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<title>bioRxiv Subject Collection: Genomics Bioinformatics Genetics Molecular Biology Developmental Biology</title>
<link>https://biorxiv.org</link>
<description>
This feed contains articles for bioRxiv Subject Collection "Genomics Bioinformatics Genetics Molecular Biology Developmental Biology"
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<link>https://www.biorxiv.org</link>
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<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.26.732348v1?rss=1">
<title>
<![CDATA[
MCD Stitcher: An open-source tool for whole-slide stitching and conversion of Imaging Mass Cytometry data 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.26.732348v1?rss=1
</link>
<description><![CDATA[
Imaging Mass Cytometry (IMC) combines metal-tagged antibody labelling with laser ablation mass spectrometry to generate highly multiplexed spatial images of tissue sections. However, the area that can be acquired within a single region of interest (ROI) is limited by hardware and software constraints, requiring large tissues to be imaged as multiple tiled ROIs. Reconstructing these ROIs into whole-slide images requires additional processing, while the proprietary .mcd file format can hinder integration with standard bioimage analysis workflows. Here, we present MCD Stitcher, an open-source Python package for converting .mcd files into OME-TIFF images with automated whole-slide stitching. The tool supports rectangular and polygonal ROIs, accommodates variable pixel sizes between ROIs, and uses memory-aware chunked reading during data ingestion to process large datasets on standard workstations. The generated OME-TIFF outputs preserve spatial, channel, and acquisition metadata for downstream analysis in tools such as QuPath, napari, and ImageJ/Fiji. MCD Stitcher provides a reproducible workflow for converting raw IMC data into interoperable image formats, enabling whole-slide spatial analysis without reliance on vendor-specific software.
]]></description>
<dc:creator><![CDATA[ Chaurasia, P. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.26.732348</dc:identifier>
<dc:title><![CDATA[MCD Stitcher: An open-source tool for whole-slide stitching and conversion of Imaging Mass Cytometry data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.26.734767v1?rss=1">
<title>
<![CDATA[
Direct probabilistic quantification of mosaic loss of chromosome Y from sequencing data 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.26.734767v1?rss=1
</link>
<description><![CDATA[
Loss of chromosome Y (LOY) is the most common aneuploidy in aging men and is increasingly recognized as a marker of aging and genomic instability. Because LOY occurs in mosaic form, its degree reflects the fraction of cells lacking the Y chromosome. Existing SNP-array- and sequencing-based methods rely largely on single genomic features and indirect transformations to estimate this fraction. We developed BaySeq-Y, a Bayesian method that directly estimates LOY mosaicism from sequencing data using VCF files with read depth (DP) and allelic depth (AD). Within a rigorous Bayesian framework, BaySeq-Y integrates complementary LOY-associated genomic features, including decreased read depth and allelic imbalance, and can additionally leverage haplotype phasing to improve precision. In simulations and fluorescence in situ hybridization validation (FISH), BaySeq-Y provided accurate estimates and outperformed existing methods. Applications to ROSMAP and GTEx supported its biological relevance through transcriptomic validation, demonstrating its utility for quantifying LOY across diverse sequencing datasets.
]]></description>
<dc:creator><![CDATA[ Lin, J.-R., Chang, Y.-C., Maslov, A. Y., Song, Y., Gao, T., Shan, J., Bennett, D. A., Milman, S., Barzilai, N., Vijg, J., Montagna, C., Zhang, Z. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.26.734767</dc:identifier>
<dc:title><![CDATA[Direct probabilistic quantification of mosaic loss of chromosome Y from sequencing data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.26.734379v1?rss=1">
<title>
<![CDATA[
Pericystic brain transcriptomics reveals molecular signatures of immune activation and neurovascular remodelling in viable and post-treatment porcine neurocysticercosis 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.26.734379v1?rss=1
</link>
<description><![CDATA[
Neurocysticercosis (NCC), the infection of the central nervous system by Taenia solium larvae, is a leading cause of acquired epilepsy in endemic regions. While viable cysticerci can persist asymptomatically for extended periods, their spontaneous or drug-induced degradation triggers marked perilesional inflammation and severe neurological symptoms. Despite well-documented histopathological characterisation of these lesion states, the host transcriptional programmes associated with viable parasite persistence and early post-treatment lesion disruption remain poorly understood. To address this gap, we performed the first bulk RNA sequencing of pericystic brain tissue using a physiologically relevant porcine model of NCC. Comparing uninfected controls (n = 3), infected untreated pigs with intact viable cysts (n = 6), and antiparasitic-treated pigs with disrupted cysts (n = 3), we identified distinct transcriptional signatures associated with each disease state. Viable infection was associated with broad transcriptional changes (461 upregulated and 175 downregulated genes), characterised by local immune activation alongside suppression of blood-brain barrier (BBB) remodelling, vascular, and neuronal signalling molecular signatures. The post-treatment state with confirmed BBB disruption was associated with a smaller but directionally distinct response (160 upregulated and 57 downregulated genes), marked by inflammatory signalling and increased expression of genes associated with endothelial activation, vascular regulation, and BBB-associated remodelling. Together, these findings suggest that, while immune engagement is a feature shared across both lesion states, the BBB-associated transcriptional axis shifts substantially following treatment. These results provide an exploratory transcriptomic framework for understanding parasite persistence, treatment-induced neuroinflammation, and neurovascular remodelling in NCC, and highlight candidate pathways and genes for future mechanistic investigation.
]]></description>
<dc:creator><![CDATA[ Apaza-Quiroz, C. A., Rojas-Portocarrero, C. C., Gutierrez Guarnizo, S. A., Ponce-Nakatahara, E. K., Bustos, J. A., Arroyo, G., Gilman, R. H., Garcia, H. H., Zimic, M. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.26.734379</dc:identifier>
<dc:title><![CDATA[Pericystic brain transcriptomics reveals molecular signatures of immune activation and neurovascular remodelling in viable and post-treatment porcine neurocysticercosis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.26.734559v1?rss=1">
<title>
<![CDATA[
MintCNA: A Unified Framework for Integrative Copy Number Profiling with Single-Cell Multi-Omics Data 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.26.734559v1?rss=1
</link>
<description><![CDATA[
Chromosomal copy number alterations (CNAs) are key drivers of tumor evolution, disease progression and therapeutic resistance, and the identification of them is an important step to delineate tumor clonal structure. However, accurately resolving CNA landscapes from single-cell data remains challenging. Most existing tools analyze one omics layer at a time and are susceptible to assay-specific noises, limiting their ability to recover shared or modality-specific CNAs. Recent single-cell multi-omics techniques enable joint sequencing of multiple molecular layers in the same cells, yet in silico methods that fully exploit such complementary multi-modal data for CNA analysis are still missing. Here we present a single-cell multi-omics integration framework, MintCNA, a unified framework for CNA detection from paired multi-omics data. MintCNA integrates traditional statistical modeling with embedded deep learning structure to enhance CNA profiling across multi-omics. We use an attention-guided convolutional autoencoder for data denoising and perform multivariate change-point detection utilizing a sliding-window screening and ranking procedure. Missingness-adjusted CUSUM statistics are constructed which jointly aggregate omics features by a data-adaptive projection to detect genome-wide chromosomal breakpoints. Across various simulations and applications to a colorectal cancer multi-omics dataset, MintCNA consistently outperforms existing single-omics CNA callers in detection accuracy. MintCNA provides a single-cell CNA tool that integrates paired scDNA-seq and scRNA-seq, supporting the study of intra-tumor heterogeneity and tumor evolution.
]]></description>
<dc:creator><![CDATA[ Bao, W., Qin, F., Xiao, F. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.26.734559</dc:identifier>
<dc:title><![CDATA[MintCNA: A Unified Framework for Integrative Copy Number Profiling with Single-Cell Multi-Omics Data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.27.734959v1?rss=1">
<title>
<![CDATA[
An axiomatic approach to cultivar ranking in multi-environment trials 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.27.734959v1?rss=1
</link>
<description><![CDATA[
Multi-environment trials are central to cultivar evaluation because they reveal how candidate cultivars perform across locations, years, management conditions, and stress environments. The resulting yield matrix is a rich source of data on genotype-by-environment interaction, and a wide literature on estimation, decomposition, visualisation, and prediction of yield potential and stability has flourished. However the ultimate question of which cultivar to recommend on the basis of such a matrix is often left implicit. The question is far from trivial, and in this paper we formulate cultivar recommendation as an axiomatic ranking problem. This framework is rich enough to encompass the existing literature on stability indices, as well as any other deterministic ranking procedure. We show that many commonly used stability-based procedures can violate minimal criteria of efficiency or consistency. The result of such violations is that a cultivar with uniformly high yield could be ranked below a cultivar with uniformly low yield, or the relative ranks of two cultivars could depend on whether or not a third cultivar is present in the matrix. Our results prove that under a small number of such criteria the space of admissible rules collapses to the family of power means and their limiting cases. If we further wish to allow multiplication normalisation of yield, we are left with the geometric mean as the unique solution.
]]></description>
<dc:creator><![CDATA[ Kondratev, A. Y., Ianovski, E., Voronina, E., Crossa, J. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.27.734959</dc:identifier>
<dc:title><![CDATA[An axiomatic approach to cultivar ranking in multi-environment trials]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.25.734678v1?rss=1">
<title>
<![CDATA[
AI-guided discovery for low-resource peptide engineering using evolutionary scale modeling 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.25.734678v1?rss=1
</link>
<description><![CDATA[
Reliable estimation of downstream performance in low-data peptide machine learning is critical for guiding early-stage AI-driven peptide engineering. Yet, it is often unclear how to assess whether a model will be effective in iterative discovery settings. Here, we show that the cross validation R2 score can serve as a simple and robust proxy for predicting active learning workflow performance, enabling early-stage evaluation of model suitability for sequential peptide optimization. To support this, we introduce SCARSE, a machine learning framework combining ESM-2 protein language model embeddings with Gaussian process regression and extremely randomized trees classification, designed for low-resource peptide property prediction (20-500 training samples). We benchmark SCARSE across 23 peptide and small-protein datasets covering substitution and indel variants, antimicrobial peptides, cell-penetrating peptides, and toxic/non-toxic peptides. SCARSE significantly outperforms a hand-engineered descriptor baseline on substitution and indel tasks, while comparable performance was achieved on shorter peptide non-mutant datasets where simpler descriptors capture enough of the signal. In simulated active learning workflows, SCARSE consistently outperforms baseline and random sampling strategies. Notably, we demonstrate that CV R2 computed from as few as 50 labeled peptides can be sufficient to estimate final active learning end-point performance, providing a practical, data-efficient criterion for deciding whether a given dataset combined with SCARSE is suitable for iterative peptide discovery. SCARSE is released as a pip package and is available via HuggingFace Spaces to facilitate integration into peptide engineering workflows.
]]></description>
<dc:creator><![CDATA[ Andrekson, L., Rydbergh, R., Mercado, R., Wenzel, M. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.25.734678</dc:identifier>
<dc:title><![CDATA[AI-guided discovery for low-resource peptide engineering using evolutionary scale modeling]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.28.735102v1?rss=1">
<title>
<![CDATA[
Fly Viral Atlas: A single-nucleus transcriptomic atlas of RNA viruses and transposable elements (TEs) in Drosophila melanogaster 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.28.735102v1?rss=1
</link>
<description><![CDATA[
Drosophila RNA viruses often persist in wild and lab populations, yet their tissue and cellular tropism is poorly understood. In the Fly Cell Atlas (a comprehensive Drosophila single-nucleus transcriptome) data, we detected four RNA virus infections: Nora virus, Drosophila A virus, Drosophila C virus, and Newfield virus. Nora and Drosophila A virus were the most abundant and widespread across tissues and cell types, while Drosophila C virus and Newfield virus RNA transcript were only found in oenocyte and fat body tissues. We found transcriptional changes associated with viral infection in canonical viral immunity genes (e.g. Vago, vir-1). Additionally, we observed that during persistent viral infections, transposable element (TE) transcripts were upregulated in somatic cells. TEs are traditionally associated with the germline, but recent studies and our data suggest they are also expressed in somatic cells. Using the Fly Cell Atlas data, we found that distinct somatic cell types express specific TE subtypes, indicating regulated and cell-type specific TE activity often overlooked in transcriptomic studies. We present Fly Viral Atlas (https://flyviralatlas.shinyapps.io/home/), a single-nucleus level atlas of RNA viruses and TE expressions in Drosophila, providing new insights into viral tropism and TE dynamics across cell types and tissues.
]]></description>
<dc:creator><![CDATA[ Roy, N., Unckless, R. L. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.28.735102</dc:identifier>
<dc:title><![CDATA[Fly Viral Atlas: A single-nucleus transcriptomic atlas of RNA viruses and transposable elements (TEs) in Drosophila melanogaster]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.26.734650v1?rss=1">
<title>
<![CDATA[
Revising the genetic and epigenetic architecture of in vitro regeneration capacity in natural Arabidopsis thaliana populations 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.26.734650v1?rss=1
</link>
<description><![CDATA[
Plant regeneration is a dynamic developmental process that spans from cell dedifferentiation to organ reconstruction in response to inductive cues, such as wounding stress and hormonal signals. Although this capacity varies widely both between and within species, a comprehensive understanding of the genetic and epigenetic bases of this variation remains incomplete. To address this issue, we revisited published datasets on natural variation in in vitro regeneration capacity in Arabidopsis thaliana. Using quantitative genetic approaches, including meta-analyses of genome-wide association studies (GWAS) and multi-locus models, we dissected the genetic architecture underlying regeneration traits. Our results showed that shoot regeneration capacity is primarily explained by allelic variation in the cis-regulatory region of WUSCHEL (WUS), a key regulator of shoot meristem formation. Notably, these polymorphisms are also associated with epigenetic variants of the DNA transposon ATDNA2T9C, which is located within the regulatory region. Furthermore, allelic variation in ARABIDOPSIS RESPONSE REGULATOR 2 (ARR2), a positive regulator of cytokinin signaling, is associated with callus formation and greening traits and may promote shoot formation through genetic interactions with WUS alleles. Although in vitro regeneration is controlled by complex, multilayered gene regulatory networks, our results suggest that, in A. thaliana, natural variation in regeneration capacity is largely shaped by a small number of major-effect modifiers together with epigenetic variation and genetic interactions, despite the substantial heterogeneity observed among natural populations.
]]></description>
<dc:creator><![CDATA[ Arima, K., Chen, Y., Sugimoto, K., Sasaki, E. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.26.734650</dc:identifier>
<dc:title><![CDATA[Revising the genetic and epigenetic architecture of in vitro regeneration capacity in natural Arabidopsis thaliana populations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.26.734694v1?rss=1">
<title>
<![CDATA[
mirCCC: Repression-aware graph learning for miRNA-mediated cell-cell communication inference 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.26.734694v1?rss=1
</link>
<description><![CDATA[
Cell-cell communication analyses usually focus on protein ligands and receptors and therefore miss the extracellular vesicle-mediated transfer of microRNAs, an important route of signalling in cancer. Here, we show that microRNA-mediated communication can be inferred from standard single-cell RNA sequencing by detecting coordinated decreases in the expression of validated miRNA target genes. We developed mirCCC, a computational framework that estimates cell-specific microRNA activity, models cellular sending and receiving capacities for extracellular vesicle transfer, and learns microRNA-resolved communication graphs from transcriptomic data. In synthetic benchmarks with strong confounding signals, mirCCC improved, whereas all comparison methods declined. Applied to a human colorectal cancer atlas, mirCCC recovered known colorectal cancer-associated microRNAs and identified stromal- and myeloid-to-epithelial communication converging on a plasticity program linked to TGF-{beta} and Wnt/{beta}-catenin signalling. These results provide a practical route for studying extracellular vesicle-mediated communication in existing single-cell atlases.
]]></description>
<dc:creator><![CDATA[ Chen, Y., Cui, J., Zhang, S., Liu, E., Xie, L., Feng, C., Chen, M. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.26.734694</dc:identifier>
<dc:title><![CDATA[mirCCC: Repression-aware graph learning for miRNA-mediated cell-cell communication inference]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.26.734692v1?rss=1">
<title>
<![CDATA[
Evolutionary Stratification of Codon Usage Bias In Plants Arises from GC3 Composition and Translational Optimization 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.26.734692v1?rss=1
</link>
<description><![CDATA[
Codon usage bias is a fundamental genomic characteristic that prefers non-random preferential use of synonymous codons. It is a major determinant of translational efficiency, gene regulation, and molecular evolution. However, the evolutionary bias and functional relevance of codon usage bias across the plant lineage is poorly defined and yet to understand what are the major factors responsible for relative synonymous codon usage (RSCU) in genomes and how codon usage bias influences the gene regulation, molecular evolution genomes. A genome-wide codon usage bias study of coding DNA sequences of 262 plant genome was conducted. It encompassed more than 4.6 billion codons from > 11 million coding sequences. Relative synonymous codon usage, codon adaptation index, codon-anticodon mapping, effective number of codon (ENC)-GC3, GC1,2-GC3, parity rule 2 (PR2-bias), molecular economy, and machine learning approaches were used for the study. It was found that codon usage bias was strongly non-random and exhibited a clear phylogenetic structuring. The higher plants favoured A/T-ending, whereas early-diverging lineages were enriched in G/C-ending codons. Analysis of RSCU, codon adaptation index, and codon-anticodon pairing indicated that translational selection is mediated by tRNA availability, contributing sustainability to these molecular patterns. Machine-learning approaches identified a small subset of codons having outsized influence on genome-wide codon usage landscapes. Further studies revealed the presence of robust inverse relationships between the effective number of codons and GC content at synonymous third positions. Neutrality analysis revealed approximately 61% of variation was driven by mutational pressure, tempered by selective constraints. Phylogenetic reconstruction showed a progressive relaxation of codon bias from algae to angiosperms while maintaining a conserved molecular economy cost of ~ 30 ATP per codon across the lineages. The study revealed codon usage bias is lineage-specific evolutionary conserved trait governed by mutation, selection, and translational optimization.
]]></description>
<dc:creator><![CDATA[ Mohanta, T. K. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.26.734692</dc:identifier>
<dc:title><![CDATA[Evolutionary Stratification of Codon Usage Bias In Plants Arises from GC3 Composition and Translational Optimization]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.25.734683v1?rss=1">
<title>
<![CDATA[
Pathogenic impact of ABCA4 missense variants in the structurally uncharacterized ECD1 region: implications for Stargardt disease. 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.25.734683v1?rss=1
</link>
<description><![CDATA[
Pathogenic mutations in the ABCA4 gene cause several inherited retinal diseases, particularly Stargardt disease (STGD1). However, many missense variants remain classified as variants of uncertain significance (VUS) due to inconclusive evidence regarding their pathogenic impact. The missense VUS span across all the domains of ABCA4, with the majority found in the larger extracellular domains (ECDs). The largest uncharacterized region of ABCA4 is located in ECD1, where limited structural information and inconsistent computational predictions hinder clinical interpretation of missense VUS in this region. Here, we integrated in silico analysis with in vitro functional assays to evaluate the pathogenicity of VUS in this region and improve their diagnostic classification. Missense VUS in the ECD1 uncharacterized region were curated from ClinVar. Six multiallelic sites were identified in the uncharacterized region and 13 missense VUS on these multiallelic sites were characterized using the integrated analysis. In the in silico platform, the pathogenicity of the VUS were predicted using multiple algorithms, and the structural effects of the variants were analyzed compared to the wild type. Recombinant variants were expressed in virus-like particles (VLPs), and protein expression, membrane localization, and ATPase activity were quantified relative to wild type to identify potential disease-causing variants. From the integrated analysis, variants with pronounced structural destabilization, impaired membrane trafficking, and reduced or absent N-retinylidene-phosphatidylethanolamine (NRPE) substrate stimulated ATPase activities were identified as potentially deleterious. Notably, VUS at p.H193P and p.I214N showed loss of function, with p.I214N reflecting selectively impaired membrane targeting and p.H193P reflecting combined expression and trafficking defects. Additionally, NRPE-stimulated ATPase activities were impaired in VUS, p.V195L, p.V195I, p.D197H, p.I214F and p.N269S. Overall structural destabilization interfered with the NRPE-stimulated ATPase activities of p.N269S, while the lack of NRPE-stimulated ATPase activities of p.D197H, p.V195L, p.V195I and p.I214F are thought to be due to impaired NRPE interactions with ABCA4. All the VUS at p.R140, p.H193Y, p.D197N and p.N269H showed both the basal and NRPE-stimulated ATPase activities but less than that of the wild type, displaying a mild functional deficit. Together, these findings demonstrated that certain VUS within the unresolved ECD1 region disrupt ABCA4 stability and function, supporting their contribution to disease pathogenesis. This integrative approach highlights key residues likely to be pathogenic and advances the interpretation of VUS in inherited retinal disorders.
]]></description>
<dc:creator><![CDATA[ Matarage Don, N. N. J., Biswas, S. B., Biswas-Fiss, E. E. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.25.734683</dc:identifier>
<dc:title><![CDATA[Pathogenic impact of ABCA4 missense variants in the structurally uncharacterized ECD1 region: implications for Stargardt disease.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.30.735607v1?rss=1">
<title>
<![CDATA[
A conserved architectural domain shapes centromere evolution in Drosophila 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.30.735607v1?rss=1
</link>
<description><![CDATA[
Centromeres ensure faithful chromosome segregation despite being embedded within rapidly evolving repetitive DNA, a contradiction known as the centromere paradox. While centromere identity is defined by the histone variant CENP-A, how conserved function is maintained amid rapid DNA turnover remains unclear. Here, we generate highly contiguous genome assemblies from single Drosophila melanogaster individuals that, for the first time, resolve a chromosome through its centromere, linking the chromosome 3 arms within a continuous sequence. Comparative assemblies from wild-derived strains reveal extensive structural variation in pericentromeric satellites, including large-scale expansions, contractions, and sequence divergence. Despite this variation, the CENP-A-associated centromeric core exhibits conserved organization across strains. Integration of Hi-C interaction maps with sequence analyses shows that flanking dodeca satellite arrays form a spatially interacting domain that bridges both sides of the centromere, whereas adjacent Prodsat arrays are more variable and show weaker interactions. These results support a model in which rapidly evolving centromeric DNA is constrained by conserved higher-order architecture, providing a framework for reconciling the rapid evolution of centromere sequence with its conserved function.
]]></description>
<dc:creator><![CDATA[ Samano, A., Chakraborty, M. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.30.735607</dc:identifier>
<dc:title><![CDATA[A conserved architectural domain shapes centromere evolution in Drosophila]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.30.735528v1?rss=1">
<title>
<![CDATA[
Single molecule footprinting measures low nucleosome occupancy in mature spermatozoa of mice and men 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.30.735528v1?rss=1
</link>
<description><![CDATA[
Nucleosomes are fundamental units of DNA packaging and gene regulation in eukaryotes. In mammalian sperm, most nucleosomes are replaced by protamines causing extreme chromatin compaction. Various epigenomic studies reported conflicting results on the distribution of residual nucleosomes in mammalian sperm, questioning their potential role in mediating intergenerational inheritance of paternal epigenetic information. Here we performed single-molecule footprinting through Nucleosome Occupancy and Methylome (NOMe) sequencing and applied the Bayesian statistical model nomeR to determine frequencies of nucleosome removal and retention at 103 specific genomic regions in thousands of developing haploid spermatids and mature spermatozoa of mice. While we readily detected footprints of nucleosomes and the transcription factor CTCF in round spermatids, chromatin became transiently highly accessible in elongating spermatids with loss of such footprints, indicating extensive chromatin reprogramming during spermiogenesis. In mature sperm, following nuclear decondensation with recombinant nucleoplasmin, we measured nucleosome occupancy frequencies ranging ~1.2 to 1.7% at mouse loci. In human sperm, nucleosome occupancy varied between ~2.3 to 4.5% at 163 genomic loci profiled. Contrasting mice, chromatin in ~25% of human sperm was accessible upon reducing disulfide bonds between protamines arguing for species specific protamine packaging. Our findings support a stochastic rather than programmed potential role of residual nucleosomes in mammalian sperm in regulating paternal gene expression during ensuing embryonic development.
]]></description>
<dc:creator><![CDATA[ Gaspa-Toneu, L., Shi, H., Ozonov, E. A., Gill, M. E., De Geyter, C., Peters, A. H. F. M. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.30.735528</dc:identifier>
<dc:title><![CDATA[Single molecule footprinting measures low nucleosome occupancy in mature spermatozoa of mice and men]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.26.734851v1?rss=1">
<title>
<![CDATA[
Genome architecture shapes the evolutionary origins of redundant enhancers in fly and mouse 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.26.734851v1?rss=1
</link>
<description><![CDATA[
Shadow enhancers are groups of DNA regulatory elements that control the same target gene and drive overlapping expression patterns. Large-scale surveys have found shadow enhancers control most developmental genes in animal genomes. The way in which shadow enhancers arise and how they subsequently evolve may further illuminate their regulatory logic and mechanisms of action. To investigate the evolutionary origins of shadow enhancers, we searched for sequence signatures of three birth mechanisms: duplication of existing enhancers, transposable element (TE) co-option, and TE-mediated splitting of ancestral regulatory elements in the Drosophila melanogaster and mouse genomes. Using 420 fly shadow enhancer sets and 9,051 mouse shadow enhancer sets, we found detectable duplication evidence in 18.3% of fly shadow enhancer sets and 33.9% of mouse sets. Duplication signatures were more frequent in larger shadow sets, suggesting that repeated duplication can expand regulatory landscapes. TE-derived enhancers were present in both species but were not enriched in shadow enhancers relative to single enhancers, suggesting that TE co-option contributes to enhancer evolution generally rather than preferentially generating redundant enhancer architectures. Finally, TE-mediated enhancer splitting was rare in both genomes. These results indicate that shadow enhancer birth is mechanistically heterogeneous, reflecting a mixture of duplication, TE co-option, and other mechanisms, whose contributions are shaped by genome architecture and evolutionary time. Therefore, we find that overlapping regulatory functions can arise through multiple evolutionary routes and that birth mechanisms can influence, but do not strictly determine, the regulatory logic of the resulting enhancer set.
]]></description>
<dc:creator><![CDATA[ Ness, J., Kosztyo, B., Wunderlich, Z. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.26.734851</dc:identifier>
<dc:title><![CDATA[Genome architecture shapes the evolutionary origins of redundant enhancers in fly and mouse]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.26.734829v1?rss=1">
<title>
<![CDATA[
BOSE: A Bayesian Order Statistics-Based Estimator for Recovering the Sample Mean and Standard Deviation 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.26.734829v1?rss=1
</link>
<description><![CDATA[
In meta-analyses of continuous outcomes, the sample mean and standard deviation (SD) are essential for synthesizing effect sizes across studies. However, clinical studies frequently report alternative summary statistics, such as the median, quartiles, and range. To enable inclusion of such studies, various methods have been proposed to estimate the sample mean and SD from these reported summaries. We propose the Bayesian Order Statistics-based Estimator (BOSE), which leverages the joint likelihood of observed order statistics together with weakly informative priors to obtain the full posterior distribution for the mean and SD without relying on computationally intensive iterative procedures such as Markov chain Monte Carlo algorithms. Our numerical studies demonstrate that BOSE performs competitively with existing approaches in estimating the mean, while achieving superior performance for estimating the SD across all evaluated scenarios, particularly in small-sample settings. Under non-normal distributions including skewed, heavy-tailed, and bimodal settings with mild or moderate deviations from normality, BOSE remains robust and stable, whereas methods specifically designed for skewed distributions may become unstable or even inapplicable. Beyond point estimation, BOSE naturally provides empirically validated posterior credible intervals, enabling researchers to formally quantify uncertainty for study-level estimates and make reliable, evidence-based decisions in meta-analytic research synthesis. A publicly accessible web application implementing BOSE and competing methods is also provided to facilitate practical use in meta-analytic research.
]]></description>
<dc:creator><![CDATA[ Pan, W., Lu, Z., Jiang, W., Lim, J., Xu, L., Wang, X. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.26.734829</dc:identifier>
<dc:title><![CDATA[BOSE: A Bayesian Order Statistics-Based Estimator for Recovering the Sample Mean and Standard Deviation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.30.735527v1?rss=1">
<title>
<![CDATA[
Penumbria: Advanced 3D cell segmentation for biomedical imaging 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.30.735527v1?rss=1
</link>
<description><![CDATA[
Quantitative analysis of three-dimensional cellular architecture is fundamental to understanding tissue organization, disease progression, and drug response. Yet 3D cell segmentation remains a critical bottleneck due to diverse cell morphologies, low signal-to-noise ratios, and data scarcity. We introduce Penumbria, a general-purpose 3D cell segmentation framework that achieves state-of-the-art accuracy across morphologically distinct cell populations and imaging conditions in volumetric microscopy. Penumbria formulates segmentation as a regression problem on distances to cell boundaries, supporting instance reconstruction without shape priors and permitting end-to-end GPU inference. A U-Net-based architecture with xLSTM bottleneck blocks and patch embeddings enables multi-scale feature extraction, long-range modeling of spatial context, and convolutional feature-volume tokenization. The model is extended with two modules: a Global Zernike Phase Layer, which learns Zernike-parameterized phase corrections in the frequency domain to undo optical aberrations such as defocus and tilt, and a Scaled Geocaps Layer, which samples features at fixed grid locations across multiple spatial scales, routing evidence between them such that a detection is only confident where concordance holds across scales simultaneously. Across four diverse 3D datasets selected to probe the limits of existing methods, Penumbria outperforms Cellpose-SAM across all evaluation thresholds and surpasses StarDist-3D on most datasets while matching it on Parhyale hawaiensis. Trained entirely from scratch, Penumbria achieves up to a 38% improvement in mean average precision over the second-best method. Strong boundary accuracy further supports downstream analyses such as quantifying membrane dynamics or protein localization.
]]></description>
<dc:creator><![CDATA[ Stockert, L., Donovan, J., Baier, H. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.30.735527</dc:identifier>
<dc:title><![CDATA[Penumbria: Advanced 3D cell segmentation for biomedical imaging]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.26.734908v1?rss=1">
<title>
<![CDATA[
Gene model for the ortholog of tgo in Drosophila busckii 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.26.734908v1?rss=1
</link>
<description><![CDATA[
Gene model for the ortholog of tango (tgo) in the Sep. 2015 (UC Berkeley ASM127793v1/DbusGB1) Genome Assembly (GenBank Accession: GCA_001277935.1) of Drosophila busckii. This ortholog was characterized as part of a developing dataset to study the evolution of the Insulin/insulin-like growth factor signaling pathway (IIS) across the genus Drosophila using the Genomics Education Partnership gene annotation protocol for Course-based Undergraduate Research Experiences.
]]></description>
<dc:creator><![CDATA[ Perez, J., Giunta, A. A., Wittke-Thompson, J. K. ]]></dc:creator>
<dc:date>2026-07-01</dc:date>
<dc:identifier>doi:10.64898/2026.06.26.734908</dc:identifier>
<dc:title><![CDATA[Gene model for the ortholog of tgo in Drosophila busckii]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.30.735557v1?rss=1">
<title>
<![CDATA[
A refined Saccharomyces cerevisiae reference transcriptome from Direct RNA Sequencing, with a reusable pipeline for UTR annotation updates 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.30.735557v1?rss=1
</link>
<description><![CDATA[
Untranslated regions (UTRs) flanking the coding sequence govern mRNA translation, localisation, stability, and decay, making accurate UTR boundaries essential for quantitative RNA sequencing and the study of post-transcriptional control in Saccharomyces cerevisiae and beyond. Reference transcriptomes built from short-read sequencing have been invaluable to the yeast community, yet in a genome as gene-dense as that of S. cerevisiae, short reads frequently cannot be assigned to a single transcript of origin, leaving roughly one quarter of transcripts without a confidently defined UTR. Here we use Oxford Nanopore Direct RNA Sequencing (DRS), in which each full-length polyadenylated molecule is read end to end, to resolve this ambiguity and deliver two complementary resources. First, an updated, ready-to-use S. cerevisiae S288C reference: change-point segmentation of per-gene DRS coverage defined boundaries for 5,416 of the 6,695 annotated genes, and a merge-max rule retaining the longer UTR from each source ensures no gene loses existing annotation. The result adds previously absent UTRs to 927 (5') and 896 (3') genes and extends 29.4% of 5' and 26.1% of 3' boundaries among comparable genes. Second, the complete, documented pipeline so that any laboratory can rebuild or update a transcriptome from its own DRS data. Validation on two independent datasets shows improved mapping rates, reduced soft-clipping, and metagene profiles consistent with genuine transcript signal.
]]></description>
<dc:creator><![CDATA[ Rossini, O., Cleynen, A., Shirokikh, N. E. ]]></dc:creator>
<dc:date>2026-06-30</dc:date>
<dc:identifier>doi:10.64898/2026.06.30.735557</dc:identifier>
<dc:title><![CDATA[A refined Saccharomyces cerevisiae reference transcriptome from Direct RNA Sequencing, with a reusable pipeline for UTR annotation updates]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.30.735501v1?rss=1">
<title>
<![CDATA[
Near-complete genomes for nine haplochromine cichlid fishes reveal a novel centromeric satellite structure organised around a pair of inverted elements 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.30.735501v1?rss=1
</link>
<description><![CDATA[
The haplochromine cichlid fishes of Lake Malawi form one of the most dramatic examples of recent rapid radiation in vertebrates. Here we describe nine new diploid telomere-to-telomere (T2T) genome sequences generated using ultra-long ONT reads, which include 78 ungapped chromosomes. We provide accurate annotations of transposable elements and tandem repeats, identify rDNA cluster regions and putative centromeres, and confirm previously reported large chromosomal inversions. The putative centromeres are primarily composed of satellite tandem arrays of previously reported 237 bp repeats, but notably on most chromosomes these are organised in a novel structure in which four blocks of satellites in alternating orientation are separated by an inverted pair of ~15 kb sequences we term 'centroids', which have similarity to a non-autonomous DNA transposable element and containing potential CENP-B binding boxes. The methylation dip region indicating the likely active centromere always lies between the centroids, whose separation is almost always around 200 kb (interquartile range 151-221kb). A structurally equivalent but non-homologous organisation is seen in the distantly related Etroplus cichlid genera from South Asia. By comparing these structures across chromosomes and species, we suggest how they may have evolved, and potentially how they could contribute to the rampant sympatric speciation seen in these species, based on meiotic drive and chromosome missegregation.
]]></description>
<dc:creator><![CDATA[ Sierra, P., Zhou, C., Fischer, B., Lim, S. W., Blumer, M., Ngochera, M., Durbin, R. ]]></dc:creator>
<dc:date>2026-06-30</dc:date>
<dc:identifier>doi:10.64898/2026.06.30.735501</dc:identifier>
<dc:title><![CDATA[Near-complete genomes for nine haplochromine cichlid fishes reveal a novel centromeric satellite structure organised around a pair of inverted elements]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.30.735235v1?rss=1">
<title>
<![CDATA[
CyStainer: A transformer-based variational autoencoder for robust marker imputation in high-parameter cytometry 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.30.735235v1?rss=1
</link>
<description><![CDATA[
High parameter cytometry is essential for clinical diagnostics through precise immune cell profiling, improved patient stratification, and monitoring, while also enhancing the understanding of cellular responses in disease and therapeutic contexts. The amount of cytometry data is growing fast, and with that, the need to merge different datasets for unified analysis. Here, we present CyStainer, a transformer-based variational autoencoder that demonstrates competitive or superior performance to existing methods on several key tasks related to marker prediction. As a key novelty, we demonstrate that CyStainer can impute markers without having a set of shared backbone markers. We performed several benchmarks using real-world FACS, CyTOF, InfinityFlow and CITE-seq datasets to show that CyStainer is a robust and flexible tool for panel merging, marker imputation, dataset integration and virtual staining of unseen samples.
]]></description>
<dc:creator><![CDATA[ Ivanov, K., Moussawy, M. A., Kirk, F., Samuli, R., Lohi, O., Olsen, L., Modvig, S., Hautamäki, V., Heinäniemi, M. ]]></dc:creator>
<dc:date>2026-06-30</dc:date>
<dc:identifier>doi:10.64898/2026.06.30.735235</dc:identifier>
<dc:title><![CDATA[CyStainer: A transformer-based variational autoencoder for robust marker imputation in high-parameter cytometry]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.25.733584v1?rss=1">
<title>
<![CDATA[
Spike-in-normalised single-cell RNA-seq reveals cell-type-specific transcriptional repression during ageing 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.25.733584v1?rss=1
</link>
<description><![CDATA[
Transcriptome analyses are widely used for biomarker discovery and to gain insights into normal processes and diseases. Age-related changes in gene expression inferred from RNA-seq are typically reported relative to the transcriptome composition using library-size normalisation. As such, absolute changes in transcript abundance with age remain poorly characterised. Here, using external spike-in normalisation in the Tabula Muris Senis dataset, we quantify age-related variation in total mRNA content and gene expression across mouse cell types. We observe widespread changes in total mRNA abundance, with decreases predominantly in non-immune cell types and increases predominantly in immune cell types. In parallel, the number of genes expressed declines across most cell types, including immune populations. Differential expression analysis based on spike-in-normalised counts identifies genes consistently downregulated across cell types, enriched for functions in RNA metabolism and protein processing. Furthermore, genes downregulated during ageing and during proliferation arrest show partial overlap, suggesting that these transcriptional changes may share regulatory processes. Together, these results are consistent with a general repression of transcriptional and metabolic activity with age, modulated by immune-specific responses. More broadly, our results demonstrate that conclusions drawn from transcriptomic ageing studies can depend strongly on whether gene expression is interpreted in relative or absolute terms, highlighting the importance of absolute normalisation approaches for the analysis of age-related transcriptomic change
]]></description>
<dc:creator><![CDATA[ de Jesus Viegas, I., Lagger, C., de Magalhaes, J. P. ]]></dc:creator>
<dc:date>2026-06-30</dc:date>
<dc:identifier>doi:10.64898/2026.06.25.733584</dc:identifier>
<dc:title><![CDATA[Spike-in-normalised single-cell RNA-seq reveals cell-type-specific transcriptional repression during ageing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.25.734631v1?rss=1">
<title>
<![CDATA[
Sequencing, Chromosome-scale Assembly, and Annotation of the Genome of the Halophilic Nanoflagellate Halocafeteria seosinensis 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.25.734631v1?rss=1
</link>
<description><![CDATA[
Compared with bacterial and archaeal extremophiles, single-celled eukaryotes living in extreme habitats are understudied and underrepresented in genomic databases. An exception is the obligately halophilic stramenopile Halocafeteria seosinensis strain EHF34. A transcriptome-focused analysis of this extremophilic protists revealed the importance of organic osmolyte regulation and transport in its adaptation to hypersaline environments. However, genomic resources for H. seosinensis are currently limited to a highly fragmented assembly generated by short-read sequencing, which has hindered further investigation of the genome biology and evolution of this fascinating organism. Here, we used long-read Oxford Nanopore sequencing to generate a highly contiguous, chromosome-scale genome assembly for H. seosinensis. The assembly is 38.8 megabase pairs (Mbp) in size and contains 60 nuclear contigs, making it the most contiguous genome for a member of the order Bicosoecida. Approximately 19% of the genome is comprised of transposable elements. Of the 11,684 predicted protein-coding genes, many appear to be associated with DNA mobility-related functions, and several may be linked to adaptation to a hypersaline environment. Analysis of the H. seosinensis long-read genome assembly presented herein will facilitate our understanding of the ways in which protists have adapted to extreme environments.
]]></description>
<dc:creator><![CDATA[ Gallot-Lavallee, L., Haro, R., Jerlstrom-Hultqvist, J., Tymoshenko, D., Roger, A., Archibald, J. M. ]]></dc:creator>
<dc:date>2026-06-30</dc:date>
<dc:identifier>doi:10.64898/2026.06.25.734631</dc:identifier>
<dc:title><![CDATA[Sequencing, Chromosome-scale Assembly, and Annotation of the Genome of the Halophilic Nanoflagellate Halocafeteria seosinensis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.25.734539v1?rss=1">
<title>
<![CDATA[
A robot model of compass cue calibration in the insect brain 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.25.734539v1?rss=1
</link>
<description><![CDATA[
Dung beetles can use a variety of orientation cues to maintain a consistent bearing during ball-rolling. Where several cues are available, they appear to learn the spatial relationship between them, providing redundancy if some cues are removed. Mounting evidence indicates that such a learning process is implemented in the insect head direction circuit; specifically, in the plastic substrate between sensory input neurons and compass neurons in the central complex. This plasticity appears to be driven by rotational movements, providing a clear link with observed beetle 'dance' behaviour. Here, we extend our functional model of this circuit and use it on a robot platform, to test it in the same behavioural assay as was used for the beetles. The robot was able to replicate the beetle's ability to substitute a directional wind cue for a point source light cue in guiding straight-line movement. However, it also revealed significant biasing coupled to dance direction. This biasing appears to be caused by inherent conflict between recurrent and instantaneous inputs to the compass circuit. We predict that the real insect should experience similar issues unless it has evolved a neural mechanism to compensate.
]]></description>
<dc:creator><![CDATA[ Mitchell, R., Dacke, M., Webb, B. ]]></dc:creator>
<dc:date>2026-06-30</dc:date>
<dc:identifier>doi:10.64898/2026.06.25.734539</dc:identifier>
<dc:title><![CDATA[A robot model of compass cue calibration in the insect brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.25.734551v1?rss=1">
<title>
<![CDATA[
Real-World Progression-Free Survival with Erlotinib versus Osimertinib in EGFR L858R+T790M Compound Mutation Non-Small Cell Lung Cancer: An Exploratory Analysis of the MSK-CHORD Dataset 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.25.734551v1?rss=1
</link>
<description><![CDATA[
Background: Osimertinib is the standard first-line treatment for EGFR- mutant non-small cell lung cancer (NSCLC) harboring common activating mutations, including exon 19 deletions and L858R. It is also active against tumors with acquired T790M resistance. However, the EGFR L858R+T790M compound mutation, where both variants co-occur within the same tumor, may confer distinct drug-sensitivity profiles not predicted by either mutation alone. Limited data exist on comparative treatment outcomes in this rare genotype. Methods: Using the MSK-CHORD clinicogenomic dataset (n=24,950), we identified patients with concurrent EGFR L858R and T790M mutations receiving erlotinib (Erlo) or osimertinib (Osi) monotherapy. Real-world progression-free survival (rwPFS) per treatment line was calculated using a strict definition requiring confirmed radiological progression events (rwPFS-strict), excluding lines with null endpoint data. Kaplan-Meier analysis, log-rank testing, Cox proportional hazards regression, and cross-cohort heterogeneity testing (Cochran's Q statistic) were performed. Two control cohorts, L858R-only (n=372) and T790M-only (n=76), were analyzed in parallel to assess mutation-context specificity of treatment response. Results: Thirty-one patients with EGFR L858R+T790M were identified; 21 contributed evaluable monotherapy lines, yielding 23 Erlo and 15 Osi treatment lines (14 unique patients per treatment group, 7 contributing to both). Median rwPFS numerically favored Erlo over Osi (7.10 vs 5.32 months; HR 1.29, 95% CI 0.66-2.52; log-rank p=0.46). This directional trend was reversed in the L858R-only control cohort, where Osi demonstrated significant superiority (9.03 vs 5.75 months; HR 0.70, 95% CI 0.55-0.89; p=0.003). The T790M-only cohort showed no significant difference (HR 1.32, p=0.12). An exploratory post-hoc heterogeneity test confirmed a significant cross-cohort interaction (Q=9.94, df=2, p=0.007). Conclusions: The expected osimertinib advantage was absent in L858R+T790M compound-mutant NSCLC. The opposing hazard ratio directions across mutation contexts (HR 1.29 vs 0.70), with a significant exploratory cross-cohort interaction (p=0.007), suggest that the EGFR L858R+T790M compound mutation may represent a pharmacologically distinct entity with differential TKI sensitivity. These hypothesis-generating findings warrant prospective validation.
]]></description>
<dc:creator><![CDATA[ Dalloul, Z., Abboud, A., Dalloul, I., Abdelsalam, M. ]]></dc:creator>
<dc:date>2026-06-30</dc:date>
<dc:identifier>doi:10.64898/2026.06.25.734551</dc:identifier>
<dc:title><![CDATA[Real-World Progression-Free Survival with Erlotinib versus Osimertinib in EGFR L858R+T790M Compound Mutation Non-Small Cell Lung Cancer: An Exploratory Analysis of the MSK-CHORD Dataset]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.25.733353v1?rss=1">
<title>
<![CDATA[
A High-Quality Acetylation Dataset Reveals Modest Data Requirements for Transfer Learning to Identify Little Studied Post-Translational Modifications 
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</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.25.733353v1?rss=1
</link>
<description><![CDATA[
Dysregulation of post-translational modifications (PTMs) is associated with severe pathologies, including cancers and Alzheimer's disease. Despite their biological importance, identifying modified peptides remains challenging due to the immense combinatorial search space. While searches benefit from prior knowledge of a peptide's modification status, the data scarcity for most PTMs hinders the development of accurate deep learning classifiers like AHLF (ad hoc learning of peptide fragmentation). Here, we overcome this data bottleneck for acetylation and ubiquitination. We harmonised a dataset with about 500,000 high quality acetylated peptide-spectrum matches (PSMs) from nine publicly available acetylation-enriched datasets. We fine-tuned AHLF with the acetylation and a 2-million spectra strong ubiquitination dataset separately and assessed the minimum data requirement for training by iteratively downsampling. Training separate models on SILAC and label-free subsets also assessed the impact of data diversity. The resulting acetylation and ubiquitination models achieve an AUC of 0.87 and 0.90 respectively. Beyond 28,500 acetylated spectra, corresponding to roughly 0.3% of the original model's training data, additional data just provides minor performance gains. Finally, we show that data diversity is beneficial for generalizability, while models trained on homogeneous data sources tend to overfit to their respective data type. All code, and model weights are available at https://gitlab.com/dacs-hpi/ahlf-ptmai.
]]></description>
<dc:creator><![CDATA[ Hartmaring, Y., Wang, S., Jones, A. R., Vizcaino, J. A., Schlaffner, C. N., Renard, B. Y. ]]></dc:creator>
<dc:date>2026-06-30</dc:date>
<dc:identifier>doi:10.64898/2026.06.25.733353</dc:identifier>
<dc:title><![CDATA[A High-Quality Acetylation Dataset Reveals Modest Data Requirements for Transfer Learning to Identify Little Studied Post-Translational Modifications]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.25.734490v1?rss=1">
<title>
<![CDATA[
Abundance, diversity and activity of endogenous retroviruses in the slow loris. 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.25.734490v1?rss=1
</link>
<description><![CDATA[
Endogenous retroviruses (ERVs) constitute a significant fraction of vertebrate genomes and serve as genomic records of past retroviral infections, while also influencing host biology through regulatory co-option and, in some cases, ongoing retrotransposition. Despite extensive examination of ERVs in haplorrhine primates, equivalent analyses in strepsirrhines remain absent, leaving a substantial gap in our understanding of ERV diversity and evolutionary dynamics across the primate order. Here, we present the first comprehensive characterisation of ERVs in a strepsirrhine primate, identifying 15 Loris Endogenous Retrovirus (LERV) families encompassing 34 subfamilies and over 6,000 insertions in the Nycticebus coucang reference genome. Phylogenetic analyses resolved LERVs into three retroviral genera: betaretroviruses (LERV1 to 4), type-D betaretroviruses (LERV5 to 9), and gammaretroviruses (LERV10 to 15). LERV2a shows multiple hallmarks of recent or potentially ongoing retrotransposition, including a median insertion age of zero, a high proportion of identical LTR pairs, dN/dS ratios comparable to the active retrovirus HTLV, and insertional polymorphism between two conspecific genomes. Comparative genomic screening across Lorisidae revealed that LERV subfamily distribution broadly mirrors estimated insertion ages, with progressively fewer subfamilies detected in more distantly related species. These findings establish a detailed foundation for understanding retroviral evolution in Strepsirrhini and reveal that ongoing retroviral activity is not restricted to haplorrhine primates.
]]></description>
<dc:creator><![CDATA[ Michie, C. A. G., Free, H. B., Nijman, V., Kanda, R. K. ]]></dc:creator>
<dc:date>2026-06-30</dc:date>
<dc:identifier>doi:10.64898/2026.06.25.734490</dc:identifier>
<dc:title><![CDATA[Abundance, diversity and activity of endogenous retroviruses in the slow loris.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.25.734475v1?rss=1">
<title>
<![CDATA[
Integrating Semantic Retrieval, LLM-based Refinement, and Structured Expert Curation for Scalable AOP Gene Mapping 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.25.734475v1?rss=1
</link>
<description><![CDATA[
Toxicogenomics can support regulatory toxicology, but its use is limited by the difficulty of translating molecular responses into mechanistic, decision-relevant interpretations. Adverse Outcome Pathways (AOPs) provide a framework for this translation, yet omics applications require scalable mapping of Key Events (KEs) to molecular features. Here, we present an AI-assisted, multi-step workflow for KE-to-gene mapping that uses embedding-based semantic retrieval to identify candidate ontology/pathway terms, large language model-assisted refinement to filter these candidates, and double-independent expert group curation with rule-based consolidation to finalize mappings and derive confidence scores. Compared with earlier NLP-based approaches, the workflow improves KE-to-ontology/pathway mapping performance and generates candidate annotations that better align with expert judgment while substantially reducing the need for manual augmentation. Explicit gene and protein mentions in KE titles were additionally grounded to improve specificity, and each curated mapping was assigned curator reason codes to support transparent, traceable, and confidence-aware reuse. Applied across AOP-Wiki, the workflow produced a comprehensive KE-to-gene set resource covering 1,254 KEs across 523 AOPs and linking 15,833 human genes. Utility is demonstrated through CTD-based AOP fingerprinting of curated reference chemical groups, highlighting expanded coverage and confidence-informed interpretation of chemical-associated gene signatures in an AOP context. The workflow and resulting resource provide a practical bridge between toxicogenomics and AOP-based mechanistic interpretation and support routine updating and future extension to additional omics layers within OECD Omics2AOP.
]]></description>
<dc:creator><![CDATA[ Schaffert, A., Fratello, M., Kangas, K., Torres Maia, M., del Giudice, G., Mobus, L., Accardi, C., Al-Abdulraheem, Z., Campini, L., Galardo, F., Federico, A., Ciancaleoni, G., Juppi, H.-K., Paparella, M., Serra, A., Greco, D. ]]></dc:creator>
<dc:date>2026-06-30</dc:date>
<dc:identifier>doi:10.64898/2026.06.25.734475</dc:identifier>
<dc:title><![CDATA[Integrating Semantic Retrieval, LLM-based Refinement, and Structured Expert Curation for Scalable AOP Gene Mapping]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.25.734481v1?rss=1">
<title>
<![CDATA[
A pan-cancer benchmark of integrated ferroptosis, cuproptosis and disulfidptosis prognostic signatures 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.25.734481v1?rss=1
</link>
<description><![CDATA[
Integrated prognostic signatures combining ferroptosis, cuproptosis, and disulfidptosis are increasingly reported in oncology as advances in risk stratification, yet their added value over simpler pathway-specific or proliferation-related models remains unclear. Here, we developed an integrated regulated cell-death signature and evaluated it through an adversarial pan-cancer benchmark. Using the TCGA pan-cancer cohort comprising 9,808 tumours across 33 cancer types, we curated 118 genes associated with the three cell-death programmes, characterised inter-pathway crosstalk, and derived a 26-gene LASSO-Cox risk signature. The model showed reproducible prognostic performance across cancers, with a pan-cancer concordance index of 0.573 (95% CI, 0.552-0.594), and was independently validated in METABRIC and CGGA cohorts, remaining significant after adjustment for standard clinical variables. However, benchmarking revealed that the integrated signature, although superior to size-matched random gene sets (empirical p < 0.001), did not outperform a ferroptosis-only model (DeLong p = 0.81), indicating no measurable gain from pathway integration. Moreover, much of the prognostic signal reflected tumour proliferation rather than regulated cell death. After adjustment for the proliferation meta-signature (meta-PCNA), ferroptosis performance declined from 0.573 to 0.504, while the integrated model decreased to 0.554. High-risk tumours were more sensitive to anti-proliferative drugs, and the risk score was most strongly associated with E2F, MYC, and G2M target programmes. The signature stratified prognosis but did not predict immune-checkpoint blockade response in IMvigor210 (AUC {approx} 0.50). Importantly, the underlying biology was not merely a modelling artefact. Signature genes showed concordance with protein abundance in CPTAC cohorts, and the three cell-death programmes co-varied within individual malignant cells, with correlations ranging from {rho} = 0.46 to 0.66. Overall, our findings indicate that integrated multi-death signatures are reproducible and biologically grounded, yet prognostically redundant and substantially confounded by proliferation. This study provides a cautionary benchmark for the rapidly expanding use of composite regulated cell-death signatures in cancer prognosis.
]]></description>
<dc:creator><![CDATA[ Demir, A. Y., Yasar, E. ]]></dc:creator>
<dc:date>2026-06-30</dc:date>
<dc:identifier>doi:10.64898/2026.06.25.734481</dc:identifier>
<dc:title><![CDATA[A pan-cancer benchmark of integrated ferroptosis, cuproptosis and disulfidptosis prognostic signatures]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.25.734473v1?rss=1">
<title>
<![CDATA[
A gapless Landrace pig genome resolves centromeres and telomeres and highlights telomere repeat structures in different pig breeds 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.25.734473v1?rss=1
</link>
<description><![CDATA[
Abstract The Duroc-derived reference genome Sscrofa11.1 has provided a critical foundation for pig genomics, providing a high-quality reference genome for accurate variant detection and comparative genomics but does not capture breed-specific variation. Here, we present a near-complete, gap-free genome assembly for the Landrace pig (Landrace_v1, GCA_963921485.1), spanning all 20 chromosomes and totaling 2.6 Gb, including 176 Mb of sequence absent from Sscrofa11.1. Comparative analyses with recently published high-quality pig genomes reveal a conserved centromere organization across breeds, accompanied by substantial variation in repeat composition and length, and identify a pig specific pattern of telomere variant repeats across eight pig breeds. The improved resolution of repetitive regions in Landrace_v1 enables more complete reconstruction of complex gene families, including olfactory receptors, and uncovers structural variation at the KIT proto-oncogene receptor tyrosine kinase locus not represented in the Duroc reference. Together, these findings highlight the limitations of single-reference genomes and demonstrate the value of breed-specific assemblies for capturing genomic diversity and improving downstream analyses.
]]></description>
<dc:creator><![CDATA[ Grove, H., Stenlokk, K. S. R., Lien, S., Gjuvsland, A. B., Arnyasi, M., van Son, M., Kent, M. ]]></dc:creator>
<dc:date>2026-06-30</dc:date>
<dc:identifier>doi:10.64898/2026.06.25.734473</dc:identifier>
<dc:title><![CDATA[A gapless Landrace pig genome resolves centromeres and telomeres and highlights telomere repeat structures in different pig breeds]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://www.biorxiv.org/content/10.64898/2026.06.25.734236v1?rss=1">
<title>
<![CDATA[
Epigenetic signatures of infection within and across generations in the endangered Loggerhead sea turtle 
]]>
</title>
<link>
https://www.biorxiv.org/content/10.64898/2026.06.25.734236v1?rss=1
</link>
<description><![CDATA[
Infection can substantially reduce host fitness and influence population dynamics, yet it is often difficult to detect and quantify in wild animal populations. Molecular tools offer a valuable means of identifying cryptic infection in natural systems. Using whole-genome bisulfite sequencing, we examined whether infection with the parasitic leech Ozobranchus margoi is associated with DNA methylation variation in loggerhead sea turtles (Caretta caretta), while also assessing the potential value of this variation as a biomarker of parasite infection. In nesting females, we identified infection-associated differentially methylated CpG sites associated with genes implicated in immune signalling and cellular regulation. Offspring of infected females also showed infection-associated methylation patterns, despite not being directly exposed to the parasite themselves. Differential methylation analyses identified genes involved in immunity, neurodevelopment and metabolic activity, with limited overlap in associated genes and no overlap in differentially methylated sites between generations. Maternal and offspring genome-wide methylation levels showed a non-linear association that differed subtly with maternal infection status, indicating that infection modifies intergenerational methylation associations. Finally, methylation profiles showed strong discriminatory power for maternal infection status in both maternal and hatchling samples using machine learning models, supporting their potential as candidate biomarkers of cryptic infection. Together, these results show that parasite infection is associated with distinct, generation-specific DNA methylation signatures, and highlight the potential value of epigenetic data for monitoring cryptic infection states in conservation-relevant systems.
]]></description>
<dc:creator><![CDATA[ Bazely, J. O., Yen, E. C., Balard, A., Gilbert, J. D., Fairweather, K., Lopes, A., Taxonera, A., Rossiter, S. J., Eizaguirre, C. ]]></dc:creator>
<dc:date>2026-06-30</dc:date>
<dc:identifier>doi:10.64898/2026.06.25.734236</dc:identifier>
<dc:title><![CDATA[Epigenetic signatures of infection within and across generations in the endangered Loggerhead sea turtle]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory</dc:publisher>
<prism:publicationDate>2026-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
</rdf:RDF>
