Biology subjects

Chen, M.

Publications and source records attributed to Chen, M..

At least 127 records · Page 7Linked to original sources

bioRxiv2025

A Chromatin-Structure-Guided Framework for Predictive and Interpretable Regulatory Genomics

Chromatin organization shapes gene regulation by linking distal elements across megabase scales, yet most predictive genomics models still treat the genome as linear, without incorporating three-dimensional structure. Hi-C provides genome-wide chromatin conformation information, but its contact maps are population-averaged, distance-biased, and noisy, obscuring the biologically specific contacts. We present CHROME, a framework built on a self-avoiding polymer ensemble null model that identifies physically specific, non-random Hi-C contacts. By integrating these contacts into graph representations, CHROME enables efficient information transfer across spatially connected loci. It integrates sequence, chromatin accessibility, or pre-trained embeddings into a graph attention architecture to predict cell line-specific ChIP-seq profiles, consistently outperforming local encoder baselines and generalizing to an unseen cell line. The resulting graph embeddings also enhance prediction on tissue-specific eQTL and ClinVar variant pathogenicity, outperforming local sequence-based embeddings. Beyond predictive performance, CHROME provides interpretability through attention-derived neighbor-to-center contributions that reveal how spatially connected loci influence local regulatory activity over multi-megabase distances. Together, these results show that incorporating physically validated chromatin interactions enables more accurate and interpretable modeling of gene regulation and variant effects.

genomics↗

bioRxiv2025

Benchmarking Real-World Applicability of Molecular Generative Models from De novo Design to Lead Optimization with MolGenBench

Structure-based drug design (SBDD) has been profoundly reshaped by the advent of deep generative models, yet their practical impact on drug discovery remains limited. A central issue is the absence of a rigorous, application-oriented benchmark that mirrors the multi-stage, target-aware workflows of real-world pharmaceutical development. Inspired by recent advances in benchmarking for computer vision and large language models, where systematic evaluation has catalysed rapid progress, we introduce MolGenBench, a comprehensive benchmark designed to close the gap between molecular generation algorithms and tangible drug discovery outcomes. MolGenBench integrates a structurally diverse, large-scale dataset spanning 120 protein targets, 5,433 chemical series comprising 220,005 experimentally confirmed active molecules. Beyond conventional de novo generation, it incorporates a dedicated hit-to-lead (H2L) optimization scenario, which represents a critical phase in hit optimization that is seldom evaluated in existing benchmarks. We further introduce novel, pharmaceutically grounded metrics that assess a models ability to both rediscover target-specific actives or progressively optimize compounds for potency. Through extensive evaluation, MolGenBench uncovers significant gaps between current generative models and the demands of real-world drug development, establishing a foundational resource for building generative models with enhanced practical impact and accelerated translational potential.

bioinformatics↗

bioRxiv2025

Aversive Learning Induces Context-Gated Global Reorganization of Neural Dynamics in Caenorhabditis elegans

Learning generates experience-dependent changes to the brain. However, how neurons of diverse functions and connectivity reorganize and modulate their activities to generate coherent changes while preserving essential functions is not well understood. Here, we address this question using an aversive olfactory learning paradigm whereby Caenorhabditis elegans learns to reduce its olfactory preference for pathogenic bacteria. Using functional imaging during olfactory stimulation in naive and trained animals, we show that, at brain-wide scale, cell type-by-cell type, learning induces context-gated reconfiguration of the organization of neural activity throughout the brain to alter neural responses only during bacteria-discrimination task, while leaving intact bacteria-sensing functions. We found that the context-gated encoding of learning is globally distributed across layers of the nervous system, composed of neurons carrying information of context or learning experience. In particular, aversive training modulates multiple functional connections within the nervous system, including those between sensory neurons and interneurons, as well as those among interneurons, in a context-gated manner. At the systems level, training modulates correlated activity of neural populations; we found that low-dimensional temporal patterns of population activity correlate well with locomotory gaits that express olfactory preferences. Upon training, the rotation and contraction of the low-dimensional neural manifolds shifts the brain into predisposed states for the context-gated display of learned behavior. Because animals encounter unpredictable environments in life, efficient learning about relevant cues while maintaining other functions is essential for survival. Our findings uncover network-level mechanisms that help explain how the brain reorganizes its activity patterns to both encode new experience and preserve essential functions.

neuroscience↗

bioRxiv2025

Neural Substrates of Approach-Avoidance Control in Motivational Conflict

Adaptive behavior requires control over automatic tendencies to approach reward and avoid threat. Dysregulation of this control characterizes disorders such as anxiety or addiction, yet the underlying neural mechanisms remain unclear. Here, we investigated circuits engaged during approach-avoidance control using fMRI with concurrent eye-tracking, and behavioral measures. Forty participants (22 females) completed an approach-avoidance conflict task with free- and forced-choice trials. Each trial comprised anticipation, response (using a joystick to approach/obtain or avoid/forgo outcomes), and outcome phases. Before scanning, participants learned that conditioned stimuli (CS) predicted an aversive stimulation (avCS+), appetitive reward (appCS+), both outcomes (confCS+), or no outcome (neuCS-). Discordant responses (e.g., approaching avCS+) were slower than concordant responses (e.g., avoiding avCS+), confirming heightened control demands. Overcoming threat-driven avoidance specifically recruited the left inferior frontal gyrus (IFG), while suppressing reward-driven approach lacked distinct neural signatures. During anticipation, confCS+ and avCS+ showed overlapping activation in salience-control networks, including middle/anterior cingulate cortex (MCC/ ACC), anterior insula, IFG, and ventral striatum (VS). Interestingly, confCS+ evoked threat-like anticipatory neurophysiological responses (pupil dilation; ACC/insula activation) but subsequently triggered reward-like approach behavior. Multivariate pattern and psychophysiological interaction analyses revealed that this dissociation was driven by differential encoding of upcoming responses in the ventral striatum during the anticipation phase and by altered functional coupling between the VS and the right temporoparietal junction (rTPJ). These findings indicate that motivational control prioritizes salience over valence and suggest a VS-rTPJ network for resolving approach-avoidance conflicts, offering novel insights into neural dynamics of flexible goal-directed behavior. Significance StatementThis study advances our understanding of how the brain dynamically resolves conflicts between approaching rewards and avoiding threats. By measuring neural activity during approach-avoidance conflicts, our study identified overlapping neural circuits for threat and conflict processing (e.g., middle/anterior cingulate, ventral striatum). It revealed that threat-like neural responses to conflicting stimuli triggered approach behaviors resembling reward-motivated actions. Critically, connectivity between the ventral striatum and the temporoparietal junction predicted individual differences in conflict resolution, linking network-level interactions to adaptive behavioral control. These findings suggest salience overrides valence in motivational control and motivate hypothesis-driven tests of network disruption in psychiatric populations.

neuroscience↗

bioRxiv2025

Bacteriophages of the predominant coral symbiont Endozoicomonas: novel models for coral holobiont interactions

Phages are important symbionts in corals that modulate the community and functions of other symbiotic bacteria. Although phages infecting coral pathogens have been reported, no phage targeting beneficial microorganisms in corals has been isolated to date. From seawater near Acropora and Stylophora corals, we isolated the first bacteriophages (designated EmPhiA and EmPhiS) that infect Endozoicomonas montiporae CL-33, a model strain of the coral-prevalent and predominant Endozoicomonas bacteria. Electron microscopic observations of both phages showed Myovirus-like morphology and head sizes characteristic of jumbophages, with cryo-electron microscopy reveals long whiskers unprecedent in known phages. Genetically, these phages shared 99.21% genome similarity and are distant from known prokaryotic viruses, suggesting that they represent a novel viral species, which we name Encorevirus taiwanensis, in a novel family Encoreviridae. The small burst sizes of these phages (13.14 PFU/cell for EmPhiA and 21.4 PFU/cell for EmPhiS) potentially enable continuous coexistence of them with host bacteria within corals, making them putative core members of coral holobionts. Furthermore, host range test showed that EmPhiA and EmPhiS infect both Endozoicomonas bacteria isolated from stony and soft corals, implying their presence in a broad spectrum of host marine invertebrates. Using EmPhiS, we also investigated phage-bacterium interaction during its infection of E. montiporae CL-33. Interestingly, in addition to modulation of host cellular machinery, we found expression of several tellurium resistance proteins by EmPhiS during infection, which may provide the host additional stress resistance. These phages provide a novel model that will greatly advance our understanding of coral-Endozoicomonas-phage interactions.

microbiology↗

bioRxiv2025

RNA viruses in water shape the viromes of shrimp and fish in aquaculture systems

Aquatic environments host immense RNA viral diversity, yet the extent to which waterborne viruses influence the virome of aquatic animals remains unclear. Here, we conducted a comprehensive longitudinal metatranscriptomic analysis of water, shrimp, and fish across multiple culture stages in aquaculture systems. We identified 3,211 RNA viruses spanning 21 viral supergroups, with 97.4% representing novel species. Water exhibited the greatest viral diversity (3,093 species), followed by shrimp (1,280) and fish (398), with most viruses detected in shrimp and fish also detected in water. Diversity analyses revealed increasing richness and significant compositional shifts in 92 high-abundance viruses (>1,000 RPM) across culture stages. Viral abundance in aquatic animals was strongly correlated with that in water, and the temporal trajectories of the 16 most abundant viruses were closely synchronized between water and shrimp. Furthermore, 337 virus species were shared among shrimp and two fish species, of which 309 were present in water. These findings demonstrated that RNA viruses in water shape the composition and dynamics of aquatic animal viromes, underscoring the importance of water virome surveillance and management for disease prevention in shrimp aquaculture.

microbiology↗

bioRxiv2025

Global Insights into Evolution and Adaptation in KPC and NDM Coproducing Carbapenem-Resistant Klebsiella pneumoniae.

ObjectivesThe worldwide dissemination of carbapenem-resistant Klebsiella pneumoniae co-producing KPC and NDM (KPC-NDM-CRKP) poses a substantial clinical challenge. MethodsThis study characterized 5 KPC-NDM-CRKP isolates from a tertiary hospital in southern China and integrated 460 global isolates genomes to demonstrate the population framework of this epidemic pathogen. Results5 clinical isolates were multidrug resistance, exhibiting high level resistance to first-line drugs including carbapenems and ceftazidime/avibactam. Globally, KPC-2-NDM-1 (50.3%) were the most common and an increasing trend of ST11-KL64 (20%) isolates carrying iucA and rmpA/A2. Resistance and virulence genes were positively associated with specific mobile elements including blaKPC-3 with Tn4401, iucABC with IncHI1B, iroBCDN with IncQ1. The phylogenetic analysis revealed distinct lineage-specific mutations and pan-genome enrichments synergistically promoted adaptive evolution: cluster 1 had membrane transport and secretion but enhanced immune evasion and horizontal gene transfer, cluster 3 adapted metabolically for nutrient-limited niches; cluster 4 reprogrammed metabolism for host adaptation, cluster 6 displayed membrane repair and reduced virulence (e.g., KC187). High-risk iucA/rmpA-positive isolates in cluster 2 acquired enhanced virulence and metabolic adaptive capacity through recombination hotspots (ABC transporters DdpABCD, efflux systems MdtABCD, metabolic enzymes XylB and MtlD, regulators BaeR and OmpR) and pan-genome enrichment (siderophore biosynthesis, toxin-antitoxin VapC and restriction-modification systems). Functionally, these traits correlated with high mucoviscosity, serum resistance, siderophore production and lower survival rates in G. mellonella that contribute to epidemiological success. ConclusionsThese findings demonstrated the discrete mutation, horizontal transfer, and accessory genome plasticity collectively drove the epidemiological success of KPC-NDM-CRKP.

microbiology↗

bioRxiv2025

A spatially-resolved human brain proteome atlas for understanding function and disease

While the brain performs specialized functions across distinct regions, the spatial organization of the human brain proteome remains largely uncharted. Here we present a comprehensive spatially-resolved proteome atlas of the human brain, analyzing over two thousand MRI- guided locations across four individuals. Proteome analysis integrated with transcriptomics reveals extensive post-transcriptional regulation, with cortical regions showing markedly higher protein diversity than transcript. Unsupervised molecular clustering defines distinct brain territories that transcend anatomical boundaries, instead reflecting metabolic demands and functional specialization patterns. Application to epilepsy brain tissue uncovered disrupted astrocyte metabolism, protein homeostasis and therapeutic targets including the seizure-associated purinergic receptor P2RX7. This resource bridges molecular and systems neuroscience to accelerate neurological drug discovery.

neuroscience↗

bioRxiv2025

Climate-Driven Ecosystem Productivity Changes Restructure Food Systems

Climate change affects food systems through multiple pathways, yet the isolated effects of climate-driven ecosystem productivity changes remain poorly understood. While field studies translate productivity changes to crop yields, at larger scales yield conflates productivity with management and technology, and critically, productivity changes occur across all vegetation types, not just agricultural lands. We isolate ecosystem productivity changes to trace their propagation through food systems across three socioeconomic scenarios (SSP1-2.6, SSP3-7.0, SSP5-8.5) by coupling the CLASSIC land surface model with GCAM integrated assessment model. Productivity changes lead to crops systematically shifting from human consumption to animal feed and bioenergy (up to 15% reallocation), while there is a significant transition of managed agricultural lands to unmanaged lands by up to 6 million km2 as productivity gains enable less intensive land use. These changes drive extreme regional divergence, with food production volume changing from +35% to -28% and substantial portfolio reorganization. Disruptions peak under regional rivalry (SSP3-7.0), revealing how fragmented governance amplifies biophysical feedbacks beyond climate forcing alone. While how much we eat may remain stable, ecosystem productivity fundamentally reshapes what we eat and where to source it.

ecology↗

bioRxiv2025

Evaluation of computational tools for predicting CRISPR gRNA on-target efficiency in plants.

CRISPR technologies has become an integral part of plant biotechnology, synthetic biology and basic plant research, routinely used by researchers for targeted genome modifications. CRISPR guide RNAs (gRNAs) undermines the highly programmable nature of CRISPR, enabling site-specific genome editing. However, different gRNA targets showed highly variable on-target effectiveness and poor gRNA design could amount to wasting valuable scientific resources. There has been broad development of computational and web-based tools for gRNA efficiency predictions but their performances in plant genome editing remains controversial or untested. Hence, in this study, we systematically evaluated over 20 accessible, web-based in silico gRNA on-target efficiency prediction tools using an experimental plant genome editing dataset. Excitingly, we identified multiple tools, mostly developed using machine learning, that were highly predictive of gRNA on-target genome editing efficiency in planta. The prediction scores assigned to gRNAs in the dataset by these tools were significantly correlated with the frequency of CRISPR-mediated InDels in plants. Furthermore, we evaluated efficiency prediction scores available on popular platforms such as CRISPOR and CRISPR-P which contain large numbers of non-model plant genomes. Our analysis showed that some prediction scores on CRISPOR performed quite well which allows efficient integration of on-target and off-target predictions. Overall, we believe that our study provided insights on improving gRNA design during conventional plant genome editing workflows and should also help unfamiliar researchers interested in CRISPR/SpCas9 genome editing.

plant biology↗

bioRxiv2025

A Population-scale Single-cell Spatial Transcriptomic Atlas of the Human Cortex

The genetic and spatial determinants of cell type diversity in human cerebral cortices remain poorly defined. Here, we present a population-level single-cell spatial transcriptomic atlas of human cortices from 71 donors across the lifespan. We identified 906 layer-specific genes showing conserved and divergent laminar expression patterns between humans and other species. Spatial analysis revealed neuronal vulnerability and glial activation during aging, together with a decline in the proportion of superficial SST neurons and their interactions with other cells. Disease-associated genes exhibited high cell-type and layer-specific expression, implicating the pathogenic role of spatially specific gene expression. Spatial cis-eQTL analysis identified regulatory variants linked to genes related to diseases like Tourette syndrome. Cross-species comparison demonstrated glial expansion in the human cortex, accompanied by enhanced neuron-glia communication via the neuregulin signaling. Together, we provide a comprehensive single-cell atlas of the human cortex that is essential for understanding aging, evolution, and disease pathogenesis.

neuroscience↗

bioRxiv2025

Prolactin links psychological stress to psoriasis via a fibroblast-chemokine pathway

Psoriasis is a chronic inflammatory skin disease that forms a vicious cycle with psychological stress. Whether and how the hypothalamic-pituitary (HP) axis-mediated neuroendocrine system regulates psoriasis remains obscure. Here, we report elevated levels of the pituitary hormone prolactin (PRL) in both psoriasis patients and imiquimod (IMQ)-induced psoriasis mice. Mechanistically, PRL acts on dermal PRLR-expressing fibroblasts to promote the production of the chemokines CCL2 and CCL7, which then recruit monocytes/macrophages into psoriatic lesional skin, thereby activating local IL-17A-producing T cells. Accordingly, pharmacological targeting of PRL signaling inhibits the recruitment of monocytes/macrophages, decreases the frequency of IL-17A-producing T cells, and alleviates IMQ-induced psoriasis in mice. In summary, our results delineate a mechanism by which the neuroendocrine hormone PRL aggravates psoriasis and highlight a potential therapeutic strategy of inhibiting PRL-PRLR signaling, particularly in psoriasis patients experiencing psychological stress.

immunology↗

bioRxiv2025

Machine learning-based definition of cellular senescence reveals pro-senescence potential implication in lung adenocarcinoma

Despite growing evidence implicating cellular senescence in tumor progression, methodological challenges in objectively quantifying senescent cell burden across cancer types continue to limit mechanistic studies and clinical translation. To address this, we developed the Predictive Cellular Senescence Model (PreCSenM), a machine learning-based tool that assigns a CS score by integrating senescence-associated features across 888 samples. Benchmarking analyses confirmed that PreCSenM markedly outperforms existing methodologies in reliably predicting senescent states within both normal and cancerous transcriptomic datasets. In lung adenocarcinoma (LUAD), PreCSenM identified the CS score as a robust predictor of clinical outcomes. Multi-omics analyses further revealed that lower CS levels correlate with decreased genomic stability and enhanced immune responses, aligning with clinical observations. Notably, drug discovery using PreCSenM identified histone deacetylase inhibitors (HDACis) as potent inducers of CS in LUAD. Transcriptional and epigenetic profiling of HDACi-treated cells pinpointed FOSB as a core transcription factor driving CS, and FOSB knockdown blocked HDACi-induced senescence. Overall, our study establishes PreCSenM as a multidimensional senescence quantification tool, bridging computational prediction with clinical relevance and mechanistic validation to enable senescence-directed therapies in precision oncology.

bioinformatics↗

bioRxiv2025

Kingdom-wide evolutionary characterization of RNA editing factors in Archaeplastida

RNA editing, a post-transcriptional modification in plant mitochondria and plastids, is essential for environmental adaptation and diverse physiological processes. Despite extensive identification of RNA editing factors, primarily including pentatricopeptide repeat (PPR), multiple organelle RNA editing factor (MORF), organelle RNA recognition motif-containing (ORRM), and organelle zinc finger (OZ) proteins, their evolutionary history remains poorly understood. Here, we perform kingdom-wide evolutionary analyses across 364 high-quality Archaeplastida genomes and find massive PPR gene expansions in early-diverging land plants, predominantly driven by dispersed duplication associated with retroposition. Furthermore, integrative analyses indicate that DYW subgroup PPR genes have been horizontally transferred from plants to bdelloid rotifers, potentially enhancing the recipients adaptation to ultraviolet radiation. MORF proteins, accessory partners of PPRs, possess MORF hallmark domains structurally similar to protein-folding peptidase S8 propeptide/proteinase inhibitor I9 domains, suggesting a role in protein folding during RNA editing. Considering diverse domain compositions, we reclassify MORF, ORRM, and OZ proteins and uncover prevalent hallmark domain fusions. Together, these findings illuminate the kingdom-wide evolution of plant RNA editing machinery.

evolutionary biology↗

bioRxiv2025

Optogenetic construction of de novo integrin-adhesion complexes reveals role for biocondensation in adhesion nucleation

Integrin-adhesion complexes (IACs) form spontaneously in cells on extracellular matrix substrates, allowing them to sense matrix composition and transduce force. However, IACs often do not form uniformly across a cell, which begs the question: What is required to nucleate an adhesion, and what factors enable the stabilization of an IAC once it has formed? Many factors have been suggested to promote formation and the subsequent stabilization of IACs. It is difficult to explicitly test these factors in vivo as IACs undergo constant remodeling. Here, we employ optogenetics to explicitly test the ability of talin in different activity and phase states to nucleate and stabilize IACs in regions where none are present. We find that fusion of intrinsically disordered regions directly to talin enhances its adhesion nucleation potential and allows new adhesions to be produced in response to optogenetic talin clustering. Similarly, expression of factors previously shown to enhance biocondensation in vitro, such as paxillin, the paxillin N-terminus, or unfolding of talin, allows for adhesion nucleation and biocondensation of talin. We show that these biocondensates of talin can cluster and activate integrins even in the absence of extracellular matrix. By applying optogenetic activation to regions of the cell with or without ventral actomyosin, we demonstrate actomyosin engagement promotes the formation and stability of adhesions. These results are corroborated by theoretical modelling which shows that phase separation of talin is enhanced by differential clutch formation in the presence of actomyosin thus enabling peripheral adhesion formation and stability. This work establishes a model in which increased cooperativity of talin enables IAC nucleation through talin biocondensation, which clusters and activates integrins. In addition to these findings, we generate multiple optogenetic tools that enable local nucleation or enhancement of IACs. HighlightsO_LIOptogenetic tools mediating talin biocondensation can locally induce focal adhesion formation C_LIO_LIPaxillin LD domains enable biocondensation of talin C_LIO_LIBiocondensation of talin enables IAC formation C_LIO_LIPhase separation of talin can activate integrins independently of ECM C_LIO_LIComputational model reconciles spatial variance in LLPS and IAC formation. C_LI

cell biology↗

bioRxiv2025

Molecular signature of neutrophils in antiphospholipid syndrome based on epigenomic and transcriptome analysis

BackgroundAntiphospholipid syndrome (APS) is an autoimmune disorder characterized by thrombosis and pregnancy loss. Recent studies indicate that neutrophils, particularly neutrophil extracellular traps (NETs), contribute to the development and progression of APS. However, the precise underlying mechanisms remain unclear. MethodsTo address this, we analyzed epigenome and transcriptome data to identify key differentially expressed genes (DEGs) of neutrophils in APS using weighted gene co-expression network analysis (WGCNA). Two datasets (GSE102215 and GSE124565) were obtained from the GEO database. The Limma R package was used to identify DEGs, while ChAMP R was applied to analyze differentially methylated genes (DMGs) between APS patients and healthy controls. Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed using ClusterProfiler, and TISIDB was used to examine associations with immunomodulators, chemokines, and receptors. GeneCards and Connectivity Map databases were further used for disease-related gene analysis and drug prediction. ResultsGO enrichment analysis revealed that DEGs were primarily enriched in leukocyte cell-cell adhesion, regulation of leukocyte cell-cell adhesion, and cytokine-mediated signaling pathways. Correspondingly, KEGG enrichment analysis demonstrated that DEGs were mainly enriched in the ribosome, NF-kB signaling pathway, NOD-like receptor signaling pathway, and other related pathways. Through WGCNA analysis, we identified two key intersection genes, CCL5 and ITK, which were positively correlated with CD8+ T cells and eosinophils, while being negatively correlated with neutrophils and follicular helper T cells. Gene set enrichment analysis (GSEA) indicated that CCL5 was enriched in hematopoietic cell lineage, ribosome, and ribosome biogenesis in eukaryotes, and ITK was enriched in ribosome, ribosome biogenesis in eukaryotes, and T-cell receptor signaling. Similarly, gene set variation analysis (GSVA) showed that CCL5 and ITK were associated with IL-2-STAT5 signaling and the P53 pathway as well as MTORC1 signaling. Furthermore, gene regulatory network analysis suggested that CCL5 and ITK are modulated by common mechanisms involving multiple transcription factors. By examining APS-related genes in the GeneCards database, we observed a significant negative correlation between CCL5 and phosphatase and tensin homolog (PTEN) (R = -0.624), and a strong positive correlation between ITK and CD40LG (R = 0.933). Finally, drug perturbation expression profiles revealed that RS-56812, acebutolol, emetine, and proscillaridin exhibited the most significant negative correlation with disease-associated expression profiles. ConclusionThese data nominate CCL5 and ITK as APS-associated genes in neutrophils and indicate associations with multiple signaling pathways. Moreover, drugs targeting these genes may represent potential therapeutic strategies for APS.

immunology↗

bioRxiv2025

Hippo/YAP1 Signaling Regulates the Oligodendrocyte-Astrocyte Fate Switch and Ependymal Gene Expression in Adult Spinal Cord Stem Cells

The adult mammalian spinal cord harbors ependymal cells that retain neural stem-cell properties. Although they possess a latent capacity to generate oligodendrocytes, these cells predominantly differentiate into astrocytes after injury. The molecular cues that govern their lineage commitment toward astrocytic versus oligodendroglial fates remain poorly defined. In this study, we addressed this gap in vitro by investigating the emergence of PDGFRA oligodendrocyte precursor cells (OPCs) in neurosphere cultures derived from adult spinal cord stem cells. We first observed that neurosphere cells exhibited a hybrid identity, co-expressing transcription factors of both astrocytic (NFIA, SOX9) and oligodendrocytic (OLIG1/2, SOX4, NKX2.2, TCF4) lineages. Upon differentiation, oligodendrocytic transcription factors were selectively maintained in OPCs but reduced in other cells. Using PdgfraH2B-GFP mice, we then isolated newly formed PDGFRA OPCs from neurospheres and performed multi-omic profiling. OPC formation was associated with the upregulation of chromatin remodelers and the downregulation of stem-cell markers such as EGFR, HES1, and TNC. Strikingly, OPC specification coincided with reduced expression of YAP1 and its partner TEAD1, key effectors of the Hippo pathway. Functional analyses revealed that YAP1 loss enhanced oligodendrocytic differentiation while reducing astrocytic and ependymal/cilia-associated gene expression. Conversely, constitutive YAP1 activation blocked differentiation into both lineages and promoted an ependymal-like transcriptional program, including upregulation of the ependymal marker CD24a and cilia-related proteins such as CROCC (Rootletin). Collectively, these findings uncover previously unrecognized roles for YAP1 in adult spinal cord stem-cell fate decisions and provide a molecular framework for leveraging these cells in regenerative strategies targeting spinal cord repair.

cell biology↗

bioRxiv2025

Hi-GREx: A 3D Genome Guided Framework for enhancing Gene Expression Prediction Using Hi-C Selected Distal SNPs

Genome-Wide Association Study (GWAS) method has been successfully used to map thousands of loci associated with complex traits, but its ability to reveal the molecular mechanisms altered in complex diseases has been limited due to not including combinations and interactions between markers when predicting a disease. Transcriptome-Wide Association Studies (TWAS) estimate the aggregate effects of multiple genetic variants on complex diseases and represent a promising approach to address the limitations of GWAS. In particular, TWAS provides insights into the functional consequences of disease-associated SNPs by linking them to gene transcription, thereby offering a mechanistic understanding that GWAS alone cannot provide. However, TWAS associated variants have been annotated with the closest or most biologically relevant candidate gene within arbitrarily defined distances but fails to account for long distance SNPs which can affect many genes and have a widespread impact on regulatory networks. Therefore, there is a need to leverage these observed enrichments and build a method that incorporates both short and long distance-associations between SNPs and complex phenotypes. Here we present a method which can utilize Hi-C data to capture "informative" long-distance SNPs and aim to improve prediction accuracy of previous TWAS method. We benchmarked our method on GTEx brain cortex genotype and expression data together with the corresponding Hi-C data. By using the "informative" long distance SNPs selected based on Hi-C, our method improved prediction accuracy of gene expression for 77.4% of the active genes across the entire genome. Particularly, our method can build significant expression models for 18% of genes which were missed by using only short-distance SNPs. Our method has demonstrated the efficiency and importance of utilizing long-distance SNPs in predicting gene expression and can further enhance the power of TWAS methods.

bioinformatics↗