dc:creator>Brand, H.</dc:creator>
<dc:creator>Wapner, R.</dc:creator>
<dc:creator>Talkowski, M. E.</dc:creator>
<dc:date>2020-08-13</dc:date>
<dc:identifier>doi:10.1101/2020.08.12.248526</dc:identifier>
<dc:title><![CDATA[Systematic evaluation of genome sequencing as a first-tier diagnostic test for prenatal and pediatric disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.17.302117v1?rss=1">
<title>
<![CDATA[
The organization and developmental establishment ofcortical interneuron presynaptic circuits 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.17.302117v1?rss=1"
</link>
<description><![CDATA[
Sensory and cognitive functions are processed in discrete cortical areas and depend upon the integration of long range cortical and subcortical inputs. PV and SST inhibitory interneurons (cINs) gate these inputs and failure to do so properly is implicated in many neurodevelopmental disorders. The logic by which these interneuron populations are integrated into cortical circuits and how these vary across sensory versus associative cortical areas is unknown. To answer this question, we began by surveying the breadth of afferents impinging upon PV and SST cINs within distinct cortical areas. We found that presynaptic inputs to both cIN populations are similar and primarily dictated by their areal location. By contrast, the timing of when they receive these afferents is cell-type specific. In sensory regions, both SST and PV cINs initially receive thalamocortical first order inputs. While by adulthood PV cINs remain heavily skewed towards first order inputs, SST cINs receive an equal balance of first and higher order thalamic afferents. Remarkably, while perturbations to sensory experience affect PV cIN thalamocortical connectivity, SST cIN connectivity is disrupted in a model of fragile X syndrome (Fmr1 loss of function) but not a model of ASD (Shank3B loss of function). Altogether, these data provide a comprehensive map of cIN afferents within different functional cortical areas and reveal the region-specific logic by which PV and SST cIN circuits are established.
]]></description>
<dc:creator>Pouchelon, G.</dc:creator>
<dc:creator>Bollmann, Y.</dc:creator>
<dc:creator>Fisher, E.</dc:creator>
<dc:creator>Agba, C. K.</dc:creator>
<dc:creator>Xu, Q.</dc:creator>
<dc:creator>Ritola, K. D.</dc:creator>
<dc:creator>Mirow, A. M.</dc:creator>
<dc:creator>Kim, S.</dc:creator>
<dc:creator>Cossart, R.</dc:creator>
<dc:creator>Fishell, G.</dc:creator>
<dc:date>2020-09-17</dc:date>
<dc:identifier>doi:10.1101/2020.09.17.302117</dc:identifier>
<dc:title><![CDATA[The organization and developmental establishment ofcortical interneuron presynaptic circuits]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.22.304279v1?rss=1">
<title>
<![CDATA[
A causal study of bumetanide on a marker of excitatory-inhibitory balance in the human brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.22.304279v1?rss=1"
</link>
<description><![CDATA[
Bumetanide has received much interest as a potential pharmacological modulator of the putative imbalance in excitatory/inhibitory (E/I) signaling that is thought to characterize autism spectrum conditions. Yet, currently, no studies of bumetanide efficacy have used an outcome measure that is modeled to depend on E/I balance in the brain. In this manuscript, we present the first causal study of the effect of bumetanide on an objective marker of E/I balance in the brain, binocular rivalry, which we have previously shown to be sensitive to pharmacological manipulation of GABA. Using a within-subjects placebo-control crossover design study, we show that, contrary to expectation, acute administration of bumetanide does not alter binocular rivalry dynamics in neurotypical adult individuals. Neither changes in response times nor response criteria can account for these results. These results raise important questions about the efficacy of acute bumetanide administration for altering E/I balance in the human brain, and highlight the importance of studies using objective markers of the underlying neural processes that drugs hope to target.
]]></description>
<dc:creator>Botch, T. L.</dc:creator>
<dc:creator>Spiegel, A.</dc:creator>
<dc:creator>Ricciardi, C.</dc:creator>
<dc:creator>Robertson, C. E.</dc:creator>
<dc:date>2020-09-23</dc:date>
<dc:identifier>doi:10.1101/2020.09.22.304279</dc:identifier>
<dc:title><![CDATA[A causal study of bumetanide on a marker of excitatory-inhibitory balance in the human brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.07.329292v1?rss=1">
<title>
<![CDATA[
A cross-species link between mTOR-related synaptic pathology and functional hyperconnectivityin autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.07.329292v1?rss=1"
</link>
<description><![CDATA[
Postmortem studies have revealed increased density of excitatory synapses in the brains of individuals with autism, with a putative link to aberrant mTOR-dependent synaptic pruning. Autism is also characterized by atypical macroscale functional connectivity as measured with resting-state fMRI (rsfMRI). These observations raise the question of whether excess of synapses cause aberrant functional connectivity in autism. Using rsfMRI, electrophysiology and in silico modelling in Tsc2 haploinsufficient mice, we show that mTOR-dependent increased spine density is associated with autism-like stereotypies and cortico-striatal hyperconnectivity. These deficits are completely rescued by pharmacological inhibition of mTOR. Notably, we further demonstrate that children with idiopathic autism exhibit analogous cortical-striatal hyperconnectivity, and document that this connectivity fingerprint is enriched for autism-dysregulated genes interacting with mTOR or TSC2. Finally, we show that the identified transcriptomic signature is predominantly expressed in a subset of children with autism, thereby defining a segregable autism subtype. Our findings causally link mTOR-related synaptic pathology to large-scale network aberrations, revealing a unifying multi-scale framework that mechanistically reconciles developmental synaptopathy and functional hyperconnectivity in autism.

SignificanceAberrant brain functional connectivity is a hallmark of autism, but the neural basis of this phenomenon remains unclear. We show that a mouse line recapitulating mTOR-dependent synaptic pruning deficits observed in postmortem autistic brains exhibits widespread functional hyperconnectivity. Importantly, pharmacological normalization of mTOR signalling completely rescues synaptic, behavioral and functional connectivity deficits. We also show that a similar connectivity fingerprint can be isolated in human fMRI scans of people with autism, where it is linked to over-expression of mTOR-related genes. Our results reveal a unifying multi-scale translational framework that mechanistically links aberrations in synaptic pruning with functional hyperconnectivity in autism.
]]></description>
<dc:creator>Pagani, M.</dc:creator>
<dc:creator>Bertero, A.</dc:creator>
<dc:creator>Trakoshis, S.</dc:creator>
<dc:creator>Ulysse, L.</dc:creator>
<dc:creator>Locarno, A.</dc:creator>
<dc:creator>Miseviciute, I.</dc:creator>
<dc:creator>De Felice, A.</dc:creator>
<dc:creator>Canella, C.</dc:creator>
<dc:creator>Supekar, K.</dc:creator>
<dc:creator>Galbusera, A.</dc:creator>
<dc:creator>Menon, V.</dc:creator>
<dc:creator>Tonini, R.</dc:creator>
<dc:creator>Deco, G.</dc:creator>
<dc:creator>Lombardo, M. V.</dc:creator>
<dc:creator>Pasqualetti, M.</dc:creator>
<dc:creator>Gozzi, A.</dc:creator>
<dc:date>2020-10-08</dc:date>
<dc:identifier>doi:10.1101/2020.10.07.329292</dc:identifier>
<dc:title><![CDATA[A cross-species link between mTOR-related synaptic pathology and functional hyperconnectivityin autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.06.329011v1?rss=1">
<title>
<![CDATA[
De novo structural mutation rates and gamete-of-origin biases revealed through genome sequencing of 2,396 families 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.06.329011v1?rss=1"
</link>
<description><![CDATA[
Each human genome includes de novo mutations that arose during gametogenesis. While these germline mutations represent a fundamental source of new genetic diversity, they can also create deleterious alleles that impact fitness. The germline mutation rate for single nucleotide variants and factors that significantly influence this rate, such as parental age, are now well established. However, far less is known about the frequency, distribution, and features that impact de novo structural mutations. We report a large, family-based study of germline mutations, excluding aneuploidy, that affect genome structure among 572 genomes from 33 families in a multigenerational CEPH-Utah cohort and 2,363 cases of non-familial autism spectrum disorder (ASD), 1,938 unaffected siblings, and both parents (9,599 genomes in total). We find that de novo structural mutations detected by alignment-based, short-read WGS occurred at an overall rate of at least 0.160 events per genome in unaffected individuals and was significantly higher (0.206 per genome) in ASD cases. In both probands and unaffected samples, nearly 73% of de novo structural mutations arose in paternal gametes, and predict most de novo structural mutations to be caused by mutational mechanisms that do not require sequence homology. After multiple testing correction we did not observe a statistically significant correlation between parental age and the rate of de novo structural variation in offspring. These results highlight that a spectrum of mutational mechanisms contribute to germline structural mutations, and that these mechanisms likely have markedly different rates and selective pressures than those leading to point mutations.
]]></description>
<dc:creator>Belyeu, J. R.</dc:creator>
<dc:creator>Brand, H.</dc:creator>
<dc:creator>Wang, H.</dc:creator>
<dc:creator>Zhao, X.</dc:creator>
<dc:creator>Pedersen, B. S.</dc:creator>
<dc:creator>Feusier, J.</dc:creator>
<dc:creator>Gupta, M.</dc:creator>
<dc:creator>Nicholas, T. J.</dc:creator>
<dc:creator>Baird, L.</dc:creator>
<dc:creator>Devlin, B.</dc:creator>
<dc:creator>Sanders, S. J.</dc:creator>
<dc:creator>Jorde, L. B.</dc:creator>
<dc:creator>Talkowski, M. E.</dc:creator>
<dc:creator>Quinlan, A. R.</dc:creator>
<dc:date>2020-10-08</dc:date>
<dc:identifier>doi:10.1101/2020.10.06.329011</dc:identifier>
<dc:title><![CDATA[De novo structural mutation rates and gamete-of-origin biases revealed through genome sequencing of 2,396 families]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.14.339192v1?rss=1">
<title>
<![CDATA[
Heterozygous deletion of SYNGAP enzymatic domains in rats causes selective learning, social and seizure phenotypes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.14.339192v1?rss=1"
</link>
<description><![CDATA[
Pathogenic variants in SYNGAP1 are one of the most common genetic causes of nonsyndromic intellectual disability (ID) and are considered a risk for autism spectrum disorder (ASD). SYNGAP1 encodes a synaptic GTPase activating protein that modulates the intrinsic GTPase activity of several small G-proteins and is implicated in regulating the composition of the postsynaptic density. By targeting the deletion of exons encoding the calcium/lipid binding (C2) and GTPase activating protein (GAP) domains, we generated a novel rat model to study SYNGAP related pathophysiology. We find that rats heterozygous for the C2/GAP domain deletion (Syngap+/{Delta}-GAP) exhibit reduced exploration and fear extinction, altered social behaviour, and spontaneous seizures, while homozygous mutants die within days after birth. This new rat model reveals that the enzymatic domains of SYNGAP are essential for normal brain function and provide an important new model system in the study of both ID/ASD and epilepsy.
]]></description>
<dc:creator>Katsanevaki, D.</dc:creator>
<dc:creator>Till, S. M.</dc:creator>
<dc:creator>Buller-Peralta, I.</dc:creator>
<dc:creator>Watson, T. C.</dc:creator>
<dc:creator>Nawaz, M. S.</dc:creator>
<dc:creator>Arkell, D.</dc:creator>
<dc:creator>Tiwari, S.</dc:creator>
<dc:creator>Kapgal, V.</dc:creator>
<dc:creator>Biswal, S.</dc:creator>
<dc:creator>Smith, J. A.</dc:creator>
<dc:creator>Anstey, N. J.</dc:creator>
<dc:creator>Mizen, L.</dc:creator>
<dc:creator>Perentos, N.</dc:creator>
<dc:creator>Jones, M. W.</dc:creator>
<dc:creator>Cousin, M. A.</dc:creator>
<dc:creator>Chattarji, S.</dc:creator>
<dc:creator>Gonzalez-Sulser, A.</dc:creator>
<dc:creator>Hardt, O.</dc:creator>
<dc:creator>Wood, E. R.</dc:creator>
<dc:creator>Kind, P. C.</dc:creator>
<dc:date>2020-10-14</dc:date>
<dc:identifier>doi:10.1101/2020.10.14.339192</dc:identifier>
<dc:title><![CDATA[Heterozygous deletion of SYNGAP enzymatic domains in rats causes selective learning, social and seizure phenotypes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.14.339796v1?rss=1">
<title>
<![CDATA[
Temporal stability of human sperm mosaic mutations results in life-long threat of transmission to offspring 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.14.339796v1?rss=1"
</link>
<description><![CDATA[
Every newborn harbors scores of new single nucleotide variants (SNVs) that may impact health and disease1-4; the majority of these are contributed by the paternal germ cells5. In some cases, these mutations are identifiable in a subset of the parents cells--a phenomenon called mosaicism, which is capable of producing disease recurrence6-8. Here, we provide a comprehensive analysis of male gonadal mosaic mutations, employing 300x whole genome sequencing (WGS) of blood and sperm in 17 healthy individuals, including assessment across multiple samples and age groups. Approximately 1 in 15 healthy males is predicted to harbor a transmissible, likely pathogenic exonic variant that is mosaic in his sperm. In general, only a third of sperm mosaic mutations were detectable in blood cells, all were remarkably stable over the course of months to years, and 23% were present in 5% or more of sperm cells. There was no evidence of age-dependent clonal expansion or collapse, as seen in hematopoiesis. Thus, despite the observed increase of mutations in offspring of men with advanced paternal age, detectable sperm mosaicism remains stable, represents a life-long transmission risk to offspring, and suggests a testis stem cell niche that prevents widespread clonality.
]]></description>
<dc:creator>Yang, X.</dc:creator>
<dc:creator>Breuss, M. W.</dc:creator>
<dc:creator>Xu, X.</dc:creator>
<dc:creator>Antaki, D.</dc:creator>
<dc:creator>James, K. N.</dc:creator>
<dc:creator>Stanley, V.</dc:creator>
<dc:creator>Ball, L. L.</dc:creator>
<dc:creator>George, R. D.</dc:creator>
<dc:creator>Wirth, S. A.</dc:creator>
<dc:creator>Cao, B.</dc:creator>
<dc:creator>Nguyen, A.</dc:creator>
<dc:creator>McEvoy-Venneri, J.</dc:creator>
<dc:creator>Chai, G.</dc:creator>
<dc:creator>Nahas, S.</dc:creator>
<dc:creator>Van Der Kraan, L.</dc:creator>
<dc:creator>Ding, Y.</dc:creator>
<dc:creator>Sebat, J.</dc:creator>
<dc:creator>Gleeson, J. G.</dc:creator>
<dc:date>2020-10-14</dc:date>
<dc:identifier>doi:10.1101/2020.10.14.339796</dc:identifier>
<dc:title><![CDATA[Temporal stability of human sperm mosaic mutations results in life-long threat of transmission to offspring]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.15.340588v1?rss=1">
<title>
<![CDATA[
Brain mapping across 16 autism mouse models reveals a spectrum of functional connectivity subtypes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.15.340588v1?rss=1"
</link>
<description><![CDATA[
Autism Spectrum Disorder (ASD) is characterized by substantial, yet highly heterogeneous abnormalities in functional brain connectivity. However, the origin and significance of this phenomenon remain unclear. To unravel ASD connectopathy and relate it to underlying etiological heterogeneity, we carried out a bi-center cross-etiological investigation of fMRI-based connectivity in the mouse, in which specific ASD-relevant mutations can be isolated and modelled minimizing environmental contributions. By performing brain-wide connectivity mapping across 16 mouse mutants, we show that different ASD-associated etiologies cause a broad spectrum of connectional abnormalities in which diverse, often diverging, connectivity signatures are recognizable. Despite this heterogeneity, the identified connectivity alterations could be classified into four subtypes characterized by discrete signatures of network dysfunction. Our findings show that etiological variability is a key determinant of connectivity heterogeneity in ASD, hence reconciling conflicting findings in clinical populations. The identification of etiologically-relevant connectivity subtypes could improve diagnostic label accuracy in the non-syndromic ASD population and paves the way for personalized treatment approaches.
]]></description>
<dc:creator>Zerbi, V.</dc:creator>
<dc:creator>Pagani, M.</dc:creator>
<dc:creator>Markicevic, M.</dc:creator>
<dc:creator>Matteoli, M.</dc:creator>
<dc:creator>Pozzi, D.</dc:creator>
<dc:creator>Fagiolini, M.</dc:creator>
<dc:creator>Bozzi, Y.</dc:creator>
<dc:creator>Galbusera, A.</dc:creator>
<dc:creator>Scattoni, M. L.</dc:creator>
<dc:creator>Provenzano, G.</dc:creator>
<dc:creator>Banerjee, A.</dc:creator>
<dc:creator>Helmchen, F.</dc:creator>
<dc:creator>Basson, A.</dc:creator>
<dc:creator>Ellegood, J.</dc:creator>
<dc:creator>Lerch, J.</dc:creator>
<dc:creator>Rudin, M.</dc:creator>
<dc:creator>Gozzi, A.</dc:creator>
<dc:creator>Wenderoth, N.</dc:creator>
<dc:date>2020-10-15</dc:date>
<dc:identifier>doi:10.1101/2020.10.15.340588</dc:identifier>
<dc:title><![CDATA[Brain mapping across 16 autism mouse models reveals a spectrum of functional connectivity subtypes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.14.339200v1?rss=1">
<title>
<![CDATA[
Full-length transcript sequencing of human and mouse identifies widespread isoform diversity and alternative splicing in the cerebral cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.14.339200v1?rss=1"
</link>
<description><![CDATA[
Alternative splicing is a post-transcriptional regulatory mechanism producing multiple distinct mRNA molecules from a single pre-mRNA. Alternative splicing has a prominent role in the central nervous system, impacting neurodevelopment and various neuronal functions as well as being increasingly implicated in brain disorders including autism, schizophrenia and Alzheimers disease. Standard short-read RNA-Seq approaches only sequence fragments of the mRNA molecule, making it difficult to accurately characterize the true nature of RNA isoform diversity. In this study, we used long-read isoform sequencing (Iso-Seq) to generate full-length cDNA sequences and map transcript diversity in the human and mouse cerebral cortex. We identify widespread RNA isoform diversity amongst expressed genes in the cortex, including many novel transcripts not present in existing genome annotations. Alternative splicing events were found to make a major contribution to RNA isoform diversity in the cortex, with intron retention being a relatively common event associated with nonsense-mediated decay and reduced transcript expression. Of note, we found evidence for transcription from novel (unannotated genes) and fusion events between neighbouring genes. Although global patterns of RNA isoform diversity were found to be generally similar between human and mouse cortex, we identified some notable exceptions. We also identified striking developmental changes in transcript diversity, with differential transcript usage between human adult and fetal cerebral cortex. Finally, we found evidence for extensive isoform diversity in genes associated with autism, schizophrenia and Alzheimers disease. Our data confirm the importance of alternative splicing in the cerebral cortex, dramatically increasing transcriptional diversity and representing an important mechanism underpinning gene regulation in the brain. We provide this transcript level data as a resource to the scientific community.
]]></description>
<dc:creator>Jeffries, A. R.</dc:creator>
<dc:creator>Leung, S. K.</dc:creator>
<dc:creator>Castanho, I.</dc:creator>
<dc:creator>Moore, K.</dc:creator>
<dc:creator>Davies, J.</dc:creator>
<dc:creator>Dempster, E.</dc:creator>
<dc:creator>Bray, N. J.</dc:creator>
<dc:creator>O'Neill, P.</dc:creator>
<dc:creator>Tseng, E. J.</dc:creator>
<dc:creator>Ahmed, Z.</dc:creator>
<dc:creator>Collier, D.</dc:creator>
<dc:creator>Prabhakar, S.</dc:creator>
<dc:creator>Scalkwyk, L.</dc:creator>
<dc:creator>Gandal, M.</dc:creator>
<dc:creator>Hannon, E.</dc:creator>
<dc:creator>Mill, J.</dc:creator>
<dc:date>2020-10-15</dc:date>
<dc:identifier>doi:10.1101/2020.10.14.339200</dc:identifier>
<dc:title><![CDATA[Full-length transcript sequencing of human and mouse identifies widespread isoform diversity and alternative splicing in the cerebral cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.21.349290v1?rss=1">
<title>
<![CDATA[
Regulation of neural gene expression by estrogen receptor alpha 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.21.349290v1?rss=1"
</link>
<description><![CDATA[
The transcription factor estrogen receptor  (ER) is a principal regulator of sex differences in the vertebrate brain and can modulate mood, behavior, and energy balance in females and males. However, the genes regulated by ER in the brain remain largely unknown. Here we reveal the genomic binding of ER within a sexually dimorphic neural circuit that regulates social behaviors. We profiled gene expression and chromatin accessibility and show ER induces a neurodevelopmental gene program in adulthood. We further demonstrate that ER binds with Nuclear factor I X-type (Nfix) to regulate a male-biased gene expression program that initiates in early life. Our results reveal a neural strategy for ER-mediated gene regulation and provide molecular targets that underlie estrogens effects on brain development, behavior, and disease.
]]></description>
<dc:creator>Gegenhuber, B.</dc:creator>
<dc:creator>Wu, M. V.</dc:creator>
<dc:creator>Bronstein, R.</dc:creator>
<dc:creator>Tollkuhn, J.</dc:creator>
<dc:date>2020-10-21</dc:date>
<dc:identifier>doi:10.1101/2020.10.21.349290</dc:identifier>
<dc:title><![CDATA[Regulation of neural gene expression by estrogen receptor alpha]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.27.353573v1?rss=1">
<title>
<![CDATA[
Spatial modulation of dark versus bright stimulus responses in mouse visual cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.27.353573v1?rss=1"
</link>
<description><![CDATA[
A fundamental task of the visual system is to respond to luminance increments and decrements. In primary visual cortex (V1) of cats and primates, luminance decrements elicit stronger, faster, and more salient neural activity (OFF responses) than luminance increments (ON responses). However, studies of V1 in ferrets and mice show that ON responses may be stronger. These discrepancies may arise from differences in species, experimental conditions, or from measuring responses in single neurons versus populations. Here, we examined OFF versus ON responses across different regions of visual space in both single neurons and populations of mouse V1. We used high-density silicon probes and whole-cell patch-clamp recordings to assess OFF versus ON dominance in local field potential (LFP), single neuron, and membrane potential responses. Across these levels, we found that OFF responses clearly dominated in the central visual field, whereas ON responses were more evident in the periphery. These observations were clearest in LFP and subthreshold membrane potential. Our findings consolidate and resolve prior conflicting results and reveal that retinotopy may provide a common organizing principle for spatially biasing OFF versus ON processing in mammalian visual systems.
]]></description>
<dc:creator>Williams, B.</dc:creator>
<dc:creator>Del Rosario, J.</dc:creator>
<dc:creator>Coletta, S.</dc:creator>
<dc:creator>Murlin, E. K.</dc:creator>
<dc:creator>Muzzu, T.</dc:creator>
<dc:creator>Speed, A.</dc:creator>
<dc:creator>Meyer-Baese, L.</dc:creator>
<dc:creator>Saleem, A. B.</dc:creator>
<dc:creator>Haider, B.</dc:creator>
<dc:date>2020-10-28</dc:date>
<dc:identifier>doi:10.1101/2020.10.27.353573</dc:identifier>
<dc:title><![CDATA[Spatial modulation of dark versus bright stimulus responses in mouse visual cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.28.359224v1?rss=1">
<title>
<![CDATA[
Brunner syndrome associated MAOA dysfunction in human dopaminergic neurons results in NMDAR hyperfunction and increased network activity. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.28.359224v1?rss=1"
</link>
<description><![CDATA[
BackgroundMonoamine neurotransmitter abundance affects motor control, emotion, and cognitive function and is regulated by monoamine oxidases. Amongst these, monoamine oxidase A (MAOA) catalyzes the degradation of dopamine, norepinephrine, and serotonin into their inactive metabolites. Loss-of-function mutations in the X-linked MAOA gene cause Brunner syndrome, which is characterized by various forms of impulsivity, maladaptive externalizing behavior, and mild intellectual disability. Impaired MAOA activity in individuals with Brunner syndrome results in bioamine aberration, but it is currently unknown how this affects neuronal function.

MethodsWe generated human induced pluripotent stem cell (hiPSC)-derived dopaminergic (DA) neurons from three individuals with Brunner syndrome carrying different mutations, and used CRISPR/Cas9 mediated homologous recombination to rescue MAOA function. We used these lines to characterize morphological and functional properties of DA neuronal cultures at the single cell and neuronal network level in vitro.

ResultsBrunner syndrome DA neurons showed reduced synaptic density but hyperactive network activity. Intrinsic functional properties and -amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-mediated synaptic transmission were not affected by MAOA dysfunction. Instead, we show that the neuronal network hyperactivity is mediated by upregulation of the GRIN2A and GRIN2B subunits of the N-methyl-D-aspartate receptor (NMDAR), and rescue of MAOA results in normalization of NMDAR function as well as restoration of network activity.

ConclusionsOur data suggest that MAOA dysfunction in Brunner syndrome increases activity of dopaminergic neurons through upregulation of NMDAR function, which may contribute to Brunner syndrome associated phenotypes.
]]></description>
<dc:creator>Shi, Y.</dc:creator>
<dc:creator>van Rhijn, J.-R.</dc:creator>
<dc:creator>Bormann, M.</dc:creator>
<dc:creator>Mossink, B.</dc:creator>
<dc:creator>Frega, M.</dc:creator>
<dc:creator>Recaioglu, H.</dc:creator>
<dc:creator>Hakobjan, M.</dc:creator>
<dc:creator>Klein Gunnewiek, T. M.</dc:creator>
<dc:creator>Schoenmaker, C.</dc:creator>
<dc:creator>Palmer, E.</dc:creator>
<dc:creator>Faivre, L.</dc:creator>
<dc:creator>Kittel-Schneider, S.</dc:creator>
<dc:creator>Schubert, D.</dc:creator>
<dc:creator>Brunner, H.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:date>2020-10-29</dc:date>
<dc:identifier>doi:10.1101/2020.10.28.359224</dc:identifier>
<dc:title><![CDATA[Brunner syndrome associated MAOA dysfunction in human dopaminergic neurons results in NMDAR hyperfunction and increased network activity.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.27.356899v1?rss=1">
<title>
<![CDATA[
A configurable model of the synaptic proteome reveals the molecular mechanisms of disease co-morbidity. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.27.356899v1?rss=1"
</link>
<description><![CDATA[
Synapses contain highly complex proteomes which control synaptic transmission, cognition and behaviour. Genes encoding synaptic proteins are associated with neuronal disorders many of which show clinical co-morbidity. Our hypothesis is that there is mechanistic overlap that is emergent from the network properties of the molecular complex. To test this requires a detailed and comprehensive molecular network model.

We integrated 57 published synaptic proteomic datasets obtained between 2000 and 2019 that describe over 7000 proteins. The complexity of the postsynaptic proteome is reaching an asymptote with a core set of ~3000 proteins, with less data on the presynaptic terminal, where each new study reveals new components in its landscape. To complete the network, we added direct protein-protein interaction data and functional metadata including disease association.

The resulting amalgamated molecular interaction network model is embedded into a SQLite database. The database is highly flexible allowing the widest range of queries to derive custom network models based on meta-data including species, disease association, synaptic compartment, brain region, and method of extraction.

This network model enables us to perform in-depth analyses that dissect molecular pathways of multiple diseases revealing shared and unique protein components. We can clearly identify common and unique molecular profiles for co-morbid neurological disorders such as Schizophrenia and Bipolar Disorder and even disease comorbidities which span biological systems such as the intersection of Alzheimers Disease with Hypertension.
]]></description>
<dc:creator>Sorokina, O.</dc:creator>
<dc:creator>McLean, C.</dc:creator>
<dc:creator>Croning, M. D.</dc:creator>
<dc:creator>Heil, K. F.</dc:creator>
<dc:creator>Wysochka, E.</dc:creator>
<dc:creator>He, X.</dc:creator>
<dc:creator>Sterratt, D. C.</dc:creator>
<dc:creator>Grant, S.</dc:creator>
<dc:creator>Simpson, I.</dc:creator>
<dc:creator>Armstrong, J. D.</dc:creator>
<dc:date>2020-10-27</dc:date>
<dc:identifier>doi:10.1101/2020.10.27.356899</dc:identifier>
<dc:title><![CDATA[A configurable model of the synaptic proteome reveals the molecular mechanisms of disease co-morbidity.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.28.359893v1?rss=1">
<title>
<![CDATA[
Neural basis of opioid-induced respiratory depression and its rescue 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.28.359893v1?rss=1"
</link>
<description><![CDATA[
Opioid-induced respiratory depression (OIRD) causes death following an opioid overdose, yet the neurobiological mechanisms of this process are not well understood. Here, we show that neurons within the lateral parabrachial nucleus that express the -opioid receptor (PBLOprm1 neurons) are involved in OIRD pathogenesis. PBLOprm1 neuronal activity is tightly correlated with respiratory rate, and this correlation is abolished following morphine injection. Chemogenetic inactivation of PBLOprm1 neurons mimics OIRD in mice, whereas their chemogenetic activation following morphine injection rescues respiratory rhythms to baseline levels. We identified several excitatory G-protein coupled receptors expressed by PBLOprm1 neurons and show that agonists for these receptors restore breathing rates in mice experiencing OIRD. Thus, PBLOprm1 neurons are critical for OIRD pathogenesis, providing a promising therapeutic target for treating OIRD in patients.
]]></description>
<dc:creator>Liu, S.</dc:creator>
<dc:creator>Kim, D.-I.</dc:creator>
<dc:creator>Oh, T. G.</dc:creator>
<dc:creator>Pao, G. M.</dc:creator>
<dc:creator>Kim, J. H.</dc:creator>
<dc:creator>Palmiter, R. D.</dc:creator>
<dc:creator>Banghart, M. M.</dc:creator>
<dc:creator>Lee, K.-F.</dc:creator>
<dc:creator>Evans, R. M.</dc:creator>
<dc:creator>Han, S.</dc:creator>
<dc:date>2020-10-29</dc:date>
<dc:identifier>doi:10.1101/2020.10.28.359893</dc:identifier>
<dc:title><![CDATA[Neural basis of opioid-induced respiratory depression and its rescue]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.03.365395v1?rss=1">
<title>
<![CDATA[
Targeted long-read sequencing resolves complex structural variants and identifies missing disease-causing variants 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.03.365395v1?rss=1"
</link>
<description><![CDATA[
BACKGROUNDDespite widespread availability of clinical genetic testing, many individuals with suspected genetic conditions do not have a precise diagnosis. This limits their opportunity to take advantage of state-of-the-art treatments. In such instances, testing sometimes reveals difficult-to-evaluate complex structural differences, candidate variants that do not fully explain the phenotype, single pathogenic variants in recessive disorders, or no variants in specific genes of interest. Thus, there is a need for better tools to identify a precise genetic diagnosis in individuals when conventional testing approaches have been exhausted.

METHODSTargeted long-read sequencing (T-LRS) was performed on 33 individuals using Read Until on the Oxford Nanopore platform. This method allowed us to computationally target up to 100 Mbp of sequence per experiment, resulting in an average of 20x coverage of target regions, a 500% increase over background. We analyzed patient DNA for pathogenic substitutions, structural variants, and methylation differences using a single data source.

RESULTSThe effectiveness of T-LRS was validated by detecting all genomic aberrations, including single-nucleotide variants, copy number changes, repeat expansions, and methylation differences, previously identified by prior clinical testing. In 6/7 individuals who had complex structural rearrangements, T-LRS enabled more precise resolution of the mutation, which led, in one case, to a change in clinical management. In nine individuals with suspected Mendelian conditions who lacked a precise genetic diagnosis, T-LRS identified pathogenic or likely pathogenic variants in five and variants of uncertain significance in two others.

CONCLUSIONST-LRS can accurately predict pathogenic copy number variants and triplet repeat expansions, resolve complex rearrangements, and identify single-nucleotide variants not detected by other technologies, including short-read sequencing. T-LRS represents an efficient and cost-effective strategy to evaluate high-priority candidate genes and regions or to further evaluate complex clinical testing results. The application of T-LRS will likely increase the diagnostic rate of rare disorders.
]]></description>
<dc:creator>Miller, D. E.</dc:creator>
<dc:creator>Sulovari, A.</dc:creator>
<dc:creator>Wang, T.</dc:creator>
<dc:creator>Loucks, H.</dc:creator>
<dc:creator>Hoekzema, K.</dc:creator>
<dc:creator>Munson, K. M.</dc:creator>
<dc:creator>Lewis, A. P.</dc:creator>
<dc:creator>Almanza Fuerte, E. P.</dc:creator>
<dc:creator>Paschal, C. R.</dc:creator>
<dc:creator>Thies, J.</dc:creator>
<dc:creator>Bennett, J. T.</dc:creator>
<dc:creator>Glass, I.</dc:creator>
<dc:creator>Dipple, K. M.</dc:creator>
<dc:creator>Patterson, K.</dc:creator>
<dc:creator>Bonkowski, E. S.</dc:creator>
<dc:creator>Nelson, Z.</dc:creator>
<dc:creator>Squire, A.</dc:creator>
<dc:creator>Sikes, M.</dc:creator>
<dc:creator>Beckman, E.</dc:creator>
<dc:creator>Bennett, R. L.</dc:creator>
<dc:creator>Earl, D.</dc:creator>
<dc:creator>Lee, W.</dc:creator>
<dc:creator>Allikmets, R.</dc:creator>
<dc:creator>Perlman, S. J.</dc:creator>
<dc:creator>Chow, P.</dc:creator>
<dc:creator>Hing, A. V.</dc:creator>
<dc:creator>Adam, M. P.</dc:creator>
<dc:creator>Sun, A.</dc:creator>
<dc:creator>Lam, C.</dc:creator>
<dc:creator>Chang, I.</dc:creator>
<dc:creator>University of Washington Center for Mendelian Genomics,</dc:creator>
<dc:creator>Cherry, T.</dc:creator>
<dc:creator>Chong, J. X.</dc:creator>
<dc:creator>Bamshad, M. J.</dc:creator>
<dc:creator>Nickerson, D. A.</dc:creator>
<dc:creator>Mefford, H. C.</dc:creator>
<dc:creator>Doherty, D.</dc:creator>
<dc:creator>Eichler, E. E.</dc:creator>
<dc:date>2020-11-04</dc:date>
<dc:identifier>doi:10.1101/2020.11.03.365395</dc:identifier>
<dc:title><![CDATA[Targeted long-read sequencing resolves complex structural variants and identifies missing disease-causing variants]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.12.380501v1?rss=1">
<title>
<![CDATA[
Sex-specific stress-related behavioral phenotypes and central amygdala dysfunction in a mouse model of 16p11.2 microdeletion 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.12.380501v1?rss=1"
</link>
<description><![CDATA[
Substantial evidence indicates that a microdeletion on human chromosome 16p11.2 is linked to neurodevelopmental disorders including autism spectrum disorders (ASD). Carriers of this deletion show divergent symptoms besides the core features of ASD, such as anxiety and emotional symptoms. The neural mechanisms underlying these symptoms are poorly understood. Here we report mice heterozygous for a deletion allele of the genomic region corresponding to the human 16p11.2 microdeletion locus (i.e., the  16p11.2 del/+ mice) have sex-specific anxiety-related behavioral and neural circuit changes. We found that female, but not male 16p11.2 del/+ mice showed enhanced fear generalization - a hallmark of anxiety disorders - after auditory fear conditioning, and displayed increased anxiety-like behaviors after physical restraint stress. Notably, such sex-specific behavioral changes were paralleled by an increase in activity in central amygdala neurons projecting to the globus pallidus in female, but not male 16p11.2 del/+ mice. Together, these results reveal female-specific anxiety phenotypes related to 16p11.2 microdeletion syndrome and a potential underlying neural circuit mechanism. Our study therefore identifies previously underappreciated sex-specific behavioral and neural changes in a genetic model of 16p11.2 microdeletion syndrome, and highlights the importance of investigating female-specific aspects of this syndrome for targeted treatment strategies.
]]></description>
<dc:creator>Giovanniello, J. R.</dc:creator>
<dc:creator>Ahrens, S.</dc:creator>
<dc:creator>Yu, K.</dc:creator>
<dc:creator>Li, B.</dc:creator>
<dc:date>2020-11-15</dc:date>
<dc:identifier>doi:10.1101/2020.11.12.380501</dc:identifier>
<dc:title><![CDATA[Sex-specific stress-related behavioral phenotypes and central amygdala dysfunction in a mouse model of 16p11.2 microdeletion]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.11.378893v1?rss=1">
<title>
<![CDATA[
Glia actively sculpt sensory neurons by controlled phagocytosis to tune animal behavior 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.11.378893v1?rss=1"
</link>
<description><![CDATA[
Glia in the central nervous system engulf neuron fragments during synapse remodeling and recycling of photoreceptor outer-segments. Whether glia passively clear shed neuronal debris, or actively remove neuron fragments is unknown. How pruning of single-neuron endings impacts animal behavior is also unclear. Here we report that adult C. elegans AMsh glia engulf sensory endings of the AFD thermosensory neuron. Engulfment is regulated by temperature, AFDs sensory input, and tracks AFD activity. Phosphatidylserine (PS) flippase TAT-1/ATP8A, functions with glial PS-receptor PSR-1/PSR and PAT-2/-integrin to initiate engulfment. Glial CED-10/Rac1 GTPase, acting through a conserved GEF complex, executes phagocytosis using the actin-remodeler WSP-1/nWASp and the membrane-sealing factor EFF-1 fusogen. CED-10 levels determine engulfment rates, and engulfment-defective mutants exhibit altered AFD-ending shape and thermosensory behavior. Our findings reveal a molecular pathway underpinning glia-dependent phagocytosis in a peripheral sense-organ, and demonstrate that glia actively engulf neuron-fragments, with profound consequences on neuron shape and animal behavior.
]]></description>
<dc:creator>Raiders, S.</dc:creator>
<dc:creator>Black, E. C.</dc:creator>
<dc:creator>Bae, A.</dc:creator>
<dc:creator>MacFarlane, S.</dc:creator>
<dc:creator>Shaham, S.</dc:creator>
<dc:creator>Singhvi, A.</dc:creator>
<dc:date>2020-11-12</dc:date>
<dc:identifier>doi:10.1101/2020.11.11.378893</dc:identifier>
<dc:title><![CDATA[Glia actively sculpt sensory neurons by controlled phagocytosis to tune animal behavior]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.18.389171v1?rss=1">
<title>
<![CDATA[
Developmental dynamics of voltage-gated sodium channel isoform expression in the human and mouse neocortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.18.389171v1?rss=1"
</link>
<description><![CDATA[
ObjectiveGenetic variants in the voltage-gated sodium channels SCN1A, SCN2A, SCN3A, and SCN8A are leading causes of epilepsy, developmental delay, and autism spectrum disorder. The mRNA splicing patterns of all four genes vary across development in the rodent brain, including mutually exclusive copies of the fifth protein-coding exon detected in the neonate (5N) and adult (5A). A second pair of mutually exclusive exons is reported in SCN8A only (18N and 18A). We aimed to quantify the expression of individual exons in the developing human neocortex.

MethodsRNA-seq data from 176 human dorsolateral prefrontal cortex samples across development were analyzed to estimate exon-level expression. Developmental changes in exon utilization were validated by assessing intron splicing. Exon expression was also estimated in RNA-seq data from 58 developing mouse neocortical samples.

ResultsIn the mature human neocortex, exon 5A is consistently expressed at least 4-fold higher than exon 5N in all four genes. For SCN2A, SCN3A, and SCN8A a synchronized 5N/5A transition occurs between 24 post-conceptual weeks (2nd trimester) and six years of age. In mice, the equivalent 5N/5A transition begins at or before embryonic day 15.5. In SCN8A, over 90% of transcripts in the mature human cortex include exon 18A. Early in fetal development, most transcripts include 18N or skip both 18N and 18A, with a transition to 18A inclusion occurring from 13 post-conceptual weeks to 6 months of age. No other protein-coding exons showed comparably dynamic developmental trajectories.

SignificanceSplice isoforms, which alter the biophysical properties of the encoded channels, may account for some of the observed phenotypic differences across development and between specific variants. Manipulation of the proportion of splicing isoforms at appropriate stages of development may act as a therapeutic strategy for specific mutations or even epilepsy in general.
]]></description>
<dc:creator>Liang, L.</dc:creator>
<dc:creator>Fazel Darbandi, S.</dc:creator>
<dc:creator>Pochareddy, S.</dc:creator>
<dc:creator>Gulden, F. O.</dc:creator>
<dc:creator>Gilson, M. C.</dc:creator>
<dc:creator>Sheppard, B. K.</dc:creator>
<dc:creator>Sahagun, A.</dc:creator>
<dc:creator>An, J.-Y.</dc:creator>
<dc:creator>Werling, D. M.</dc:creator>
<dc:creator>Rubenstein, J. L. R.</dc:creator>
<dc:creator>Sestan, N.</dc:creator>
<dc:creator>Bender, K.</dc:creator>
<dc:creator>Sanders, S. J.</dc:creator>
<dc:date>2020-11-18</dc:date>
<dc:identifier>doi:10.1101/2020.11.18.389171</dc:identifier>
<dc:title><![CDATA[Developmental dynamics of voltage-gated sodium channel isoform expression in the human and mouse neocortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.25.006643v1?rss=1">
<title>
<![CDATA[
The need to connect: Acute social isolation causes neural craving responses similar to hunger. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.25.006643v1?rss=1"
</link>
<description><![CDATA[
When people are forced to be isolated from one another, do they crave social interactions? To address this question, we used functional magnetic resonance imaging (fMRI) to measure neural responses evoked by food and social cues after participants (n=40) experienced ten hours of mandated fasting or total social isolation. After isolation, people felt lonely and craved social interaction. Midbrain regions showed selective activation to food cues after fasting and to social cues after isolation; these responses were correlated with self-reported craving. By contrast, striatal and cortical regions differentiated between craving food versus social interaction. Across deprivation sessions, we find that deprivation narrows and focuses the brains motivational responses to the deprived target. Our results support the intuitive idea that acute isolation causes social craving, similar to the way fasting causes hunger.
]]></description>
<dc:creator>Tomova, L.</dc:creator>
<dc:creator>Wang, K.</dc:creator>
<dc:creator>Thompson, T.</dc:creator>
<dc:creator>Matthews, G.</dc:creator>
<dc:creator>Takahashi, A.</dc:creator>
<dc:creator>Tye, K.</dc:creator>
<dc:creator>Saxe, R.</dc:creator>
<dc:date>2020-03-26</dc:date>
<dc:identifier>doi:10.1101/2020.03.25.006643</dc:identifier>
<dc:title><![CDATA[The need to connect: Acute social isolation causes neural craving responses similar to hunger.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.26.394676v1?rss=1">
<title>
<![CDATA[
Can machine learning aid in identifying disease genes? The case of autism spectrum disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.26.394676v1?rss=1"
</link>
<description><![CDATA[
Discovering genes involved in complex human genetic disorders is a major challenge. Many have suggested that machine learning (ML) algorithms using gene networks can be used to supplement traditional genetic association-based approaches to predict or prioritize disease genes. However, questions have been raised about the utility of ML methods for this type of task due to biases within the data, and poor real-world performance. Using autism spectrum disorder (ASD) as a test case, we sought to investigate the question: Can machine learning aid in the discovery of disease genes? We collected thirteen published ASD gene prioritization studies and evaluated their performance using known and novel high-confidence ASD genes. We also investigated their biases towards generic gene annotations, like number of association publications. We found that ML methods which do not incorporate genetics information have limited utility for prioritization of ASD risk genes. These studies perform at a comparable level to generic measures of likelihood for the involvement of genes in any condition, and do not out-perform genetic association studies. Future efforts to discover disease genes should be focused on developing and validating statistical models for genetic association, specifically for association between rare variants and disease, rather than developing complex machine learning methods using complex heterogeneous biological data with unknown reliability.
]]></description>
<dc:creator>Gunning, M.</dc:creator>
<dc:creator>Pavlidis, P.</dc:creator>
<dc:date>2020-11-27</dc:date>
<dc:identifier>doi:10.1101/2020.11.26.394676</dc:identifier>
<dc:title><![CDATA[Can machine learning aid in identifying disease genes? The case of autism spectrum disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.09.418590v1?rss=1">
<title>
<![CDATA[
Developmental loss of ErbB4 in PV interneurons disrupts state-dependent cortical circuit dynamics. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.09.418590v1?rss=1"
</link>
<description><![CDATA[
GABAergic inhibition plays an important role in the establishment and maintenance of cortical circuits during development. Neuregulin 1 (Nrg1) and its interneuron-specific receptor ErbB4 are key elements of a signaling pathway critical for the maturation and proper synaptic connectivity of interneurons. Using conditional deletions of the ERBB4 gene in mice, we tested the role of this signaling pathway at two developmental timepoints in parvalbumin-expressing (PV) interneurons, the largest subpopulation of cortical GABAergic cells. Loss of ErbB4 in PV interneurons during embryonic, but not late postnatal, development leads to alterations in the activity of excitatory and inhibitory cortical neurons, along with severe disruption of cortical temporal organization. These impairments emerge by the end of the second postnatal week, prior to the complete maturation of the PV interneurons themselves. Early loss of ErbB4 in PV interneurons also results in profound dysregulation of excitatory pyramidal neuron dendritic architecture and a redistribution of spine density at the apical dendritic tuft. In association with these deficits, excitatory cortical neurons exhibit normal tuning for sensory inputs, but a loss of state-dependent modulation of the gain of sensory responses. Together these data support a key role for early developmental Nrg1/ErbB4 signaling in PV interneurons as powerful mechanism underlying the maturation of both the inhibitory and excitatory components of cortical circuits.
]]></description>
<dc:creator>Batista-Brito, R.</dc:creator>
<dc:creator>Majumdar, A.</dc:creator>
<dc:creator>Nuno, A.</dc:creator>
<dc:creator>Vinck, M.</dc:creator>
<dc:creator>Cardin, J. A.</dc:creator>
<dc:date>2020-12-10</dc:date>
<dc:identifier>doi:10.1101/2020.12.09.418590</dc:identifier>
<dc:title><![CDATA[Developmental loss of ErbB4 in PV interneurons disrupts state-dependent cortical circuit dynamics.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.14.422645v1?rss=1">
<title>
<![CDATA[
Chromatin remodeler Arid1a regulates subplate neuron identity and wiring of cortical connectivity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.14.422645v1?rss=1"
</link>
<description><![CDATA[
Loss-of-function mutations in chromatin remodeler gene ARID1A are a cause of Coffin-Siris syndrome, a developmental disorder characterized by dysgenesis of corpus callosum. Here, we characterize Arid1a function during cortical development and find unexpectedly selective roles for Arid1a in subplate neurons. Subplate neurons (SPNs), strategically positioned at the interface of cortical grey and white matter, orchestrate multiple developmental processes indispensable for neural circuit wiring. We find that pan-cortical deletion of Arid1a leads to extensive mistargeting of intracortical axons and agenesis of corpus callosum. Sparse Arid1a deletion, however, does not autonomously misroute callosal axons, implicating non-cell autonomous Arid1a functions in axon guidance. Supporting this possibility, the ascending axons of thalamocortical neurons, which are not autonomously affected by cortical Arid1a deletion, are also disrupted in their pathfinding into cortex and innervation of whisker barrels. Coincident with these miswiring phenotypes, which are reminiscent of subplate ablation, we unbiasedly find a selective loss of SPN gene expression following Arid1a deletion. In addition, multiple characteristics of SPNs crucial to their wiring functions, including subplate organization, subplate-thalamocortical axon co-fasciculation ("handshake"), and extracellular matrix, are severely disrupted. To empirically test Arid1a sufficiency in subplate, we generate a cortical plate deletion of Arid1a that spares SPNs. In this model, subplate Arid1a expression is sufficient for subplate-thalamocortical axon co-fasciculation and extracellular matrix assembly. Consistent with these wiring functions, subplate Arid1a sufficiently enables normal callosum formation, thalamocortical axon targeting, and whisker barrel development. Thus, Arid1a is a multifunctional regulator of subplate-dependent guidance mechanisms essential to cortical circuit wiring.

SignificanceThe cognitive, perceptive, and motor capabilities of the mammalian cerebral cortex depend on assembly of circuit connectivity during development. Subplate neurons, strategically located at the junction of grey and white matter, orchestrate the wiring of cortical circuits. Using a new approach to study gene necessity and sufficiency in subplate neurons, we uncover an essential role for chromatin remodeler Arid1a in subplate neuron gene expression and axon guidance functions. Cortical deletion of Arid1a disrupts subplate-dependent formation of corpus callosum, targeting of thalamocortical axons, and development of sensory maps. Together, our study identifies Arid1a as a central regulator of subplate-dependent axon pathfinding, establishes subplate function as essential to callosum development, and highlights non-cell autonomous mechanisms in neural circuit formation and disorders thereof.
]]></description>
<dc:creator>Doyle, D. Z.</dc:creator>
<dc:creator>Lam, M. M.</dc:creator>
<dc:creator>Qalieh, A.</dc:creator>
<dc:creator>Qalieh, Y.</dc:creator>
<dc:creator>Sorel, A.</dc:creator>
<dc:creator>Funk, O. H.</dc:creator>
<dc:creator>Kwan, K. Y.</dc:creator>
<dc:date>2020-12-14</dc:date>
<dc:identifier>doi:10.1101/2020.12.14.422645</dc:identifier>
<dc:title><![CDATA[Chromatin remodeler Arid1a regulates subplate neuron identity and wiring of cortical connectivity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.30.424813v1?rss=1">
<title>
<![CDATA[
Drosophila functional screening of de novo variants in autism uncovers deleterious variants and facilitates discovery of rare neurodevelopmental diseases 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.30.424813v1?rss=1"
</link>
<description><![CDATA[
Individuals with autism spectrum disorders (ASD) exhibit an increased burden of de novo variants in a broadening range of genes. We functionally tested the effects of ASD missense variants using Drosophila through  humanization rescue and overexpression-based strategies. We studied 79 ASD variants in 74 genes identified in the Simons Simplex Collection and found 38% of them caused functional alterations. Moreover, we identified GLRA2 as the cause of a spectrum of neurodevelopmental phenotypes beyond ASD in eight previously undiagnosed subjects. Functional characterization of variants in ASD candidate genes point to conserved neurobiological mechanisms and facilitates gene discovery for rare neurodevelopmental diseases.
]]></description>
<dc:creator>Marcogliese, P. C.</dc:creator>
<dc:creator>Deal, S. L.</dc:creator>
<dc:creator>Andrews, J.</dc:creator>
<dc:creator>Harnish, J. M.</dc:creator>
<dc:creator>Bhavana, V. H.</dc:creator>
<dc:creator>Graves, H. K.</dc:creator>
<dc:creator>Jangam, S.</dc:creator>
<dc:creator>Luo, X.</dc:creator>
<dc:creator>Liu, N.</dc:creator>
<dc:creator>Bei, D.</dc:creator>
<dc:creator>Chao, Y.-H.</dc:creator>
<dc:creator>Hull, B.</dc:creator>
<dc:creator>Lee, P.-T.</dc:creator>
<dc:creator>Pan, H.</dc:creator>
<dc:creator>Longley, C. M.</dc:creator>
<dc:creator>Chao, H.-T.</dc:creator>
<dc:creator>Chung, H.</dc:creator>
<dc:creator>Haelterman, N. A.</dc:creator>
<dc:creator>Kanca, O.</dc:creator>
<dc:creator>Manivannan, S. N.</dc:creator>
<dc:creator>Rossetti, L. Z.</dc:creator>
<dc:creator>Gerard, A.</dc:creator>
<dc:creator>Schwaibold, E. M. C.</dc:creator>
<dc:creator>Guerrini, R.</dc:creator>
<dc:creator>Vetro, A.</dc:creator>
<dc:creator>England, E.</dc:creator>
<dc:creator>Murali, C. N.</dc:creator>
<dc:creator>Barakat, T. S.</dc:creator>
<dc:creator>van Dooren, M. F.</dc:creator>
<dc:creator>Wilke, M.</dc:creator>
<dc:creator>van Slegtenhorst, M.</dc:creator>
<dc:creator>Lesca, G.</dc:creator>
<dc:creator>Sabatier, I.</dc:creator>
<dc:creator>Chatron, N.</dc:creator>
<dc:creator>Brownstein, C. A.</dc:creator>
<dc:creator>Madden, J. A.</dc:creator>
<dc:creator>Agrawal, P. B.</dc:creator>
<dc:creator>Keller, R.</dc:creator>
<dc:creator>Pavinato, L.</dc:creator>
<dc:creator>Brusco, A.</dc:creator>
<dc:creator>Rosenfeld, J. A.</dc:creator>
<dc:creator>Marom, R.</dc:creator>
<dc:creator>Wangler,</dc:creator>
<dc:date>2021-01-01</dc:date>
<dc:identifier>doi:10.1101/2020.12.30.424813</dc:identifier>
<dc:title><![CDATA[Drosophila functional screening of de novo variants in autism uncovers deleterious variants and facilitates discovery of rare neurodevelopmental diseases]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-01-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.17.423129v1?rss=1">
<title>
<![CDATA[
Broad transcriptomic dysregulation across the cerebral cortex in ASD 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.17.423129v1?rss=1"
</link>
<description><![CDATA[
Classically, psychiatric disorders have been considered to lack defining pathology, but recent work has demonstrated consistent disruption at the molecular level, characterized by transcriptomic and epigenetic alterations.1-3 In ASD, upregulation of microglial, astrocyte, and immune signaling genes, downregulation of specific synaptic genes, and attenuation of regional gene expression differences are observed.1,2,4-6 However, whether these changes are limited to the cortical association areas profiled is unknown. Here, we perform RNA-sequencing (RNA-seq) on 725 brain samples spanning 11 distinct cortical areas in 112 ASD cases and neurotypical controls. We identify substantially more genes and isoforms that differentiate ASD from controls than previously observed. These alterations are pervasive and cortex-wide, but vary in magnitude across regions, roughly showing an anterior to posterior gradient, with the strongest signal in visual cortex, followed by parietal cortex and the temporal lobe. We find a notable enrichment of ASD genetic risk variants among cortex-wide downregulated synaptic plasticity genes and upregulated protein folding gene isoforms. Finally, using snRNA-seq, we determine that regional variation in the magnitude of transcriptomic dysregulation reflects changes in cellular proportion and cell-type-specific gene expression, particularly impacting L3/4 excitatory neurons. These results highlight widespread, genetically-driven neuronal dysfunction as a major component of ASD pathology in the cerebral cortex, extending beyond association cortices to involve primary sensory regions.
]]></description>
<dc:creator>Haney, J. R.</dc:creator>
<dc:creator>Wamsley, B.</dc:creator>
<dc:creator>Chen, G. T.</dc:creator>
<dc:creator>Parhami, S.</dc:creator>
<dc:creator>Emani, P. S.</dc:creator>
<dc:creator>Chang, N.</dc:creator>
<dc:creator>Hoftman, G. D.</dc:creator>
<dc:creator>de Alba, D.</dc:creator>
<dc:creator>Kale, G.</dc:creator>
<dc:creator>Ramaswami, G.</dc:creator>
<dc:creator>Hartl, C. L.</dc:creator>
<dc:creator>Jin, T.</dc:creator>
<dc:creator>Wang, D.</dc:creator>
<dc:creator>Ou, J.</dc:creator>
<dc:creator>Wu, Y. E.</dc:creator>
<dc:creator>Parikshak, N. N.</dc:creator>
<dc:creator>Swarup, V.</dc:creator>
<dc:creator>Belgard, T. G.</dc:creator>
<dc:creator>Gerstein, M.</dc:creator>
<dc:creator>Pasaniuc, B.</dc:creator>
<dc:creator>Gandal, M. J.</dc:creator>
<dc:creator>Geschwind, D. H.</dc:creator>
<dc:date>2020-12-18</dc:date>
<dc:identifier>doi:10.1101/2020.12.17.423129</dc:identifier>
<dc:title><![CDATA[Broad transcriptomic dysregulation across the cerebral cortex in ASD]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.01.20.427439v1?rss=1">
<title>
<![CDATA[
Human neuronal networks on micro-electrode arrays are a highly robust tool to study disease-specific genotype-phenotype correlations in vitro 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.01.20.427439v1?rss=1"
</link>
<description><![CDATA[
Micro-electrode arrays (MEAs) are increasingly used to characterize neuronal network activity of human induced pluripotent stem-cell (hiPSC)-derived neurons. Despite their gain in popularity, MEA recordings from hiPSC-derived neuronal networks are not always used to their full potential in respect to experimental design, execution and data analysis. Therefore, we benchmarked the robustness and sensitivity of MEA-derived neuronal activity patterns derived from ten healthy individual control lines. We provide recommendations on experimental design and analysis to achieve standardization. With such standardization, MEAs can be used as a reliable platform to distinguish (disease-specific) network phenotypes. In conclusion, we show that MEAs are a powerful and robust tool to uncover functional neuronal network phenotypes from hiPSC-derived neuronal networks, and provide an important resource to advance the hiPSC field towards the use of MEAs for disease-phenotyping and drug discovery.
]]></description>
<dc:creator>Mossink, B.</dc:creator>
<dc:creator>Verboven, A. H. A.</dc:creator>
<dc:creator>van Hugte, E. J. H.</dc:creator>
<dc:creator>Klein Gunnewiek, T. M.</dc:creator>
<dc:creator>Parodi, G.</dc:creator>
<dc:creator>Linda, K.</dc:creator>
<dc:creator>Schoenmaker, C.</dc:creator>
<dc:creator>Kleefstra, T.</dc:creator>
<dc:creator>Kozicz, T.</dc:creator>
<dc:creator>van Bokhoven, H.</dc:creator>
<dc:creator>Schubert, D.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:creator>Frega, M.</dc:creator>
<dc:date>2021-01-21</dc:date>
<dc:identifier>doi:10.1101/2021.01.20.427439</dc:identifier>
<dc:title><![CDATA[Human neuronal networks on micro-electrode arrays are a highly robust tool to study disease-specific genotype-phenotype correlations in vitro]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-01-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.02.429423v1?rss=1">
<title>
<![CDATA[
Paradoxical hyperexcitability from NaV1.2 sodium channel loss in neocortical pyramidal cells 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.02.429423v1?rss=1"
</link>
<description><![CDATA[
Loss-of-function variants in the gene SCN2A, which encodes the sodium channel NaV1.2, are strongly associated with autism spectrum disorder and intellectual disability. An estimated 20-30% of children with these variants are co-morbid for epilepsy, with altered neuronal activity originating in neocortex, a region where NaV1.2 channels are expressed predominantly in excitatory pyramidal cells. This is paradoxical, as sodium channel loss in excitatory cells would be expected to dampen neocortical activity rather than promote seizure. Here, we examined pyramidal neurons lacking NaV1.2 channels and found that they were intrinsically hyperexcitable, firing high-frequency bursts of action potentials (APs) despite decrements in AP size and speed. Compartmental modeling and dynamic clamp recordings revealed that NaV1.2 loss prevented potassium channels from properly repolarizing neurons between APs, increasing overall excitability by allowing neurons to reach threshold for subsequent APs more rapidly. This cell-intrinsic mechanism may therefore account for why SCN2A loss-of-function can paradoxically promote seizure.
]]></description>
<dc:creator>Spratt, P. W.</dc:creator>
<dc:creator>Ben-Shalom, R.</dc:creator>
<dc:creator>Sahagun, A.</dc:creator>
<dc:creator>Keeshen, C. M.</dc:creator>
<dc:creator>Sanders, S. J.</dc:creator>
<dc:creator>Bender, K. J.</dc:creator>
<dc:date>2021-02-02</dc:date>
<dc:identifier>doi:10.1101/2021.02.02.429423</dc:identifier>
<dc:title><![CDATA[Paradoxical hyperexcitability from NaV1.2 sodium channel loss in neocortical pyramidal cells]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.10.427198v1?rss=1">
<title>
<![CDATA[
Customized de novo mutation detection for any variant calling pipeline: SynthDNM 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.10.427198v1?rss=1"
</link>
<description><![CDATA[
MotivationAs sequencing technologies and analysis pipelines evolve, DNM calling tools must be adapted. Therefore, a flexible approach is needed that can accurately identify de novo mutations from genome or exome sequences from a variety of datasets and variant calling pipelines.

ResultsHere, we describe SynthDNM, a random-forest based classifier that can be readily adapted to new sequencing or variant-calling pipelines by applying a flexible approach to constructing simulated training examples from real data. The optimized SynthDNM classifiers predict de novo SNPs and indels with robust accuracy across multiple methods of variant calling.

AvailabilitySynthDNM is freely available on Github (https://github.com/james-guevara/synthdnm)

Contactjsebat@ucsd.edu

Supplementary informationSupplementary data are available at Bioinformatics online.
]]></description>
<dc:creator>Lian, A.</dc:creator>
<dc:creator>Guevara, J.</dc:creator>
<dc:creator>Xia, K.</dc:creator>
<dc:creator>Sebat, J.</dc:creator>
<dc:date>2021-02-10</dc:date>
<dc:identifier>doi:10.1101/2021.02.10.427198</dc:identifier>
<dc:title><![CDATA[Customized de novo mutation detection for any variant calling pipeline: SynthDNM]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.10.430669v1?rss=1">
<title>
<![CDATA[
Mice Make Targeted Saccades 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.10.430669v1?rss=1"
</link>
<description><![CDATA[
Animals investigate their environments by directing their gaze towards salient stimuli. In the prevailing view, mouse gaze shifts are led by head rotations that trigger compensatory, brainstem-mediated eye movements, including saccades to reset the eyes. These "recentering" saccades are attributed to head movement-related vestibular and optokinetic cues. However, microstimulating mouse superior colliculus (SC) elicits directed head and eye movements that resemble SC-dependent sensory-guided gaze shifts made by other species, raising the possibility mice generate additional types of gaze shifts. We investigated this possibility by tracking eye and attempted head movements in a head-fixed preparation that eliminates head movement-related sensory cues. We found tactile stimuli evoke gaze shifts involving directed saccades that precede attempted head rotations. Optogenetic perturbations revealed SC drives touch-evoked gaze shifts. Thus, mice make sensory-guided, SC-dependent gaze shifts led by directed saccades. Our findings uncover diversity in mouse gaze shifts and provide a foundation for studying head-eye coupling.
]]></description>
<dc:creator>Zahler, S. H.</dc:creator>
<dc:creator>Taylor, D. E.</dc:creator>
<dc:creator>Adams, J. M.</dc:creator>
<dc:creator>Feinberg, E. H.</dc:creator>
<dc:date>2021-02-11</dc:date>
<dc:identifier>doi:10.1101/2021.02.10.430669</dc:identifier>
<dc:title><![CDATA[Mice Make Targeted Saccades]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.03.16.435742v1?rss=1">
<title>
<![CDATA[
fmr1 mutation interacts with sensory experience to alter the early development of behavior and sensory coding in zebrafish 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.03.16.435742v1?rss=1"
</link>
<description><![CDATA[
While Autism Spectrum Disorders (ASDs) are developmental in origin little is known about how they affect the early development of behavior and sensory coding, or how this is modulated by the sensory environment. The most common inherited form of autism is Fragile X syndrome, caused by a mutation in FMR1. Here we show that zebrafish fmr1-/- mutant larvae raised in a naturalistic visual environment display early deficits in hunting behavior, tectal map development, tectal network properties and decoding of spatial stimuli. However when given a choice they preferred an environment with reduced visual stimulation, and rearing them in this environment improved these metrics. Older fmr1-/- fish showed differences in social behavior, spending more time observing a conspecific, but responding more slowly to social cues. Together these results help reveal how fmr1-/- changes the early development of vertebrate brain function, and how manipulating the environment could potentially help reduce these changes.
]]></description>
<dc:creator>Zhu, S.</dc:creator>
<dc:creator>McCullough, M.</dc:creator>
<dc:creator>Pujic, Z.</dc:creator>
<dc:creator>Sibberas, J.</dc:creator>
<dc:creator>Sun, B.</dc:creator>
<dc:creator>Bucknall, B.</dc:creator>
<dc:creator>Avitan, L.</dc:creator>
<dc:creator>Goodhill, G.</dc:creator>
<dc:date>2021-03-17</dc:date>
<dc:identifier>doi:10.1101/2021.03.16.435742</dc:identifier>
<dc:title><![CDATA[fmr1 mutation interacts with sensory experience to alter the early development of behavior and sensory coding in zebrafish]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-03-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.03.30.437620v1?rss=1">
<title>
<![CDATA[
NRF1 Association with AUTS2-Polycomb Mediates Specific Gene Activation in the Brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.03.30.437620v1?rss=1"
</link>
<description><![CDATA[
The heterogeneous complexes comprising the family of Polycomb Repressive Complex 1 (PRC1) are instrumental to establishing facultative heterochromatin that is repressive to transcription. Yet, two PRC1 species, PRC1.3 and PRC1.5, are known to comprise novel components, AUTS2, P300, and CK2 that convert this repressive function to that of transcription activation. Here, we report that patients harboring mutations in the HX repeat domain of AUTS2 exhibit defects in AUTS2 and P300 interaction as well as a developmental disorder reflective of Rubinstein-Taybi syndrome, which is mostly associated with a heterozygous pathogenic variant in CREBBP/EP300. As well, the absence of AUTS2 gives rise to a mis-regulation of a subset of developmental genes and curtails motor neuron differentiation from embryonic stem cells in the context of a well-defined system. Moreover, the transcription factor, Nuclear Respiratory Factor 1 (NRF1) exhibits a novel and integral role in this aspect of the neurodevelopmental process, being required for PRC1.3 recruitment to chromatin.
]]></description>
<dc:creator>Liu, S.</dc:creator>
<dc:creator>Aldinger, K. A.</dc:creator>
<dc:creator>Cheng, C. V.</dc:creator>
<dc:creator>Kiyama, T.</dc:creator>
<dc:creator>Dave, M.</dc:creator>
<dc:creator>McNamara, H. K.</dc:creator>
<dc:creator>Caraffi, S. G.</dc:creator>
<dc:creator>Ivanovski, I.</dc:creator>
<dc:creator>Errichiello, E.</dc:creator>
<dc:creator>Zweier, C.</dc:creator>
<dc:creator>Zuffardi, O.</dc:creator>
<dc:creator>Schneider, M.</dc:creator>
<dc:creator>Papavasiliou, A. S.</dc:creator>
<dc:creator>Perry, M. S.</dc:creator>
<dc:creator>Cho, M. T.</dc:creator>
<dc:creator>Weber, A.</dc:creator>
<dc:creator>Swale, A.</dc:creator>
<dc:creator>Badea, T. C.</dc:creator>
<dc:creator>Mao, C.-A.</dc:creator>
<dc:creator>Garavelli, L.</dc:creator>
<dc:creator>Dobyns, W. B.</dc:creator>
<dc:creator>Reinberg, D.</dc:creator>
<dc:date>2021-03-30</dc:date>
<dc:identifier>doi:10.1101/2021.03.30.437620</dc:identifier>
<dc:title><![CDATA[NRF1 Association with AUTS2-Polycomb Mediates Specific Gene Activation in the Brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-03-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.03.31.437118v1?rss=1">
<title>
<![CDATA[
Microglia complement signaling promotes neuronal elimination and normal brain functional connectivity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.03.31.437118v1?rss=1"
</link>
<description><![CDATA[
Complement signaling is thought to serve as an opsonization signal to promote the phagocytosis of synapses by microglia. However, while its role in synaptic remodeling has been demonstrated in the retino-thalamic system, it remains unclear whether complement signaling mediates synaptic pruning in the brain more generally. Here we show that mice lacking the complement 3 receptor (C3r), the major microglia complement receptor, fail to show a deficit in either synaptic pruning or axon elimination in the developing mouse cortex. Instead, mice lacking C3r show a deficit in the perinatal elimination of neurons, both in the retina as well as in the cortex, a deficit that is associated with increased cortical thickness and enhanced functional connectivity in these regions in adulthood. These data demonstrate a preferential role for complement in promoting neuronal elimination in the developing brain and argue for a reconsideration of the role of complement in synaptic pruning.
]]></description>
<dc:creator>Deivasigamani, S.</dc:creator>
<dc:creator>Miteva, M. T.</dc:creator>
<dc:creator>Natale, S.</dc:creator>
<dc:creator>Gutierrez-Barragan, D.</dc:creator>
<dc:creator>Basilico, B.</dc:creator>
<dc:creator>Di Angelantonio, S.</dc:creator>
<dc:creator>Pape, C.</dc:creator>
<dc:creator>Bolasco, G.</dc:creator>
<dc:creator>Galbusera, A.</dc:creator>
<dc:creator>Gozzi, A.</dc:creator>
<dc:creator>Ragozzino, D.</dc:creator>
<dc:creator>Gross, C. T.</dc:creator>
<dc:date>2021-04-02</dc:date>
<dc:identifier>doi:10.1101/2021.03.31.437118</dc:identifier>
<dc:title><![CDATA[Microglia complement signaling promotes neuronal elimination and normal brain functional connectivity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-04-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.07.438852v1?rss=1">
<title>
<![CDATA[
Autism risk gene POGZ promotes chromatin accessibility and expression of clustered synaptic genes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.07.438852v1?rss=1"
</link>
<description><![CDATA[
De novo mutations in POGZ, which encodes the chromatin regulator Pogo Transposable Element with ZNF Domain protein, are strongly associated with autism spectrum disorder (ASD). Here we find that in the developing mouse and human brain POGZ binds predominantly euchromatic loci and these are enriched for human neurodevelopmental disorder genes and transposable elements. We profile chromatin accessibility and gene expression in Pogz-/- mice and find that POGZ promotes chromatin accessibility of candidate regulatory elements (REs) and the expression of clustered synaptic genes. We further demonstrate that POGZ forms a nuclear complex and co-occupies loci with HP1{gamma} and ADNP, another high-confidence ASD risk gene. In Pogz+/- mice, Adnp expression is reduced. We postulate that reduced POGZ dosage disrupts cortical function through alterations in the POGZ-ADNP balance which modifies neuronal gene expression.
]]></description>
<dc:creator>Markenscoff, E.</dc:creator>
<dc:creator>Binyameen, F.</dc:creator>
<dc:creator>Whalen, S.</dc:creator>
<dc:creator>Price, J.</dc:creator>
<dc:creator>Lim, K.</dc:creator>
<dc:creator>Catta-Preta, R.</dc:creator>
<dc:creator>Pai, E. L.-L.</dc:creator>
<dc:creator>Mu, X.</dc:creator>
<dc:creator>Xu, D.</dc:creator>
<dc:creator>Pollard, K. S.</dc:creator>
<dc:creator>Nord, A.</dc:creator>
<dc:creator>State, M. W.</dc:creator>
<dc:creator>Rubenstein, J. L. R.</dc:creator>
<dc:date>2021-04-08</dc:date>
<dc:identifier>doi:10.1101/2021.04.07.438852</dc:identifier>
<dc:title><![CDATA[Autism risk gene POGZ promotes chromatin accessibility and expression of clustered synaptic genes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-04-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.18.253443v1?rss=1">
<title>
<![CDATA[
Atypical genomic patterning of the cerebral cortex in autism with poor early language outcome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.18.253443v1?rss=1"
</link>
<description><![CDATA[
Cortical regional identities develop through anterior-posterior (A-P) and dorsal-ventral (D-V) prenatal genomic patterning gradients. Here we find that A-P and D-V genomic patterning of cortical surface area (SA) and thickness (CT) is intact in typically developing and autistic toddlers with good language outcome, but is absent in autistic toddlers with poor early language outcome. Genes driving this effect are prominent in midgestational A-P and D-V gene expression gradients and prenatal cell types driving SA and CT variation (e.g., progenitor cells versus excitatory neurons). These genes are also important for vocal learning, human-specific evolution, and prenatal co-expression networks enriched for high-penetrance autism risk genes. Autism with poor early language outcome may be linked to atypical genomic cortical patterning starting in prenatal periods and which impacts later development of regional functional specialization and circuit formation.

One Sentence SummaryGenomic patterning of the cortex is atypical in autistic toddlers with poor early language outcome.
]]></description>
<dc:creator>Lombardo, M. V.</dc:creator>
<dc:creator>Eyler, L.</dc:creator>
<dc:creator>Pramparo, T.</dc:creator>
<dc:creator>Gazestani, V. H.</dc:creator>
<dc:creator>Hagler, D. J.</dc:creator>
<dc:creator>Chen, C.-H.</dc:creator>
<dc:creator>Dale, A. M.</dc:creator>
<dc:creator>Seidlitz, J.</dc:creator>
<dc:creator>Bethlehem, R. A. I.</dc:creator>
<dc:creator>Bertelsen, N.</dc:creator>
<dc:creator>Carter Barnes, C.</dc:creator>
<dc:creator>Lopez, L.</dc:creator>
<dc:creator>Campbell, K.</dc:creator>
<dc:creator>Lewis, N. E.</dc:creator>
<dc:creator>Pierce, K.</dc:creator>
<dc:creator>Courchesne, E.</dc:creator>
<dc:date>2020-08-18</dc:date>
<dc:identifier>doi:10.1101/2020.08.18.253443</dc:identifier>
<dc:title><![CDATA[Atypical genomic patterning of the cerebral cortex in autism with poor early language outcome]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.07.20.452995v1?rss=1">
<title>
<![CDATA[
ASXL3 controls cortical neuron fate specification through extrinsic self-renewal pathways 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.07.20.452995v1?rss=1"
</link>
<description><![CDATA[
During corticogenesis, transcription plasticity is fundamental to the restriction of neural progenitor cell (NPC) multipotency and production of cortical neuron heterogeneity. Human and mouse genetic studies have highlighted the role of Polycomb transcriptional regulation in this process. ASXL3, which encodes a component of the Polycomb repressive deubiquitination (PR-DUB) complex, has been identified as a high confidence autism spectrum disorder (ASD) risk gene. Genetic inactivation of Asxl3, in a mouse model that carries a clinically relevant ASXL3 frameshift (Asxl3fs) variant, disrupts lateral expansion of NPCs and delays cortical neuron differentiation. Single-cell RNA sequencing analysis implicates Notch signaling, which alters the composition of excitatory neurons and fidelity of cortical layer deposition. Our data provides a new link between extrinsic signaling cues and intrinsic epigenetic regulation that together control the timing of cell fate programs. Furthermore, transcriptomic analysis revealed dysregulation of other known ASD risk genes indicating that a convergent developmental pathway is affected. Collectively our work provides important insights about developmental mechanisms that contribute to ASD neuropathology.
]]></description>
<dc:creator>McGrath, B. T.</dc:creator>
<dc:creator>Wu, P.</dc:creator>
<dc:creator>Salvi, S.</dc:creator>
<dc:creator>Girgla, N.</dc:creator>
<dc:creator>Xu, C.</dc:creator>
<dc:creator>Zhu, J.</dc:creator>
<dc:creator>KC, R.</dc:creator>
<dc:creator>Tsan, Y.-C.</dc:creator>
<dc:creator>Moccia, A.</dc:creator>
<dc:creator>Srivastava, A.</dc:creator>
<dc:creator>Zhou, X.</dc:creator>
<dc:creator>Bielas, S. L.</dc:creator>
<dc:date>2021-07-21</dc:date>
<dc:identifier>doi:10.1101/2021.07.20.452995</dc:identifier>
<dc:title><![CDATA[ASXL3 controls cortical neuron fate specification through extrinsic self-renewal pathways]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-07-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.05.01.538987v1?rss=1">
<title>
<![CDATA[
Towards Preclinical Validation of Arbaclofen (R-baclofen) Treatment for 16p11.2 Deletion Syndrome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.05.01.538987v1?rss=1"
</link>
<description><![CDATA[
A microdeletion on human chromosome 16p11.2 is one of the most common copy number variants associated with autism spectrum disorder and other neurodevelopmental disabilities. Arbaclofen, a GABA(B) receptor agonist, is a component of racemic baclofen, which is FDA-approved for treating spasticity, and has been shown to alleviate behavioral phenotypes, including recognition memory deficits, in animal models of 16p11.2 deletion. Given the lack of reproducibility sometimes observed in mouse behavioral studies, we brought together a consortium of four laboratories to study the effects of arbaclofen on behavior in three different mouse lines with deletions in the mouse region syntenic to human 16p11.2 to test the robustness of these findings. Arbaclofen rescued cognitive deficits seen in two 16p11.2 deletion mouse lines in traditional recognition memory paradigms. Using an unsupervised machine-learning approach to analyze behavior, one lab found that arbaclofen also rescued differences in exploratory behavior in the open field in 16p11.2 deletion mice. Arbaclofen was not sedating and had modest off-target behavioral effects at the doses tested. Our studies show that arbaclofen consistently rescues behavioral phenotypes in 16p11.2 deletion mice, providing support for clinical trials of arbaclofen in humans with this deletion.

One sentence summaryExperiments across four laboratories found that arbaclofen rescued cognitive deficits in mouse models of 16p11.2 deletion, without sedation or significant off-target behavioral effects.
]]></description>
<dc:creator>Gundersen, B. B.</dc:creator>
<dc:creator>O'Brien, W. T.</dc:creator>
<dc:creator>Schaffler, M. D.</dc:creator>
<dc:creator>Schultz, M. N.</dc:creator>
<dc:creator>Tsukahara, T.</dc:creator>
<dc:creator>Lorenzo, S. M.</dc:creator>
<dc:creator>Nalesso, V.</dc:creator>
<dc:creator>Clayton, A. H. L.</dc:creator>
<dc:creator>Abel, T.</dc:creator>
<dc:creator>Crawley, J. N.</dc:creator>
<dc:creator>Datta, S. R.</dc:creator>
<dc:creator>Herault, Y.</dc:creator>
<dc:date>2023-05-02</dc:date>
<dc:identifier>doi:10.1101/2023.05.01.538987</dc:identifier>
<dc:title><![CDATA[Towards Preclinical Validation of Arbaclofen (R-baclofen) Treatment for 16p11.2 Deletion Syndrome]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-05-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.03.25.534016v1?rss=1">
<title>
<![CDATA[
Cell-type-specificity of isoform diversity in the developing human neocortex informs mechanisms of neurodevelopmental disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.03.25.534016v1?rss=1"
</link>
<description><![CDATA[
RNA splicing is highly prevalent in the brain and has strong links to neuropsychiatric disorders, yet the role of cell-type-specific splicing or transcript-isoform diversity during human brain development has not been systematically investigated. Here, we leveraged single-molecule long-read sequencing to deeply profile the full-length transcriptome of the germinal zone (GZ) and cortical plate (CP) regions of the developing human neocortex at tissue and single-cell resolution. We identified 214,516 unique isoforms, of which 72.6% are novel (unannotated in Gencode-v33), and uncovered a substantial contribution of transcript-isoform diversity, regulated by RNA binding proteins, in defining cellular identity in the developing neocortex. We leveraged this comprehensive isoform-centric gene annotation to re-prioritize thousands of rare de novo risk variants and elucidate genetic risk mechanisms for neuropsychiatric disorders.

One-Sentence SummaryA cell-specific atlas of gene isoform expression helps shape our understanding of brain development and disease.

Structured AbstractO_ST_ABSINTRODUCTIONC_ST_ABSThe development of the human brain is regulated by precise molecular and genetic mechanisms driving spatio-temporal and cell-type-specific transcript expression programs. Alternative splicing, a major mechanism increasing transcript diversity, is highly prevalent in the human brain, influences many aspects of brain development, and has strong links to neuropsychiatric disorders. Despite this, the cell-type-specific transcript-isoform diversity of the developing human brain has not been systematically investigated.

RATIONALEUnderstanding splicing patterns and isoform diversity across the developing neocortex has translational relevance and can elucidate genetic risk mechanisms in neurodevelopmental disorders. However, short-read sequencing, the prevalent technology for transcriptome profiling, is not well suited to capturing alternative splicing and isoform diversity. To address this, we employed third-generation long-read sequencing, which enables capture and sequencing of complete individual RNA molecules, to deeply profile the full-length transcriptome of the germinal zone (GZ) and cortical plate (CP) regions of the developing human neocortex at tissue and single-cell resolution.

RESULTSWe profiled microdissected GZ and CP regions of post-conception week (PCW) 15-17 human neocortex in bulk and at single-cell resolution across six subjects using high-fidelity long-read sequencing (PacBio IsoSeq). We identified 214,516 unique isoforms, of which 72.6% were novel (unannotated in Gencode), and >7,000 novel exons, expanding the proteome by 92,422 putative proteoforms. We uncovered thousands of isoform switches during cortical neurogenesis predicted to impact RNA regulatory domains or protein structure and implicating previously uncharacterized RNA-binding proteins in cellular identity and neuropsychiatric disease. At the single-cell level, early-stage excitatory neurons exhibited the greatest isoform diversity, and isoform-centric single-cell clustering led to the identification of previously uncharacterized cell states. We systematically assessed the contribution of transcriptomic features, and localized cell and spatio-temporal transcript expression signatures across neuropsychiatric disorders, revealing predominant enrichments in dynamic isoform expression and utilization patterns and that the number and complexity of isoforms per gene is strongly predictive of disease. Leveraging this resource, we re-prioritized thousands of rare de novo risk variants associated with autism spectrum disorders (ASD), intellectual disability (ID), and neurodevelopmental disorders (NDDs), more broadly, to potentially more severe consequences and revealed a larger proportion of cryptic splice variants with the expanded transcriptome annotation provided in this study.

CONCLUSIONOur study offers a comprehensive landscape of isoform diversity in the human neocortex during development. This extensive cataloging of novel isoforms and splicing events sheds light on the underlying mechanisms of neurodevelopmental disorders and presents an opportunity to explore rare genetic variants linked to these conditions. The implications of our findings extend beyond fundamental neuroscience, as they provide crucial insights into the molecular basis of developmental brain disorders and pave the way for targeted therapeutic interventions. To facilitate exploration of this dataset we developed an online portal (https://sciso.gandallab.org/).
]]></description>
<dc:creator>Patowary, A.</dc:creator>
<dc:date>2023-03-26</dc:date>
<dc:identifier>doi:10.1101/2023.03.25.534016</dc:identifier>
<dc:title><![CDATA[Cell-type-specificity of isoform diversity in the developing human neocortex informs mechanisms of neurodevelopmental disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-03-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.03.18.533255v1?rss=1">
<title>
<![CDATA[
Neuron cilia constrain glial regulators to microdomains around distal neurons 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.03.18.533255v1?rss=1"
</link>
<description><![CDATA[
Each glia interacts with multiple neurons, but the fundamental logic of whether it interacts with all equally remains unclear. We find that a single sense-organ glia modulates different contacting neurons distinctly. To do so, it partitions regulatory cues into molecular microdomains at specific neuron contact-sites, at its delimited apical membrane. For one glial cue, K/Cl transporter KCC-3, microdomain-localization occurs through a two-step, neuron-dependent process. First, KCC-3 shuttles to glial apical membranes. Second, some contacting neuron cilia repel it, rendering it microdomain-localized around one distal neuron-ending. KCC-3 localization tracks animal aging, and while apical localization is sufficient for contacting neuron function, microdomain-restriction is required for distal neuron properties. Finally, we find the glia regulates its microdomains largely independently. Together, this uncovers that glia modulate cross-modal sensor processing by compartmentalizing regulatory cues into microdomains. Glia across species contact multiple neurons and localize disease-relevant cues like KCC-3. Thus, analogous compartmentalization may broadly drive how glia regulate information processing across neural circuits.
]]></description>
<dc:creator>Ray, S.</dc:creator>
<dc:creator>Gurung, P.</dc:creator>
<dc:creator>Manning, R. S.</dc:creator>
<dc:creator>Kravchuk, A.</dc:creator>
<dc:creator>Singhvi, A.</dc:creator>
<dc:date>2023-03-19</dc:date>
<dc:identifier>doi:10.1101/2023.03.18.533255</dc:identifier>
<dc:title><![CDATA[Neuron cilia constrain glial regulators to microdomains around distal neurons]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-03-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.03.30.534927v1?rss=1">
<title>
<![CDATA[
Electrophysiological indices of hierarchical speech processing differentially reflect the comprehension of speech in noise 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.03.30.534927v1?rss=1"
</link>
<description><![CDATA[
The past few years have seen an increase in the use of encoding models to explain neural responses to natural speech. The goal of these models is to characterize how the human brain converts acoustic energy into distinct linguistic representations that enable everyday speech comprehension. For example, researchers have shown that electroencephalography (EEG) data can be modeled in terms of acoustic features of speech, such as its amplitude envelope or spectrogram, linguistic features such as phonemes and phoneme probability, and higher-level linguistic features like context-based word predictability. However, it is unclear how reliably EEG indices of these speech feature representations reflect comprehension in different listening conditions. To address this, we recorded EEG from neurotypical adults who listened to segments of an audiobook in various levels of background noise. We modeled how their EEG responses reflected a range of acoustic and linguistic speech features and how this tracking varied with behavior across noise levels. EEG tracking of nearly all examined features showed SNR-dependent changes in unique variance explained, with the largest changes occurring for linguistic features. We hypothesized that only higher-level feature tracking would predict behavior but instead found that both high and low-level features were associated with behavioral scores depending on the noise level. EEG markers of the influence of top-down, context-based prediction on bottom-up acoustic processing also correlated with behavior. These findings help characterize the relationship between brain and behavior by comprehensively linking hierarchical indices of neural speech processing to language comprehension metrics.

SIGNIFICANCE STATEMENTAcoustic and linguistic features of speech have been shown to be consistently tracked by neural activity even in noisy conditions. However, it is unclear how signatures of low- and high-level features covary with one another and relate to behavior across these listening conditions. Here, we find that linguistic (phonetic feature and word probability-based feature) processing is affected by noise more than low-level acoustic feature processing. We also find that behavioral performance is associated with acoustic, phonetic, and lexical surprisal tracking, and that these associations depend on background noise levels. These results extend our understanding of how various speech features are comparatively reflected in electrical brain activity and how they relate to perception in challenging listening conditions.
]]></description>
<dc:creator>Synigal, S. R.</dc:creator>
<dc:creator>Anderson, A. J.</dc:creator>
<dc:creator>Lalor, E. C.</dc:creator>
<dc:date>2023-03-31</dc:date>
<dc:identifier>doi:10.1101/2023.03.30.534927</dc:identifier>
<dc:title><![CDATA[Electrophysiological indices of hierarchical speech processing differentially reflect the comprehension of speech in noise]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-03-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.03.10.530869v1?rss=1">
<title>
<![CDATA[
Molecular cascades and cell-type specific signatures in ASD revealed by single cell genomics 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.03.10.530869v1?rss=1"
</link>
<description><![CDATA[
Understanding how genetic variation exerts its effects on the human brain in health and disease has been greatly informed by functional genomic characterization. Studies over the last decade have demonstrated robust evidence of convergent transcriptional and epigenetic profiles in post-mortem cerebral cortex from individuals with Autism Spectrum Disorder (ASD). Here, we perform deep single nuclear (sn) RNAseq to elucidate changes in cell composition, cellular transcriptomes and putative candidate drivers associated with ASD, which we corroborate using snATAC-seq and spatial profiling. We find changes in cell state composition representing transitions from homeostatic to reactive profiles in microglia and astrocytes, a pattern extending to oligodendrocytes and blood brain barrier cells. We identify profound changes in differential expression involving thousands of genes across neuronal and glial subtypes, of which a substantial portion can be accounted for by specific transcription factor networks that are significantly enriched in common and rare genetic risk for ASD. These data, which are available as part of the PsychENCODE consortium, provide robust causal anchors and resultant molecular phenotypes for understanding ASD changes in human brain.

One-Sentence SummaryWe define the molecular cascades and cells disrupted in post-mortem brain in ASD by performing spatial, single nuclear RNA, and epigenetic profiling, and characterize, at unmatched resolution, the functional regulation of cell-type specific signatures underlying the molecular differences and physiology of ASD.

Main TextPsychiatric disorders are defined primarily by behavioral and cognitive characteristics and are classically distinguished from neurological disorders by lacking the associated visible histological or macroscopic pathology observed in neurological conditions. However, a growing body of evidence based on genomic profiling reveals consistent molecular differences in brain tissue from specific neuropsychiatric conditions compared with brain tissue from neurotypical individuals (1-5). In Autism Spectrum Disorder (ASD) robust transcriptomic and epigenetic alterations in the cerebral cortex from patients have been documented over the last decade, delineating a reproducible pattern of molecular pathology (5-13). This robust molecular signature obtained primarily from transcriptomic profiling of bulk cortical tissue has identified convergent biological pathways in ASD brain, which is characterized by an upregulation of immune signaling genes, downregulation of specific neuronal markers, synaptic genes, and an attenuation of the typical patterns of gene expression associated with cortical regional identity (6-8,12-14).

These genomic data represent an essential lens through which to understand the cellular and physiological changes occurring in the brains of autistic individuals and to describe potential causal mechanisms via their integration with genetic risk variants (1,4,5). However, small sample sizes in the case of single cell analysis (13), or profiling restricted to bulk tissue have limited biological insights as to the differences in laminar, circuit level, and cell-type specific pathways affected in ASD, as well as their underlying gene regulatory mechanisms. To address these limitations, we leveraged improvement in single cell analyses to profile the largest ASD cohort to date, consisting of 64 cases and controls. This resource, generated as a core component of the PsychENCODE consortium (1,2,4,5,8; http://www.psychencode.org), also enables us to characterize underlying candidate regulatory mechanisms and to connect causal drivers with the observed changes at a cell-type specific level in ASD, providing a deeper and more generalizable understanding of the cell types and biological mechanisms that underlie ASD. These data are available via PsychEncode portals for download (http://psychencode.synapse.org) and on the PsychSCREEN browser (in development, http://psychscreen.beta.wenglab.org).
]]></description>
<dc:creator>Wamsley, B.</dc:creator>
<dc:creator>Bicks, L.</dc:creator>
<dc:creator>Cheng, Y.</dc:creator>
<dc:creator>Kawaguchi, R.</dc:creator>
<dc:creator>Quintero, D.</dc:creator>
<dc:creator>Grundman, J.</dc:creator>
<dc:creator>Liu, J.</dc:creator>
<dc:creator>Xiao, S.</dc:creator>
<dc:creator>Hawken, N.</dc:creator>
<dc:creator>Margolis, M.</dc:creator>
<dc:creator>Mazariegos, S.</dc:creator>
<dc:creator>Geschwind, D. H.</dc:creator>
<dc:date>2023-03-10</dc:date>
<dc:identifier>doi:10.1101/2023.03.10.530869</dc:identifier>
<dc:title><![CDATA[Molecular cascades and cell-type specific signatures in ASD revealed by single cell genomics]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-03-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.03.16.532307v1?rss=1">
<title>
<![CDATA[
Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.03.16.532307v1?rss=1"
</link>
<description><![CDATA[
Keypoint tracking algorithms have revolutionized the analysis of animal behavior, enabling investigators to flexibly quantify behavioral dynamics from conventional video recordings obtained in a wide variety of settings. However, it remains unclear how to parse continuous keypoint data into the modules out of which behavior is organized. This challenge is particularly acute because keypoint data is susceptible to high frequency jitter that clustering algorithms can mistake for transitions between behavioral modules. Here we present keypoint-MoSeq, a machine learning-based platform for identifying behavioral modules ("syllables") from keypoint data without human supervision. Keypoint-MoSeq uses a generative model to distinguish keypoint noise from behavior, enabling it to effectively identify syllables whose boundaries correspond to natural sub-second discontinuities inherent to mouse behavior. Keypoint-MoSeq outperforms commonly used alternative clustering methods at identifying these transitions, at capturing correlations between neural activity and behavior, and at classifying either solitary or social behaviors in accordance with human annotations. Keypoint-MoSeq therefore renders behavioral syllables and grammar accessible to the many researchers who use standard video to capture animal behavior.
]]></description>
<dc:creator>Weinreb, C.</dc:creator>
<dc:creator>Osman, M. A. M.</dc:creator>
<dc:creator>Zhang, L.</dc:creator>
<dc:creator>Lin, S.</dc:creator>
<dc:creator>Pearl, J.</dc:creator>
<dc:creator>Annapragada, S.</dc:creator>
<dc:creator>Conlin, E.</dc:creator>
<dc:creator>Gillis, W. F.</dc:creator>
<dc:creator>Jay, M.</dc:creator>
<dc:creator>Ye, S.</dc:creator>
<dc:creator>Mathis, A.</dc:creator>
<dc:creator>Mathis, M. W.</dc:creator>
<dc:creator>Pereira, T.</dc:creator>
<dc:creator>Linderman, S. W.</dc:creator>
<dc:creator>Datta, S. R.</dc:creator>
<dc:date>2023-03-17</dc:date>
<dc:identifier>doi:10.1101/2023.03.16.532307</dc:identifier>
<dc:title><![CDATA[Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-03-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.05.25.542312v1?rss=1">
<title>
<![CDATA[
Mouse models of SYNGAP1-related intellectual disability 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.05.25.542312v1?rss=1"
</link>
<description><![CDATA[
SYNGAP1 is a Ras-GTPase activating protein highly enriched at excitatory synapses in the brain. De novo loss-of-function mutations in SYNGAP1 are a major cause of genetically defined neurodevelopmental disorders (NDD). These mutations are highly penetrant and cause SYNGAP1-related intellectual disability (SRID), a NDD characterized by cognitive impairment, social deficits, early-onset seizures, and sleep disturbances (1-5). Studies in rodent neurons have shown that Syngap1 regulates developing excitatory synapse structure and function (6-11), and heterozygous Syngap1 knockout mice have deficits in synaptic plasticity, learning and memory, and have seizures (9, 12-14). However, how specific SYNGAP1 mutations found in humans lead to disease has not been investigated in vivo. To explore this, we utilized the CRISPR-Cas9 system to generate knock-in mouse models with two distinct known causal variants of SRID: one with a frameshift mutation leading to a premature stop codon, SYNGAP1; L813RfsX22, and a second with a single-nucleotide mutation in an intron that creates a cryptic splice acceptor site leading to premature stop codon, SYNGAP1; c.3583-9G>A. While reduction in Syngap1 mRNA varies from 30-50% depending on the specific mutation, both models show [~]50% reduction in Syngap1 protein, have deficits in synaptic plasticity, and recapitulate key features of SRID including hyperactivity and impaired working memory. These data suggest that half the amount of SYNGAP1 protein is key to the pathogenesis of SRID. These results provide a resource to study SRID and establish a framework for the development of therapeutic strategies for this disorder.

Significance StatementSYNGAP1 is a protein enriched at excitatory synapses in the brain that is an important regulator of synapse structure and function. SYNGAP1 mutations cause SYNGAP1-related intellectual disability (SRID), a neurodevelopmental disorder with cognitive impairment, social deficits, seizures, and sleep disturbances. To explore how SYNGAP1 mutations found in humans lead to disease, we generated the first knock-in mouse models with causal SRID variants: one with a frameshift mutation and a second with an intronic mutation that creates a cryptic splice acceptor site. Both models show decreased Syngap1 mRNA and Syngap1 protein and recapitulate key features of SRID including hyperactivity and impaired working memory. These results provide a resource to study SRID and establish a framework for the development of therapeutic strategies.

HighlightsO_LITwo mouse models with SYNGAP1-related intellectual disability (SRID) mutations found in humans were generated: one with a frameshift mutation that results in a premature stop codon and the other with an intronic mutation resulting in a cryptic splice acceptor site and premature stop codon.
C_LIO_LIBoth SRID mouse models show 35[~]50% reduction in mRNA and [~]50% reduction in Syngap1 protein.
C_LIO_LIBoth SRID mouse models display deficits in synaptic plasticity and behavioral phenotypes found in people.
C_LIO_LIRNA-seq confirmed cryptic splice acceptor activity in one SRID mouse model and revealed broad transcriptional changes also identified in Syngap1+/- mice.
C_LIO_LINovel SRID mouse models generated here provide a resource and establish a framework for development of future therapeutic intervention.
C_LI
]]></description>
<dc:creator>Araki, Y.</dc:creator>
<dc:creator>Gerber, E. E.</dc:creator>
<dc:creator>Rajkovich, K. E.</dc:creator>
<dc:creator>Hong, I.</dc:creator>
<dc:creator>Johnson, R. C.</dc:creator>
<dc:creator>Lee, H.-K.</dc:creator>
<dc:creator>Kirkwood, A.</dc:creator>
<dc:creator>Huganir, R. L.</dc:creator>
<dc:date>2023-05-25</dc:date>
<dc:identifier>doi:10.1101/2023.05.25.542312</dc:identifier>
<dc:title><![CDATA[Mouse models of SYNGAP1-related intellectual disability]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-05-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.01.31.526505v1?rss=1">
<title>
<![CDATA[
Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.01.31.526505v1?rss=1"
</link>
<description><![CDATA[
Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-seq data in GTEx v8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased WGS data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.
]]></description>
<dc:creator>Einson, J.</dc:creator>
<dc:creator>Glinos, D.</dc:creator>
<dc:creator>Boerwinkle, E.</dc:creator>
<dc:creator>Castaldi, P.</dc:creator>
<dc:creator>Darbar, D.</dc:creator>
<dc:creator>de Andrade, M.</dc:creator>
<dc:creator>Ellinor, P.</dc:creator>
<dc:creator>Fornage, M.</dc:creator>
<dc:creator>Gabriel, S.</dc:creator>
<dc:creator>Germer, S.</dc:creator>
<dc:creator>Gibbs, R.</dc:creator>
<dc:creator>Hersh, C.</dc:creator>
<dc:creator>Johnsen, J.</dc:creator>
<dc:creator>Kaplan, R.</dc:creator>
<dc:creator>Konkle, B.</dc:creator>
<dc:creator>Kooperberg, C.</dc:creator>
<dc:creator>Nassir, R.</dc:creator>
<dc:creator>Loos, R. J. F.</dc:creator>
<dc:creator>Meyers, D. A.</dc:creator>
<dc:creator>Mitchell, B. D.</dc:creator>
<dc:creator>Psaty, B.</dc:creator>
<dc:creator>Vasan, R. S.</dc:creator>
<dc:creator>Rich, S. S.</dc:creator>
<dc:creator>Rienstra, M.</dc:creator>
<dc:creator>Rotter, J. I.</dc:creator>
<dc:creator>Saferali, A.</dc:creator>
<dc:creator>Shoemaker, M. B.</dc:creator>
<dc:creator>Silverman, E.</dc:creator>
<dc:creator>Smith, A. V.</dc:creator>
<dc:creator>Mohammadi, P.</dc:creator>
<dc:creator>Castel, S. E.</dc:creator>
<dc:creator>Iossifov, I.</dc:creator>
<dc:creator>Lappalainen, T.</dc:creator>
<dc:date>2023-01-31</dc:date>
<dc:identifier>doi:10.1101/2023.01.31.526505</dc:identifier>
<dc:title><![CDATA[Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-01-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.01.27.525940v1?rss=1">
<title>
<![CDATA[
HAT: de novo variant calling for highly accurate short-read and long-read sequencing data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.01.27.525940v1?rss=1"
</link>
<description><![CDATA[
Motivationde novo variant (DNV) calling is challenging from parent-child sequenced trio data. We developed Hare And Tortoise (HAT) to work as an automated workflow to detect DNVs in highly accurate short-read and long-read sequencing data. Reliable detection of DNVs is important for human genetics studies (e.g., autism, epilepsy).

ResultsHAT is a workflow to detect DNVs from short-read and long read sequencing data. This workflow begins with aligned read data (i.e., CRAM or BAM) from a parent-child sequenced trio and outputs DNVs. HAT detects high-quality DNVs from short-read whole-exome sequencing, short-read wholegenome sequencing, and highly accurate long-read sequencing data.

Availabilityhttps://github.com/TNTurnerLab/HAT

Contacttychele@wustl.edu

Supplementary informationSupplementary data are available at bioRxiv.
]]></description>
<dc:creator>Ng, J. K.</dc:creator>
<dc:creator>Turner, T. N.</dc:creator>
<dc:date>2023-01-28</dc:date>
<dc:identifier>doi:10.1101/2023.01.27.525940</dc:identifier>
<dc:title><![CDATA[HAT: de novo variant calling for highly accurate short-read and long-read sequencing data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-01-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.12.26.521704v1?rss=1">
<title>
<![CDATA[
Epithelia delimits glial apical polarity against mechanical shear to maintain glia-neuron architecture 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.12.26.521704v1?rss=1"
</link>
<description><![CDATA[
For an organ to maintain proper architecture and function, its different component cell-types must coordinate their cell-shapes with each other through life. While cell-intrinsic developmental mechanisms driving homotypic cell-cell coordination are known, how heterotypic cells collectively regulate cell-shape is less-clear. We report that, in a sense-organ, epithelial cells delimit and maintain polarity domains of contacting glia, and thereby, associated neuron shapes throughout life. Briefly, Hsp co-chaperone UNC-23/BAG2 keeps epithelial apical domains from deforming with animal movement. Epithelial apical domains stretch aberrantly and progressively in adult unc-23 mutant animals, which in an FGFR-dependent manner, dislocates glial apical cytoskeleton proteins SMA-1/{beta}H-Spectrin and actin. This alters glial apical polarity and cell shape, and concomitantly, associated neuron-ending shape. Notably, UNC-23 acts temporally at a developmental critical period to maintain glia-neuron shape in adults, and spatially within a defined anatomical zone. Lastly, intervention in either epithelia, glia or neuron ameliorate or phenocopy unc-23 neural defects. Epi/endothelia resist mechanical stress and contact glia-neuron units across central/peripheral nervous systems and species, and all components of the identified molecular pathway are conserved and disease-relevant. Thus, we posit that analogous epithelia-glia mechanobiological coupling may broadly regulate glia-neuron shapes through animal life.
]]></description>
<dc:creator>Martin, C. G.</dc:creator>
<dc:creator>Bent, J. S.</dc:creator>
<dc:creator>Singhvi, A.</dc:creator>
<dc:date>2022-12-27</dc:date>
<dc:identifier>doi:10.1101/2022.12.26.521704</dc:identifier>
<dc:title><![CDATA[Epithelia delimits glial apical polarity against mechanical shear to maintain glia-neuron architecture]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-12-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.12.22.521680v1?rss=1">
<title>
<![CDATA[
Systematic multi-trait AAV capsid engineering for efficient gene delivery 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.12.22.521680v1?rss=1"
</link>
<description><![CDATA[
Broadening gene therapy applications requires manufacturable vectors that efficiently transduce target cells in humans and preclinical models. Conventional selections of adeno-associated virus (AAV) capsid libraries are inefficient at searching the vast sequence space for the small fraction of vectors possessing multiple traits essential for clinical translation. Here, we present Fit4Function, a generalizable machine learning (ML) approach for systematically engineering multi-trait AAV capsids. By leveraging a capsid library that evenly samples the manufacturable sequence space, reproducible screening data are generated to train accurate sequence-to-function models. Combining six models, we designed a multi-trait (liver-targeted, manufacturable) capsid library and validated 89% of library variants on all six predetermined criteria. Furthermore, the models, trained only on mouse in vivo and human in vitro Fit4Function data, accurately predicted AAV capsid variant biodistribution in macaque. Top candidates exhibited high production yields, efficient murine liver transduction, up to 1000-fold greater human hepatocyte transduction, and increased enrichment, relative to AAV9, in a screen for liver transduction in macaques. The Fit4Function strategy ultimately makes it possible to predict cross-species traits of peptide-modified AAV capsids and is a critical step toward assembling an ML atlas that predicts AAV capsid performance across dozens of traits.
]]></description>
<dc:creator>Eid, F.-E.</dc:creator>
<dc:creator>Chen, A. T.</dc:creator>
<dc:creator>Chan, K. Y.</dc:creator>
<dc:creator>Huang, Q.</dc:creator>
<dc:creator>Zheng, Q.</dc:creator>
<dc:creator>Tobey, I. G.</dc:creator>
<dc:creator>Pacouret, S.</dc:creator>
<dc:creator>Brauer, P. P.</dc:creator>
<dc:creator>Keyes, C.</dc:creator>
<dc:creator>Powell, M.</dc:creator>
<dc:creator>Johnston, J.</dc:creator>
<dc:creator>Zhao, B.</dc:creator>
<dc:creator>Lage, K.</dc:creator>
<dc:creator>Tarantal, A. F.</dc:creator>
<dc:creator>Chan, Y. A.</dc:creator>
<dc:creator>Deverman, B. E.</dc:creator>
<dc:date>2022-12-22</dc:date>
<dc:identifier>doi:10.1101/2022.12.22.521680</dc:identifier>
<dc:title><![CDATA[Systematic multi-trait AAV capsid engineering for efficient gene delivery]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-12-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.12.16.520778v1?rss=1">
<title>
<![CDATA[
Quantifying constraint in human mitochondrial DNA 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.12.16.520778v1?rss=1"
</link>
<description><![CDATA[
Mitochondrial DNA (mtDNA) has an important, yet often overlooked, role in health and disease. Constraint models quantify the removal of deleterious variation from the population by selection, representing a powerful tool for identifying genetic variation underlying human phenotypes1-4. However, a constraint model for the mtDNA has not been developed, due to its unique features. Here we describe the development of a mitochondrial constraint model and its application to the Genome Aggregation Database (gnomAD), a large-scale population dataset reporting mtDNA variation across 56,434 humans5. Our results demonstrate strong depletion of expected variation, suggesting most deleterious mtDNA variants remain undiscovered. To aid their identification, we compute constraint metrics for every mitochondrial protein, tRNA, and rRNA gene, revealing a spectrum of intolerance to variation. We characterize the most constrained regions within genes via regional constraint, and positions across the entire mtDNA via local constraint, showing their enrichment in pathogenic variation and functionally critical sites, including topological clustering in 3D protein and RNA structures. Notably, we identify constraint at often overlooked sites, such as rRNAs and non-coding regions. Lastly, we demonstrate how these metrics can improve the discovery of mtDNA variation underlying rare and common human phenotypes.
]]></description>
<dc:creator>Lake, N. J.</dc:creator>
<dc:creator>Liu, W.</dc:creator>
<dc:creator>Battle, S. L.</dc:creator>
<dc:creator>Laricchia, K. M.</dc:creator>
<dc:creator>Tiao, G.</dc:creator>
<dc:creator>Compton, A. G.</dc:creator>
<dc:creator>Cowie, S.</dc:creator>
<dc:creator>Christodoulou, J.</dc:creator>
<dc:creator>Thorburn, D. R.</dc:creator>
<dc:creator>Zhao, H.</dc:creator>
<dc:creator>Arking, D. E.</dc:creator>
<dc:creator>Sunyaev, S. R.</dc:creator>
<dc:creator>Lek, M.</dc:creator>
<dc:date>2022-12-19</dc:date>
<dc:identifier>doi:10.1101/2022.12.16.520778</dc:identifier>
<dc:title><![CDATA[Quantifying constraint in human mitochondrial DNA]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-12-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.12.13.520333v1?rss=1">
<title>
<![CDATA[
Robust hierarchically organized whole-brain patterns of dysconnectivity in schizophrenia spectrum disorders observed after Personalized Intrinsic Network Topography 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.12.13.520333v1?rss=1"
</link>
<description><![CDATA[
BackgroundSpatial patterns of brain functional connectivity can vary substantially at the individual level. Applying cortical surface-based approaches with individualized rather than group templates may accelerate the discovery of biological markers related to psychiatric disorders. We investigated cortico-subcortical networks from multi-cohort data in people with schizophrenia spectrum disorders (SSDs) and healthy controls using individualized connectivity profiles.

MethodsWe utilized resting state and anatomical MRI data from n=406 participants (n = 203 SSD, n = 203 healthy controls) from four cohorts. For each participant, functional timeseries were extracted from 80 cortical regions of interest, representing 6 intrinsic networks using 1) a volume-based approach 2) a surface-based group atlas approach, and 3) Personalized Intrinsic Network Topography (PINT), a personalized surface-based approach (Dickie et al., 2018). Timeseries were also extracted from previously defined intrinsic network subregions of the striatum (Choi et al 2011), thalamus (Ji et al 2019), and cerebellum (Buckner et al 2011).

ResultsCompared to a volume-based approach, the correlations between all cortical networks and the expected subregions of the striatum, cerebellum, and thalamus were increased using a surface-based approach (Cohens D volume vs surface 0.27-1.00, all p<10^-6) and further increased after PINT (Cohens D surface vs PINT 0.18-0.96, all p <10^-4). In SSD vs HC comparisons, controlling for age, sex, scanner and in-scanner motion, we observed robust patterns of dysconnectivity that were strengthened using a surface-based approach and PINT (Number of differing pairwise-correlations: volume: 357, surface: 562, PINT: 630, FDR corrected). These patterns were found from four different cortical networks - frontal-parietal, sensory-motor, visual, and default mode -- to subcortical regions.

ConclusionOur results indicate that individualized approaches can more sensitively delineate cortical network dysconnectivity differences in people with SSDs. These robust patterns of dysconnectivity were visibly organized in accordance with the cortical hierarchy, as predicted by computational models (Murray et al 2019). Our results also change our understanding of the specific network-network functional connectivity alterations in people with SSDs, and the extent of those alterations. Future work will examine these new patterns of dysconnectivity with behaviour using dimensional models.

Highlights- We evaluated the impact of cortical mapping method (volume-based, surface-based, vs surface personalized: PINT) on resting-state fMRI results in Schizophrenia Spectrum Disorders (SSD).
- The use of surface-based approaches and PINT increased the connectivity of cortical networks with the expected subregions of the striatum, thalamus and cerebellum, in comparison to a volume-based approach
- whole-brain case-control differences in functional connectivity were more pronounced after surface-based approach and PINT, in comparison to a volume-based approach
]]></description>
<dc:creator>Dickie, E. W.</dc:creator>
<dc:creator>Shahab, S.</dc:creator>
<dc:creator>Hawco, C.</dc:creator>
<dc:creator>Miranda, D.</dc:creator>
<dc:creator>Herman, G.</dc:creator>
<dc:creator>Argyelan, M.</dc:creator>
<dc:creator>Ji, J. L. W.</dc:creator>
<dc:creator>Jeyachandra, J.</dc:creator>
<dc:creator>Anticevic, A.</dc:creator>
<dc:creator>Malhotra, A. K.</dc:creator>
<dc:creator>Voineskos, A. N.</dc:creator>
<dc:date>2022-12-15</dc:date>
<dc:identifier>doi:10.1101/2022.12.13.520333</dc:identifier>
<dc:title><![CDATA[Robust hierarchically organized whole-brain patterns of dysconnectivity in schizophrenia spectrum disorders observed after Personalized Intrinsic Network Topography]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-12-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.12.09.519776v1?rss=1">
<title>
<![CDATA[
An in vivo platform for rebuilding functional neocortical tissue 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.12.09.519776v1?rss=1"
</link>
<description><![CDATA[
Recent progress in cortical stem cell transplantation has demonstrated its potential to repair the brain. However, current transplant models have yet to demonstrate that the circuitry of transplant-derived neurons can encode useful function to the host. This is likely due to missing cell types within the grafts, abnormal proportions of cell types, abnormal cytoarchitecture, and inefficient vascularization. Here, we devised a transplant platform for testing neocortical tissue prototypes. Dissociated mouse embryonic telencephalic cells in a liquid scaffold were transplanted into aspiration-lesioned adult mouse cortices. The donor neuronal precursors differentiated into upper and deep layer neurons that exhibited synaptic puncta, projected outside of the graft to appropriate brain areas, became electrophysiologically active within one month post-transplant, and responded to visual stimuli. Interneurons and oligodendrocytes were present at normal densities in grafts. Grafts became fully vascularized by 1-week post-transplant and vessels in grafts were perfused with blood. With this paradigm, we could also organize cells into layers. Overall, we have provided proof of concept for an in vivo platform that can be used for developing and testing neocortical-like tissue prototypes.
]]></description>
<dc:creator>Quezada, A.</dc:creator>
<dc:creator>Ward, C.</dc:creator>
<dc:creator>Bader, E. R.</dc:creator>
<dc:creator>Zolotavin, P.</dc:creator>
<dc:creator>Altun, E.</dc:creator>
<dc:creator>Hong, S.</dc:creator>
<dc:creator>Killian, N.</dc:creator>
<dc:creator>Xie, C.</dc:creator>
<dc:creator>Batista-Brito, R.</dc:creator>
<dc:creator>Hebert, J. M.</dc:creator>
<dc:date>2022-12-11</dc:date>
<dc:identifier>doi:10.1101/2022.12.09.519776</dc:identifier>
<dc:title><![CDATA[An in vivo platform for rebuilding functional neocortical tissue]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-12-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.11.30.518589v1?rss=1">
<title>
<![CDATA[
Regulation of stress-induced sleep fragmentation by preoptic glutamatergic neurons 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.11.30.518589v1?rss=1"
</link>
<description><![CDATA[
Sleep disturbances are detrimental for our behavioral and emotional well-being. Stressful events disrupt sleep, in particular by inducing brief awakenings (microarousals, MAs) resulting in sleep fragmentation. The preoptic area of the hypothalamus (POA) is crucial for sleep control. However, how POA neurons contribute to the regulation of MAs and thereby impact sleep quality is unknown. Using fiber photometry recordings in mice, we examined the activity changes of genetically defined POA subpopulations during sleep. We found that POA glutamatergic neurons are rhythmically activated in synchrony with an infraslow rhythm in the spindle band of the electroencephalogram during non-rapid eye movement sleep (NREMs) and are transiently activated during MAs. Optogenetic stimulation of these neurons strongly promotes MAs. Exposure to acute social defeat stress significantly increased the number of transients in the calcium activity of POA glutamatergic neurons during NREMs. Optogenetic inhibition during spontaneous sleep and after stress reduced MAs during NREMs and consequently consolidated sleep. Monosynaptically-restricted rabies tracing revealed that POA glutamatergic neurons are innervated by brain regions regulating stress and sleep. Our findings uncover a novel circuit mechanism by which POA excitatory neurons regulate sleep quality after stress.
]]></description>
<dc:creator>Smith, J.</dc:creator>
<dc:creator>Honig-Frand, A.</dc:creator>
<dc:creator>Antila, H.</dc:creator>
<dc:creator>Weber, F.</dc:creator>
<dc:creator>Chung, S.</dc:creator>
<dc:date>2022-12-01</dc:date>
<dc:identifier>doi:10.1101/2022.11.30.518589</dc:identifier>
<dc:title><![CDATA[Regulation of stress-induced sleep fragmentation by preoptic glutamatergic neurons]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-12-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.11.28.518207v1?rss=1">
<title>
<![CDATA[
A new theoretical framework jointly explains behavioral and neural variability across subjects performing flexible decision-making 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.11.28.518207v1?rss=1"
</link>
<description><![CDATA[
The ability to flexibly switch our response to external stimuli according to contextual information is critical for successful interactions with a complex world. Context-dependent computations are necessary across many domains1-3, yet their neural implementations remain poorly understood. Here we developed a novel behavioral task in rats to study context-dependent selection and accumulation of evidence for decision-making4-6. Under assumptions supported by both monkey and rat data, we first show mathematically that a network can solve this problem through a combination of three defined components. These components can be identified and tested directly with experimental data. We further show that existing electrophysiological and modeling data are compatible with the full variety of possible combinations of these components, suggesting that different individuals could use different component combinations. To study variability across individual subjects, we developed automated, high-throughput methods to train rats on our task, and we trained many subjects on it. Consistent with theoretical predictions, neural and behavioral analyses revealed substantial heterogeneity across rats, despite uniformly good task performance. Our theory further predicts a specific link between behavioral and neural signatures, which was robustly supported in the data. In summary, our results provide a new experimentally-supported theoretical framework to analyze individual variability in biological and artificial systems performing flexible decision-making tasks, they open the door to cellular-resolution studies of individual variability in higher cognition, and they provide insights into neural mechanisms of context-dependent computation more generally.
]]></description>
<dc:creator>Pagan, M.</dc:creator>
<dc:creator>Tang, V. D.</dc:creator>
<dc:creator>Aoi, M. C.</dc:creator>
<dc:creator>Pillow, J. W.</dc:creator>
<dc:creator>Mante, V.</dc:creator>
<dc:creator>Sussillo, D.</dc:creator>
<dc:creator>Brody, C. D.</dc:creator>
<dc:date>2022-11-28</dc:date>
<dc:identifier>doi:10.1101/2022.11.28.518207</dc:identifier>
<dc:title><![CDATA[A new theoretical framework jointly explains behavioral and neural variability across subjects performing flexible decision-making]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-11-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.11.25.517899v1?rss=1">
<title>
<![CDATA[
Transcriptional diversity in synaptic gene sets is sufficient to discriminate cortical neuronal identity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.11.25.517899v1?rss=1"
</link>
<description><![CDATA[
Synapse diversity has been described from different perspectives, ranging from the specific neurotransmitters released, to their diverse biophysical properties and proteome profiles. However, synapse diversity at the transcriptional level has not been systematically identified across all synapse populations in the brain. To quantify postsynaptic and identify specific synaptic features of neuronal cell types we combined the SynGO (Synaptic Gene Ontology) database with single-cell RNA sequencing data of the mouse neocortex. We show that cell types can be discriminated by synaptic genes alone with the same power as all genes. The cell type discriminatory power is not equally distributed across synaptic genes as we could identify functional categories and synaptic compartments with greater cell type specific expression. Synaptic genes, and specific SynGO categories, belonged to three different types of gene modules: gradient expression over all cell types, gradient expression in selected cell types and cell class- or type-specific profiles. This data provides a deeper understanding of synapse diversity in the neocortex and identifies potential markers to selectively identify synapses from specific neuronal populations.
]]></description>
<dc:creator>Roig Adam, A.</dc:creator>
<dc:creator>Martinez Lopez, J.</dc:creator>
<dc:creator>van der Spek, S.</dc:creator>
<dc:creator>The SYNGO consortium,</dc:creator>
<dc:creator>Sullivan, P. F.</dc:creator>
<dc:creator>Smit, A.</dc:creator>
<dc:creator>Verhage, M.</dc:creator>
<dc:creator>Hjerling-Leffler, J.</dc:creator>
<dc:date>2022-11-25</dc:date>
<dc:identifier>doi:10.1101/2022.11.25.517899</dc:identifier>
<dc:title><![CDATA[Transcriptional diversity in synaptic gene sets is sufficient to discriminate cortical neuronal identity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-11-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.11.22.517556v1?rss=1">
<title>
<![CDATA[
Deficits in integrative NMDA receptors caused by Grin1 disruption can be rescued in adulthood 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.11.22.517556v1?rss=1"
</link>
<description><![CDATA[
Glutamatergic NMDA receptors (NMDAR) are critical for cognitive function, and their reduced expression leads to intellectual disability. Since subpopulations of NMDARs exist in distinct subcellular environments, their functioning may be unevenly vulnerable to genetic disruption. Here, we investigate synaptic and extrasynaptic NMDARs on the major output neurons of the prefrontal cortex in mice deficient for the obligate NMDAR subunit encoded by Grin1 and wild-type littermates. With whole-cell recording in brain slices, we find that single, low-intensity stimuli elicit surprisingly-similar glutamatergic synaptic currents in both genotypes. By contrast, clear genotype differences emerge with manipulations that recruit extrasynaptic NMDARs, including stronger, repetitive, or pharmacological stimulation. These results reveal a disproportionate functional deficit of extrasynaptic NMDARs compared to their synaptic counterparts. To probe the repercussions of this deficit, we examine an NMDAR-dependent phenomenon considered a building block of cognitive integration, basal dendrite plateau potentials. Since we find this phenomenon is readily evoked in wild-type but not in Grin1-deficient mice, we ask whether plateau potentials can be restored by an adult intervention to increase Grin1 expression. This genetic manipulation, previously shown to restore cognitive performance in adulthood, successfully rescues electrically-evoked basal dendrite plateau potentials after a lifetime of NMDAR compromise. Taken together, our work demonstrates NMDAR subpopulations are not uniformly vulnerable to the genetic disruption of their obligate subunit. Furthermore, the window for functional rescue of the more-sensitive integrative NMDARs remains open into adulthood.
]]></description>
<dc:creator>Venkatesan, S.</dc:creator>
<dc:creator>Binko, M. A.</dc:creator>
<dc:creator>Mielnik, C. A.</dc:creator>
<dc:creator>Ramsey, A. J.</dc:creator>
<dc:creator>Lambe, E. K.</dc:creator>
<dc:date>2022-11-23</dc:date>
<dc:identifier>doi:10.1101/2022.11.22.517556</dc:identifier>
<dc:title><![CDATA[Deficits in integrative NMDA receptors caused by Grin1 disruption can be rescued in adulthood]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-11-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.10.25.513747v1?rss=1">
<title>
<![CDATA[
Sex-biasing influence of autism-associated Ube3a gene overdosage at connectomic, behavioral and transcriptomic levels 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.10.25.513747v1?rss=1"
</link>
<description><![CDATA[
Many neurodevelopmental conditions, including autism, affect males more than females. Genomic mechanisms enhancing risk in males may contribute to this sex-bias. The ubiquitin protein ligase E3A gene (Ube3a) exerts pleiotropic effects on cellular homeostasis via control of protein turnover and by acting as transcriptional coactivator with steroid hormone receptors. Overdosage of Ube3a via duplication or triplication of chromosomal region 15q11-13 causes 1-2% of autistic cases. Here, we test the hypothesis that increased dosage of Ube3a may influence autism-relevant phenotypes in a sex-biased manner. We report robust sex-biasing effects on brain connectomics and repetitive behaviors in mice with extra copies of Ube3a. These effects were associated with a profound transcriptional dysregulation of several known autism-associated genes (e.g., FMR1, SCN2A, PTEN, MEF2C, SHANK3, TSC2) as well as differentially-expressed genes identified in human 15q duplication and in autistic patients. Notably, increased Ube3a dosage also affects multiple sex-relevant mechanisms, including genes on the X chromosome, genes influenced by sex steroid hormones, downstream targets of the androgen and estrogen receptors, or genes that are sex-differentially regulated by transcription factors. These results suggest that Ube3a overdosage can critically contribute to sex-bias in neurodevelopmental conditions via influence on sex-differential mechanisms.
]]></description>
<dc:creator>Montani, C.</dc:creator>
<dc:creator>Pagani, M.</dc:creator>
<dc:creator>De Guzman, E.</dc:creator>
<dc:creator>Balasco, L.</dc:creator>
<dc:creator>Alvino, F.</dc:creator>
<dc:creator>De Felice, A.</dc:creator>
<dc:creator>Galbusera, A.</dc:creator>
<dc:creator>Nickl-Jockstat, T.</dc:creator>
<dc:creator>Lau, P.</dc:creator>
<dc:creator>Borsotti, N.</dc:creator>
<dc:creator>Pasqualetti, M.</dc:creator>
<dc:creator>Mattioni, L.</dc:creator>
<dc:creator>Provenzano, G.</dc:creator>
<dc:creator>Bozzi, Y.</dc:creator>
<dc:creator>Lombardo, M.</dc:creator>
<dc:creator>Gozzi, A.</dc:creator>
<dc:date>2022-10-25</dc:date>
<dc:identifier>doi:10.1101/2022.10.25.513747</dc:identifier>
<dc:title><![CDATA[Sex-biasing influence of autism-associated Ube3a gene overdosage at connectomic, behavioral and transcriptomic levels]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-10-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.11.16.516849v1?rss=1">
<title>
<![CDATA[
Cell type-specific assessment of cholesterol distribution in models of neurodevelopmental disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.11.16.516849v1?rss=1"
</link>
<description><![CDATA[
Most nervous system disorders manifest through alterations in neuronal signaling based on abnormalities in neuronal excitability, synaptic transmission, and cell survival. However, such neuronal phenotypes are frequently accompanied - or even caused - by metabolic dysfunctions in neuronal or non-neuronal cells. The tight packing and highly heterogenous properties of neural, glial and vascular cell types pose significant challenges to dissecting metabolic aspects of brain disorders. Perturbed cholesterol homeostasis has recently emerged as key parameter associated with sub-sets of neurodevelopmental disorders. However, approaches for tracking and visualizing endogenous cholesterol distribution in the brain have limited capability of resolving cell type-specific differences. We here develop tools for genetically-encoded sensors that report on cholesterol distribution in the mouse brain with cellular resolution. We apply these probes to examine sub-cellular cholesterol accumulation in two genetic mouse models of neurodevelopmental disorders, Npc1 and Ptchd1 knock-out mice. While both genes encode proteins with sterol-sensing domains that have been implicated in cholesterol transport, we uncover highly selective and cell type-specific phenotypes in cholesterol homeostasis. The tools established in this work should facilitate probing sub-cellular cholesterol distribution in complex tissues like the mammalian brain and enable capturing cell type-specific alterations in cholesterol flow between cells in models of brain disorders.
]]></description>
<dc:creator>Czernecki, C.</dc:creator>
<dc:creator>Dixit, S.</dc:creator>
<dc:creator>Riezman, I.</dc:creator>
<dc:creator>Innocenti, S.</dc:creator>
<dc:creator>Pfrieger, F.</dc:creator>
<dc:creator>Riezman, H.</dc:creator>
<dc:creator>Scheiffele, P.</dc:creator>
<dc:date>2022-11-17</dc:date>
<dc:identifier>doi:10.1101/2022.11.16.516849</dc:identifier>
<dc:title><![CDATA[Cell type-specific assessment of cholesterol distribution in models of neurodevelopmental disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-11-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.11.18.517098v1?rss=1">
<title>
<![CDATA[
A single-cell trajectory atlas of striatal development 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.11.18.517098v1?rss=1"
</link>
<description><![CDATA[
The striatum integrates dense neuromodulatory inputs from many brain regions to coordinate complex behaviors. This integration relies on the coordinated responses from distinct striatal cell types. While previous studies have characterized the cellular and molecular composition of the striatum using single-cell RNA-sequencing at distinct developmental timepoints, the molecular changes spanning embryonic through postnatal development at the single-cell level have not been examined. Here, we combine published mouse striatal single-cell datasets from both embryonic and postnatal timepoints to analyze the developmental trajectory patterns and transcription factor regulatory networks within striatal cell types. Using this integrated dataset, we found that dopamine receptor-1 expressing spiny projection neurons have an extended period of postnatal development with greater transcriptional complexity compared to dopamine receptor-2 expressing neurons. Moreover, we found the transcription factor, FOXP1, exerts indirect changes to oligodendrocytes. These data can be accessed and further analyzed through an interactive website (https://cells-test.gi.ucsc.edu/?ds=mouse-striatal-dev).
]]></description>
<dc:creator>Anderson, A. G.</dc:creator>
<dc:creator>Kulkarni, A.</dc:creator>
<dc:creator>Konopka, G.</dc:creator>
<dc:date>2022-11-18</dc:date>
<dc:identifier>doi:10.1101/2022.11.18.517098</dc:identifier>
<dc:title><![CDATA[A single-cell trajectory atlas of striatal development]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-11-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.09.20.508670v1?rss=1">
<title>
<![CDATA[
Ventral striatal dopamine encodes unique properties of visual stimuli in mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.09.20.508670v1?rss=1"
</link>
<description><![CDATA[
The mesolimbic dopamine system is an evolutionarily conserved set of brain circuits that plays a role in attention, appetitive behavior, and reward processing. In this circuitry, ascending dopaminergic projections from the ventral midbrain innervate targets throughout the limbic forebrain, such as the ventral striatum/nucleus accumbens (NAc). Dopaminergic signaling in the NAc has been widely studied for its role in behavioral reinforcement, reward prediction error encoding, and motivational salience. Less well characterized is the role of dopaminergic neurotransmission in the response to surprising or alerting sensory events. To address this, we used the genetically encoded dopamine sensor dLight1 and fiber photometry to explore the ability of striatal dopamine release in to encode the properties of salient sensory stimuli in mice, such as threatening looming discs. Here, we report that NAc lateral shell (LNAc) dopamine release encodes the rate and magnitude of environmental luminance changes rather than visual stimulus threat level. This encoding is highly sensitive, as LNAc dopamine could be evoked by light intensities that were imperceptible to human experimenters. We also found that light-evoked dopamine responses are wavelength-dependent at low irradiances, independent of the circadian cycle, robust to previous exposure history, and involve multiple phototransduction pathways. Thus, we have further elaborated the mesolimbic dopamine systems ability to encode visual information in mice, which is likely relevant to a wide body of scientists employing light sources or optical methods in behavioral research involving rodents.
]]></description>
<dc:creator>Gonzalez, L. S.</dc:creator>
<dc:creator>Fisher, A. A.</dc:creator>
<dc:creator>Cotella, E. M.</dc:creator>
<dc:creator>Robinson, J. E.</dc:creator>
<dc:date>2022-09-22</dc:date>
<dc:identifier>doi:10.1101/2022.09.20.508670</dc:identifier>
<dc:title><![CDATA[Ventral striatal dopamine encodes unique properties of visual stimuli in mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-09-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.06.16.496362v1?rss=1">
<title>
<![CDATA[
Data-driven dissection of the Fever Effect in Autism Spectrum Disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.06.16.496362v1?rss=1"
</link>
<description><![CDATA[
Some individuals with autism spectrum disorder (ASD) demonstrate marked behavioral improvements during febrile episodes, in what is perhaps the only present-day means of modulating the core ASD phenotype. Understanding the nature of this so-called fever effect is therefore essential for leveraging this natural temporary relief of symptoms to a sustained efficacious intervention. Towards this goal, we used machine learning to analyze the rich clinical data of the Simons Simplex Collection, in which 1 out of every 6 children with ASD was reported to improve during febrile episodes, across multiple ASD domains. Reported behavioral improvements during febrile episodes were associated with maternal infection in pregnancy (OR = 1.7, 95% CI = [1.42, 2.03], P = 4.24x10-4) and gastrointestinal (GI) dysfunction (OR=1.46, 95% CI = [1.15, 1.81], P = 1.94x10-3). Family members of children reported to improve when febrile have an increased prevalence of autoimmune disorders (OR=1.43, 95% CI = [1.23, 1.67], P = 3.0x10-6), language disorders (OR=1.63, 95% CI = [1.29, 2.04], P = 2.5x10-5), and neuropsychiatric disorders (OR=1.59, 95% CI = [1.34, 1.89], P < 1x10-6). Since both GI abnormalities and maternal immune activation have been linked to ASD via proinflammatory cytokines, these results might suggest a possible involvement of immune dysregulation in the fever effect, consistent with findings in mouse models. This work advances our understanding of the fever-responsive ASD subtype and motivates future studies to directly test the link between proinflammatory cytokines and behavioral modifications in individuals with ASD.

Lay summarySome individuals with ASD demonstrate marked behavioral improvements when they have a fever. However, the magnitude, scope, nature, and underlying neurobiological basis of the so-called fever effect remain unknown. This large-scale biomedical data analysis found that children with ASD reported to improve when febrile tend to be those with worse gastrointestinal symptoms and whose mothers reported an infection during pregnancy. These and other findings point to the involvement of proinflammatory cytokines in this phenomenon.
]]></description>
<dc:creator>Muller, E.</dc:creator>
<dc:creator>Shalev, I.</dc:creator>
<dc:creator>Bachmat, E.</dc:creator>
<dc:creator>Eran, A.</dc:creator>
<dc:date>2022-06-17</dc:date>
<dc:identifier>doi:10.1101/2022.06.16.496362</dc:identifier>
<dc:title><![CDATA[Data-driven dissection of the Fever Effect in Autism Spectrum Disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-06-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.11.01.514692v1?rss=1">
<title>
<![CDATA[
Ketamine induces multiple individually distinct whole-brain functional connectivity signatures 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.11.01.514692v1?rss=1"
</link>
<description><![CDATA[
BackgroundKetamine has emerged as one of the most promising therapies for treatment-resistant depression. However, inter-individual variability in response to ketamine is still not well understood and it is unclear how ketamines molecular mechanisms connect to its neural and behavioral effects.

MethodsWe conducted a double-blind placebo-controlled study in which 40 healthy participants received acute ketamine (initial bolus 0.23 mg/kg, continuous infusion 0.58 mg/kg/hour). We quantified resting-state functional connectivity via data-driven global brain connectivity, related it to individual ketamine-induced symptom variation, and compared it to cortical gene expression targets.

ResultsWe found that: i) both the neural and behavioral effects of acute ketamine are multi-dimensional, reflecting robust inter-individual variability; ii) ketamines data-driven principal neural gradient effect matched somatostatin (SST) and parvalbumin (PVALB) cortical gene expression patterns in humans, implicating the role of SST and PVALB interneurons in ketamines acute effects; and iii) behavioral data-driven individual symptom variation mapped onto distinct neural gradients of ketamine, which were resolvable at the single-subject level.

ConclusionsCollectively, these findings support the possibility for developing individually precise pharmacological biomarkers for treatment selection in psychiatry.

FundingThis study was supported by NIH grants DP5OD012109-01 (A.A.), 1U01MH121766 (A.A.), R01MH112746 (J.D.M.), 5R01MH112189 (A.A.), 5R01MH108590 (A.A.), NIAAA grant 2P50AA012870-11 (A.A.); NSF NeuroNex grant 2015276 (J.D.M.); Brain and Behavior Research Foundation Young Investigator Award (A.A.); SFARI Pilot Award (J.D.M., A.A.); Heffter Research Institute (Grant No. 1-190420); Swiss Neuromatrix Foundation (Grant No. 2016-0111m Grant No. 2015 - 010); Swiss National Science Foundation under the frame-work of Neuron Cofund (Grant No. 01EW1908), Usona Institute (2015 - 2056).
]]></description>
<dc:creator>Moujaes, F.</dc:creator>
<dc:creator>Ji, J. L.</dc:creator>
<dc:creator>Rahmati, M.</dc:creator>
<dc:creator>Burt, J.</dc:creator>
<dc:creator>Schleifer, C. H.</dc:creator>
<dc:creator>Adkinson, B.</dc:creator>
<dc:creator>Savic, A.</dc:creator>
<dc:creator>Santamauro, N.</dc:creator>
<dc:creator>Tamayo, Z.</dc:creator>
<dc:creator>Diehl, C.</dc:creator>
<dc:creator>Kolobaric, A.</dc:creator>
<dc:creator>Flynn, M.</dc:creator>
<dc:creator>Rieser, N. M.</dc:creator>
<dc:creator>Fonteneau, C.</dc:creator>
<dc:creator>Camarro, T.</dc:creator>
<dc:creator>Xu, J.</dc:creator>
<dc:creator>Cho, Y.</dc:creator>
<dc:creator>Repovs, G.</dc:creator>
<dc:creator>Fineberg, S.</dc:creator>
<dc:creator>Morgan, P.</dc:creator>
<dc:creator>Seifritz, E.</dc:creator>
<dc:creator>Vollenweider, F. X.</dc:creator>
<dc:creator>Krystal, J.</dc:creator>
<dc:creator>Murray, J. D.</dc:creator>
<dc:creator>Preller, K. H.</dc:creator>
<dc:creator>Anticevic, A.</dc:creator>
<dc:date>2022-11-01</dc:date>
<dc:identifier>doi:10.1101/2022.11.01.514692</dc:identifier>
<dc:title><![CDATA[Ketamine induces multiple individually distinct whole-brain functional connectivity signatures]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-11-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.10.24.513565v1?rss=1">
<title>
<![CDATA[
Rubella virus tropism and single cell responses in human primary tissue and microglia-containing organoids 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.10.24.513565v1?rss=1"
</link>
<description><![CDATA[
Rubella virus is an important human pathogen that can cause neurologic deficits in a developing fetus when contracted during pregnancy. Despite successful vaccination programs in the Americas and many developed countries, rubella remains endemic in many regions worldwide and outbreaks occur wherever population immunity is insufficient. Intense interest since rubella virus was first isolated in 1962 has advanced our understanding of clinical outcomes after infection disrupts key processes of fetal neurodevelopment. Yet it is still largely unknown which cell types in the developing brain are targeted. We show that in human brain slices, rubella virus predominantly infects microglia. This infection occurs in a heterogeneous population but not in a highly microglia-enriched monoculture in the absence of other cell types. By using an organoid-microglia model, we further demonstrate that rubella virus infection leads to a profound interferon response in non-microglial cells, including neurons and neural progenitor cells, and this response is attenuated by the presence of microglia.
]]></description>
<dc:creator>Popova, G.</dc:creator>
<dc:creator>Retallack, H.</dc:creator>
<dc:creator>Kim, C. N.</dc:creator>
<dc:creator>Shin, D.</dc:creator>
<dc:creator>Wang, A.</dc:creator>
<dc:creator>DeRisi, J. J.</dc:creator>
<dc:creator>Nowakowski, T. J.</dc:creator>
<dc:date>2022-10-24</dc:date>
<dc:identifier>doi:10.1101/2022.10.24.513565</dc:identifier>
<dc:title><![CDATA[Rubella virus tropism and single cell responses in human primary tissue and microglia-containing organoids]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-10-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.11.05.515231v1?rss=1">
<title>
<![CDATA[
Challenges in screening for de novo noncoding variants contributing to genetically complex phenotypes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.11.05.515231v1?rss=1"
</link>
<description><![CDATA[
Understanding the genetic basis for complex, heterogeneous disorders, such as autism spectrum disorder (ASD), is a persistent challenge in human medicine. Owing to their phenotypic complexity, the genetic mechanisms underlying these disorders may be highly variable across individual patients. Furthermore, much of their heritability is unexplained by known regulatory or coding variants. Indeed, there is evidence that much of the causal genetic variation stems from rare and de novo variants arising from ongoing mutation. These variants occur mostly in noncoding regions, likely affecting regulatory processes for genes linked to the phenotype of interest. However, because there is no uniform code for assessing regulatory function, it is difficult to separate these mutations into likely functional and nonfunctional subsets. This makes finding associations between complex diseases and potentially causal de novo single-nucleotide variants (dnSNVs) a difficult task. To date, all but one published study in this area has failed to find any significant associations between dnSNVs from ASD patients and any class of known regulatory elements. We sought to identify the underlying reasons for this and present strategies for overcoming these challenges. We show that, contrary to previous claims, the main reason for failure to find robust statistical enrichments is not the number of families sampled, but the quality and relevance to ASD of the annotations used to prioritize dnSNVs, and the reliability of the set of dnSNVs itself. We present a list of recommendations for designing future studies of this sort that will help researchers avoid common pitfalls.
]]></description>
<dc:creator>Castro, C. P.</dc:creator>
<dc:creator>Diehl, A. G.</dc:creator>
<dc:creator>Boyle, A. P.</dc:creator>
<dc:date>2022-11-05</dc:date>
<dc:identifier>doi:10.1101/2022.11.05.515231</dc:identifier>
<dc:title><![CDATA[Challenges in screening for de novo noncoding variants contributing to genetically complex phenotypes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-11-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.11.08.514512v1?rss=1">
<title>
<![CDATA[
Mapping human social brain specialisation beyond the neuron using multimodal imaging in human infants 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.11.08.514512v1?rss=1"
</link>
<description><![CDATA[
The specialised regional functionality of the mature human cortex partly emerges through experience-dependent specialisation during early development. Our existing understanding of this process is based on evidence from unitary imaging modalities and has thus focused on isolated changes in spatial or temporal precision of neural or haemodynamic activation alone, giving an incomplete picture of the process. We speculate that neural specialisation of function will be underpinned by better coordinated haemodynamic and metabolic changes in a broader orchestrated physiological response. Thus, we present a harmonised framework in which specialisation is indexed by the emergence of coupling between neuronal activity and vascular supply of oxygen and energy. Here, we combine simultaneous measures of coordinated neural activity (EEG), metabolic rate and oxygenated blood supply (broadband near-infrared spectroscopy) to measure emerging specialisation in the infant brain. In 4-to-7-month-old infants, we show that social processing is accompanied by spatially and temporally specific increases in coupled activation in the temporal-parietal junction, a core hub region of the adult social brain. During non-social processing coupled activation decreased in the same region, indicating specificity to social processing. Coupling was strongest with high frequency brain activity (beta and gamma), consistent with the greater energetic requirements and more localised action of high frequency brain activity. We conclude that functional specialisation of the brain is a coordinated activity across neural, haemodynamic, and metabolic changes, and our ability to measure these simultaneously opens new vistas in understanding how the brain is shaped by its environment.
]]></description>
<dc:creator>Siddiqui, M.</dc:creator>
<dc:creator>Pinti, P.</dc:creator>
<dc:creator>Brigadoi, S.</dc:creator>
<dc:creator>Lloyd-Fox, S.</dc:creator>
<dc:creator>Elwell, C. E.</dc:creator>
<dc:creator>Johnson, M. H.</dc:creator>
<dc:creator>Tachtsidis, I.</dc:creator>
<dc:creator>Jones, E. J.</dc:creator>
<dc:date>2022-11-09</dc:date>
<dc:identifier>doi:10.1101/2022.11.08.514512</dc:identifier>
<dc:title><![CDATA[Mapping human social brain specialisation beyond the neuron using multimodal imaging in human infants]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-11-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.06.03.494750v1?rss=1">
<title>
<![CDATA[
QuNex -- An Integrative Platform forReproducible Neuroimaging Analytics 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.06.03.494750v1?rss=1"
</link>
<description><![CDATA[
Neuroimaging technology has experienced explosive growth and transformed the study of neural mechanisms across health and disease. However, given the diversity of sophisticated tools for handling neuroimaging data, the field faces challenges in method integration (1-3), particularly across multiple modalities and species. Specifically, researchers often have to rely on siloed approaches which limit reproducibility, with idiosyncratic data organization and limited software interoperability. To address these challenges, we have developed Quantitative Neuroimaging Environment & Toolbox (QuNex), a platform for consistent end-to-end processing and analytics. QuNex provides several novel functionalities for neuroimaging analyses, including a "turnkey" command for the reproducible deployment of custom workflows, from onboarding raw data to generating analytic features. The platform enables inter-operable integration of multi-modal, community-developed neuroimaging software through an extension framework with a software development kit (SDK) for seamless integration of community tools. Critically, it supports high-throughput, parallel processing in high-performance compute environments, either locally or in the cloud. Notably, QuNex has successfully processed over 10,000 scans across neuroimaging consortia (4), including multiple clinical datasets. Moreover, QuNex enables integration of human and non-human workflows via a cohesive translational platform. Collectively, this effort stands to significantly impact neuroimaging method integration across acquisition approaches, pipelines, datasets, computational environments, and species. Building on this platform will enable more rapid, scalable, and reproducible impact of neuroimaging technology across health and disease.
]]></description>
<dc:creator>Ji, J. L.</dc:creator>
<dc:creator>Demsar, J.</dc:creator>
<dc:creator>Fonteneau, C.</dc:creator>
<dc:creator>Tamayo, Z.</dc:creator>
<dc:creator>Pan, L.</dc:creator>
<dc:creator>Kraljic, A.</dc:creator>
<dc:creator>Matkovic, A.</dc:creator>
<dc:creator>Purg, N.</dc:creator>
<dc:creator>Helmer, M.</dc:creator>
<dc:creator>Warrington, S.</dc:creator>
<dc:creator>Sotiropoulos, S.</dc:creator>
<dc:creator>Harms, M.</dc:creator>
<dc:creator>Murray, J. D.</dc:creator>
<dc:creator>Anticevic, A.</dc:creator>
<dc:creator>Repovs, G.</dc:creator>
<dc:date>2022-06-05</dc:date>
<dc:identifier>doi:10.1101/2022.06.03.494750</dc:identifier>
<dc:title><![CDATA[QuNex -- An Integrative Platform forReproducible Neuroimaging Analytics]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-06-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.09.27.509791v1?rss=1">
<title>
<![CDATA[
In vivo proximity ligation reveals endogenous candidate interactors of Neurexin's intracellular domain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.09.27.509791v1?rss=1"
</link>
<description><![CDATA[
Neurexins are highly-spliced transmembrane cell adhesion molecules that bind an array of partners via their extracellular domains. However, much less is known about the signaling pathways downstream of neurexins largely-invariant intracellular domain. C. elegans contains a single neurexin gene that we have previously shown is required for presynaptic assembly and stabilization. To gain insight into the signaling pathways mediating neurexins presynaptic functions, we employed a proximity ligation method, endogenously tagging neurexins intracellular domain with the promiscuous biotin ligase TurboID, allowing us to isolate adjacent biotinylated proteins by streptavidin pull-down and mass spectrometry. We compared our experimental strain to a control strain in which neurexin, endogenously tagged with TurboID, was dispersed from presynaptic active zones by the deletion of its C-terminal PDZ-binding motif. Using this approach we identified both known and novel intracellular interactors of neurexin, including active zone scaffolds, actin-binding proteins (including almost every member of the Arp2/3 complex), signaling molecules, and mediators of RNA trafficking, protein synthesis and degradation, among others. Characterization of mutants for candidate neurexin interactors revealed that they recapitulate aspects of the nrx-1 mutant phenotype, suggesting they may be involved in neurexin signaling. Finally, to investigate a possible role for neurexin in local actin assembly, we endogenously tagged its intracellular domain with actin depolymerizing and sequestering peptides (DeActs), and found that this led to defects in active zone assembly.
]]></description>
<dc:creator>Schaan Profes, M.</dc:creator>
<dc:creator>Tiroumalechetty, A.</dc:creator>
<dc:creator>Patel, N.</dc:creator>
<dc:creator>Lauar, S. S.</dc:creator>
<dc:creator>Sidoli, S.</dc:creator>
<dc:creator>Kurshan, P.</dc:creator>
<dc:date>2022-09-28</dc:date>
<dc:identifier>doi:10.1101/2022.09.27.509791</dc:identifier>
<dc:title><![CDATA[In vivo proximity ligation reveals endogenous candidate interactors of Neurexin's intracellular domain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-09-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.08.25.505166v1?rss=1">
<title>
<![CDATA[
Rapid specification of human pluripotent stem cells to functional astrocytes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.08.25.505166v1?rss=1"
</link>
<description><![CDATA[
Astrocytes are essential for the formation and maintenance of neural networks through metabolic support, facilitation of synaptic function, and optimization of electrophysiological activity. However, a major technical challenge for investigating astrocyte function and disease-related pathophysiology has been the limited ability to obtain functional human astrocytes. Here we present a novel method to efficiently differentiate human pluripotent stem cell (hPSC)-derived neural progenitors to functional astrocytes in 28 days using a culture medium containing leukemia inhibitory factor (LIF) and bone morphogenetic protein 4 (BMP4). This approach yields highly pure populations of astrocytes expressing canonical astrocyte markers, which we confirmed by immunofluorescence, flow cytometry and RNA sequencing. Human PSC-derived astrocytes efficiently buffer glutamate and robustly support neural network activity. Co-cultures of hPSC-derived astrocytes and neurons on multi-electrode arrays generated robust network activity within 2 days and synchronous network bursts after 6 days. Whole cell patch-clamp recordings revealed an increased frequency of postsynaptic currents in human hPSC-derived neurons co-cultured with hPSC-derived versus primary rodent astrocytes, consistent with a corresponding increase in synapse density. Furthermore, hPSC-derived astrocytes retained their hominid morphology when transplanted into a mouse brain. In conclusion, we present a novel protocol to obtain functional astrocytes from human pluripotent stem cells, providing a platform for investigating human astrocyte function and neuronal-glial interactions.
]]></description>
<dc:creator>Lendemeijer, B.</dc:creator>
<dc:creator>Unkel, M.</dc:creator>
<dc:creator>Mossink, B.</dc:creator>
<dc:creator>Hijazi, S.</dc:creator>
<dc:creator>Sampedro, S. G.</dc:creator>
<dc:creator>Shpak, G.</dc:creator>
<dc:creator>Slump, D. E.</dc:creator>
<dc:creator>van den Hout, M. C. G. N.</dc:creator>
<dc:creator>van IJcken, W. F. J.</dc:creator>
<dc:creator>Bindels, E. M. J.</dc:creator>
<dc:creator>Hoogendijk, W. J. G.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:creator>de Vrij, F. M. S.</dc:creator>
<dc:creator>Kushner, S. A.</dc:creator>
<dc:date>2022-08-26</dc:date>
<dc:identifier>doi:10.1101/2022.08.25.505166</dc:identifier>
<dc:title><![CDATA[Rapid specification of human pluripotent stem cells to functional astrocytes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-08-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.09.15.508118v1?rss=1">
<title>
<![CDATA[
Single-cell brain organoid screening identifies developmental defects in autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.09.15.508118v1?rss=1"
</link>
<description><![CDATA[
Development of the human brain involves processes that are not seen in many other species, but can contribute to neurodevelopmental disorders (1-4). Cerebral organoids can be used to investigate neurodevelopmental disorders in a human context but are limited by variability and low throughput. We have developed the CRISPR-human organoids-scRNA-seq (CHOOSE) system that utilizes verified pairs of gRNAs, inducible CRISPR/Cas9-based genetic disruption, and single-cell transcriptomics for pooled loss-of-function screening in mosaic organoids. Genetic perturbations of 36 high-risk autism spectrum disorder (ASD) genes related to transcriptional regulation allowed us to identify their effects on cell fate determination and discover developmental stages susceptible to ASD gene perturbations. We construct a developmental gene regulatory network (GRN) of cerebral organoids from single-cell multiomic data including transcriptome and chromatin modalities and identify ASD-associated and perturbation-enriched regulatory modules. We show that perturbing members of the BAF chromatin remodeling complex leads to an expanded population of ventral telencephalon progenitors. Specifically, the BAF subunit ARID1B controls the fate transitions of progenitors to oligodendrocyte precursor cells and interneurons, which we confirmed in patient-specific induced pluripotent stem cell (iPSC) derived organoids. Our study paves the way for phenotypically characterizing disease susceptibility genes in human organoid models with cell type, developmental trajectory, and gene regulatory network readouts.
]]></description>
<dc:creator>Li, C.</dc:creator>
<dc:creator>Fleck, J. S.</dc:creator>
<dc:creator>Martins-Costa, C.</dc:creator>
<dc:creator>Burkard, T. R.</dc:creator>
<dc:creator>Stuempflen, M.</dc:creator>
<dc:creator>Vertesy, A.</dc:creator>
<dc:creator>Peer, A. M.</dc:creator>
<dc:creator>Esk, C.</dc:creator>
<dc:creator>Elling, U.</dc:creator>
<dc:creator>Kasprian, G.</dc:creator>
<dc:creator>Corsini, N. S.</dc:creator>
<dc:creator>Treutlein, B.</dc:creator>
<dc:creator>Knoblich, J. A.</dc:creator>
<dc:date>2022-09-15</dc:date>
<dc:identifier>doi:10.1101/2022.09.15.508118</dc:identifier>
<dc:title><![CDATA[Single-cell brain organoid screening identifies developmental defects in autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-09-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.09.17.508382v1?rss=1">
<title>
<![CDATA[
Dysregulation of mTOR Signaling Mediates Common Neurite and Migration Defects in Both Idiopathic and 16p11.2 Deletion Autism Neural Precursor Cells 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.09.17.508382v1?rss=1"
</link>
<description><![CDATA[
Autism spectrum disorder (ASD) is defined by common behavioral characteristics, raising the possibility of shared pathogenic mechanisms. Yet, vast clinical and etiological heterogeneity suggests personalized phenotypes. Surprisingly, our iPSC studies find that six individuals from two distinct ASD-subtypes, idiopathic and 16p11.2 deletion, have common reductions in neural precursor cell (NPC) neurite outgrowth and migration even though whole genome sequencing demonstrates no genetic overlap between the datasets. To identify signaling differences that may contribute to these developmental defects, an unbiased phospho-(p)-proteome screen was performed. Surprisingly despite the genetic heterogeneity, hundreds of shared p-peptides were identified between autism subtypes including the mTOR pathway. mTOR signaling alterations were confirmed in all NPCs across both ASD-subtypes, and mTOR modulation rescued ASD phenotypes and reproduced autism defects in controls. Thus, our studies demonstrate that genetically distinct ASD subtypes have common defects in neurite outgrowth and migration which are driven by the shared pathogenic mechanism of mTOR signaling dysregulation.
]]></description>
<dc:creator>Prem, S.</dc:creator>
<dc:creator>Dev, B.</dc:creator>
<dc:creator>Peng, C.</dc:creator>
<dc:creator>Mehta, M.</dc:creator>
<dc:creator>Alibutud, R.</dc:creator>
<dc:creator>Connacher, R. J.</dc:creator>
<dc:creator>St. Thomas, M.</dc:creator>
<dc:creator>Zhou, X.</dc:creator>
<dc:creator>Matteson, P.</dc:creator>
<dc:creator>Xing, J.</dc:creator>
<dc:creator>Millonig, J.</dc:creator>
<dc:creator>DiCicco-Bloom, E.</dc:creator>
<dc:date>2022-09-20</dc:date>
<dc:identifier>doi:10.1101/2022.09.17.508382</dc:identifier>
<dc:title><![CDATA[Dysregulation of mTOR Signaling Mediates Common Neurite and Migration Defects in Both Idiopathic and 16p11.2 Deletion Autism Neural Precursor Cells]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-09-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.05.25.493390v1?rss=1">
<title>
<![CDATA[
Variation in glutamate and GABA genes and their association with brain structure and chemistry in autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.05.25.493390v1?rss=1"
</link>
<description><![CDATA[
The excitatory/inhibitory (E/I) imbalance hypothesis posits that an imbalance between glutamatergic and GABAergic neurotransmission contributes to autism symptomatology. Whether this is due to altered GABAergic or glutamatergic functioning, or both, remains largely unknown. We integrated genetic, brain structure and brain chemistry data to investigate the relationship between E/I genetic variation and expression, glutamate concentrations and cortical thickness (CT). Participants (60 autism and 104 neurotypical controls, aged 8-13 years) underwent magnetic resonance imaging and spectroscopy for glutamate quantification in the anterior cingulate cortex (ACC) and left dorsal striatum. Genetic involvement in these regional glutamate concentration levels was investigated using competitive gene-set association and polygenic scores (PGS). Further, glutamate as well as GABA gene-set expression profiles were investigated in relation to CT. Aggregated genetic variation in the glutamate gene-set was associated with ACC but not striatal glutamate concentrations. PGS analysis, however, showed a genome-wide PGS for autism to be predictive of striatal but not ACC glutamate levels. Expression profiles of GABAergic-but not glutamatergic genes were associated with differences in cortical thickness between groups. This study showed differential involvement of aggregated glutamatergic and GABAergic genetic variation in brain structure and chemistry in autism, which suggests regional variability in E/I imbalance.
]]></description>
<dc:creator>Naaijen, J.</dc:creator>
<dc:creator>Arenella, M.</dc:creator>
<dc:creator>Zoellner, H. J.</dc:creator>
<dc:creator>Puts, N.</dc:creator>
<dc:creator>Lythgoe, D. J.</dc:creator>
<dc:creator>Brandeis, D.</dc:creator>
<dc:creator>Durston, S.</dc:creator>
<dc:creator>Poelmans, G.</dc:creator>
<dc:creator>Ruisch, I. H.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:date>2022-05-25</dc:date>
<dc:identifier>doi:10.1101/2022.05.25.493390</dc:identifier>
<dc:title><![CDATA[Variation in glutamate and GABA genes and their association with brain structure and chemistry in autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-05-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.05.31.494205v1?rss=1">
<title>
<![CDATA[
Physical and functional convergence of the autism risk genes Scn2a and Ank2 in neocortical pyramidal cell dendrites 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.05.31.494205v1?rss=1"
</link>
<description><![CDATA[
Dysfunction in sodium channels and their ankyrin scaffolding partners have both been implicated in neurodevelopmental disorders, including autism spectrum disorder (ASD). In particular, the genes SCN2A, which encodes the sodium channel NaV1.2, and ANK2, which encodes ankyrin-B, have strong ASD association. Recent studies indicate that ASD-associated haploinsufficiency in Scn2a impairs dendritic excitability and synaptic function in neocortical pyramidal cells, but how NaV1.2 is anchored within dendritic regions is unknown. Here, we show that ankyrin-B is essential for scaffolding NaV1.2 to the dendritic membrane of mouse neocortical neurons, and that haploinsufficiency of Ank2 phenocopies intrinsic dendritic excitability and synaptic deficits observed in Scn2a+/- conditions. Thus, these results establish a direct, convergent link between two major ASD risk genes and reinforce an emerging framework suggesting that neocortical pyramidal cell dendritic dysfunction can be etiological to neurodevelopmental disorder pathophysiology.
]]></description>
<dc:creator>Nelson, A. D.</dc:creator>
<dc:creator>Catalfio, A. M.</dc:creator>
<dc:creator>Gupta, J. M.</dc:creator>
<dc:creator>Min, L.</dc:creator>
<dc:creator>Caballero-Floran, R. N.</dc:creator>
<dc:creator>Dean, K. P.</dc:creator>
<dc:creator>Elvira, C. C.</dc:creator>
<dc:creator>Derderian, K. D.</dc:creator>
<dc:creator>Kyoung, H.</dc:creator>
<dc:creator>Sahagun, A.</dc:creator>
<dc:creator>Sanders, S. J.</dc:creator>
<dc:creator>Bender, K.</dc:creator>
<dc:creator>Jenkins, P. M.</dc:creator>
<dc:date>2022-05-31</dc:date>
<dc:identifier>doi:10.1101/2022.05.31.494205</dc:identifier>
<dc:title><![CDATA[Physical and functional convergence of the autism risk genes Scn2a and Ank2 in neocortical pyramidal cell dendrites]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-05-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.06.01.494444v1?rss=1">
<title>
<![CDATA[
Ankyrin-B is lipid-modified by S-palmitoylation to promote dendritic membrane scaffolding of voltage-gated sodium channel Nav1.2 in neurons 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.06.01.494444v1?rss=1"
</link>
<description><![CDATA[
Neuronal ankyrin-B is an intracellular scaffolding protein that plays multiple roles in the axon. By contrast, relatively little is known about the function of ankyrin-B in dendrites, where ankyrin-B is also localized in mature neurons. Recently, we showed that ankyrin-B acts as a scaffold for the voltage-gated sodium channel, NaV1.2, in dendrites of neocortical pyramidal neurons. How ankyrin-B is itself targeted to the dendritic membrane is not well understood. Here, we report that ankyrin-B is lipid-modified by S-palmitoylation to promote dendritic localization of NaV1.2. We identify the palmitoyl acyl transferase zDHHC17 as a key mediator of ankyrin-B palmitoylation in heterologous cells and in neurons. Additionally, we find that zDHHC17 regulates ankyrin-B protein levels independently of its S-acylation function through a conserved binding mechanism between the ANK repeat domain of zDHHC17 and the zDHHC ankyrin-repeat binding motif of ankyrin-B. We subsequently identify five cysteines in the N-terminal ankyrin repeat domain of ankyrin-B that are necessary for ankyrin-B palmitoylation. Mutation of these five cysteines to alanines not only abolishes ankyrin-B palmitoylation, but also prevents ankyrin-B from scaffolding Nav1.2 at dendritic membranes of neurons due to ankyrin-Bs inability to localize properly at dendrites. Thus, we show palmitoylation is critical for localization and function of ankyrin-B at dendrites. Strikingly, loss of ankyrin-B palmitoylation does not affect ankyrin-B-mediated axonal cargo transport of synaptic vesicle synaptotagmin-1 in neurons. This is the first demonstration of S-palmitoylation of ankyrin-B as an underlying mechanism required for ankyrin-B localization and function in scaffolding Nav1.2 at dendrites.
]]></description>
<dc:creator>Gupta, J. P.</dc:creator>
<dc:creator>Jenkins, P. M.</dc:creator>
<dc:date>2022-06-02</dc:date>
<dc:identifier>doi:10.1101/2022.06.01.494444</dc:identifier>
<dc:title><![CDATA[Ankyrin-B is lipid-modified by S-palmitoylation to promote dendritic membrane scaffolding of voltage-gated sodium channel Nav1.2 in neurons]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-06-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.06.02.494499v1?rss=1">
<title>
<![CDATA[
Peripheral Auditory Nerve Impairment in a Mouse Model of Syndromic Autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.06.02.494499v1?rss=1"
</link>
<description><![CDATA[
Dysfunction of the peripheral auditory nerve (AN) contributes to dynamic changes throughout the central auditory system, resulting in abnormal auditory processing, including hypersensitivity. Altered sound sensitivity is frequently observed in autism spectrum disorder (ASD), suggesting that AN deficits and changes in auditory information processing may contribute to ASD-associated symptoms, including social communication deficits and hyperacusis. The MEF2C transcription factor is associated with risk for several neurodevelopmental disorders, and mutations or deletions of MEF2C produce a haploinsufficiency syndrome characterized by ASD, language and cognitive deficits. A mouse model of this syndromic ASD (i.e., Mef2c+/- or Mef2c-Het) recapitulates many of the MEF2C Haploinsufficiency syndrome-linked behaviors including communication deficits. We show here that Mef2c-Het mice exhibit functional impairment of the peripheral AN and a modest reduction in hearing sensitivity. We find that MEF2C is expressed during development in multiple AN and cochlear cell types, and in Mef2c-Het mice, we observe multiple cellular and molecular alterations associated with the AN, including abnormal myelination, neuronal degeneration, neuronal mitochondria dysfunction, and increased macrophage activation and cochlear inflammation. These results reveal the importance of MEF2C function in inner ear development and function and the engagement of immune cells and other non-neuronal cells, which suggests that microglia/macrophages and other non-neuronal cells might contribute, directly or indirectly, to AN dysfunction and ASD-related phenotypes. Finally, our study establishes a comprehensive approach for characterizing AN function at the physiological, cellular, and molecular levels in mice, which can be applied to animal models with a wide range of human auditory processing impairments.

Significance StatementThis is the first report of peripheral auditory nerve (AN) impairment in a mouse model of human MEF2C haploinsufficiency syndrome that has well-characterized ASD related behaviors including communication deficits, hyperactivity, repetitive behavior, and social deficits. We identify multiple underlying cellular, sub-cellular, and molecular abnormalities that may contribute to peripheral AN impairment. Our findings also highlight the important roles of immune cells (e.g., cochlear macrophages) and other non-neuronal elements (e.g., glial cells and cells in the stria vascularis) in auditory impairment in ASD. The methodological significance of the study is the establishment of a comprehensive approach for evaluating peripheral AN function and impact of peripheral AN deficits with minimal hearing loss.
]]></description>
<dc:creator>McChesney, N.</dc:creator>
<dc:creator>Barth, J. L.</dc:creator>
<dc:creator>Rumschlag, J. A.</dc:creator>
<dc:creator>Tan, J.</dc:creator>
<dc:creator>Harrington, A.</dc:creator>
<dc:creator>Noble, K.</dc:creator>
<dc:creator>McClaskey, C.</dc:creator>
<dc:creator>Elvis, P.</dc:creator>
<dc:creator>Vaena, S.</dc:creator>
<dc:creator>Romeo, M.</dc:creator>
<dc:creator>Harris, K. C.</dc:creator>
<dc:creator>Cowan, C. W.</dc:creator>
<dc:creator>Lang, H.</dc:creator>
<dc:date>2022-06-03</dc:date>
<dc:identifier>doi:10.1101/2022.06.02.494499</dc:identifier>
<dc:title><![CDATA[Peripheral Auditory Nerve Impairment in a Mouse Model of Syndromic Autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-06-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.07.10.498576v1?rss=1">
<title>
<![CDATA[
Human iPSC-derived neuron of 16p11.2 deletion reveals haplotype-specific expression of MAPK3 and its contribution to variable NDD phenotypes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.07.10.498576v1?rss=1"
</link>
<description><![CDATA[
Recurrent proximal 16p11.2 deletion (16p11.2del) is risk factor of diverse neurodevelopmental disorders (NDDs) with variable penetrance. Although previous human induced pluripotent stem cell (hiPSC) models of 16p11.2del confirmed disrupted neuron development, it is not known which gene(s) at this interval are mainly responsible for the abnormal cellular phenotypes and how the NDD penetrance is regulated. After haplotype phasing of 16p11.2 region, we generated hiPSCs for two 16p11.2del families with distinct residual haplotypes and variable NDD phenotypes. We also differentiated the hiPSCs to cortical neural cells and demonstrated MAPK3 as a driver signal of 16p11.2 region contributing to the dysfunctions in multiple pathways related to neuron development, which leads to altered morphological or electrophysiological properties in neuron cells. Furthermore, residual haplotype-specific MAPK3 expression was identified in 16p11.2del neuron cells, associating MAPK3 down-expression with the minor allele of the residual haplotype. Ten SNPs of the residual haplotype are mapped as enhancer SNPs (enSNPs) of MAPK3, eight enSNPs were functionally validated by luciferase assays, implying enSNPs contribute to residual haplotype-specific MAPK3 expression via cis-regulation. Finally, the analyses of three different patient cohorts showed that the residual haplotype of 16p11.2del is associated with variable NDD phenotypes.
]]></description>
<dc:creator>Liu, F.</dc:creator>
<dc:creator>Liang, C.</dc:creator>
<dc:creator>Li, Z.</dc:creator>
<dc:creator>Zhao, S.</dc:creator>
<dc:creator>Shangguan, S.</dc:creator>
<dc:creator>Yuan, H.</dc:creator>
<dc:creator>Yao, R.</dc:creator>
<dc:creator>Qin, Z.</dc:creator>
<dc:creator>Zhang, S.</dc:creator>
<dc:creator>Zou, L.</dc:creator>
<dc:creator>Gao, Z.</dc:creator>
<dc:creator>Chen, Q.</dc:creator>
<dc:creator>Wen, S.</dc:creator>
<dc:creator>Peng, J.</dc:creator>
<dc:creator>Yin, F.</dc:creator>
<dc:creator>Chen, F.</dc:creator>
<dc:creator>Qiu, X.</dc:creator>
<dc:creator>Luo, J.</dc:creator>
<dc:creator>Xie, Y.</dc:creator>
<dc:creator>Lu, D.</dc:creator>
<dc:creator>Zhang, Y.</dc:creator>
<dc:creator>Xie, H.</dc:creator>
<dc:creator>Wang, H.</dc:creator>
<dc:creator>Cui, X.</dc:creator>
<dc:creator>Wang, J.</dc:creator>
<dc:creator>Huang, H.</dc:creator>
<dc:creator>Liu, R.</dc:creator>
<dc:creator>Sun, X.</dc:creator>
<dc:creator>Chen, C.</dc:creator>
<dc:creator>Wu, N.</dc:creator>
<dc:creator>Liu, C.</dc:creator>
<dc:creator>Shen, Y.</dc:creator>
<dc:creator>Gusella, J. F.</dc:creator>
<dc:creator>Chen, X.</dc:creator>
<dc:date>2022-07-11</dc:date>
<dc:identifier>doi:10.1101/2022.07.10.498576</dc:identifier>
<dc:title><![CDATA[Human iPSC-derived neuron of 16p11.2 deletion reveals haplotype-specific expression of MAPK3 and its contribution to variable NDD phenotypes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-07-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.03.15.484308v1?rss=1">
<title>
<![CDATA[
CDKL5 deficiency slows synaptic vesicle endocytosis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.03.15.484308v1?rss=1"
</link>
<description><![CDATA[
Cyclin-dependent kinase-like 5 (CDKL5) deficiency disorder (CDD) is a severe early-onset epileptic encephalopathy resulting mainly from de novo mutations in the X-linked CDKL5 gene. To determine whether loss of presynaptic CDKL5 function contributes to CDD, we examined synaptic vesicle (SV) recycling in primary hippocampal neurons generated from a Cdkl5 knockout rat model. Using a genetically-encoded reporter, we revealed that CDKL5 is selectively required for efficient SV endocytosis. We showed that CDKL5 kinase activity is both necessary and sufficient for optimal SV endocytosis, since kinase-inactive mutations failed to correct endocytosis in Cdkl5 knockout neurons, whereas the isolated CDKL5 kinase domain fully restored SV endocytosis kinetics. Finally, we demonstrated that CDKL5-mediated phosphorylation of amphiphysin 1, a putative presynaptic target, is not required for CDKL5-dependent control of SV endocytosis. Overall, our findings reveal a key presynaptic role for CDKL5 kinase activity and enhance our insight into how its dysfunction may culminate in CDD.
]]></description>
<dc:creator>Kontaxi, C.</dc:creator>
<dc:creator>Davenport, E. C.</dc:creator>
<dc:creator>Kind, P. C.</dc:creator>
<dc:creator>Cousin, M. A.</dc:creator>
<dc:date>2022-03-16</dc:date>
<dc:identifier>doi:10.1101/2022.03.15.484308</dc:identifier>
<dc:title><![CDATA[CDKL5 deficiency slows synaptic vesicle endocytosis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-03-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.08.25.504851v1?rss=1">
<title>
<![CDATA[
GATK-gCNV: A Rare Copy Number Variant Discovery Algorithm and Its Application to Exome Sequencing in the UK Biobank 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.08.25.504851v1?rss=1"
</link>
<description><![CDATA[
Copy number variants (CNVs) are major contributors to genetic diversity and disease. To date, exome sequencing (ES) has been generated for millions of individuals in international biobanks, human disease studies, and clinical diagnostic screening. While standardized methods exist for detecting short variants (single nucleotide and insertion/deletion variants) using tools such as the Genome Analysis ToolKit (GATK), technical challenges have confounded similarly uniform large-scale CNV analyses from ES data. Given the profound impact of rare and de novo coding CNVs on genome organization and human disease, the lack of widely-adopted and robustly benchmarked rare CNV discovery tools has presented a barrier to routine exome-wide assessment of this critical class of variation. Here, we introduce GATK-gCNV, a flexible algorithm to discover rare CNVs from genome sequencing read-depth information, which we distribute as an open-source tool packaged in GATK. GATK-gCNV uses a probabilistic model and inference framework that accounts for technical biases while simultaneously predicting CNVs, which enables self-consistency between technical read-depth normalization and variant calling. We benchmarked GATK-gCNV in 7,962 exomes from individuals in quartet families with matched genome sequencing and microarray data. These analyses demonstrated 97% recall of rare ([&le;]1% site frequency) coding CNVs detected by microarrays and 95% recall of rare coding CNVs discovered by genome sequencing at a resolution of more than two exons. We applied GATK-gCNV to generate a reference catalog of rare coding CNVs in 197,306 individuals with ES from the UK Biobank. We observed strong correlations between CNV rates per gene and measures of mutational constraint, as well as rare CNV associations with multiple traits. In summary, GATK-gCNV is a tunable approach for sensitive and specific CNV discovery in ES, which can easily be applied across trait association and clinical screening.
]]></description>
<dc:creator>Babadi, M.</dc:creator>
<dc:creator>Fu, J. M.</dc:creator>
<dc:creator>Lee, S. K.</dc:creator>
<dc:creator>Smirnov, A. N.</dc:creator>
<dc:creator>Gauthier, L. D.</dc:creator>
<dc:creator>Walker, M.</dc:creator>
<dc:creator>Benjamin, D. I.</dc:creator>
<dc:creator>Karczewski, K. J.</dc:creator>
<dc:creator>Wong, I.</dc:creator>
<dc:creator>Collins, R. L.</dc:creator>
<dc:creator>Sanchis-Juan, A.</dc:creator>
<dc:creator>Brand, H.</dc:creator>
<dc:creator>Banks, E.</dc:creator>
<dc:creator>Talkowski, M. E.</dc:creator>
<dc:date>2022-08-26</dc:date>
<dc:identifier>doi:10.1101/2022.08.25.504851</dc:identifier>
<dc:title><![CDATA[GATK-gCNV: A Rare Copy Number Variant Discovery Algorithm and Its Application to Exome Sequencing in the UK Biobank]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-08-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.04.23.489093v1?rss=1">
<title>
<![CDATA[
Rare CNVs and phenome-wide profiling: a tale of brain-structural divergence and phenotypical convergence 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.04.23.489093v1?rss=1"
</link>
<description><![CDATA[
Copy number variations (CNVs) are rare genomic deletions and duplications that can exert profound effects on brain and behavior. Previous reports of pleiotropy in CNVs imply that they converge on shared mechanisms at some level of pathway cascades, from genes to large-scale neural circuits to the phenome. However, studies to date have primarily examined single CNV loci in small clinical cohorts. It remains unknown how distinct CNVs escalate the risk for the same developmental and psychiatric disorders. Here, we quantitatively dissect the impact on brain organization and behavioral differentiation across eight key CNVs. In 534 clinical CNV carriers from multiple sites, we explored CNV-specific brain morphology patterns. We extensively annotated these CNV-associated patterns with deep phenotyping assays through the UK Biobank resource. Although the eight CNVs cause disparate brain changes, they are tied to similar phenotypic profiles across [~]1000 lifestyle indicators. Our population-level investigation established brain structural divergences and phenotypical convergences of CNVs, with direct relevance to major brain disorders.
]]></description>
<dc:creator>Kopal, J.</dc:creator>
<dc:creator>Kumar, K.</dc:creator>
<dc:creator>Saltoun, K.</dc:creator>
<dc:creator>Modenato, C.</dc:creator>
<dc:creator>Moreau, C. A.</dc:creator>
<dc:creator>Martin-Brevet, S.</dc:creator>
<dc:creator>Huguet, G.</dc:creator>
<dc:creator>Jean-Louis, M.</dc:creator>
<dc:creator>Martin, C.-O.</dc:creator>
<dc:creator>Saci, Z.</dc:creator>
<dc:creator>Younis, N.</dc:creator>
<dc:creator>Tamer, P.</dc:creator>
<dc:creator>Douard, E. A.</dc:creator>
<dc:creator>Maillard, A.</dc:creator>
<dc:creator>Rodriguez-Herreros, B.</dc:creator>
<dc:creator>Pain, A.</dc:creator>
<dc:creator>Richetin, S.</dc:creator>
<dc:creator>Kushan, L.</dc:creator>
<dc:creator>Silva, A. I.</dc:creator>
<dc:creator>van den Bree, M. B.</dc:creator>
<dc:creator>Linden, D. E.</dc:creator>
<dc:creator>Owen, M. J.</dc:creator>
<dc:creator>Hall, J.</dc:creator>
<dc:creator>Lippe, S.</dc:creator>
<dc:creator>Draganski, B.</dc:creator>
<dc:creator>Sonderby, I. E.</dc:creator>
<dc:creator>Andreassen, O. A.</dc:creator>
<dc:creator>Glahn, D. C.</dc:creator>
<dc:creator>Thompson, P.</dc:creator>
<dc:creator>Bearden, C. E.</dc:creator>
<dc:creator>Jacquemont, S.</dc:creator>
<dc:creator>Bzdok, D.</dc:creator>
<dc:date>2022-04-25</dc:date>
<dc:identifier>doi:10.1101/2022.04.23.489093</dc:identifier>
<dc:title><![CDATA[Rare CNVs and phenome-wide profiling: a tale of brain-structural divergence and phenotypical convergence]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-04-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.04.26.489525v1?rss=1">
<title>
<![CDATA[
Fine-grained topographic organization within somatosensory cortex during resting-state and emotional face-matching task and its association with ASD traits 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.04.26.489525v1?rss=1"
</link>
<description><![CDATA[
BACKGROUNDSensory atypicalities are particularly common in autism spectrum disorders (ASD). Nevertheless, our knowledge about the divergence of the underlying somatosensory region and its association with ASD phenotype features is limited.

METHODSWe applied a data-driven approach to map the fine-grained variations in functional connectivity of the primary somatosensory cortex (S1) to the rest of the brain in 240 autistic and 164 neurotypical individuals from the EU-AIMS LEAP dataset, aged between 7 and 30. We estimated the S1 connection topography ( connectopy) during rest and during the emotional face-matching (Hariri) task, an established measure of emotion reactivity, and accessed its association with a set of clinical and behavioral variables.

RESULTSWe demonstrated that the S1 connectopy is organized along a dorsoventral axis, mapping onto the somatotopic organization of S1. We found that its spatial characteristics were linked to the individuals adaptive functioning skills, as measured by the Vineland Adaptive Behavior Scales, across the whole sample. Higher functional differentiation characterized the S1 connectopies of individuals with higher daily life adaptive skills. Notably, we detected significant differences between rest and the Hariri task in the S1 connectopies, as well as their projection maps onto the rest of the brain suggesting a task-modulating effect on S1 due to emotion processing.

CONCLUSIONSVariation of daily life adaptive skills appears to be reflected in the brains mesoscale neural circuitry, as shown by the S1 connectivity profile, which is also differentially modulated during rest and emotional processing.
]]></description>
<dc:creator>Isakoglou, C.</dc:creator>
<dc:creator>Haak, K. V.</dc:creator>
<dc:creator>Wolfers, T.</dc:creator>
<dc:creator>Floris, D. L.</dc:creator>
<dc:creator>Llera, A.</dc:creator>
<dc:creator>Oldehinkel, M.</dc:creator>
<dc:creator>Forde, N. J.</dc:creator>
<dc:creator>Oakley, B. F. M.</dc:creator>
<dc:creator>Tillmann, J.</dc:creator>
<dc:creator>Holt, R. J.</dc:creator>
<dc:creator>Moessnang, C.</dc:creator>
<dc:creator>Loth, E.</dc:creator>
<dc:creator>Bourgeron, T.</dc:creator>
<dc:creator>Baron-Cohen, S.</dc:creator>
<dc:creator>Charman, T.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Murphy, D. G. M.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>EU-AIMS LEAP Group,</dc:creator>
<dc:date>2022-04-27</dc:date>
<dc:identifier>doi:10.1101/2022.04.26.489525</dc:identifier>
<dc:title><![CDATA[Fine-grained topographic organization within somatosensory cortex during resting-state and emotional face-matching task and its association with ASD traits]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-04-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.04.27.489700v1?rss=1">
<title>
<![CDATA[
CLARITY increases sensitivity and specificity of fluorescence immunostaining in long-term archived human brain tissue 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.04.27.489700v1?rss=1"
</link>
<description><![CDATA[
Immunohistochemistry on archival human brains is often limited because several conditions arise that complicate the use for high-resolution fluorescence microscopy. In this study, we developed a novel clearing approach for immunofluorescence-based analysis of perfusion- and immersion-fixed post mortem human brain tissue, termed hCLARITY. hCLARITY is optimized for specificity by reducing off-target labeling and yields very sensitive stainings in human brain sections allowing for super-resolution microscopy with unprecedented imaging of pre- and postsynaptic compartments. Moreover, hallmarks of the Alzheimers disease were preserved with hCLARITY, and importantly classical DAB or Nissl stainings are compatible with this protocol. hCLARITY is extremely versatile as demonstrated by the use of more than 30 well performing antibodies and allows for de- and subsequent re-staining of the same tissue section, which is important for multi-labelling approaches, e.g., in super-resolution microscopy. Taken together, hCLARITY enables research of the human brain with highest sensitivity and down to sub-diffraction resolution and therefore has enormous potential for the investigation of local morphological changes, e.g., in neurodegenerative diseases.

Striking Image / Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/489700v1_ufig1.gif" ALT="Figure 1">
View larger version (79K):
org.highwire.dtl.DTLVardef@1732df2org.highwire.dtl.DTLVardef@cda615org.highwire.dtl.DTLVardef@152b44aorg.highwire.dtl.DTLVardef@ba972a_HPS_FORMAT_FIGEXP  M_FIG Summary of the main advantages of hCLARITY. CLARITY was applied on human post mortem brain tissue in direct comparison to untreated sections (minus CLARITY). Owing to removal of lipids during the clearing with SDS and the resulting reduction in light scattering, cleared sections were less opaque. The denaturing effect of the detergent SDS most likely results in better accessibility of certain epitopes. The major benefits of hCLARITY were found in an increased sensitivity and specificity of antibodies for neuronal cells. The adapted hCLARITY protocol is compatible with staining techniques for confocal microscopy, super-resolution microscopy, and light microscopy.

C_FIG
]]></description>
<dc:creator>Woelfle, S.</dc:creator>
<dc:creator>Deshpande, D.</dc:creator>
<dc:creator>Feldengut, S.</dc:creator>
<dc:creator>Roselli, F.</dc:creator>
<dc:creator>Deisseroth, K.</dc:creator>
<dc:creator>Michaelis, J.</dc:creator>
<dc:creator>Böckers, T.</dc:creator>
<dc:creator>Schoen, M.</dc:creator>
<dc:date>2022-04-29</dc:date>
<dc:identifier>doi:10.1101/2022.04.27.489700</dc:identifier>
<dc:title><![CDATA[CLARITY increases sensitivity and specificity of fluorescence immunostaining in long-term archived human brain tissue]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-04-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.05.07.491031v1?rss=1">
<title>
<![CDATA[
Oxytocin attenuates microglial activation and restores social and non-social memory in the APP/PS1 mouse model of Alzheimer's disease 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.05.07.491031v1?rss=1"
</link>
<description><![CDATA[
Alzheimers disease (AD) is the main cause of dementia in the elderly and is characterized by memory loss, social withdrawal and neurodegeneration, eventually leading to death. Brain inflammation has emerged as a key pathogenic mechanism in AD. We hypothesized that oxytocin, a pro-social hypothalamic neuropeptide with anti-inflammatory properties, could have therapeutic actions in AD. We investigated oxytocin production in mouse models of AD, and evaluated the therapeutic potential of intranasal oxytocin. We observed lower levels of hypothalamic oxytocin in wild-type mice following brain infusion of amyloid-{beta} oligomers (A{beta}Os), as well as in APP/PS1 AD model mice. Treatment of APP/PS1 mice with intranasal oxytocin reduced microglial activation and favored deposition of A{beta} in dense core plaques, a potentially neuroprotective mechanism. Oxytocin further alleviated social and non-social memory impairments in APP/PS1 mice. Our findings point to oxytocin as a potential therapeutic target to reduce brain inflammation and correct memory deficits in AD.
]]></description>
<dc:creator>Selles, M. C.</dc:creator>
<dc:creator>Fortuna, J. T. S.</dc:creator>
<dc:creator>de Faria, Y. P. R.</dc:creator>
<dc:creator>Longo, B. M.</dc:creator>
<dc:creator>Froemke, R.</dc:creator>
<dc:creator>Chao, M. V.</dc:creator>
<dc:creator>Ferreira, S. T.</dc:creator>
<dc:date>2022-05-08</dc:date>
<dc:identifier>doi:10.1101/2022.05.07.491031</dc:identifier>
<dc:title><![CDATA[Oxytocin attenuates microglial activation and restores social and non-social memory in the APP/PS1 mouse model of Alzheimer's disease]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-05-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.03.16.484431v1?rss=1">
<title>
<![CDATA[
Saturated reconstruction of living brain tissue 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.03.16.484431v1?rss=1"
</link>
<description><![CDATA[
Complex wiring between neurons underlies the information-processing network enabling all brain functions, including cognition and memory. For understanding how the network is structured, processes information, and changes over time, comprehensive visualization of the architecture of living brain tissue with its cellular and molecular components would open up major opportunities. However, electron microscopy (EM) provides nanometre-scale resolution required for full in-silico reconstruction1-5, yet is limited to fixed specimens and static representations. Light microscopy allows live observation, with super-resolution approaches6-12 facilitating nanoscale visualization, but comprehensive 3D-reconstruction of living brain tissue has been hindered by tissue photo-burden, photobleaching, insufficient 3D-resolution, and inadequate signal-to-noise ratio (SNR). Here we demonstrate saturated reconstruction of living brain tissue. We developed an integrated imaging and analysis technology, adapting stimulated emission depletion (STED) microscopy6,13 in extracellularly labelled tissue14 for high SNR and near-isotropic resolution. Centrally, a two-stage deep-learning approach leveraged previously obtained information on sample structure to drastically reduce photo-burden and enable automated volumetric reconstruction down to single synapse level. Live reconstruction provides unbiased analysis of tissue architecture across time in relation to functional activity and targeted activation, and contextual understanding of molecular labelling. This adoptable technology will facilitate novel insights into the dynamic functional architecture of living brain tissue.
]]></description>
<dc:creator>Velicky, P.</dc:creator>
<dc:creator>Miguel, E.</dc:creator>
<dc:creator>Michalska, J. M.</dc:creator>
<dc:creator>Wei, D.</dc:creator>
<dc:creator>Lin, Z.</dc:creator>
<dc:creator>Watson, J. F.</dc:creator>
<dc:creator>Troidl, J.</dc:creator>
<dc:creator>Beyer, J.</dc:creator>
<dc:creator>Ben-Simon, Y.</dc:creator>
<dc:creator>Sommer, C.</dc:creator>
<dc:creator>Jahr, W.</dc:creator>
<dc:creator>Cenameri, A.</dc:creator>
<dc:creator>Broichhagen, J.</dc:creator>
<dc:creator>Grant, S. G. N.</dc:creator>
<dc:creator>Jonas, P.</dc:creator>
<dc:creator>Novarino, G.</dc:creator>
<dc:creator>Pfister, H.</dc:creator>
<dc:creator>Bickel, B.</dc:creator>
<dc:creator>Danzl, J. G.</dc:creator>
<dc:date>2022-03-18</dc:date>
<dc:identifier>doi:10.1101/2022.03.16.484431</dc:identifier>
<dc:title><![CDATA[Saturated reconstruction of living brain tissue]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-03-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.05.19.491028v1?rss=1">
<title>
<![CDATA[
Narrowband gamma oscillations propagate and synchronize throughout the mouse thalamocortical visual system 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.05.19.491028v1?rss=1"
</link>
<description><![CDATA[
Rhythmic oscillations of neural activity permeate sensory systems. Studies in the visual system propose that broadband gamma oscillations (30 - 80 Hz) facilitate neuronal communication underlying visual perception. However, broadband gamma oscillations within and across visual areas show widely varying frequency and phase, providing constraints for synchronizing spike timing. Here, we analyzed data from the Allen Brain Observatory and performed new experiments that show narrowband gamma (NBG) oscillations (50 - 70 Hz) propagate and synchronize throughout the awake mouse thalamocortical visual system. Lateral geniculate (LGN) neurons fired with millisecond precision relative to NBG phase in primary visual cortex (V1) and multiple higher visual areas (HVAs). NBG in HVAs depended upon retinotopically aligned V1 activity, and neurons that fired at NBG frequencies showed enhanced functional connectivity within and across visual areas. Remarkably, LGN ON versus OFF neurons showed distinct and reliable spike timing relative to NBG oscillation phase across LGN, V1, and HVAs. Taken together, NBG oscillations may serve as a novel substrate for precise coordination of spike timing in functionally distinct subnetworks of neurons spanning multiple brain areas during awake vision.
]]></description>
<dc:creator>Shin, D.</dc:creator>
<dc:creator>Peelman, K.</dc:creator>
<dc:creator>Del Rosario, J.</dc:creator>
<dc:creator>Haider, B.</dc:creator>
<dc:date>2022-05-20</dc:date>
<dc:identifier>doi:10.1101/2022.05.19.491028</dc:identifier>
<dc:title><![CDATA[Narrowband gamma oscillations propagate and synchronize throughout the mouse thalamocortical visual system]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-05-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.03.19.484988v1?rss=1">
<title>
<![CDATA[
ASD modelling in organoids reveals imbalance of excitatory cortical neuron subtypes during early neurogenesis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.03.19.484988v1?rss=1"
</link>
<description><![CDATA[
There is no clear genetic etiology or convergent pathophysiology for autism spectrum disorders (ASD). Using cortical organoids and single-cell transcriptomics, we modeled alterations in the formation of the forebrain between sons with idiopathic ASD and their unaffected fathers in thirteen families. Alterations in the transcriptome suggest that ASD pathogenesis in macrocephalic and normocephalic probands involves an opposite disruption of the balance between the excitatory neurons of the dorsal cortical plate and other lineages such as the early-generated neurons from the putative preplate. The imbalance stemmed from a divergent expression of transcription factors driving cell fate during early cortical development. While we did not find probands genomic variants explaining the observed transcriptomic alterations, a significant overlap between altered transcripts and reported ASD risk genes affected by rare variants suggests a degree of gene convergence between rare forms of ASD and developmental transcriptome in idiopathic ASD.
]]></description>
<dc:creator>Jourdon, A.</dc:creator>
<dc:creator>Wu, F.</dc:creator>
<dc:creator>Mariani, J.</dc:creator>
<dc:creator>Capauto, D.</dc:creator>
<dc:creator>Norton, S.</dc:creator>
<dc:creator>Tomasini, L.</dc:creator>
<dc:creator>Amiri, A.</dc:creator>
<dc:creator>Suvakov, M.</dc:creator>
<dc:creator>Schreiner, J.</dc:creator>
<dc:creator>Jang, Y.</dc:creator>
<dc:creator>Nguyen, C. K.</dc:creator>
<dc:creator>Cummings, E. M.</dc:creator>
<dc:creator>Han, G.</dc:creator>
<dc:creator>Powell, K.</dc:creator>
<dc:creator>Szekely, A.</dc:creator>
<dc:creator>McPartland, J. C.</dc:creator>
<dc:creator>Pelphrey, K.</dc:creator>
<dc:creator>Chawarska, K.</dc:creator>
<dc:creator>Ventola, P.</dc:creator>
<dc:creator>Abyzov, A.</dc:creator>
<dc:creator>Vaccarino, F. M.</dc:creator>
<dc:date>2022-03-20</dc:date>
<dc:identifier>doi:10.1101/2022.03.19.484988</dc:identifier>
<dc:title><![CDATA[ASD modelling in organoids reveals imbalance of excitatory cortical neuron subtypes during early neurogenesis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-03-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.03.21.484899v1?rss=1">
<title>
<![CDATA[
Dissociable Cellular and Genetic Mechanisms of Cortical Thinning at Different Life Stages 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.03.21.484899v1?rss=1"
</link>
<description><![CDATA[
Mechanisms underpinning age-related variations in cortical thickness in the human brain remain poorly understood. We investigated whether inter-regional age-related variations in cortical thinning (in a multicohort neuroimaging dataset from the ENIGMA Lifespan Working Group totalling 14,248 individuals, aged 4-89 years) depended on cell-specific marker gene expression levels. We found differences amidst early-life (<20 years), mid-life (20-60 years), and late-life (>60 years) in the patterns of association between inter-regional profiles of cortical thickness and expression profiles of marker genes for CA1 and S1 pyramidal cells, astrocytes, and microglia. Gene ontology and enrichment analyses indicated that each of the three life-stages was associated with different biological processes and cellular components: synaptic modeling in early life, neurotransmission in mid-life, and neurodegeneration in late-life. These findings provide mechanistic insights into age-related cortical thinning during typical development and aging.
]]></description>
<dc:creator>Modabbernia, A.</dc:creator>
<dc:creator>Vidal-Pineiro, D.</dc:creator>
<dc:creator>Agartz, I.</dc:creator>
<dc:creator>Andreassen, O. A.</dc:creator>
<dc:creator>Ayesa-Arriola, R.</dc:creator>
<dc:creator>Bertolino, A.</dc:creator>
<dc:creator>Boomsma, D. I.</dc:creator>
<dc:creator>Bourque, J.</dc:creator>
<dc:creator>Breier, A.</dc:creator>
<dc:creator>Brouwer, R. M.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Canales-Rodriguez, E. J.</dc:creator>
<dc:creator>Caseras, X.</dc:creator>
<dc:creator>Conrod, P. J.</dc:creator>
<dc:creator>Crespo-Facorro, B.</dc:creator>
<dc:creator>Crivello, F.</dc:creator>
<dc:creator>Crone, E. A.</dc:creator>
<dc:creator>de Zubicaray, G. I.</dc:creator>
<dc:creator>Dickie, E. W.</dc:creator>
<dc:creator>Dima, D.</dc:creator>
<dc:creator>Frenzel, S.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Glahn, D. C.</dc:creator>
<dc:creator>Grabe, H.-J.</dc:creator>
<dc:creator>Grotegerd, D.</dc:creator>
<dc:creator>Gruber, O.</dc:creator>
<dc:creator>Guerrero-Pedraza, A.</dc:creator>
<dc:creator>Gur, R. E.</dc:creator>
<dc:creator>Gur, R. C.</dc:creator>
<dc:creator>Hartman, C. A.</dc:creator>
<dc:creator>Hoekstra, P. J.</dc:creator>
<dc:creator>Hulshoff Pol, H. E.</dc:creator>
<dc:creator>Jahanshad, N.</dc:creator>
<dc:creator>Jernigan, T. L.</dc:creator>
<dc:creator>Jiang, J.</dc:creator>
<dc:creator>Kalnin, A. J.</dc:creator>
<dc:creator>Kochan, N. A.</dc:creator>
<dc:creator>Mazoyer,</dc:creator>
<dc:date>2022-03-22</dc:date>
<dc:identifier>doi:10.1101/2022.03.21.484899</dc:identifier>
<dc:title><![CDATA[Dissociable Cellular and Genetic Mechanisms of Cortical Thinning at Different Life Stages]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-03-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.03.25.485726v1?rss=1">
<title>
<![CDATA[
Mobile elements in human population-specific genome and phenotype divergence 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.03.25.485726v1?rss=1"
</link>
<description><![CDATA[
Mobile genetic elements (MEs) are heritable mutagens that contribute to divergence between lineages by recursively generating structural variants. ME variants (MEVs) are difficult to genotype, obscuring their impact on recent genome and trait diversification. We developed a tool that uses short-read sequence data to accurately genotype MEVs, enabling us to study them using statistical genetics methods in global human genomes. We observe population-specific differences in the distribution of Alu insertions that distinguish Japanese from other populations. We integrated MEVs with epigenomic and expression quantitative trait loci (eQTL) maps to determine how they impact traits. This reveals coherent patterns by which specific MEs regulate tissue-specific gene expression, including creating or attenuating enhancers and recruiting post-transcriptional regulators. We pinpoint MEVs as genetic causes of disease risk, including a LINE-1 insertion linked to keloid and other diseases of fibroblast inflammation, by introducing MEVs into the genome-wide association study (GWAS) framework. In addition to nominating previously-hidden MEVs as causes of human diseases, this work highlights MEs as accelerators of human population divergence and begins to decipher the semantics of MEs.
]]></description>
<dc:creator>Kojima, S.</dc:creator>
<dc:creator>Koyama, S.</dc:creator>
<dc:creator>Ka, M.</dc:creator>
<dc:creator>Saito, Y.</dc:creator>
<dc:creator>Parrish, E. H.</dc:creator>
<dc:creator>Endo, M.</dc:creator>
<dc:creator>Takata, S.</dc:creator>
<dc:creator>Mizukoshi, M.</dc:creator>
<dc:creator>Hikino, K.</dc:creator>
<dc:creator>Takeda, A.</dc:creator>
<dc:creator>Gelinas, A. F.</dc:creator>
<dc:creator>Heaton, S. M.</dc:creator>
<dc:creator>Koide, R.</dc:creator>
<dc:creator>Kamada, A. J.</dc:creator>
<dc:creator>Noguchi, M.</dc:creator>
<dc:creator>Hamada, M.</dc:creator>
<dc:creator>Biobank Japan Project Consortium,</dc:creator>
<dc:creator>Kamatani, Y.</dc:creator>
<dc:creator>Murakawa, Y.</dc:creator>
<dc:creator>Ishigaki, K.</dc:creator>
<dc:creator>Nakamura, Y.</dc:creator>
<dc:creator>Ito, K.</dc:creator>
<dc:creator>Terao, C.</dc:creator>
<dc:creator>Momozawa, Y.</dc:creator>
<dc:creator>Parrish, N. F.</dc:creator>
<dc:date>2022-03-27</dc:date>
<dc:identifier>doi:10.1101/2022.03.25.485726</dc:identifier>
<dc:title><![CDATA[Mobile elements in human population-specific genome and phenotype divergence]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-03-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.03.29.486195v1?rss=1">
<title>
<![CDATA[
Glial dysregulation in human brain in Fragile X-related disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.03.29.486195v1?rss=1"
</link>
<description><![CDATA[
AbstractWhile large trinucleotide repeat expansions at the FMR1 locus cause Fragile X Syndrome (FXS), smaller "premutations" are associated with the late-onset condition Fragile X-associated tremor/ataxia syndrome (FXTAS), which shows very different clinical and pathological features, with no clear molecular explanation for these marked differences. One prevailing theory posits that the premutation uniquely causes neurotoxic increases in FMR1 mRNA (i.e., 4-8-fold increases), but evidence to support this hypothesis is largely derived from analysis of peripheral blood. We applied single- nucleus RNA-sequencing to post-mortem frontal cortex and cerebellum from 9 individuals with Fragile X mutations as well as age and sex matched controls (n=6) to assess cell-type specific molecular neuropathology. We found robust reduction of FMR1 mRNA in FXS as expected, with modest but significant upregulation ([~]1.3 fold) of FMR1 in glial clusters associated with premutation expansions. In premutation cases we identified alterations in glia number in cortex and cerebellum. Differential expression analysis demonstrated altered cortical oligodendrocyte development, while gene ontology analysis revealed alterations in neuroregulatory roles of glia, such as glial modulation of neurotransmission and synaptic structure. We identified significant enrichment of known FMR1 protein target genes in differentially expressed gene lists in FXS as well as the premutation, suggesting FMR1 protein target pathways may represent a shared source of dysfunction in both conditions despite opposite FMR1 mRNA changes. These findings challenge existing dogma regarding FXTAS and implicate glial dysregulation as a critical facet of premutation pathophysiology, representing novel therapeutic targets directly derived from the human condition.
]]></description>
<dc:creator>Dias, C. M.</dc:creator>
<dc:creator>Talukdar, M.</dc:creator>
<dc:creator>Akula, S.</dc:creator>
<dc:creator>Walsh, K. G.</dc:creator>
<dc:creator>Walsh, C. A.</dc:creator>
<dc:date>2022-03-29</dc:date>
<dc:identifier>doi:10.1101/2022.03.29.486195</dc:identifier>
<dc:title><![CDATA[Glial dysregulation in human brain in Fragile X-related disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-03-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.03.30.486483v1?rss=1">
<title>
<![CDATA[
CRISPR activation rescues abnormalities in SCN2A haploinsufficiency-associated autism spectrum disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.03.30.486483v1?rss=1"
</link>
<description><![CDATA[
The majority of autism spectrum disorder (ASD) risk genes are associated with ASD due to haploinsufficiency, where only one gene copy is functional. Here, using SCN2A haploinsufficiency, a major risk factor for ASD, we show that increasing the expression of the existing functional SCN2A allele with CRISPR activation (CRISPRa) can provide a viable therapeutic approach. We first demonstrate therapeutic potential by showing that restoring Scn2a expression in adolescent heterozygous Scn2a conditional knock-in mice rescues electrophysiological deficits associated with Scn2a haploinsufficiency. Next, using an rAAV-CRISPRa based treatment, we restore electrophysiological deficits in both Scn2a heterozygous mice and human stem-cell-derived neurons. Our results provide a novel therapeutic approach for numerous ASD-associated genes and demonstrate that rescue of Scn2a haploinsufficiency, even at adolescent stages, can ameliorate neurodevelopmental phenotypes.
]]></description>
<dc:creator>Tamura, S.</dc:creator>
<dc:creator>Nelson, A. D.</dc:creator>
<dc:creator>Spratt, P. W.</dc:creator>
<dc:creator>Kyoung, H.</dc:creator>
<dc:creator>Zhou, X.</dc:creator>
<dc:creator>Li, Z.</dc:creator>
<dc:creator>Zhao, J.</dc:creator>
<dc:creator>Holden, S. S.</dc:creator>
<dc:creator>Sahagun, A.</dc:creator>
<dc:creator>Keeshen, C. M.</dc:creator>
<dc:creator>Lu, C.</dc:creator>
<dc:creator>Hamada, E. C.</dc:creator>
<dc:creator>Ben-Shalom, R.</dc:creator>
<dc:creator>Pan, J. Q.</dc:creator>
<dc:creator>Paz, J. T.</dc:creator>
<dc:creator>Sanders, S. J.</dc:creator>
<dc:creator>Matharu, N.</dc:creator>
<dc:creator>Ahituv, N.</dc:creator>
<dc:creator>Bender, K. J.</dc:creator>
<dc:date>2022-04-01</dc:date>
<dc:identifier>doi:10.1101/2022.03.30.486483</dc:identifier>
<dc:title><![CDATA[CRISPR activation rescues abnormalities in SCN2A haploinsufficiency-associated autism spectrum disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-04-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.07.04.451055v1?rss=1">
<title>
<![CDATA[
De novo human brain enhancers created by single nucleotide mutations 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.07.04.451055v1?rss=1"
</link>
<description><![CDATA[
Advanced human cognition is attributed to increased neocortex size and complexity, but the underlying gene regulatory mechanisms are unknown. Using deep learning model of embryonic neocortical enhancers, and human and macaque embryonic neocortex H3K27ac data, we identified ~4000 enhancers gained de novo in the human, largely attributable to single-nucleotide essential mutations. The genes near de novo gained enhancers exhibit increased expression in human embryonic neocortex relative to macaque, are involved in critical neural developmental processes, and are expressed specifically in the progenitor cells and interneurons. The gained enhancers, especially the essential mutations, are associated with central nervous system disorders/traits. Integrative computational analyses suggest that the essential mutations establish enhancer activities through affecting binding of key transcription factors of embryonic neocortex. Overall, our results suggest that non-coding mutations may have led to de novo enhancer gains in the embryonic human neocortex, that orchestrate the expression of genes involved in critical developmental processes associated with human cognition.
]]></description>
<dc:creator>Li, S.</dc:creator>
<dc:creator>Hannenhalli, S.</dc:creator>
<dc:creator>Ovcharenko, I.</dc:creator>
<dc:date>2021-07-05</dc:date>
<dc:identifier>doi:10.1101/2021.07.04.451055</dc:identifier>
<dc:title><![CDATA[De novo human brain enhancers created by single nucleotide mutations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-07-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.04.04.486775v1?rss=1">
<title>
<![CDATA[
Gut Enterochromaffin Cells are Critical Drivers of Visceral Pain and Anxiety 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.04.04.486775v1?rss=1"
</link>
<description><![CDATA[
Gastrointestinal (GI) discomfort is a hallmark of most gut disorders and represents a significant component of chronic visceral pain 1. For the growing population afflicted by irritable bowel syndrome (IBS), GI hypersensitivity and pain persist long after signs of tissue injury have resolved 2. IBS also exhibits a strong sex bias afflicting women three-fold more than men 1. Identifying the molecules, cells, and circuits that mediate both the acute and persistent phases of visceral pain is a critical first step in understanding how environmental and endogenous factors produce long-term changes in the nervous system or associated tissues to engender chronic pain syndromes 3,4. Enterochromaffin (EC) cells within the gut epithelium are exceedingly rare sensory neuroendocrine cells that detect and transduce noxious stimuli to nearby nerve endings via serotonin. Here, we manipulate murine EC cell activity using genetic strategies to ascertain their contributions to visceral pain. We show that acute EC cell activation is sufficient to elicit hypersensitivity to gut distension and necessary for the sensitizing actions of isovalerate, a bacterially derived short-chain fatty acid irritant associated with inflammatory GI disorders. Remarkably, prolonged EC cell activation by itself is sufficient to produce persistent visceral hypersensitivity, even in the absence of an instigating inflammatory episode. Perturbing the activity of these rare EC cells led to a marked increase in anxiety-like behaviors that normalized after blocking serotonergic signaling. Sex differences were also observed accross a range of assays indicating that females have a higher baseline visceral sensitivity. Our findings validate a critical role for EC cell-mucosal afferent signaling in acute and persistent GI pain while highlighting mechanistically defined genetic models for studying visceral hypersensitivity, sex differences, and associated behaviors.
]]></description>
<dc:creator>Bayrer, J. R.</dc:creator>
<dc:creator>Castro, J.</dc:creator>
<dc:creator>Venkataramen, A.</dc:creator>
<dc:creator>Touhara, K. K.</dc:creator>
<dc:creator>Rossen, N. D.</dc:creator>
<dc:creator>Morrie, R. D.</dc:creator>
<dc:creator>Hendry, A.</dc:creator>
<dc:creator>Madden, J.</dc:creator>
<dc:creator>Braverman, K.</dc:creator>
<dc:creator>Schober, G.</dc:creator>
<dc:creator>Brizuela, M.</dc:creator>
<dc:creator>Bueno Silva, C.</dc:creator>
<dc:creator>Ingraham, H. A.</dc:creator>
<dc:creator>Brierley, S. M.</dc:creator>
<dc:creator>Julius, D.</dc:creator>
<dc:date>2022-04-05</dc:date>
<dc:identifier>doi:10.1101/2022.04.04.486775</dc:identifier>
<dc:title><![CDATA[Gut Enterochromaffin Cells are Critical Drivers of Visceral Pain and Anxiety]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-04-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.01.446561v1?rss=1">
<title>
<![CDATA[
Spatial and temporal autocorrelation weave human brain networks 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.01.446561v1?rss=1"
</link>
<description><![CDATA[
High-throughput experimental methods in neuroscience have led to an explosion of techniques for measuring complex interactions and multi-dimensional patterns. However, whether sophisticated measures of emergent phenomena can be traced back to simpler low-dimensional statistics is largely unknown. To explore this question, we examine resting state fMRI (rs-fMRI) data using complex topology measures from network neuroscience. We show that spatial and temporal autocorrelation are reliable statistics which explain numerous measures of network topology. Surrogate timeseries with subject-matched spatial and temporal autocorrelation capture nearly all reliable individual and regional variation in these topology measures. Network topology changes during aging are driven by spatial autocorrelation, and multiple serotonergic drugs causally induce the same topographic change in temporal autocorrelation. This reductionistic interpretation of widely-used complexity measures may help link them to neurobiology.
]]></description>
<dc:creator>Shinn, M.</dc:creator>
<dc:creator>Hu, A.</dc:creator>
<dc:creator>Turner, L.</dc:creator>
<dc:creator>Noble, S.</dc:creator>
<dc:creator>Achard, S.</dc:creator>
<dc:creator>Anticevic, A.</dc:creator>
<dc:creator>Scheinost, D.</dc:creator>
<dc:creator>Constable, R. T.</dc:creator>
<dc:creator>Lee, D.</dc:creator>
<dc:creator>Bullmore, E. T.</dc:creator>
<dc:creator>Murray, J. D.</dc:creator>
<dc:date>2021-06-01</dc:date>
<dc:identifier>doi:10.1101/2021.06.01.446561</dc:identifier>
<dc:title><![CDATA[Spatial and temporal autocorrelation weave human brain networks]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.02.13.480215v1?rss=1">
<title>
<![CDATA[
Quantitative fate mapping: Reconstructing progenitor field dynamics via retrospective lineage barcoding 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.02.13.480215v1?rss=1"
</link>
<description><![CDATA[
Natural and induced somatic mutations that accumulate in the genome during development record the phylogenetic relationships of cells; however, whether these lineage barcodes can capture the dynamics of complex progenitor fields remains unclear. Here, we introduce quantitative fate mapping, an approach to simultaneously map the fate and quantify the commitment time, commitment bias, and population size of multiple progenitor groups during development based on a time-scaled phylogeny of their descendants. To reconstruct time-scaled phylogenies from lineage barcodes, we introduce Phylotime, a scalable maximum likelihood clustering approach based on a generalizable barcoding mutagenesis model. We validate these approaches using realistically-simulated barcoding results as well as experimental results from a barcoding stem cell line. We further establish criteria for the minimum number of cells that must be analyzed for robust quantitative fate mapping. Overall, this work demonstrates how lineage barcodes, natural or synthetic, can be used to obtain quantitative fate maps, thus enabling analysis of progenitor dynamics long after embryonic development in any organism.
]]></description>
<dc:creator>Fang, W.</dc:creator>
<dc:creator>Bell, C. M.</dc:creator>
<dc:creator>Sapirstein, A.</dc:creator>
<dc:creator>Asami, S.</dc:creator>
<dc:creator>Leeper, K.</dc:creator>
<dc:creator>Zack, D. J.</dc:creator>
<dc:creator>Ji, H.</dc:creator>
<dc:creator>Kalhor, R.</dc:creator>
<dc:date>2022-02-14</dc:date>
<dc:identifier>doi:10.1101/2022.02.13.480215</dc:identifier>
<dc:title><![CDATA[Quantitative fate mapping: Reconstructing progenitor field dynamics via retrospective lineage barcoding]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-02-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.02.16.480649v1?rss=1">
<title>
<![CDATA[
Autism is associated with inter-individual variations of gray and white matter morphology 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.02.16.480649v1?rss=1"
</link>
<description><![CDATA[
BackgroundAlthough many studies have explored atypicalities in gray and white matter (GM, WM) morphology of autism, most of them rely on unimodal analyses that do not benefit from the likelihood that different imaging modalities may reflect common neurobiology. We aimed to establish multimodal brain patterns that differentiate between autism and typically developing (TD) controls and explore associations between these brain patterns and clinical measures.

MethodsWe studied 183 individuals with autism and 157 TD individuals (6-30 years) in a large deeply phenotyped autism dataset (EU-AIMS LEAP). Linked Independent Component Analysis was utilized to link all participants GM and WM images, and group comparisons of modality shared variances were examined. Subsequently, we performed a canonical correlation analysis to explore the aggregated effects between all multimodal GM-WM covariations and clinical profiles.

ResultsOne multimodal pattern was significantly related to autism. This pattern was primarily associated with GM in bilateral insula, frontal, pre- and post-central, cingulate, and caudate areas, and co-occurred with altered WM features in the superior longitudinal fasciculus. The canonical analysis showed a significant multivariate correlation primarily between multimodal brain patterns that involved variation of corpus callosum, and symptoms of social affect in the autism group.

ConclusionsOur findings demonstrate the assets of integrated analyses of GM and WM alterations to study the brain mechanisms that underpin autism, and show that the complex clinical autism phenotype can be interpreted by multimodal brain patterns that are spread across the brain involving both cortical and subcortical areas.
]]></description>
<dc:creator>Mei, T.</dc:creator>
<dc:creator>Forde, N. J.</dc:creator>
<dc:creator>Floris, D. L.</dc:creator>
<dc:creator>Dell'Acqua, F.</dc:creator>
<dc:creator>Stones, R.</dc:creator>
<dc:creator>Ilioska, I.</dc:creator>
<dc:creator>Durston, S.</dc:creator>
<dc:creator>Moessnang, C.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Holt, R. J.</dc:creator>
<dc:creator>Baron-Cohen, S.</dc:creator>
<dc:creator>Rausch, A.</dc:creator>
<dc:creator>Loth, E.</dc:creator>
<dc:creator>Oakley, B.</dc:creator>
<dc:creator>Charman, T.</dc:creator>
<dc:creator>Ecker, C.</dc:creator>
<dc:creator>Murphy, D. G. M.</dc:creator>
<dc:creator>the EU-AIMS LEAP group,</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Llera, A.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:date>2022-02-17</dc:date>
<dc:identifier>doi:10.1101/2022.02.16.480649</dc:identifier>
<dc:title><![CDATA[Autism is associated with inter-individual variations of gray and white matter morphology]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-02-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.02.22.481408v1?rss=1">
<title>
<![CDATA[
Patterns of connectome variability in autism across five functional activation tasks. Fndings from the LEAP project 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.02.22.481408v1?rss=1"
</link>
<description><![CDATA[
BackgroundAutism spectrum disorder (autism) is a complex neurodevelopmental condition with pronounced behavioural, cognitive, and neural heterogeneities across individuals. Here, our goal was to characterise heterogeneity in autism by identifying patterns of neural diversity as reflected in BOLD fMRI in the way individuals with autism engage with a varied array of cognitive tasks.

MethodsAll analyses were based on the EU-AIMS/AIMS-2-TRIALS multisite Longitudinal European Autism Project (LEAP) with participants with autism and typically developing controls (TD) between 6 and 30 years of age. We employed a novel task-potency approach which combines the unique aspects of both resting-state fMRI and task-fMRI to quantify task-induced variations in the functional connectome. Normative modelling was used to map atypicality of features on an individual basis with respect to their distribution in neurotypical control participants. We applied robust out-of-sample canonical correlation analysis (CCA) to relate connectome data to behavioural data.

ResultsDeviation from the normative ranges of global functional connectivity was greater for individuals with autism compared to TD in each fMRI task paradigm (all tasks p<0.001). The similarity across individuals of the deviation pattern was significantly increased in autistic relative to TD individuals (p<0.002). The CCA identified significant and robust brainbehavior covariation between functional connectivity atypicality and autism-related behavioral features.

ConclusionsIndividuals with autism engage with tasks in a globally atypical way, but the particular spatial pattern of this atypicality is nevertheless similar across tasks. Atypicalities in the tasks originate mostly from prefrontal cortex and default mode network regions, but also speech and auditory networks. We show, moving forward, sophisticated modeling methods such as task-potency and normative modeling will prove key to unravelling complex heterogeneous conditions like autism.
]]></description>
<dc:creator>Looden, T.</dc:creator>
<dc:creator>Floris, D. L.</dc:creator>
<dc:creator>Llera Arenas, A.</dc:creator>
<dc:creator>Chauvin, R. J.</dc:creator>
<dc:creator>Charman, T.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Murphy, D.</dc:creator>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>the AIMS-2-TRIALS group,</dc:creator>
<dc:date>2022-02-23</dc:date>
<dc:identifier>doi:10.1101/2022.02.22.481408</dc:identifier>
<dc:title><![CDATA[Patterns of connectome variability in autism across five functional activation tasks. Fndings from the LEAP project]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-02-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.02.28.482352v1?rss=1">
<title>
<![CDATA[
EphB1 controls proper long-range cortical axon guidance through a cell non-autonomous role in GABAergic cells 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.02.28.482352v1?rss=1"
</link>
<description><![CDATA[
EphB1 is required for proper guidance of cortical axon projections during brain development, but how EphB1 regulates this process remains unclear. We show here that EphB1 conditional knockout (cKO) in GABAergic cells (Vgat-Cre or Dlx1/2-Cre), but not in cortical excitatory neurons (Emx1-Cre), reproduced the cortical axon guidance defects observed in global EphB1 KO mice. Interestingly, in EphB1 cKOVgat mice, the misguided axon bundles contained comingled striatal GABAergic and somatosensory cortical glutamatergic axons. In wildtype mice, somatosensory axons also co-fasciculated with striatal axons notably in the globus pallidus, suggesting that a subset of glutamatergic cortical axons normally follows long-range GABAergic axons to reach their targets. Surprisingly, the ectopic axons in EphB1 KO mice were juxtaposed to major blood vessels. However, conditional loss of EphB1 in endothelial cells (Tie2-Cre), or in mural and oligodendrocyte precursor cells (Cspg4-Cre) did not produce the axon guidance defects, suggesting that EphB1 in GABAergic neurons normally promotes avoidance of these ectopic axons from following the developing vasculature. Together, our data reveal a new role for EphB1 in GABAergic neurons to influence proper cortical glutamatergic axon guidance during brain development.
]]></description>
<dc:creator>Assali, A.</dc:creator>
<dc:creator>Chenaux, G.</dc:creator>
<dc:creator>Cowan, C. W.</dc:creator>
<dc:date>2022-03-01</dc:date>
<dc:identifier>doi:10.1101/2022.02.28.482352</dc:identifier>
<dc:title><![CDATA[EphB1 controls proper long-range cortical axon guidance through a cell non-autonomous role in GABAergic cells]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-03-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.03.06.483119v1?rss=1">
<title>
<![CDATA[
Measuring the response to visually presented faces in the human lateral prefrontal cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.03.06.483119v1?rss=1"
</link>
<description><![CDATA[
Neuroimaging studies have identified multiple face-selective areas. In the current study we compared the functional response of the face area in the lateral prefrontal cortex to that of other face-selective areas. In Experiment 1 participants (N=32) were scanned viewing videos containing faces, bodies, scenes, objects, and scrambled objects. We identified a face-selective area in the right inferior frontal gyrus (rIFG). In Experiment 2 participants (N=24) viewed the videos or static images. Results showed that the rIFG, posterior superior temporal sulcus (pSTS) and occipital face area (OFA) exhibited a greater response to moving than static faces. In Experiment 3 participants (N=18) viewed face videos presented in the contralateral and ipsilateral visual fields. Results showed that the face areas in the IFG and pSTS responded equally to faces in both visual fields, while the OFA and fusiform face area (FFA) showed a contralateral bias. These experiments suggest two conclusions; firstly, in all three experiments the face area in the IFG was not as reliably identified as face areas in the occipitotemporal cortex. Secondly, the similarity of the response patterns in the IFG and pSTS face areas suggests that the areas are functionally connected, a conclusion consistent with neuroanatomical and functional connectivity evidence.
]]></description>
<dc:creator>Nikel, L.</dc:creator>
<dc:creator>Sliwinska, M.</dc:creator>
<dc:creator>Kucuk, E.</dc:creator>
<dc:creator>Ungerleider, L.</dc:creator>
<dc:creator>Pitcher, D.</dc:creator>
<dc:date>2022-03-07</dc:date>
<dc:identifier>doi:10.1101/2022.03.06.483119</dc:identifier>
<dc:title><![CDATA[Measuring the response to visually presented faces in the human lateral prefrontal cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-03-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.02.25.482050v1?rss=1">
<title>
<![CDATA[
Multi-omic analysis along the gut-brain axis points to a functional architecture of autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.02.25.482050v1?rss=1"
</link>
<description><![CDATA[
Autism is a highly heritable neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut-brain axis (GBA) has been implicated in autism, with dozens of cross-sectional microbiome and other omic studies revealing autism-specific profiles along the GBA albeit with little agreement in composition or magnitude. To explore the functional architecture of autism, we developed an age and sex-matched Bayesian differential ranking algorithm that identified autism-specific profiles across 10 cross-sectional microbiome datasets and 15 other omic datasets, including dietary patterns, metabolomics, cytokine profiles, and human brain expression profiles. The analysis uncovered a highly significant, functional architecture along the GBA that encapsulated the overall heterogeneity of autism phenotypes. This architecture was determined by autism-specific amino acid, carbohydrate and lipid metabolism profiles predominantly encoded by microbial species in the genera Prevotella, Enterococcus, Bifidobacterium, and Desulfovibrio, and was mirrored in brain-associated gene expression profiles and restrictive dietary patterns in individuals with autism. Pro-inflammatory cytokine profiling and virome association analysis further supported the existence of an autism-specific architecture associated with particular microbial genera. Re-analysis of a longitudinal intervention study in autism recapitulated the cross-sectional profiles, and showed a strong association between temporal changes in microbiome composition and autism symptoms. Further elucidation of the functional architecture of autism, including of the role the microbiome plays in it, will require deep, multi-omic longitudinal intervention studies on well-defined stratified cohorts to support causal and mechanistic inference.
]]></description>
<dc:creator>Morton, J. T.</dc:creator>
<dc:creator>Jin, D.-m.</dc:creator>
<dc:creator>Mills, R.</dc:creator>
<dc:creator>Shao, Y.</dc:creator>
<dc:creator>Rahman, G.</dc:creator>
<dc:creator>Harold-Berding, K.</dc:creator>
<dc:creator>Needham, B. D.</dc:creator>
<dc:creator>Zurita, M. F.</dc:creator>
<dc:creator>David, M.</dc:creator>
<dc:creator>Averina, O.</dc:creator>
<dc:creator>Kovtun, A.</dc:creator>
<dc:creator>Noto, A.</dc:creator>
<dc:creator>Mussap, M.</dc:creator>
<dc:creator>Wang, M.</dc:creator>
<dc:creator>Frank, D.</dc:creator>
<dc:creator>Li, E.</dc:creator>
<dc:creator>Zhou, W.</dc:creator>
<dc:creator>Fanos, V.</dc:creator>
<dc:creator>Danilenko, V.</dc:creator>
<dc:creator>Wall, D. P.</dc:creator>
<dc:creator>Cardenas, P. A.</dc:creator>
<dc:creator>Baldeon, M.</dc:creator>
<dc:creator>xavier, r. j.</dc:creator>
<dc:creator>Mazmanian, S.</dc:creator>
<dc:creator>Knight, R.</dc:creator>
<dc:creator>Gilbert, J.</dc:creator>
<dc:creator>Donovan, S.</dc:creator>
<dc:creator>Lawley, T.</dc:creator>
<dc:creator>Carpenter, B.</dc:creator>
<dc:creator>Bonneau, R.</dc:creator>
<dc:creator>Taroncher-Oldenburg, G.</dc:creator>
<dc:date>2022-02-26</dc:date>
<dc:identifier>doi:10.1101/2022.02.25.482050</dc:identifier>
<dc:title><![CDATA[Multi-omic analysis along the gut-brain axis points to a functional architecture of autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-02-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.01.21.476409v1?rss=1">
<title>
<![CDATA[
Molecular and connectomic vulnerability shape cross-disorder cortical abnormalities 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.01.21.476409v1?rss=1"
</link>
<description><![CDATA[
Numerous brain disorders demonstrate structural brain abnormalities, which are thought to arise from molecular perturbations or connectome miswiring. The unique and shared contributions of these molecular and connectomic vulnerabilities to brain disorders remain unknown, and has yet to be studied in a single multi-disorder framework. Using MRI morphometry from the ENIGMA consortium, we construct maps of cortical abnormalities for thirteen neurodevelopmental, neurological, and psychiatric disorders from N = 21 000 patients and N = 26 000 controls, collected using a harmonized processing protocol. We systematically compare cortical maps to multiple micro-architectural measures, including gene expression, neurotransmitter density, metabolism, and myelination (molecular vulnerability), as well as global connectomic measures including number of connections, centrality, and connection diversity (connectomic vulnerability). We find that regional molecular vulnerability and macroscale brain network architecture interact to drive the spatial patterning of cortical abnormalities in multiple disorders. Local attributes, particularly neurotransmitter receptor profiles, constitute the best predictors of both disorder-specific cortical morphology and cross-disorder similarity. Finally, we find that cross-disorder abnormalities are consistently subtended by a small subset of network epicentres in bilateral sensory-motor, medial temporal lobe, precuneus, and superior parietal cortex. Collectively, our results highlight how local biological attributes and global connectivity jointly shape cross-disorder cortical abnormalities.
]]></description>
<dc:creator>Hansen, J. Y.</dc:creator>
<dc:creator>Shafiei, G. Y.</dc:creator>
<dc:creator>Vogel, J. W.</dc:creator>
<dc:creator>Smart, K.</dc:creator>
<dc:creator>Bearden, C. E.</dc:creator>
<dc:creator>Hoogman, M.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>van Rooij, D.</dc:creator>
<dc:creator>Buitelaar, J.</dc:creator>
<dc:creator>McDonald, C. R.</dc:creator>
<dc:creator>Sisodiya, S.</dc:creator>
<dc:creator>Schmaal, L.</dc:creator>
<dc:creator>Veltman, D. J.</dc:creator>
<dc:creator>van den Heuvel, O. A.</dc:creator>
<dc:creator>Stein, D. J.</dc:creator>
<dc:creator>van Erp, T. G.</dc:creator>
<dc:creator>Ching, C.</dc:creator>
<dc:creator>Andreassen, O. A.</dc:creator>
<dc:creator>Hajek, T.</dc:creator>
<dc:creator>Opel, N.</dc:creator>
<dc:creator>Modinos, G.</dc:creator>
<dc:creator>Aleman, A.</dc:creator>
<dc:creator>van der Werf, Y.</dc:creator>
<dc:creator>Jahanshad, N.</dc:creator>
<dc:creator>Thomopoulos, S. I.</dc:creator>
<dc:creator>Thompson, P. M.</dc:creator>
<dc:creator>Carson, R. E.</dc:creator>
<dc:creator>Dagher, A.</dc:creator>
<dc:creator>Misic, B.</dc:creator>
<dc:date>2022-01-21</dc:date>
<dc:identifier>doi:10.1101/2022.01.21.476409</dc:identifier>
<dc:title><![CDATA[Molecular and connectomic vulnerability shape cross-disorder cortical abnormalities]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-01-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.01.20.477039v1?rss=1">
<title>
<![CDATA[
Astrocyte glutamate transport is modulated by motor learning and regulates neuronal correlations and movement encoding by motor cortex neurons 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.01.20.477039v1?rss=1"
</link>
<description><![CDATA[
While motor cortex is crucial for learning precise and reliable movements, whether and how astrocytes contribute to its plasticity and function during motor learning is unknown. Here we report that primary motor cortex (M1) astrocytes in mice show in vivo plasticity during learning of a lever push task, as revealed by transcriptomic and functional modifications. In particular, we observe changes in expression of glutamate transporter genes and increased coincidence of intracellular calcium events. Astrocyte-specific manipulations of M1 are sufficient to alter motor learning and execution, and neuronal population coding, in the same task. Mice expressing decreased levels of the astrocyte glutamate transporter GLT1 show impaired and variable movement trajectories. Mice with increased astrocyte Gq signaling show decreased performance rates, delayed response times and impaired trajectories, along with abnormally high levels of GLT1. In both groups of mice, M1 neurons have altered inter-neuronal correlations and impaired population representations of task parameters, including response time and movement trajectories. Thus, astrocytes have a specific role in coordinating M1 neuronal activity during motor learning, and control learned movement execution and dexterity through mechanisms that importantly include fine regulation of glutamate transport.
]]></description>
<dc:creator>Delepine, C.</dc:creator>
<dc:creator>Li, K.</dc:creator>
<dc:creator>Shih, J.</dc:creator>
<dc:creator>Gaudeaux, P.</dc:creator>
<dc:creator>Sur, M.</dc:creator>
<dc:date>2022-01-21</dc:date>
<dc:identifier>doi:10.1101/2022.01.20.477039</dc:identifier>
<dc:title><![CDATA[Astrocyte glutamate transport is modulated by motor learning and regulates neuronal correlations and movement encoding by motor cortex neurons]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-01-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2022.01.24.477572v1?rss=1">
<title>
<![CDATA[
Variability in sampling of cortex-wide neural dynamics explains individual differences in functional connectivity and behavioral phenotype 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2022.01.24.477572v1?rss=1"
</link>
<description><![CDATA[
Individual differences in behavior are associated with changes in the correlation of neural activity between brain areas. Such differences in  functional connectivity are thought to reflect individual differences in brain structure that alter the flow of neural activity between regions. Here, in contrast, we show that individual differences in functional connectivity and behavior can be explained by differences in how frequently an individual expresses distinct cortex-wide spatiotemporal patterns of neural activity. This suggests variability in sampling of cortex-wide neural dynamics may underlie individuals unique behavioral phenotypes.
]]></description>
<dc:creator>MacDowell, C. J.</dc:creator>
<dc:creator>Briones, B. A.</dc:creator>
<dc:creator>Lenzi, M. J.</dc:creator>
<dc:creator>Gustison, M. L.</dc:creator>
<dc:creator>Buschman, T. J.</dc:creator>
<dc:date>2022-01-25</dc:date>
<dc:identifier>doi:10.1101/2022.01.24.477572</dc:identifier>
<dc:title><![CDATA[Variability in sampling of cortex-wide neural dynamics explains individual differences in functional connectivity and behavioral phenotype]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2022-01-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.11.21.469432v1?rss=1">
<title>
<![CDATA[
Patient brain organoids identify a link between the 16p11.2 copy number variant and the RBFOX1 gene. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.11.21.469432v1?rss=1"
</link>
<description><![CDATA[
Copy number variants (CNVs) that delete or duplicate 30 genes within the 16p11.2 genomic region give rise to a range of neurodevelopmental phenotypes with high penetrance in humans. Despite the identification of this small region, the mechanisms by which 16p11.2 CNVs lead to disease are unclear. Relevant models, like human cortical organoids (hCOs), are needed to understand the human-specific mechanisms of neurodevelopmental disease. We generated hCOs from 18 patients and controls, profiling 167,958 cells with single cell (sc)RNA-seq. Analysis revealed neuronal-specific differential expression of genes outside of the 16p11.2 region that were related to cell-cell adhesion, neuronal projection growth, and neurodevelopmental disorders. Furthermore, 16p11.2 deletion syndrome organoids exhibited reduced mRNA and protein levels of RBFOX1, a gene which can also harbor CNVs linked to neurodevelopmental phenotypes. We found that many genes previously shown to be regulated by RBFOX1 are also perturbed in organoids from patients with 16p11.2 deletion syndrome, and thus identified a novel link between independent CNVs associated with neuronal development and autism. Overall, this work suggests convergent signaling, which indicates the possibility of a common therapeutic mechanism across multiple rare neuronal diseases.
]]></description>
<dc:creator>Kostic, M.</dc:creator>
<dc:creator>Raymond, J. J.</dc:creator>
<dc:creator>Henry, B.</dc:creator>
<dc:creator>Tumkaya, T.</dc:creator>
<dc:creator>Khlghatyan, J.</dc:creator>
<dc:creator>Dvornik, J.</dc:creator>
<dc:creator>Hsiao, J.</dc:creator>
<dc:creator>Cheon, S. H.</dc:creator>
<dc:creator>Chung, J.</dc:creator>
<dc:creator>Sun, Y.</dc:creator>
<dc:creator>Dolmetsch, R.</dc:creator>
<dc:creator>Worringer, K. A.</dc:creator>
<dc:creator>Ihry, R.</dc:creator>
<dc:date>2021-11-23</dc:date>
<dc:identifier>doi:10.1101/2021.11.21.469432</dc:identifier>
<dc:title><![CDATA[Patient brain organoids identify a link between the 16p11.2 copy number variant and the RBFOX1 gene.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-11-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.11.23.469743v1?rss=1">
<title>
<![CDATA[
The PAIR-R24M Dataset for Multi-animal 3D Pose Estimation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.11.23.469743v1?rss=1"
</link>
<description><![CDATA[
Understanding the biological basis of social and collective behaviors in animals is a key goal of the life sciences, and may yield important insights for engineering intelligent multi-agent systems. A critical step in interrogating the mechanisms underlying social behaviors is a precise readout of the 3D pose of interacting animals. While approaches for multi-animal pose estimation are beginning to emerge, they remain challenging to compare due to the lack of standardized training and benchmark datasets. Here we introduce the PAIR-R24M (Paired Acquisition of Interacting oRganisms - Rat) dataset for multi-animal 3D pose estimation, which contains 24.3 million frames of RGB video and 3D ground-truth motion capture of dyadic interactions in laboratory rats. PAIR-R24M contains data from 18 distinct pairs of rats and 24 different viewpoints. We annotated the data with 11 behavioral labels and 3 interaction categories to facilitate benchmarking in rare but challenging behaviors. To establish a baseline for markerless multi-animal 3D pose estimation, we developed a multi-animal extension of DANNCE, a recently published network for 3D pose estimation in freely behaving laboratory animals. As the first large multi-animal 3D pose estimation dataset, PAIR-R24M will help advance 3D animal tracking approaches and aid in elucidating the neural basis of social behaviors.
]]></description>
<dc:creator>Marshall, J. D.</dc:creator>
<dc:creator>Klibaite, U.</dc:creator>
<dc:creator>Gellis, A. J.</dc:creator>
<dc:creator>Aldarondo, D. E.</dc:creator>
<dc:creator>Olveczky, B. P.</dc:creator>
<dc:creator>Dunn, T. W.</dc:creator>
<dc:date>2021-11-25</dc:date>
<dc:identifier>doi:10.1101/2021.11.23.469743</dc:identifier>
<dc:title><![CDATA[The PAIR-R24M Dataset for Multi-animal 3D Pose Estimation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-11-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.12.17.473207v1?rss=1">
<title>
<![CDATA[
Environmental carcinogens disproportionally mutate genes implicated in neurodevelopmental disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.12.17.473207v1?rss=1"
</link>
<description><![CDATA[
De novo mutations contribute to a large proportion of sporadic psychiatric and developmental disorders, yet the potential role of environmental carcinogens as drivers of causal de novo mutations in neurodevelopmental disorders is poorly studied. We demonstrate that several mutagens, including polycyclic aromatic hydrocarbons (PAHs), disproportionately mutate genes related to neurodevelopmental disorders including autism spectrum disorders (ASD), schizophrenia, and attention deficit hyperactivity disorder (ADHD). Other disease genes including amyotrophic lateral sclerosis (ALS), Alzheimers disease, congenital heart disease, orofacial clefts, and coronary artery disease were generally not mutated more than expected. Our findings support a new paradigm of neurodevelopmental disease etiology driven by a contribution of environmentally induced rather than random mutations.
]]></description>
<dc:creator>Baker, B. H.</dc:creator>
<dc:creator>Zhang, S.</dc:creator>
<dc:creator>Simon, J. M.</dc:creator>
<dc:creator>McLarnan, S. M.</dc:creator>
<dc:creator>Chung, W. K.</dc:creator>
<dc:creator>Pearson, B. L.</dc:creator>
<dc:date>2021-12-20</dc:date>
<dc:identifier>doi:10.1101/2021.12.17.473207</dc:identifier>
<dc:title><![CDATA[Environmental carcinogens disproportionally mutate genes implicated in neurodevelopmental disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-12-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.11.01.466849v1?rss=1">
<title>
<![CDATA[
Sex significantly impacts the function of major depression-linked variants in vivo 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.11.01.466849v1?rss=1"
</link>
<description><![CDATA[
Genome-wide association studies have discovered blocks of common variants--likely transcriptional-regulatory--associated with major depressive disorder (MDD), though the functional subset and their biological impacts remain unknown. Likewise, why depression occurs in females more frequently than males is unclear. We therefore tested the hypothesis that risk-associated functional variants interact with sex and produce greater impact in female brains. We developed methods to directly measure regulatory variant activity and sex interactions using massively parallel reporter assays (MPRAs) in the mouse brain in vivo, in a cell type-specific manner. We measured activity of >1,000 variants from >30 MDD loci, identifying extensive sex-by-allele effects in mature hippocampal neurons and suggesting sex-differentiated impacts of genetic risk may underlie sex bias in disease. Unbiased informatics approaches indicated that functional MDD variants recurrently disrupt sex hormone receptor binding sequences. We confirmed this with MPRAs in neonatal brains, comparing brains undergoing the masculinizing hormone surge to hormonally-quiescent juveniles. Our study provides novel insights into the influence of age, biological sex, and cell type on regulatory-variant function, and provides a framework for in vivo parallel assays to functionally define interactions between organismal variables like sex and regulatory variation.

One-Sentence SummaryMassively parallel assays in vivo identified extensive functional and sex-interacting common variants in depression risk loci.
]]></description>
<dc:creator>Mulvey, B.</dc:creator>
<dc:creator>Selmanovic, D.</dc:creator>
<dc:creator>Dougherty, J. D.</dc:creator>
<dc:date>2021-11-04</dc:date>
<dc:identifier>doi:10.1101/2021.11.01.466849</dc:identifier>
<dc:title><![CDATA[Sex significantly impacts the function of major depression-linked variants in vivo]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-11-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.11.12.468364v1?rss=1">
<title>
<![CDATA[
Cortical wiring by synapse-specific control of local protein synthesis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.11.12.468364v1?rss=1"
</link>
<description><![CDATA[
Neurons use local protein synthesis as a mechanism to support their morphological complexity, which requires independent control across multiple subcellular compartments including individual synapses. However, to what extent local translation is differentially regulated at the level of specific synaptic connections remains largely unknown. Here, we identify a signaling pathway that regulates the local synthesis of proteins required for the formation of excitatory synapses on parvalbumin-expressing (PV+) interneurons in the mouse cerebral cortex. This process involves the regulation of the mTORC1 inhibitor Tsc2 by the receptor tyrosine kinase ErbB4, which enables the local control of mRNA translation in a cell type-specific and synapse-specific manner. Ribosome-associated mRNA profiling reveals a molecular program of synaptic proteins that regulates the formation of excitatory inputs on PV+ interneurons downstream of ErbB4 signaling. Our work demonstrates that local protein translation is regulated at the level of specific connections to control synapse formation in the nervous system.
]]></description>
<dc:creator>Bernard, C.</dc:creator>
<dc:creator>Exposito-Alonso, D.</dc:creator>
<dc:creator>Selten, M.</dc:creator>
<dc:creator>Sanalidou, S.</dc:creator>
<dc:creator>Hanusz-Godoy, A.</dc:creator>
<dc:creator>Oozeer, F.</dc:creator>
<dc:creator>Maeso, P.</dc:creator>
<dc:creator>Rico, B.</dc:creator>
<dc:creator>Marin, O.</dc:creator>
<dc:date>2021-11-13</dc:date>
<dc:identifier>doi:10.1101/2021.11.12.468364</dc:identifier>
<dc:title><![CDATA[Cortical wiring by synapse-specific control of local protein synthesis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-11-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.09.13.460060v1?rss=1">
<title>
<![CDATA[
Adaptation and serial choice bias are unaltered in autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.09.13.460060v1?rss=1"
</link>
<description><![CDATA[
Autism Spectrum Disorder (ASD) or autism is characterized by social and non-social symptoms, including sensory hyper- and hyposensitivities. A suggestion has been put forward that some of these symptoms could be explained by differences in how sensory information is integrated with its context, including a lower tendency to leverage the past in the processing of new perceptual input. At least two history-dependent effects of opposite directions have been described in the visual perception literature: a repulsive adaptation effect, where perception of a stimulus is biased away from an adaptor stimulus, and an attractive serial choice bias, where perceptual choices are biased towards the previous choice. In this study, we investigated whether autistic participants differed in either bias from typically developing controls (TD). Sixty-four adolescent participants (31 with ASD, 33 TD) were asked to categorize oriented line stimuli in two tasks which were designed so that we would induce either adaptation or serial choice bias. Although our tasks successfully induced both biases, in comparing the two groups, we found no differences in the magnitude of adaptation nor in the modulation of perceptual choices by the previous choice. In conclusion, we find no evidence of a decreased integration of the past in visual perception of autistic individuals.
]]></description>
<dc:creator>Bosch, E.</dc:creator>
<dc:creator>Fritsche, M.</dc:creator>
<dc:creator>Utzerath, C.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2021-09-15</dc:date>
<dc:identifier>doi:10.1101/2021.09.13.460060</dc:identifier>
<dc:title><![CDATA[Adaptation and serial choice bias are unaltered in autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-09-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.09.418632v1?rss=1">
<title>
<![CDATA[
Dual color mesoscopic imaging reveals spatiotemporally heterogeneous coordination of cholinergic and neocortical activity. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.09.418632v1?rss=1"
</link>
<description><![CDATA[
Variation in an animals behavioral state is linked to fluctuations in brain activity and cognitive ability. In the neocortex, state-dependent control of circuit dynamics may reflect neuromodulatory influences including acetylcholine (ACh). While early literature suggested ACh exerts broad, homogeneous control over cortical function, recent evidence indicates potential anatomical and functional segregation of cholinergic signaling. Additionally, it is unclear whether states as defined by different behavioral markers reflect heterogeneous cholinergic and cortical network activity. We performed simultaneous, dual-color mesoscopic imaging of both ACh and calcium across the neocortex of awake mice to investigate their relationships with behavioral variables. We find that increasing arousal, categorized by different motor behaviors, is associated with spatiotemporally dynamic patterns of cholinergic release and enhanced large-scale network correlations. Overall, our findings demonstrate that ACh provides a highly dynamic and spatially heterogeneous signal that links fluctuations in behavior to functional reorganization of cortical networks.
]]></description>
<dc:creator>Lohani, S.</dc:creator>
<dc:creator>Moberly, A. H.</dc:creator>
<dc:creator>Benisty, H.</dc:creator>
<dc:creator>Landa, B.</dc:creator>
<dc:creator>Jing, M.</dc:creator>
<dc:creator>Li, Y.</dc:creator>
<dc:creator>Higley, M.</dc:creator>
<dc:creator>Cardin, J. A.</dc:creator>
<dc:date>2020-12-11</dc:date>
<dc:identifier>doi:10.1101/2020.12.09.418632</dc:identifier>
<dc:title><![CDATA[Dual color mesoscopic imaging reveals spatiotemporally heterogeneous coordination of cholinergic and neocortical activity.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.09.28.462195v1?rss=1">
<title>
<![CDATA[
Computational Fingerprints: Modeling Interactions Between Brain Regions as Points in a Function Space 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.09.28.462195v1?rss=1"
</link>
<description><![CDATA[
In this paper we propose a novel technique to investigate the nonlinear interactions between brain regions that captures both the strength and the type of the functional relationship. Inspired by the field of functional analysis, we propose that the relationship between activity in two different brain areas can be viewed as a point in function space, identified by coordinates along an infinite set of basis functions. Using Hermite Polynomials as basis functions, we estimate from fMRI data a truncated set of coordinates that serve as a "computational fingerprint," characterizing the interaction between two brain areas. We provide a proof of the convergence of the estimates in the limit, and we validate the method with simulations in which the ground truth is known, additionally showing that computational fingerprints detect statistical dependence also when correlations ("functional connectivity") is near zero. We then use computational fingerprints to examine the neural interactions with a seed region of choice: the Fusiform Face Area (FFA). Using k-means clustering across each voxels computational fingerprint, we illustrate that the addition of the nonlinear basis functions allows for the discrimination of inter-regional interactions that are otherwise grouped together when only linear dependence is used. Finally, we show that regions in V5 and medial occipital and temporal lobes exhibit significant nonlinear interactions with the FFA.
]]></description>
<dc:creator>Poskanzer, C.</dc:creator>
<dc:creator>Anzellotti, S.</dc:creator>
<dc:date>2021-09-30</dc:date>
<dc:identifier>doi:10.1101/2021.09.28.462195</dc:identifier>
<dc:title><![CDATA[Computational Fingerprints: Modeling Interactions Between Brain Regions as Points in a Function Space]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-09-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.10.01.462832v1?rss=1">
<title>
<![CDATA[
A general framework for identifying rare variant combinations in complex disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.10.01.462832v1?rss=1"
</link>
<description><![CDATA[
Genetic studies of complex disorders such as autism and intellectual disability (ID) are often based on enrichment of individual rare variants or their aggregate burden in affected individuals compared to controls. However, these studies overlook the influence of combinations of rare variants that may not be deleterious on their own due to statistical challenges resulting from rarity and combinatorial explosion when enumerating variant combinations, limiting our ability to study oligogenic basis for these disorders. We present a framework that combines the apriori algorithm and statistical inference to identify specific combinations of mutated genes associated with complex phenotypes. Our approach overcomes computational barriers and exhaustively evaluates variant combinations to identify non-additive relationships between simultaneously mutated genes. Using this approach, we analyzed 6,189 individuals with autism and identified 718 combinations significantly associated with ID, and carriers of these combinations showed lower IQ than expected in an independent cohort of 1,878 individuals. These combinations were enriched for nervous system genes such as NIN and NGF, showed complex inheritance patterns, and were depleted in unaffected siblings. We found that an affected individual can carry many oligogenic combinations, each contributing to the same phenotype or distinct phenotypes at varying effect sizes. We also used this framework to identify combinations associated with multiple comorbid phenotypes, including mutations of COL28A1 and MFSD2B for ID and schizophrenia and ABCA4, DNAH10 and MC1R for ID and anxiety/depression. Our framework identifies a key component of missing heritability and provides a novel paradigm to untangle the genetic architecture of complex disorders.

SIGNIFICANCEWhile rare mutations in single genes or their collective burden partially explain the genetic basis for complex disorders, the role of specific combinations of rare variants is not completely understood. This is because combinations of rare variants are rarer and evaluating all possible combinations would result in a combinatorial explosion, creating difficulties for statistical and computational analysis. We developed a data mining approach that overcomes these limitations to precisely quantify the influence of combinations of two or more mutated genes on a specific clinical feature or multiple co-occurring features. Our framework provides a new paradigm for dissecting the genetic causes of complex disorders and provides an impetus for its utility in clinical diagnosis.
]]></description>
<dc:creator>Pounraja, V. K.</dc:creator>
<dc:creator>Girirajan, S.</dc:creator>
<dc:date>2021-10-01</dc:date>
<dc:identifier>doi:10.1101/2021.10.01.462832</dc:identifier>
<dc:title><![CDATA[A general framework for identifying rare variant combinations in complex disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-10-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.10.25.465789v1?rss=1">
<title>
<![CDATA[
Biophysical Kv channel alterations dampen excitability of cortical PV interneurons and contribute to network hyperexcitability in early Alzheimer's 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.10.25.465789v1?rss=1"
</link>
<description><![CDATA[
In Alzheimers disease (AD), a multitude of genetic risk factors and early biomarkers are known. Nevertheless, the causal factors responsible for initiating cognitive decline in AD remain controversial. Toxic plaques and tangles correlate with progressive neuropathology, yet disruptions in circuit activity emerge before their deposition in AD models and patients. Parvalbumin (PV) interneurons are potential candidates for dysregulating cortical excitability, as they display altered AP firing before neighboring excitatory neurons in prodromal AD. Here we report a novel mechanism responsible for PV hypoexcitability in young adult familial AD mice. We found that biophysical modulation of K+ channels, but not changes in mRNA expression, are responsible for dampened excitability. These K+ conductances could efficiently regulate near-threshold AP firing, resulting in gamma-frequency specific network hyperexcitability. Our findings suggest that posttranslational modulation of ion channels can reshape cortical network activity prior to changes in their gene expression in early AD.
]]></description>
<dc:creator>Olah, V. J.</dc:creator>
<dc:creator>Goettemoeller, A. M.</dc:creator>
<dc:creator>Dimidschstein, J.</dc:creator>
<dc:creator>Rowan, M. J.</dc:creator>
<dc:date>2021-10-26</dc:date>
<dc:identifier>doi:10.1101/2021.10.25.465789</dc:identifier>
<dc:title><![CDATA[Biophysical Kv channel alterations dampen excitability of cortical PV interneurons and contribute to network hyperexcitability in early Alzheimer's]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-10-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/786822v1?rss=1">
<title>
<![CDATA[
MeCP2 deletion impaired layer 2/3-dominant dynamic reorganization of cortical circuit during motor skill learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/786822v1?rss=1"
</link>
<description><![CDATA[
Rett Syndrome (RTT) is a severe neurodevelopmental disorder caused by loss of function of the X-linked Methyl-CpG-binding protein 2 (MECP2). Several case studies report that gross motor function can be improved in children with RTT through treadmill walking, but whether the MeCP2-deficient motor circuit can support actual motor learning remains unclear. We used two-photon calcium imaging to simultaneously observe layer (L) 2/3 and L5a excitatory neuronal activity in the motor cortex (M1) while mice adapted to changing speeds on a computerized running wheel. Despite circuit hypoactivity and weakened functional connectivity across L2/3 and L5a, the Mecp2-null circuits firing pattern evolved with improved performance over two weeks. Moreover, trained mice became less anxious and lived 20% longer than untrained mice. Since motor deficits and anxiety are core symptoms of Rett, which is not diagnosed until well after symptom onset, these results underscore the benefit of motor learning.
]]></description>
<dc:creator>Yue, Y.</dc:creator>
<dc:creator>Xu, P.</dc:creator>
<dc:creator>Liu, Z.</dc:creator>
<dc:creator>Chen, Z.</dc:creator>
<dc:creator>Su, J.</dc:creator>
<dc:creator>Chen, A.</dc:creator>
<dc:creator>Ash, R.</dc:creator>
<dc:creator>Barut, E.</dc:creator>
<dc:creator>Simha, R.</dc:creator>
<dc:creator>Smirnakis, S. M.</dc:creator>
<dc:creator>Zeng, C.</dc:creator>
<dc:creator>Lu, H.</dc:creator>
<dc:date>2019-09-30</dc:date>
<dc:identifier>doi:10.1101/786822</dc:identifier>
<dc:title><![CDATA[MeCP2 deletion impaired layer 2/3-dominant dynamic reorganization of cortical circuit during motor skill learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.05.28.446151v1?rss=1">
<title>
<![CDATA[
Differences in social brain function in autism spectrum disorder are linked to the serotonin transporter 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.05.28.446151v1?rss=1"
</link>
<description><![CDATA[
Alterations in the serotonergic control of brain pathways responsible for facial-emotion processing in people with autism spectrum disorder (ASD) may be a target for intervention. However, the molecular underpinnings of autistic-neurotypical serotonergic differences are challenging to access in vivo. Receptor-Enriched Analysis of functional Connectivity by Targets (REACT) has helped define molecular-enriched fMRI brain networks based on a priori information about the spatial distribution of neurochemical systems from available PET templates. Here, we used REACT to estimate the dominant fMRI signal related to the serotonin transporter (5-HTT) distribution during processing of aversive facial expressions of emotion processing in adults with and without ASD. We first predicted a group difference in baseline (placebo) functioning of this system. We next used a single 20 mg oral dose of citalopram, i.e. a serotonin reuptake inhibitor, to test the hypothesis that network activity in people with and without ASD would respond differently to inhibition of 5-HTT. To confirm the specificity of our findings, we also repeated the analysis with 5-HT1A, 5-HT1B, 5-HT2A, and 5-HT4 receptor maps.

We found a baseline group difference in the 5-HTT-enriched response to faces in the ventromedial prefrontal cortex. A single oral dose of citalopram  shifted the response in the ASD group towards the neurotypical baseline but did not alter response in the control group.

Our findings suggest that the 5HTT-enriched functional network is dynamically different in ASD during processing of socially relevant stimuli. Whether this acute neurobiological response to citalopram in ASD translates to a clinical target will be an important next step.
]]></description>
<dc:creator>Wong, N. M. L.</dc:creator>
<dc:creator>Dipasquale, O.</dc:creator>
<dc:creator>Turkheimer, F. E.</dc:creator>
<dc:creator>Findon, J. L.</dc:creator>
<dc:creator>Wichers, R. H.</dc:creator>
<dc:creator>Dimitrov, M.</dc:creator>
<dc:creator>Murphy, C. M.</dc:creator>
<dc:creator>Stoencheva, V.</dc:creator>
<dc:creator>Robertson, D. M.</dc:creator>
<dc:creator>Murphy, D. G.</dc:creator>
<dc:creator>Daly, E.</dc:creator>
<dc:creator>McAlonan, G. M.</dc:creator>
<dc:date>2021-05-28</dc:date>
<dc:identifier>doi:10.1101/2021.05.28.446151</dc:identifier>
<dc:title><![CDATA[Differences in social brain function in autism spectrum disorder are linked to the serotonin transporter]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-05-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.06.447245v1?rss=1">
<title>
<![CDATA[
The ciliary gene INPP5E confers dorsal telencephalic identity to human cortical organoids by negatively regulating Sonic Hedgehog signalling 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.06.447245v1?rss=1"
</link>
<description><![CDATA[
Defects in primary cilia, cellular antennas that controls multiple intracellular signalling pathways, underlie several neurodevelopmental disorders, but how cilia control essential steps in human brain formation remains elusive. Here, we show that cilia are present on the apical surface of radial glial cells in human foetal forebrain. Interfering with cilia signalling in human organoids by mutating the INPP5E gene leads to the formation of ventral telencephalic cell types instead of cortical progenitors and neurons. INPP5E mutant organoids also showed increased SHH signalling and cyclopamine treatment partially rescued this ventralisation. In addition, ciliary expression of SMO was increased and the integrity of the transition zone was compromised. Overall, these findings establish the importance of primary cilia for dorsal/ventral patterning in human corticogenesis, indicate a tissue specific role of INPP5E as a negative regulator of SHH signalling and have implications for the emerging roles of cilia in the pathogenesis of neurodevelopmental disorders.
]]></description>
<dc:creator>Schembs, L.</dc:creator>
<dc:creator>Willems, A.</dc:creator>
<dc:creator>Hasenpusch-Theil, K.</dc:creator>
<dc:creator>Cooper, J. D.</dc:creator>
<dc:creator>Whiting, K.</dc:creator>
<dc:creator>Burr, K.</dc:creator>
<dc:creator>Bostrand, S. M. K.</dc:creator>
<dc:creator>Selvaraj, B. T.</dc:creator>
<dc:creator>Chandran, S.</dc:creator>
<dc:creator>Theil, T.</dc:creator>
<dc:date>2021-06-06</dc:date>
<dc:identifier>doi:10.1101/2021.06.06.447245</dc:identifier>
<dc:title><![CDATA[The ciliary gene INPP5E confers dorsal telencephalic identity to human cortical organoids by negatively regulating Sonic Hedgehog signalling]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.03.446811v1?rss=1">
<title>
<![CDATA[
Computational Neuroimaging of Cognition-Emotion Interactions: Affective and Task-similar Interference Differentially Impact Working Memory 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.03.446811v1?rss=1"
</link>
<description><![CDATA[
Cognition depends on resisting interference and responding to relevant stimuli. Distracting information, however, varies based on content, requiring distinct filtering mechanisms. For instance, affective information captures attention, disrupts performance and attenuates activation along frontal-parietal regions during cognitive engagement, while recruiting bottom-up regions. Conversely, distraction matching task features (i.e. task-similar) increases fronto-parietal activity. Neural mechanisms behind unique effects of different distraction on cognition remain unknown. Using fMRI in 45 adults, we tested whether affective versus task-similar interference show distinct signals during delayed working memory (WM). We found robust differences between distractor types along fronto-parietal versus affective-ventral neural systems. We studied a hypothesized mechanism of this effect via a biophysically-based computational WM model that implements a functional antagonism between affective/cognitive neural  modules. This architecture reproduced experimental effects: task-similar distractors increased, whereas affective distractors attenuated cognitive module activity while increasing affective module signals. The model architecture suggested that task-based connectivity may be altered in affective-ventral vs. fronto-parietal networks depending on distractor type. Empirically, affective interference significantly increased connectivity within the affective-ventral network, but reduced connectivity between affective-ventral and fronto-parietal networks, which predicted WM performance. These findings detail an antagonistic architecture between cognitive and affective systems, capable of flexibly engaging distinct distractions during cognition.
]]></description>
<dc:creator>Ji, J. L.</dc:creator>
<dc:creator>Repovs, G.</dc:creator>
<dc:creator>Yang, G. J.</dc:creator>
<dc:creator>Savic, A.</dc:creator>
<dc:creator>Murray, J. D.</dc:creator>
<dc:creator>Anticevic, A.</dc:creator>
<dc:date>2021-06-03</dc:date>
<dc:identifier>doi:10.1101/2021.06.03.446811</dc:identifier>
<dc:title><![CDATA[Computational Neuroimaging of Cognition-Emotion Interactions: Affective and Task-similar Interference Differentially Impact Working Memory]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.03.446920v1?rss=1">
<title>
<![CDATA[
Identifying developing interneurons as a potential target for multiple genetic autism risk factors in human and rodent forebrain. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.03.446920v1?rss=1"
</link>
<description><![CDATA[
Autism spectrum condition or  autism is associated with numerous monogenic and polygenic genetic risk factors including the polygenic 16p11.2 microdeletion. A central question is what neural cells are affected. To systematically investigate we analysed single cell transcriptomes from gestational week (GW) 8-26 human foetal prefrontal cortex and identified a subset of interneurons (INs) first appearing at GW23 with enriched expression of a disproportionately large fraction of risk factor transcripts. This suggests the hypothesis that these INs are disproportionately vulnerable to mutations causing autism. We investigated this in a rat model of the 16p11.2 microdeletion. We found no change in the numbers or position of either excitatory or inhibitory neurons in the somatosensory cortex or CA1 of 16p11.2+/- rats but found that CA1 Sst INs were hyperexcitable with an enlarged axon initial segment, which was not the case for CA1 pyramidal cells. This study prompts deeper investigation of IN development as a convergent target for autism genetic risk factors.
]]></description>
<dc:creator>Yang, Y.</dc:creator>
<dc:creator>Booker, S. A.</dc:creator>
<dc:creator>Clegg, J. M.</dc:creator>
<dc:creator>Quintana-Urzainqui, I.</dc:creator>
<dc:creator>Sumera, A.</dc:creator>
<dc:creator>Kozic, Z. R.</dc:creator>
<dc:creator>Dando, O. R.</dc:creator>
<dc:creator>Martin Lorenzo, S.</dc:creator>
<dc:creator>Herault, Y.</dc:creator>
<dc:creator>Kind, P. C.</dc:creator>
<dc:creator>Price, D. J.</dc:creator>
<dc:creator>Pratt, T.</dc:creator>
<dc:date>2021-06-03</dc:date>
<dc:identifier>doi:10.1101/2021.06.03.446920</dc:identifier>
<dc:title><![CDATA[Identifying developing interneurons as a potential target for multiple genetic autism risk factors in human and rodent forebrain.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.07.01.450793v1?rss=1">
<title>
<![CDATA[
Atypical gaze patterns in autism are heterogeneous across subjects but reliable within individuals 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.07.01.450793v1?rss=1"
</link>
<description><![CDATA[
People with autism spectrum disorder (ASD) have atypical gaze onto both static visual images 1,2 and dynamic videos 3,4 that could be leveraged for diagnostic purposes 5,6. Eye tracking is important for characterizing ASD across the lifespan 7 and nowadays feasible at home (e.g., from smartphones 8). Yet gaze-based classification has been difficult to achieve, due to sources of variance both across and within subjects. Here we test three competing hypotheses: (a) that ASD could be successfully classified from the fact that gaze patterns are less reliable or noisier than in controls, (b) that gaze patterns are atypical and heterogeneous across ASD subjects but reliable over time within a subject, or (c) that gaze patterns are individually reliable and also homogenous among individuals with ASD. Leveraging dense eye tracking data from two different full-length television sitcom episodes in a total of over 150 subjects (N = 53 ASD, 107 controls) collected at two different sites, we demonstrate support for the second of these hypotheses. The findings pave the way for the investigation of autism subtypes, and for elucidating the specific visual features that best discriminate gaze patterns -- directions that will also inform neuroimaging and genetic studies of this complex disorder.
]]></description>
<dc:creator>Keles, U.</dc:creator>
<dc:creator>Kliemann, D.</dc:creator>
<dc:creator>Byrge, L.</dc:creator>
<dc:creator>Saarimaki, H.</dc:creator>
<dc:creator>Paul, L. K.</dc:creator>
<dc:creator>Kennedy, D. P.</dc:creator>
<dc:creator>Adolphs, R.</dc:creator>
<dc:date>2021-07-02</dc:date>
<dc:identifier>doi:10.1101/2021.07.01.450793</dc:identifier>
<dc:title><![CDATA[Atypical gaze patterns in autism are heterogeneous across subjects but reliable within individuals]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-07-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.07.16.452740v1?rss=1">
<title>
<![CDATA[
Interpreting Polygenic Score Effects in Sibling Analysis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.07.16.452740v1?rss=1"
</link>
<description><![CDATA[
Researchers often claim that sibling analysis can be used to separate causal genetic effects from the assortment of biases that contaminate most downstream genetic studies. Indeed, typical results from sibling models show large (>50%) attenuations in the associations between polygenic scores and phenotypes compared to non-sibling models, consistent with researchers expectations about bias reduction. This paper explores these expectations by using family (quad) data and simulations that include indirect genetic effect processes and evaluates the ability of sibling models to uncover direct genetic effects. We find that sibling models, in general, fail to uncover direct genetic effects; indeed, these models have both upward and downward biases that are difficult to sign in typical data. When genetic nurture effects exist, sibling models create "measurement error" that attenuate associations between polygenic scores and phenotypes. As the correlation between direct and indirect effect changes, this bias can increase or decrease. Our findings suggest that interpreting results from sibling analysis aimed at uncovering direct genetic effects should be treated with caution.
]]></description>
<dc:creator>Fletcher, J.</dc:creator>
<dc:creator>Wu, Y.</dc:creator>
<dc:creator>Li, T.</dc:creator>
<dc:creator>Lu, Q.</dc:creator>
<dc:date>2021-07-17</dc:date>
<dc:identifier>doi:10.1101/2021.07.16.452740</dc:identifier>
<dc:title><![CDATA[Interpreting Polygenic Score Effects in Sibling Analysis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-07-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.18.431674v1?rss=1">
<title>
<![CDATA[
Effects of early geometric confinement on the transcriptomic profile of human cerebral organoids 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.18.431674v1?rss=1"
</link>
<description><![CDATA[
BackgroundBiophysical factors such as shape and mechanical forces are known to play crucial roles in stem cell differentiation, embryogenesis and neurodevelopment. However, the complexity and experimental challenges capturing such early stages of development, and ethical concerns associated with human embryo and fetal research, limit our understanding of how these factors affect human brain organogenesis. Human cerebral organoids (hCO) are attractive models due to their ability to model important brain regions and transcriptomics of early in vivo brain development. Furthermore, they provide three-dimensional environments that better mimic the in vivo environment. To date, they have been used to understand the effects of genetics and soluble factors on neurodevelopment. Establishing links between spatial factors and hCO development will require the development of new approaches.

ResultsHere, we investigated the effects of early geometric confinements on transcriptomic changes during hCO differentiation. Using a custom and tunable agarose microwell platform we generated embryoid bodies (EB) of diverse shapes and then further differentiated those EBs to whole brain hCOs. Our results showed that the microwells did not have negative gross impacts on the ability of the hCOs to differentiate generally towards neural fates, and there were clear shape dependent effects on neural lineage specification. In particular, we observed that non-spherical shapes showed signs of altered neurodevelopmental kinetics and favored the development of medial ganglionic eminence-associated brain regions and cell types over cortical regions.

ConclusionsThe findings presented here suggest a role for spatial factors in brain region specification during hCO development. Understanding these spatial patterning factors will not only improve understanding of in vivo development and differentiation, but also provide important handles with which to advance and improve control over human model systems for in vitro applications.
]]></description>
<dc:creator>Sen, D.</dc:creator>
<dc:creator>Voulgaropoulos, A.</dc:creator>
<dc:creator>Keung, A. J.</dc:creator>
<dc:date>2021-02-19</dc:date>
<dc:identifier>doi:10.1101/2021.02.18.431674</dc:identifier>
<dc:title><![CDATA[Effects of early geometric confinement on the transcriptomic profile of human cerebral organoids]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.28.433258v1?rss=1">
<title>
<![CDATA[
Somatosensory processing deficits and altered cortico-hippocampal connectivity in Shank3b-/- mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.28.433258v1?rss=1"
</link>
<description><![CDATA[
Abnormal tactile response is considered an integral feature of Autism Spectrum Disorders (ASDs), and hypo-responsiveness to tactile stimuli is often associated with the severity of ASDs core symptoms. Patients with Phelan-McDermid syndrome (PMS), caused by mutations in the SHANK3 gene, show ASD-like symptoms associated with aberrant tactile responses. However, the neural underpinnings of these somatosensory abnormalities are still poorly understood. Here we investigated, in Shank3b-/- adult mice, the neural substrates of whisker-guided behaviors, a key component of rodents interaction with the surrounding environment. To this aim, we assessed whisker-dependent behaviors in Shank3b-/- adult mice and age-matched controls, using the textured novel object recognition (tNORT) and whisker nuisance (WN) test. Shank3b-/- mice showed deficits in whisker-dependent texture discrimination in tNORT and behavioral hypo-responsiveness to repetitive whisker stimulation in WN. Notably, sensory hypo-responsiveness was accompanied by a significantly reduced activation of the primary somatosensory cortex (S1) and hippocampus, as measured by c-fos mRNA in situ hybridization, a proxy of neuronal activity following whisker stimulation. Moreover, resting-state fMRI showed a significantly reduced S1-hippocampal connectivity in Shank3b mutant mice. Together, these findings suggest that impaired crosstalk between hippocampus and S1 might underlie Shank3b-/- hypo-reactivity to whisker-dependent cues, highlighting a potentially generalizable form of dysfunctional somatosensory processing in ASD.

Significance StatementPatients with Phelan-McDermid syndrome, a syndromic form of ASD caused by mutation of the SHANK3 gene, often show aberrant responses to touch. However, the neural basis of atypical sensory responses in ASD remains undetermined. Here we used Shank3 deficient mice to investigate the neural substrates of behavioral responses to repetitive stimulation of the whiskers, a highly developed sensory organ in mice. We found that mice lacking the Shank3 gene are hypo-responsive to repetitive whisker stimulation. This trait was associated with reduced engagement and connectivity between the primary somatosensory cortex and hippocampus. These results suggest that dysfunctional cortico-hippocampal coupling may underlie somatosensory processing deficits in SHANK3 mutation carriers and related syndromic forms of ASD.
]]></description>
<dc:creator>Balasco, L.</dc:creator>
<dc:creator>Pagani, M.</dc:creator>
<dc:creator>Pangrazzi, L.</dc:creator>
<dc:creator>Schlosman, E.</dc:creator>
<dc:creator>Mattioni, L.</dc:creator>
<dc:creator>Galbusera, A.</dc:creator>
<dc:creator>Provenzano, G.</dc:creator>
<dc:creator>Gozzi, A.</dc:creator>
<dc:creator>Bozzi, Y.</dc:creator>
<dc:date>2021-02-28</dc:date>
<dc:identifier>doi:10.1101/2021.02.28.433258</dc:identifier>
<dc:title><![CDATA[Somatosensory processing deficits and altered cortico-hippocampal connectivity in Shank3b-/- mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.30.442205v1?rss=1">
<title>
<![CDATA[
Generation of fate patterns via intercellular forces 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.30.442205v1?rss=1"
</link>
<description><![CDATA[
Studies of fate patterning during development typically emphasize cell-cell communication via diffusible signals. Recent experiments on monolayer stem cell colonies, however, suggest that mechanical forces between cells may also play a role. These findings inspire a model of mechanical patterning: fate affects cell contractility, and pressure in the cell layer biases fate. Cells at the colony boundary, more contractile than cells at the center, seed a pattern that propagates via force transmission. In agreement with previous observations, our model implies that the width of the outer fate domain depends only weakly on colony diameter. We further predict and confirm experimentally that this same width varies non-monotonically with substrate stiffness. This finding supports the idea that mechanical stress can mediate patterning in a manner similar to a morphogen; we argue that a similar dependence on substrate stiffness can be achieved by a chemical signal only if strong constraints on the signaling pathways mechanobiology are met.
]]></description>
<dc:creator>Nunley, H.</dc:creator>
<dc:creator>Xue, X.</dc:creator>
<dc:creator>Fu, J.</dc:creator>
<dc:creator>Lubensky, D. K.</dc:creator>
<dc:date>2021-05-01</dc:date>
<dc:identifier>doi:10.1101/2021.04.30.442205</dc:identifier>
<dc:title><![CDATA[Generation of fate patterns via intercellular forces]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-05-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.04.429640v1?rss=1">
<title>
<![CDATA[
NeuroSCORE: A Genome-wide Omics-Based Model to Identify Candidate Disease Genes of the Central Nervous System 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.04.429640v1?rss=1"
</link>
<description><![CDATA[
To identify and prioritize candidate disease genes of the central nervous system (CNS) we created the Neurogenetic Systematic Correlation of Omics-Related Evidence (NeuroSCORE). We used five genome-wide metrics highly associated with neurological phenotypes to score 19,598 protein-coding genes. Genes scored one point per metric, resulting in a range of scores from 0-5. Approximately 13,000 genes were then paired with phenotype data from the Online Mendelian Inheritance in Man (OMIM) database. We used logistic regression to determine the odds ratio of each metric and compared genes scoring 1+ to cause a known CNS-related phenotype compared to genes that scored zero. We tested NeuroSCORE using microarray copy number variants (CNVs) in case-control cohorts, mouse model phenotype data, and gene ontology (GO) and pathway analyses. NeuroSCORE identified 8,296 genes scored [&ge;]1, of which 1,580 are "high scoring" genes (scores [&ge;]3). High scoring genes are significantly associated with CNS phenotypes (OR=5.5, p<2x10-16), enriched in case CNVs, and enriched in mouse ortholog genes associated with behavioral and nervous system abnormalities. GO and pathway analyses showed high scoring genes were enriched in chromatin remodeling, mRNA splicing, dendrite development, and neuron projection. OMIM has no phenotype for 1,062 high scoring genes (67%). Top scoring genes include ANKRD17, CCAR1, CLASP1, DOCK9, EIF4G2, G3BP2, GRIA1, MAP4K4, MARK2, PCBP2, RNF145, SF1, SYNCRIP, TNPO2, and ZSWIM8. NeuroSCORE identifies and prioritizes CNS-disease candidate genes, many not yet associated with any phenotype in OMIM. These findings can help direct future research and improve molecular diagnostics for individuals with neurological conditions.
]]></description>
<dc:creator>Davis, K. W.</dc:creator>
<dc:creator>Bilancia, C. G.</dc:creator>
<dc:creator>Martin, M.</dc:creator>
<dc:creator>Vanzo, R.</dc:creator>
<dc:creator>Rimmasch, M.</dc:creator>
<dc:creator>Hom, Y.</dc:creator>
<dc:creator>Uddin, M.</dc:creator>
<dc:creator>Serrano, M.</dc:creator>
<dc:date>2021-02-06</dc:date>
<dc:identifier>doi:10.1101/2021.02.04.429640</dc:identifier>
<dc:title><![CDATA[NeuroSCORE: A Genome-wide Omics-Based Model to Identify Candidate Disease Genes of the Central Nervous System]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.26.355602v1?rss=1">
<title>
<![CDATA[
Gamete simulation improves polygenic transmission disequilibrium analysis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.26.355602v1?rss=1"
</link>
<description><![CDATA[
Polygenic risk scores (PRS) derived from summary statistics of genome-wide association studies (GWAS) have enjoyed great popularity in human genetics research. Applied to population cohorts, PRS can effectively stratify individuals by risk group and has promising applications in early diagnosis and clinical intervention. However, our understanding of within-family polygenic risk is incomplete, in part because the small samples per family significantly limits power. Here, to address this challenge, we introduce ORIGAMI, a computational framework that uses parental genotype data to simulate offspring genomes. ORIGAMI uses state-of-the-art genetic maps to simulate realistic recombination events on phased parental genomes and allows quantifying the prospective PRS variability within each family. We quantify and showcase the substantially reduced yet highly heterogeneous PRS variation within families for numerous complex traits. Further, we incorporate within-family PRS variability to improve polygenic transmission disequilibrium test (pTDT). Through simulations, we demonstrate that modeling within-family risk substantially improves the statistical power of pTDT. Applied to 7,805 trios of autism spectrum disorder (ASD) probands and healthy parents, we successfully replicated previously reported over-transmission of ASD, educational attainment, and schizophrenia risk, and identified multiple novel traits with significant transmission disequilibrium. These results provided novel etiologic insights into the shared genetic basis of various complex traits and ASD.
]]></description>
<dc:creator>Chen, J.</dc:creator>
<dc:creator>You, J.</dc:creator>
<dc:creator>Zhao, Z.</dc:creator>
<dc:creator>Ni, Z.</dc:creator>
<dc:creator>Huang, K.</dc:creator>
<dc:creator>Wu, Y.</dc:creator>
<dc:creator>Fletcher, J.</dc:creator>
<dc:creator>Lu, Q.</dc:creator>
<dc:date>2020-10-27</dc:date>
<dc:identifier>doi:10.1101/2020.10.26.355602</dc:identifier>
<dc:title><![CDATA[Gamete simulation improves polygenic transmission disequilibrium analysis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.24.265389v1?rss=1">
<title>
<![CDATA[
TRAP-based allelic translation efficiency imbalance analysis to identify genetic regulation of ribosome occupancy in specific cell types in vivo. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.24.265389v1?rss=1"
</link>
<description><![CDATA[
The alteration of gene expression due to variations in the sequences of transcriptional regulatory elements has been a focus of substantial inquiry in humans and model organisms. However, less is known about the extent to which natural variation contributes to post-transcriptional regulation. Allelic Expression Imbalance (AEI) is a classical approach for studying the association of specific haplotypes with relative changes in transcript abundance. Here, we piloted a new TRAP based approach to associate genetic variation with transcript occupancy on ribosomes in specific cell types, to determine if it will allow examination of Allelic Translation Imbalance (ATI), and Allelic Translation Efficiency Imbalance, using as a test case mouse astrocytes in vivo. We show that most changes of the mRNA levels on ribosomes were reflected in transcript abundance, though [~]1.5% of transcripts have variants that clearly alter loading onto ribosomes orthogonally to transcript levels. These variants were often in conserved residues and altered sequences known to regulate translation such as upstream ORFs, PolyA sites, and predicted miRNA binding sites. Such variants were also common in transcripts showing altered abundance, suggesting some genetic regulation of gene expression may function through post-transcriptional mechanisms. Overall, our work shows that naturally occurring genetic variants can impact ribosome occupancy in astrocytes in vivo and suggests that mechanisms may also play a role in genetic contributions to disease.
]]></description>
<dc:creator>Liu, Y.</dc:creator>
<dc:creator>Fischer, A. D.</dc:creator>
<dc:creator>St. Pierre, C. L.</dc:creator>
<dc:creator>Macias-Velasco, J. F.</dc:creator>
<dc:creator>Lawson, H. A.</dc:creator>
<dc:creator>Dougherty, J. D.</dc:creator>
<dc:date>2020-08-24</dc:date>
<dc:identifier>doi:10.1101/2020.08.24.265389</dc:identifier>
<dc:title><![CDATA[TRAP-based allelic translation efficiency imbalance analysis to identify genetic regulation of ribosome occupancy in specific cell types in vivo.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.15.375386v1?rss=1">
<title>
<![CDATA[
Identifying cell type specific driver genes in autism-associated copy number loci from cerebral organoids 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.15.375386v1?rss=1"
</link>
<description><![CDATA[
Neuropsychiatric and neurodevelopmental disorders have been particularly challenging to study using animal models, and recently, human-derived cerebral organoids demonstrate great promise for discovering molecular processes that are important in these disorders. However, several challenges remain in achieving robust phenotyping to discover cell type specific genes. We perform RNA sequencing on 71 samples comprising of 1,420 cerebral organoids from 25 donors, and describe a framework (Orgo-Seq) to identify cell type specific driver genes, for 16p11.2 deletions and 15q11-13 duplications. We identify neuroepithelial cells as critical cell types for 16p11.2 deletions, and discover novel and previously reported cell type specific driver genes. Finally, we validated our results that mutations in KCTD13 in the 16p11.2 locus lead to imbalances in the proportion of neuroepithelial cells, using CRISPR/Cas9-edited mosaic organoids. Our work presents a quantitative discovery and validation framework for identifying cell type specific driver genes associated with complex diseases using cerebral organoids.
]]></description>
<dc:creator>Lim, E. T.</dc:creator>
<dc:date>2020-11-17</dc:date>
<dc:identifier>doi:10.1101/2020.11.15.375386</dc:identifier>
<dc:title><![CDATA[Identifying cell type specific driver genes in autism-associated copy number loci from cerebral organoids]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.01.29.428895v1?rss=1">
<title>
<![CDATA[
Whole-genome analysis of de novo and polymorphic retrotransposon insertions in Autism Spectrum Disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.01.29.428895v1?rss=1"
</link>
<description><![CDATA[
Retrotransposons are dynamic forces in evolutionary genomics and have been implicated as causes of Mendelian disease and hereditary cancer, but their role in Autism Spectrum Disorder (ASD) has never been systematically defined. Here, we report 86,154 polymorphic retrotransposon insertions including >60% not previously reported and 158 de novo retrotransposition events identified in whole genome sequencing (WGS) data of 2,288 families with ASD from the Simons Simplex Collection (SSC). As expected, the overall burden of de novo events was similar between ASD individuals and unaffected siblings, with 1 de novo insertion per 29, 104, and 192 births for Alu, L1, and SVA respectively, and 1 de novo insertion per 20 births total, while the location of transposon insertions differed between ASD and unaffected individuals. ASD cases showed more de novo L1 insertions than expected in ASD genes, and we also found de novo intronic retrotransposition events in known syndromic ASD genes in affected individuals but not in controls. Additionally, we observed exonic insertions in genes with a high probability of being loss-of-function intolerant, including a likely causative exonic insertion in CSDE1, only in ASD individuals. Although de novo retrotransposition occurs less frequently than single nucleotide and copy number variants, these findings suggest a modest, but important, impact of intronic and exonic retrotransposition mutations in ASD and highlight the utility of developing specific bioinformatic tools for high-throughput detection of transposable element insertions.
]]></description>
<dc:creator>Borges Monroy, R.</dc:creator>
<dc:creator>Chu, C.</dc:creator>
<dc:creator>Dias, C.</dc:creator>
<dc:creator>Choi, J.</dc:creator>
<dc:creator>Lee, S.</dc:creator>
<dc:creator>Gao, Y.</dc:creator>
<dc:creator>Shin, T.</dc:creator>
<dc:creator>Park, P. J.</dc:creator>
<dc:creator>Walsh, C. A.</dc:creator>
<dc:creator>Lee, E. A.</dc:creator>
<dc:date>2021-01-31</dc:date>
<dc:identifier>doi:10.1101/2021.01.29.428895</dc:identifier>
<dc:title><![CDATA[Whole-genome analysis of de novo and polymorphic retrotransposon insertions in Autism Spectrum Disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-01-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.01.29.428754v1?rss=1">
<title>
<![CDATA[
SFARI Genes and where to find them; classification modelling to identify genes associated with Autism Spectrum Disorder from RNA-seq data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.01.29.428754v1?rss=1"
</link>
<description><![CDATA[
MotivationAutism spectrum disorder (ASD) has a strong, yet heterogeneous, genetic component. Among the various methods that are being developed to help reveal the underlying molecular aetiology of the disease, one that is gaining popularity is the combination of gene expression and clinical genetic data. For ASD, the SFARI-gene database comprises lists of curated genes in which presumed causative mutations have been identified in patients. In order to predict novel candidate SFARI-genes we built classification models combining differential gene expression data for ASD patients and unaffected individuals with a genes status in the SFARI-gene list.

ResultsSFARI-genes were not found to be significantly associated with differential gene expression patterns, nor were they enriched in gene co-expression network modules that had a strong correlation with ASD diagnosis. However, network analysis and machine learning models that incorporate information from the whole gene co-expression network were able to predict novel candidate genes that share features of existing SFARI genes and have support for roles in ASD in the literature. We found a statistically significant bias related to the absolute level of gene expression for existing SFARI genes and their scores. It is essential that this bias be taken into account when studies interpret ASD gene expression data at gene, module and whole-network levels.

AvailabilitySource code is available from GitHub (https://doi.org/10.5281/zenodo.4463693) and the accompanying data from The University of Edinburgh DataStore (https://doi.org/10.7488/ds/2980)

Contactian.simpson@ed.ac.uk
]]></description>
<dc:creator>Navarro, M.</dc:creator>
<dc:creator>Simpson, I.</dc:creator>
<dc:date>2021-02-01</dc:date>
<dc:identifier>doi:10.1101/2021.01.29.428754</dc:identifier>
<dc:title><![CDATA[SFARI Genes and where to find them; classification modelling to identify genes associated with Autism Spectrum Disorder from RNA-seq data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.03.235358v1?rss=1">
<title>
<![CDATA[
Insights into dispersed duplications and complex structural mutations from whole genome sequencing 706 families 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.03.235358v1?rss=1"
</link>
<description><![CDATA[
Two intriguing forms of genome structural variation (SV) - dispersed duplications, and de novo rearrangements of complex, multi-allelic loci - have long escaped genomic analysis. We describe a new way to find and characterize such variation by utilizing identity-by-descent (IBD) relationships between siblings together with high-precision measurements of segmental copy number. Analyzing whole-genome sequence data from 706 families, we find hundreds of "IBD-discordant" (IBDD) CNVs: loci at which siblings CNV measurements and IBD states are mathematically inconsistent. We found that commonly-IBDD CNVs identify dispersed duplications; we mapped 95 of these common dispersed duplications to their true genomic locations through family-based linkage and population linkage disequilibrium (LD), and found several to be in strong LD with genome-wide association (GWAS) signals for common diseases or gene expression variation at their revealed genomic locations. Other CNVs that were IBDD in a single family appear to involve de novo mutations in complex and multi-allelic loci; we identified 26 de novo structural mutations that had not been previously detected in earlier analyses of the same families by diverse SV analysis methods. These included a de novo mutation of the amylase gene locus and multiple de novo mutations at chromosome 15q14. Combining these complex mutations with more-conventional CNVs, we estimate that segmental mutations larger than 1kb arise in about one per 22 human meioses. These methods are complementary to previous techniques in that they interrogate genomic regions that are home to segmental duplication, high CNV allele frequencies, and multi-allelic CNVs.

Author SummaryCopy number variation is an important form of genetic variation in which individuals differ in the number of copies of segments of their genomes. Certain aspects of copy number variation have traditionally been difficult to study using short-read sequencing data. For example, standard analyses often cannot tell whether the duplicated copies of a segment are located near the original copy or are dispersed to other regions of the genome. Another aspect of copy number variation that has been difficult to study is the detection of mutations in the copy number of DNA segments passed down from parents to their children, particularly when the mutations affect genome segments which already display common copy number variation in the population. We develop an analytical approach to solving these problems when sequencing data is available for all members of families with at least two children. This method is based on determining the number of parental haplotypes the two siblings share at each location in their genome, and using that information to determine the possible inheritance patterns that might explain the copy numbers we observe in each family member. We show that dispersed duplications and mutations can be identified by looking for copy number variants that do not follow these expected inheritance patterns. We use this approach to determine the location of 95 common duplications which are dispersed to distant regions of the genome, and demonstrate that these duplications are linked to genetic variants that affect disease risk or gene expression levels. We also identify a set of copy number mutations not detected by previous analyses of sequencing data from a large cohort of families, and show that repetitive and complex regions of the genome undergo frequent mutations in copy number.
]]></description>
<dc:creator>Whelan, C. W.</dc:creator>
<dc:creator>Handsaker, R. E.</dc:creator>
<dc:creator>Genovese, G.</dc:creator>
<dc:creator>Kashin, S.</dc:creator>
<dc:creator>Lek, M.</dc:creator>
<dc:creator>Hughes, J.</dc:creator>
<dc:creator>McElwee, J.</dc:creator>
<dc:creator>Lenardo, M.</dc:creator>
<dc:creator>MacArthur, D.</dc:creator>
<dc:creator>McCarroll, S. A.</dc:creator>
<dc:date>2020-08-04</dc:date>
<dc:identifier>doi:10.1101/2020.08.03.235358</dc:identifier>
<dc:title><![CDATA[Insights into dispersed duplications and complex structural mutations from whole genome sequencing 706 families]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.17.302042v1?rss=1">
<title>
<![CDATA[
Demyelination induces selective vulnerability of inhibitory networks in multiple sclerosis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.17.302042v1?rss=1"
</link>
<description><![CDATA[
In multiple sclerosis (MS), a chronic demyelinating disease of the central nervous system, neurodegeneration is detected early in the disease course and is associated with the long-term disability of patients. Neurodegeneration is linked to both inflammation and demyelination, but its exact cause remains unknown. This gap in knowledge contributes to the current lack of treatments for the neurodegenerative phase of MS. Here we ask if neurodegeneration in MS affects specific neuronal components and if it is the result of demyelination. Neuropathological examination of secondary progressive MS motor cortices revealed a selective vulnerability of inhibitory interneurons in MS. The generation of a rodent model of focal subpial cortical demyelination proved that this selective neurodegeneration is secondary to demyelination providing the first temporal evidence of demyelination-induced neurodegeneration and a new preclinical model for the study of neuroprotective treatments.
]]></description>
<dc:creator>Zoupi, L.</dc:creator>
<dc:creator>Booker, S. A.</dc:creator>
<dc:creator>Eigel, D.</dc:creator>
<dc:creator>Werner, C.</dc:creator>
<dc:creator>Kind, P. C.</dc:creator>
<dc:creator>Spires-Jones, T.</dc:creator>
<dc:creator>Newland, B.</dc:creator>
<dc:creator>Williams, A.</dc:creator>
<dc:date>2020-09-19</dc:date>
<dc:identifier>doi:10.1101/2020.09.17.302042</dc:identifier>
<dc:title><![CDATA[Demyelination induces selective vulnerability of inhibitory networks in multiple sclerosis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.09.940965v1?rss=1">
<title>
<![CDATA[
Genome-wide molecular effects of the neuropsychiatric 16p11 CNVs in an iPSC-to-iN neuronal model 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.09.940965v1?rss=1"
</link>
<description><![CDATA[
Copy number variants (CNVs), either deletions or duplications, at the 16p11.2 locus in the human genome are known to increase the risk for autism spectrum disorders (ASD), schizophrenia, and for several other developmental conditions. Here, we investigate the global effects on gene expression and DNA methylation using a 16p11.2 CNV patient-derived induced pluripotent stem cell (iPSC) to induced neuron (iN) cell model system. This approach revealed genome-wide and cell-type specific alterations to both gene expression and DNA methylation patterns and also yielded specific leads on genes potentially contributing to some of the known 16p11.2 patient phenotypes. PCSK9 is identified as a possible contributing factor to the symptoms seen in carriers of the 16p11.2 CNVs. The protocadherin (PCDH) gene family is found to have altered DNA methylation patterns in the CNV patient samples. The iPSC lines used for this study are available through a repository as a resource for research into the molecular etiology of the clinical phenotypes of 16p11.2 CNVs and into that of neuropsychiatric and neurodevelopmental disorders in general.
]]></description>
<dc:creator>Ward, T. R.</dc:creator>
<dc:creator>Zhang, X.</dc:creator>
<dc:creator>Leung, L. C.</dc:creator>
<dc:creator>Zhou, B.</dc:creator>
<dc:creator>Muench, K.</dc:creator>
<dc:creator>Roth, J. G.</dc:creator>
<dc:creator>Khechaduri, A.</dc:creator>
<dc:creator>Plastini, M. J.</dc:creator>
<dc:creator>Charlton, C.</dc:creator>
<dc:creator>Pattni, R.</dc:creator>
<dc:creator>Ho, S.</dc:creator>
<dc:creator>Ho, M.</dc:creator>
<dc:creator>Huang, Y.</dc:creator>
<dc:creator>Hallmayer, J. F.</dc:creator>
<dc:creator>Mourrain, P.</dc:creator>
<dc:creator>Palmer, T. D.</dc:creator>
<dc:creator>Urban, A. E.</dc:creator>
<dc:date>2020-02-10</dc:date>
<dc:identifier>doi:10.1101/2020.02.09.940965</dc:identifier>
<dc:title><![CDATA[Genome-wide molecular effects of the neuropsychiatric 16p11 CNVs in an iPSC-to-iN neuronal model]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.06.20.545788v1?rss=1">
<title>
<![CDATA[
Structural neuroplasticity after sleep loss modifies behavior and requires neurexin and neuroligin 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.06.20.545788v1?rss=1"
</link>
<description><![CDATA[
Sleep is conserved across species, and alterations in sleep are associated with a multitude of neurologic conditions. Structural neuroplasticity, or changes in the size, strength, number, and targets of neuronal synaptic connections, can be modified by sleep and sleep disruption. However, the causal relationships between sleep loss and neuroplasticity, behavioral impacts, and genetic perturbations are poorly understood. The C. elegans GABAergic DVB neuron undergoes structural plasticity in adult males that rewires synaptic connections and alters behavior; the rewiring is dependent on the conserved autism-associated genes NRXN1/nrx-1 and NLGN3/nlg-1. Stress exposure during sexual maturation, which overlaps with a developmental sleep period, alters DVB structural plasticity in early adulthood. Here, we use four distinct methods to ask whether sleep deprivation results in altered structural and behavioral plasticity of the DVB neuron. Following sleep deprivation using the genetic mutants (aptf-1 and npr-1), vibration stimulus, or chemo-genetic silencing of a sleep-producing neuron, we find that DVB neurite outgrowth at day 1 of adulthood. Sleep deprivation also leads to an increase in the time to spicule protraction, the behavioral output of DVB function. We find that nrx-1 and nlg-1 both function to regulate sleep loss induced DVB structural and functional changes. Lastly, differences in DVB neurite outgrowth in sleep deprived animals at day 1 are transient, with DVB morphology being indistinguishable from controls by day 3. These results show that sleep loss modifies DVB structural plasticity and its behavioral consequences. Further, we show nrx-1 and nlg-1 mediate the effect of sleep deprivation on behavior at the level of DVB structural plasticity. These insights into sleep, neuroplasticity, behavior, and conserved autism genes have important implications for the role of sleep in neurologic disease.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/545788v1_figu1.gif" ALT="Figure 1">
View larger version (34K):
org.highwire.dtl.DTLVardef@2320c4org.highwire.dtl.DTLVardef@3c3b86org.highwire.dtl.DTLVardef@67dc96org.highwire.dtl.DTLVardef@c3033d_HPS_FORMAT_FIGEXP  M_FIG Graphical AbstractGABAergic morphologic and behavioral plasticity induced by developmental sleep deprivation depends on the conserved autism genes, nrx-1 and nlg-1 A) Sleep depriving male C. elegans during all larval sleep periods in development (aptf-1 or npr-1) or selectively inhibiting sleep during L4-adult molt (vibration or RIS silencing) results in an increase in DVB outgrowth. B) Mutations in nrx-1 (and nlg-1 in npr-1 animals) prevent sleep deprivation induced morphologic plasticity changes. C) DVB neurite outgrowth results in a functional change in spicule protraction rate as a result of increased GABAergic inhibitory signaling, which also depends on nrx-1 and nlg-1.

C_FIG
]]></description>
<dc:creator>Cowen, M. H.</dc:creator>
<dc:creator>Raizen, D. M.</dc:creator>
<dc:creator>Hart, M. P.</dc:creator>
<dc:date>2023-06-24</dc:date>
<dc:identifier>doi:10.1101/2023.06.20.545788</dc:identifier>
<dc:title><![CDATA[Structural neuroplasticity after sleep loss modifies behavior and requires neurexin and neuroligin]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-06-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.06.26.546567v1?rss=1">
<title>
<![CDATA[
Compensation between FOXP transcription factors maintains proper striatal function 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.06.26.546567v1?rss=1"
</link>
<description><![CDATA[
Spiny projection neurons (SPNs) of the striatum are critical in integrating neurochemical information to coordinate motor and reward-based behavior. Mutations in the regulatory transcription factors expressed in SPNs can result in neurodevelopmental disorders (NDDs). Paralogous transcription factors Foxp1 and Foxp2, which are both expressed in the dopamine receptor 1 (D1) expressing SPNs, are known to have variants implicated in NDDs. Utilizing mice with a D1-SPN specific loss of Foxp1, Foxp2, or both and a combination of behavior, electrophysiology, and cell-type specific genomic analysis, loss of both genes results in impaired motor and social behavior as well as increased firing of the D1-SPNs. Differential gene expression analysis implicates genes involved in autism risk, electrophysiological properties, and neuronal development and function. Viral mediated re-expression of Foxp1 into the double knockouts was sufficient to restore electrophysiological and behavioral deficits. These data indicate complementary roles between Foxp1 and Foxp2 in the D1-SPNs.
]]></description>
<dc:creator>Ahmed, N. I.</dc:creator>
<dc:creator>Khandelwal, N.</dc:creator>
<dc:creator>Anderson, A. G.</dc:creator>
<dc:creator>Kulkarni, A.</dc:creator>
<dc:creator>Gibson, J.</dc:creator>
<dc:creator>Konopka, G.</dc:creator>
<dc:date>2023-06-26</dc:date>
<dc:identifier>doi:10.1101/2023.06.26.546567</dc:identifier>
<dc:title><![CDATA[Compensation between FOXP transcription factors maintains proper striatal function]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-06-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.06.29.546438v1?rss=1">
<title>
<![CDATA[
Developmental molecular controls over arealization of descending cortical motor pathways 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.06.29.546438v1?rss=1"
</link>
<description><![CDATA[
Layer 5 extratelencephalic (ET) neurons are a main class of neocortical projection neurons that predominate in the motor cortex and send their axon to the pons and spinal cord, and collaterals to the thalamus and multiple deep subcerebral structures1-3. Precise connectivity of ET neurons is critical for fine motor control; they are central to loss of function upon spinal cord injury and specifically degenerate in select neurodegenerative disorders4, 5. ET neurons consist of several types of cells with distinct laminar and areal locations, molecular identities, connectivities, and functions6, 7. Within layer 5 of the cortex, two cardinal subtypes of ET neurons have been identified: "ETlower" neurons, which express Slco2a1 and project to distal targets including the spinal cord, "ETupper" neurons, which express Nprs1 or Hpgd and project more proximally to the pons and thalamus6. Despite their critical function, how these neuronal subtypes emerge during development and acquire their area-specific distributions remains unaddressed. Here, using combinations of anatomical labeling, MAPseq mapping8, and single-nucleus transcriptomics across developing cortical areas, we reveal that these two subtypes of ET neurons are present at birth along opposite antero-posterior cortical gradients. We first characterize area-specific developmental axonal dynamics of ETlower and ETupper neurons and find that the latter can emerge by pruning of subsets of ETlower neurons. We next identify area- and ET neuron type-specific developmental transcriptional programs to identify key target genes in vivo. Finally, we reprogram ET neuron area-specific connectivity from motor to visual by postnatal in vivo combinatorial knockout of three key type-specific transcription factors. Together, these findings delineate the functional transcriptional programs controlling ET neuron diversity across cortical areas and provide a molecular blueprint to investigate and direct the developmental emergence of corticospinal motor control.
]]></description>
<dc:creator>Abe, P.</dc:creator>
<dc:creator>Lavalley, A.</dc:creator>
<dc:creator>Morassut, I.</dc:creator>
<dc:creator>Klingler, E.</dc:creator>
<dc:creator>Santinha, A. J.</dc:creator>
<dc:creator>Platt, R. J.</dc:creator>
<dc:creator>Jabaudon, D.</dc:creator>
<dc:date>2023-06-30</dc:date>
<dc:identifier>doi:10.1101/2023.06.29.546438</dc:identifier>
<dc:title><![CDATA[Developmental molecular controls over arealization of descending cortical motor pathways]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.07.07.548182v1?rss=1">
<title>
<![CDATA[
Reprogramming method does not impact the neuronal differentiation potential of 16p11.2 deletion patient iPSCs 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.07.07.548182v1?rss=1"
</link>
<description><![CDATA[
A major impediment to the actualization of the induced pluripotent stem cell (iPSC)-based personalized medicine revolution is the lack of widely accepted standard operating procedures (SOPs) across different groups and institutions. The various methods employed can include choice of starting materials, reprogramming agents, and culture conditions, with each of these factors hypothesized to influence the reprogramming efficiency and transcriptional identity of iPSCs. As such, we systematically compared iPSC reprogramming procedures using cells derived from the somatic cells of three patients with 16p11.2 deletion syndrome (16p11.2del) and found remarkable similarity among the different methods. FACS analysis revealed that regardless of somatic cell type (fibroblast, lymphocyte, erythroblast), route of reprogramming factor introduction (mRNA, Sendai virus, episome), donor sex, or facility (Rutgers, NYSCF), 16p11.2del patient iPSCs were viable as high purity cultures expressing pluripotency marker proteins. This observation was supported at the transcript level by qPCR analysis, which demonstrated the ability for the iPSCs to differentiate into all three embryonic germ cell lineages after 12 days in culture as embryoid bodies. NGN2-mediated differentiation of these iPSCs produced functional neurons that formed active synaptic networks as revealed by multi-electrode array (MEA) recordings. Importantly, no group-wise comparisons among the reprogramming methods yielded consistent statistically significant differences, indicating that these procedures are equally capable of producing pluripotent stem cells that can efficiently differentiate into mature, functional neurons. This work highlights the utility of these reprogramming methods and supports the use of differentially reprogrammed iPSCs for direct comparative studies of human neurodevelopment.
]]></description>
<dc:creator>Wells, M. F.</dc:creator>
<dc:creator>Guss, E.</dc:creator>
<dc:creator>Zhou, H.</dc:creator>
<dc:creator>Sun, B.</dc:creator>
<dc:creator>Martinez, H.</dc:creator>
<dc:creator>Akopian, V.</dc:creator>
<dc:creator>Noggle, S.</dc:creator>
<dc:creator>Paull, D.</dc:creator>
<dc:creator>Moore, J.</dc:creator>
<dc:creator>Sheldon, M.</dc:creator>
<dc:creator>Sommer, J.</dc:creator>
<dc:creator>Benedetti, M.</dc:creator>
<dc:creator>Meissner, A.</dc:creator>
<dc:creator>Eggan, K.</dc:creator>
<dc:date>2023-07-08</dc:date>
<dc:identifier>doi:10.1101/2023.07.07.548182</dc:identifier>
<dc:title><![CDATA[Reprogramming method does not impact the neuronal differentiation potential of 16p11.2 deletion patient iPSCs]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-07-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.07.13.548866v1?rss=1">
<title>
<![CDATA[
The organisation and turnover of synaptic proteins within molecular supercomplexes. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.07.13.548866v1?rss=1"
</link>
<description><![CDATA[
The concept that dimeric protein complexes in synapses can sequentially replace their subunits has been a cornerstone of Francis Cricks 1984 hypothesis, explaining how long-term memories could be maintained in the face of short protein lifetimes. However, it is unknown whether the subunits of protein complexes that mediate memory are sequentially replaced in the brain and if this process is linked to protein lifetime. We address these issues by focusing on supercomplexes assembled by the abundant postsynaptic scaffolding protein PSD95, which plays a crucial role in memory. We used single-molecule detection, super-resolution microscopy and MINFLUX to probe the molecular composition of PSD95 supercomplexes in mice carrying genetically encoded HaloTags, eGFP and mEos2. We found a population of PSD95-containing supercomplexes comprised of two copies of PSD95, with a dominant 12.7 nm separation. Time-stamping of PSD95 subunits in vivo revealed that each PSD95 subunit was sequentially replaced over days and weeks. Comparison of brain regions showed subunit replacement was slowest in the cortex, where PSD95 protein lifetime is longest. Our findings reveal that protein supercomplexes within the postsynaptic density can be maintained by gradual replacement of individual subunits providing a mechanism for stable maintenance of their organization. Moreover, we extend Cricks model by suggesting that synapses with slow subunit replacement of protein supercomplexes and long protein lifetimes are specialized for long-term memory storage and that these synapses are highly enriched in superficial layers of the cortex where long-term memories are stored.
]]></description>
<dc:creator>Morris, K.</dc:creator>
<dc:creator>Bulovaite, E.</dc:creator>
<dc:creator>Kaizuka, T.</dc:creator>
<dc:creator>Adams, C.</dc:creator>
<dc:creator>Komiyama, N.</dc:creator>
<dc:creator>Grant, S. G. N.</dc:creator>
<dc:creator>Horrocks, M. H.</dc:creator>
<dc:date>2023-07-13</dc:date>
<dc:identifier>doi:10.1101/2023.07.13.548866</dc:identifier>
<dc:title><![CDATA[The organisation and turnover of synaptic proteins within molecular supercomplexes.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-07-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.08.01.551579v1?rss=1">
<title>
<![CDATA[
Distinct roles of putative excitatory and inhibitory neurons in the macaque inferior temporal cortex in core object recognition behavior 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.08.01.551579v1?rss=1"
</link>
<description><![CDATA[
A spatially distributed population of neurons in the macaque inferior temporal (IT) cortex supports object recognition behavior, but the cell-type specificity of the population in forming "behaviorally sufficient" object decodes remains poorly understood. To address this, we recorded neural signals from the macaque IT cortex and compared the object identity information and the alignment of decoding strategies derived from putative inhibitory (Inh) and excitatory (Exc) neurons to the monkeys behavior. We observed that while Inh neurons represented significant category information, decoding strategies based on Exc neural population activity outperformed those from Inh neurons in overall accuracy and their image-level match to the monkeys behavioral reports. Interestingly, both Exc and Inh responses explained a fraction of unique variance of the monkeys behavior, demonstrating a distinct role of the two cell types in generating object identity solutions for a downstream readout. We observed that current artificial neural network (ANN) models of primate ventral stream, designed with AI goals of performance optimization on image categorization, better predict Exc neurons (and their contribution to object recognition behavior) than Inh neurons. Beyond, refining the linking propositions between IT neurons and object recognition behavior, our results guide the development of next-generation biologically constrained brain models by offering novel cell-type specific neural benchmarks.
]]></description>
<dc:creator>Sanghavi, S.</dc:creator>
<dc:creator>Kar, K.</dc:creator>
<dc:date>2023-08-03</dc:date>
<dc:identifier>doi:10.1101/2023.08.01.551579</dc:identifier>
<dc:title><![CDATA[Distinct roles of putative excitatory and inhibitory neurons in the macaque inferior temporal cortex in core object recognition behavior]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-08-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.08.28.554882v1?rss=1">
<title>
<![CDATA[
Characterizing Subcortical Structural Heterogeneity in Autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.08.28.554882v1?rss=1"
</link>
<description><![CDATA[
Autism presents with significant phenotypic and neuroanatomical heterogeneity, and neuroimaging studies of the thalamus, globus pallidus and striatum in autism have produced inconsistent and contradictory results. These structures are critical mediators of functions known to be atypical in autism, including sensory gating and motor function. We examined both volumetric and fine-grained localized shape differences in autism using a large (n=3145, 1045-1318 after strict quality control), cross-sectional dataset of T1-weighted structural MRI scans from 32 sites, including both males and females (assigned-at-birth). We investigated three potentially important sources of neuroanatomical heterogeneity: sex, age, and intelligence quotient (IQ), using a meta-analytic technique after strict quality control to minimize non-biological sources of variation. We observed no volumetric differences in the thalamus, globus pallidus, or striatum in autism. Rather, we identified a variety of localized shape differences in all three structures. Including age, but not sex or IQ, in the statistical model improved the fit for both the pallidum and striatum, but not for the thalamus. Age-centered shape analysis indicated a variety of age-dependent regional differences. Overall, our findings help confirm that the neurodevelopment of the striatum, globus pallidus and thalamus are atypical in autism, in a subtle location-dependent manner that is not reflected in overall structure volumes, and that is highly non-uniform across the lifespan.
]]></description>
<dc:creator>MacDonald, D. N.</dc:creator>
<dc:creator>Bedford, S. A.</dc:creator>
<dc:creator>Olafson, E.</dc:creator>
<dc:creator>Park, M. T. M.</dc:creator>
<dc:creator>Devenyi, G. A.</dc:creator>
<dc:creator>Tullo, S.</dc:creator>
<dc:creator>Patel, R.</dc:creator>
<dc:creator>Anagnostou, E.</dc:creator>
<dc:creator>Baron-Cohen, S.</dc:creator>
<dc:creator>Bullmore, E. T.</dc:creator>
<dc:creator>Chura, L. R.</dc:creator>
<dc:creator>Craig, M. C.</dc:creator>
<dc:creator>Ecker, C.</dc:creator>
<dc:creator>Floris, D. L.</dc:creator>
<dc:creator>Holt, R. J.</dc:creator>
<dc:creator>Lenroot, R.</dc:creator>
<dc:creator>Lerch, J. P.</dc:creator>
<dc:creator>Lombardo, M. V.</dc:creator>
<dc:creator>Murphy, D. G. M.</dc:creator>
<dc:creator>Raznahan, A.</dc:creator>
<dc:creator>Ruigrok, A. N. V.</dc:creator>
<dc:creator>Smith, E.</dc:creator>
<dc:creator>Shinohara, R. T.</dc:creator>
<dc:creator>Spencer, M. D.</dc:creator>
<dc:creator>Suckling, J.</dc:creator>
<dc:creator>Taylor, M. J.</dc:creator>
<dc:creator>Thurm, A.</dc:creator>
<dc:creator>MRC AIMS Consortium,</dc:creator>
<dc:creator>Lai, M.-C.</dc:creator>
<dc:creator>Chakravarty, M. M.</dc:creator>
<dc:date>2023-08-29</dc:date>
<dc:identifier>doi:10.1101/2023.08.28.554882</dc:identifier>
<dc:title><![CDATA[Characterizing Subcortical Structural Heterogeneity in Autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-08-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2023.09.22.559056v1?rss=1">
<title>
<![CDATA[
Single cell analysis of dup15q syndrome reveals developmental and postnatal molecular changes in autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2023.09.22.559056v1?rss=1"
</link>
<description><![CDATA[
Duplication 15q (dup15q) syndrome is the most common genetic cause of autism spectrum disorder (ASD). Due to a higher genetic and phenotypic homogeneity compared to idiopathic autism, dup15q syndrome provides a well-defined setting to investigate ASD mechanisms. Previous bulk gene expression studies identified shared molecular changes in ASD. However, how cell type specific changes compare across different autism subtypes and how they change during development is largely unknown. In this study, we used single cell and single nucleus mRNA sequencing of dup15q cortical organoids from patient iPSCs, as well as post-mortem patient brain samples. We find cell-type specific dysregulated programs that underlie dup15q pathogenesis, which we validate by spatial resolved transcriptomics using brain tissue samples. We find degraded identity and vulnerability of deep-layer neurons in fetal stage organoids and highlight increased molecular burden of postmortem upper-layer neurons implicated in synaptic signaling, a finding shared between idiopathic ASD and dup15q syndrome. Gene co-expression network analysis of organoid and postmortem excitatory neurons uncovers modules enriched with autism risk genes. Organoid developmental modules were involved in transcription regulation via chromatin remodeling, while postmortem modules were associated with synaptic transmission and plasticity. The findings reveal a shifting landscape of ASD cellular vulnerability during brain development.
]]></description>
<dc:creator>Perez, Y.</dc:creator>
<dc:creator>Velmeshev, D.</dc:creator>
<dc:creator>Wang, L.</dc:creator>
<dc:creator>White, M.</dc:creator>
<dc:creator>Siebert, C.</dc:creator>
<dc:creator>Baltazar, J.</dc:creator>
<dc:creator>Dutton, N. G.</dc:creator>
<dc:creator>Wang, S.</dc:creator>
<dc:creator>Haeussler, M.</dc:creator>
<dc:creator>Chamberlain, S.</dc:creator>
<dc:creator>Kriegstein, A.</dc:creator>
<dc:date>2023-09-22</dc:date>
<dc:identifier>doi:10.1101/2023.09.22.559056</dc:identifier>
<dc:title><![CDATA[Single cell analysis of dup15q syndrome reveals developmental and postnatal molecular changes in autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2023-09-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2024.02.08.579330v1?rss=1">
<title>
<![CDATA[
The Genotype and Phenotypes in Families (GPF) platform manages the large and complex data at SFARI 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2024.02.08.579330v1?rss=1"
</link>
<description><![CDATA[
The exploration of genotypic variants impacting phenotypes is a cornerstone in genetics research. The emergence of vast collections containing deeply genotyped and phenotyped families has made it possible to pursue the search for variants associated with complex diseases. However, managing these large-scale datasets requires specialized computational tools tailored to organize and analyze the extensive data. GPF (Genotypes and Phenotypes in Families) is an open-source platform (https://github.com/iossifovlab/gpf) that manages genotypes and phenotypes derived from collections of families. The GPF interface allows interactive exploration of genetic variants, enrichment analysis for de novo mutations, and phenotype/genotype association tools. In addition, GPF allows researchers to share their data securely with the broader scientific community. GPF is used to disseminate two large-scale family collection datasets (SSC, SPARK) for the study of autism funded by the SFARI foundation. However, GPF is versatile and can manage genotypic data from other small or large family collections. Our GPF-SFARI GPF instance (https://gpf.sfari.org/) provides protected access to comprehensive genotypic and phenotypic data for the SSC and SPARK. In addition, GPF-SFARI provides public access to an extensive collection of de novo mutations identified in individuals with autism and related disorders and to gene-level statistics of the protected datasets characterizing the genes roles in autism. Here, we highlight the primary features of GPF within the context of GPF-SFARI.
]]></description>
<dc:creator>Chorbadjiev, L.</dc:creator>
<dc:creator>Cokol, M.</dc:creator>
<dc:creator>Weinstein, Z.</dc:creator>
<dc:creator>Shi, K.</dc:creator>
<dc:creator>Fleisch, C.</dc:creator>
<dc:creator>Dimitrov, N.</dc:creator>
<dc:creator>Mladenov, S.</dc:creator>
<dc:creator>Xu, S.</dc:creator>
<dc:creator>Hall, J.</dc:creator>
<dc:creator>Ford, S.</dc:creator>
<dc:creator>Lee, Y.-h.</dc:creator>
<dc:creator>Yamrom, B.</dc:creator>
<dc:creator>Marks, S.</dc:creator>
<dc:creator>Munoz, A.</dc:creator>
<dc:creator>Lash, A.</dc:creator>
<dc:creator>Volfovsky, N.</dc:creator>
<dc:creator>Iossifov, I.</dc:creator>
<dc:date>2024-02-11</dc:date>
<dc:identifier>doi:10.1101/2024.02.08.579330</dc:identifier>
<dc:title><![CDATA[The Genotype and Phenotypes in Families (GPF) platform manages the large and complex data at SFARI]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2024-02-11</prism:publicationDate>
<prism:section></prism:section>
</item>
</rdf:RDF>
