Biology subjects

Zhou, H.

Publications and source records attributed to Zhou, H..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

A programmable mRNA platform for miRNA detection via miRNA-mRNA2 triplex-mediated ribosomal frameshifting

Programmed -1 ribosomal frameshifting (-1 PRF) is a recoding mechanism utilized by viruses to expand their coding capacity and modulate the stoichiometric ratio of -1 frame and 0 frame translation products. The stability of mRNA secondary structure at the ribosomal entry site within the frameshifting stimulating elements (FSEs) determines the frameshifting efficiency. Here, we report the development of a programmable mRNA-based platform that detects specific mature microRNA (miRNA or miR) by converting their presence into a quantifiable protein output through miRNA-triggered -1 PRF. We designed a triplex-forming mRNA (TF-mRNA) platform to selectively trap target miRNAs through the formation of major-groove mRNA-miRNA-mRNA (miR-mRNA2) triplexes. Bio-layer interferometry and fluorescence binding studies confirmed that TF-mRNA forms stable complexes with cognate miRNAs with low nanomolar affinity and prolonged dissociation rate. Critically, the formation of miR-mRNA2 triplex robustly stimulated ribosomal frameshifting in a cell-free dual-luciferase translation system, acting as a miRNA-dependent molecular switch. The generality of this TF-mRNA platform has been verified for several disease-associated purine-rich miRNAs, and it is suitable for targeting a wide range of other purine-enriched miRNAs. This programmable TF-mRNA platform establishes a foundation for developing novel diagnostic tools and synthetic biology circuits that convert the presence of miRNA into a quantifiable protein output. TOC Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/690164v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1d6d9f7org.highwire.dtl.DTLVardef@8008e6org.highwire.dtl.DTLVardef@1c8344borg.highwire.dtl.DTLVardef@e153ec_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

SpaTRACE: Spatiotemporal recurrent auto-encoder for reconstructing signaling and regulatory networks from spatiotemporal transcriptomics data

Cell-cell communication and gene regulatory programs jointly coordinate cellular behaviors during development, regeneration, and disease. Recent advances in spatial transcriptomics enable measurement of gene expression with spatial context across developmental trajectories, providing new opportunities to study dynamic signaling and regulatory processes. However, most existing methods analyze either ligand-receptor (LR) signaling or gene regulatory networks (GRNs) separately, rely on curated interaction databases, and often assume steady-state gene expression, limiting their ability to capture temporal regulatory dynamics and discover novel interactions. We present SpaTRACE, a spatiotemporal recurrent autoencoder framework for joint inference of intercellular signaling and gene regulatory networks from spatial transcriptomics data. SpaTRACE models time-lagged dependencies along pseudotime-sampled cellular trajectories using an attention-based encoder-decoder architecture that predicts future target gene expression from upstream intra- and intercellular signals. The learned attention structure enables simultaneous reconstruction of transcription factor-target gene (TF-TG) regulatory interactions, ligand-receptor-target gene (LR-TG) signaling pathways, and ligand-receptor binding relationships without requiring predefined LR databases. Across synthetic benchmarks, SpaTRACE accurately recovers both GRN and signaling interactions and outperforms existing GRN and cell-cell communication inference methods. Applications to mouse midbrain development reveal transcriptional regulators and signaling programs associated with neuronal differentiation, while analysis of axolotl brain regeneration identifies stage-specific signaling dynamics and candidate interactions involved in tissue repair. Availability: Source code and documentation are available at https://github.com/VariaanZhou/SpaTRACE.

bioinformatics↗

bioRxiv2025

Hidden-driver inference reveals synergistic brain-penetrant therapies for medulloblastoma

Effective therapies for high-risk medulloblastoma (MB), particularly MYC-driven Group 3 (G3) MB, remain elusive due to limited druggable mutations, poor blood-brain barrier (BBB) penetration, and rapid resistance. We developed SINBA (Synergy Inference by Data-driven Network-Based Bayesian Analysis), a systems biology framework that computationally prioritizes synergistic, BBB-permeable drug combinations by identifying hidden drivers sustaining oncogenic programs. Integrating MB-specific networks, transcriptomic data, and drug-gene interactions, SINBA nominated 32 candidates, of which 19 were experimentally validated as synergistic. Through iterative prioritization and experimental refinement, the MEK inhibitor mirdametinib and p38 inhibitor regorafenib emerged as the top brain-penetrant pair, suppressing G3 MB progression and extending survival in xenograft and immunocompetent models, with efficacy enhanced by low-dose radiation. Single-cell analysis revealed selective targeting of developmental origins and immune reprogramming. These findings establish SINBA as a computationally assisted discovery framework for clinically actionable combinations in high-risk MB.

cancer biology↗

bioRxiv2025

Near-atomistic simulations reveal the molecular principles that control chromatin structure and phase separation

Understanding how chromatins physicochemical properties shape its emergent organisation is central to deciphering genome function. To address this, we present OpenCGChromatin, a high-performance coarse-grained model that achieves near-atomistic simulations of chromatin systems an order of magnitude larger than previously possible, spanning biomolecular condensates and fibers tens of kilobases in length. OpenCGChromatin simulations independently predict, from physicochemical principles, the linker-DNA-dependent chromatin structures observed by cryo-ET and the relative thermodynamic stability of condensates inferred from biochemical assays. Crucially, OpenCGChromatin resolves histone-tail dynamics and interaction networks that remain inaccessible experimentally, explaining how linker-DNA length controls histone tail accessibility and the resulting multiscale structure of chromatin condensates. Extending simulations to 108-nucleosome fibers shows that acetylation disrupts chromatin compaction in a pattern-specific manner by weakening key tail-mediated interactions, with H4K16 and H3K9 emerging as the most energetically disruptive modifications. These results position OpenCGChromatin as a powerful framework for linking molecular detail to emergent chromatin organization.

biophysics↗

bioRxiv2025

Host EV derived lipids promote malaria parasite development via mosquito fatty acid oxidation

Malaria parasites must transition between mammals and mosquitoes, but how they adapt to such distinct environments is unclear. We show that blood from infected mammals buffers this environmental shift by packaging parasite-induced signals into extracellular vesicles (EVs). EVs internalized by mosquito midgut increases expression of VLCAD and raises levels of a 22-carbon fatty acid, driving fatty acid breakdown and acetyl-CoA production. The parasite exploits this metabolic shift to synthesize its own lipids during oocyst growth. Stable isotope tracing confirmed that13C4-labelled behenic acid is degraded and incorporated into parasite fatty acids. Lipidomic profiling further revealed that ceramides enriched in the EVs are key mediators. These findings identify a mechanism by which host bood-derived EVs reprogram mosquito lipid metabolism to promote parasite transmission.

microbiology↗

bioRxiv2025

GlueFinder: A Data-Driven Framework for the Rational Discovery of Molecular Glues

Molecular glues can drive targeted protein degradation by stabilizing ternary complexes between proteins of interest and E3 ubiquitin ligases, but rational design has lagged due to limited rules for interface recognition and an overreliance on a few ligases (e.g., VHL or Cereblon). We introduce GlueFinder, a systematic, unbiased platform that leverages structural bioinformatics to mine the Protein Data Bank for ligand binding pockets adjacent to the protein interface which are ligandable sites near protein-protein interfaces that can nucleate glue-mediated complex formation. After validating its performance on a benchmark of experimentally solved dimeric structures with known and predicted glues, we applied GlueFinder to three therapeutically important targets, EGFR, HER2, and KRAS, and predicted candidate glues that recruit 24, 111, and 148 distinct E3 ligases to these targets, respectively. We further demonstrate that GlueFinder can promote the formation of non-native EGFR complexes, possibly enabling ternary assemblies that would not form on their own. Together, these results establish a general, computation-guided strategy for molecular glue discovery that decouples design from legacy degrader scaffolds and specific ligase dependencies, expands the usable E3 ligase repertoire, and enables rational targeting of interfacial binding pockets. GlueFinder thus broadens both the scope and precision of targeted protein degradation and moves the field toward mechanism-driven, systematic glue development across diverse therapeutic contexts. SignificanceMolecular glues are small molecules that destroy disease-causing proteins by helping them attach to cellular disposal machinery. However, current glue discovery depends on a few known ligases and lacks clear design rules. GlueFinder provides a general, computation-guided method that scans protein structures to find pockets near interfaces where glues can act. Applied to key targets such as EGFR, HER2, and KRAS, it predicts glues that connect many different ligases and even create new protein complexes. By revealing where and how glues can work, GlueFinder expands the range of degradable proteins and accelerates the rational design of future therapeutics.

bioinformatics↗

bioRxiv2025

Effective repurposed antivirals against an emerging virus

The ongoing global monkeypox virus (MPXV) outbreak urgently needs effective medications, which be accelerated through drug repurposing. However, it is challenging to poinpoint protein targets. Here we introduce a novel method rooted in molecular evolutionary theory for quick drug target identification for MPXV. It identifies drug targets as positively selected genes of viral proteins which bind host proteins. From the identified targets, we select a top gene product OPG021 for virtural drug screening. One top-ranked drug nilotinib is experimentally shown to have a significant 69% of antiviral efficacy of the FDA-approved antiviral tecovirimat (TPOXX(R) or ST-246). Higher binding affinity but not antiviral efficacy of repursposed drugs than FDA-approved drugs suggests the complexity of drug repurposing and underscores the importance of experimental validation. This innovative drug target identification strategy will contribute to combating the ongoing MPXV outbreak and other viral acute and chronic viral diseases.

pathology↗

bioRxiv2025

The Spirogyra genome: signatures of shared and divergent division and differentiation

Zygnematophytes emerged as the unexpected closest algal relatives of land plants despite their simple body plans, raising questions about the morphogenetic toolkit present in the last common ancestor of land plants and algae. Genomic analyses have revealed that zygnematophytes are cellular giants, sharing homologous frameworks for several phytohormones, secondary metabolites, and key morphogenetic and transcriptional regulatory processes. Zygnematophytes fall into five orders, each of which has charted its own evolutionary path. Here, we have sequenced a contiguous genome of Spirogyra pratensis, the eponymous representative of Spirogyrales and a classical model system for evolutionary cell biology in the green lineage. Building on this genome, we transcriptionally profiled the tractable life cycle of Spirogyra and its responses to a bifactorial gradient of light and temperature. Our data highlight the activation of quiescence and homeostatic programs. Yet what stands out most in Spirogyra is its spiral chloroplast--undulating intracellularly and abscising during mixed phragmoplast formation and furrowing. Leveraging the genome in tandem with co-expression network analyses, we describe the molecular underpinnings of the unique cytokinetic processes that govern both cell and plastid division. We find that Spirogyra deploys a molecular program characteristic of Phragmoplastophyta, yet lacks the deeply conserved plastid division machinery found in other archaeplastid plastids.

plant biology↗

bioRxiv2025

Water body size shapes body size evolution via subgenomic selection in allopolyploid fish

Allopolyploidization is a major force in species evolution, and studying allopolyploids in diverse environments provides insights into their genetic mechanisms. Here, we investigated how water body size variation influences body size in allopolyploid fish. We used a nascent allopolyploid lineage derived from goldfish (Carassius auratus) and common carp (Cyprinus carpio) and established two populations in small and large water bodies for two generations. Genomic, transcriptomic, and epigenomic analyses revealed that the larger population had higher genetic diversity in subgenome R, while the smaller population had higher diversity in subgenome C. Potential selection regions were associated with growth regulatory genes, suggesting a role for gene regulation in body size adaptation. Dynamic gene expression patterns in various tissues indicated potential mechanisms underlying muscle development and adaptation to smaller water bodies. Furthermore, selection regions were linked to changes in chromatin accessibility, with subgenome R being more susceptible to these changes during genetic divergence. Our findings demonstrate that water body size variation drives body size in allopolyploid fish through subgenomic selection, impacting genetic variation, gene regulation, and epigenetic mechanisms.

genomics↗

bioRxiv2025

Overcoming impaired antigen presentation in tumor draining lymph nodes facilitates immunotherapy

Immunotherapies have revolutionized cancer care in recent decades, but approved therapies often fail and currently only target specific steps in the generation of anti-cancer immune responses. Notably, the majority of approved immunotherapies do not target antigen processing and presentation, which are key steps in the development of immune responses and harbor potential as targets to improve immunotherapy. Here, we demonstrate that breast tumors induce locoregional lymph node impairment in antigen presentation--but not in antigen processing--which limits anti-cancer antigen- specific T cell responses. Inhibition of the locoregional T cell response was due to a tumor-mediated reduction of the cytokine IL1{beta} in tumor draining lymph nodes, which impaired antigen presentation. Further, we tested the ability of dendritic cells in lymph nodes at various distances from the primary tumor to be activated utilizing an antigen- agnostic adjuvant delivery strategy. We observed improved anti-tumor T cell responses when the adjuvant was delivered to cancer antigen-positive lymph nodes distant from the tumor, suggesting these lymph nodes can be targeted to improve anti-cancer immune responses. When combined with immune checkpoint blockade, delivery of the adjuvant to distant lymph nodes led to long-term survival and protection from recurrence. Antigen presentation and T cell responses could also be recovered by exogenous delivery of IL1{beta} via intratumoral injection, with improved survival when combined with immune checkpoint blockade. Our study demonstrates that tumor- induced locoregional impairment of antigen presentation can be overcome by the appropriate introduction of immunological adjuvant to tumor-distant lymph nodes or by restoring IL1{beta} to the tumor-draining lymph node. These strategies can induce high- quality, durable immune responses and have clinical implications for expanding the efficacy of immunotherapies. SummaryBreast tumors induce locoregional lymph node impairments in antigen presentation, which can be remedied via either IL1{beta} delivery or antigen-agnostic adjuvant therapies to distant lymph nodes, facilitating better immunotherapy responses.

cancer biology↗

bioRxiv2025

SpaPheno: Linking Spatial Transcriptomics to Clinical Phenotypes with Interpretable Machine Learning

Linking spatial transcriptomic data to clinically relevant phenotypes is essential for advancing spatially informed precision oncology. Here, we present SpaPheno, an interpretable machine learning framework that integrates spatial transcriptomics with clinically annotated bulk RNA-seq to identify spatially resolved biomarkers predictive of patient outcomes, including survival, tumor stage, and immunotherapy response. SpaPheno provides multi-scale interpretability from tissue regions to cell types and individual spatial spots, enabling clear biological insights from complex spatial data. We validate SpaPheno through extensive simulations and applications to multiple cancer cohorts--primary liver cancer, clear cell renal cell carcinoma, breast cancer, and melanoma--demonstrating robust predictive performance alongside biologically meaningful spatial patterns. SpaPheno offers a generalizable strategy to translate spatial omics data into clinically actionable knowledge, facilitating precision oncology informed by tumor spatial architecture.

bioinformatics↗

bioRxiv2025

Phosphorylation enables progressive microtubule-associated protein proteolysis and functionalisation during neural development

Neurological diseases are frequently characterised by dysregulation of the microtubule cytoskeleton, which is critical for neuronal integrity and functioning. However, the precise mechanisms by which microtubule dynamics are regulated during the development of the nervous system remain poorly understood. Here, we use global phosphoproteomic screening to identify cytoskeletal substrates of Ser-Arg Protein Kinase (SRPK), which is implicated in several neurodevelopmental and neurodegenerative conditions. We show that SRPK directly phosphorylates Microtubule Associated Protein (MAP)1S at multiple sites in a C-terminal region involved in proteolytic maturation and microtubule binding. SRPK-dependent MAP1S phosphorylation modulates the affinity of the MAP1S microtubule binding domain for microtubules and MAP1S proteolytic processing by the Calpain (CAPN)10 protease. Finally, we show that MAP1S proteolytic processing occurs progressively during neurodevelopment via a specific CAPN10 expression switch, corresponding with MAP1S acquisition of microtubule binding activity. Our results demonstrate a role for SRPK in coordinating processing and functionalisation of a key microtubule regulatory protein during neurodevelopment and provide insight into mechanisms by which the microtubule cytoskeleton may be dysregulated in neurological diseases.

biochemistry↗

bioRxiv2025

The two-component nuclease-active KELShedu system confers broad antiphage activity via abortive infection

Bacteriophages and bacteria engage in a continuous evolutionary arms race, driving the development of intricate bacterial defense systems such as CRISPR-Cas, BREX, Gabija, and Shedu. Here, we characterize a two-component KELShedu system in Escherichia coli that confers resistance to phages via abortive infection. The KELShedu system comprises KELA, a dsDNA-binding protein, and KELB, a metal ion-dependent nuclease harboring the DUF4263 domain. In addition, we find that physiological levels of NTP inhibit the DNA cleavage activity of the KELShedu system, suggesting that KELShedus activation depends on reduced intracellular NTP levels during phage invasion. Our research demonstrates that the KELShedu system responds to nucleotide depletion triggered by phage replication, leading to non-specific degradation of cellular DNA and ultimately inducing abortive infection. These insights into the KELShedu system expand the repertoire of bacterial anti-phage mechanisms and lay the groundwork for novel applications in microbial engineering and therapeutic development. TeaserThe KELShedu system exerts anti-phage function by aborting infection in response to physiological changes following phage infection

microbiology↗

bioRxiv2025

Multi-omics analysis reveals genetic regulatory mechanismsof muscle traits in wild and domesticated Bactrian camels

Bactrian camels, large domesticated animals adapted to extreme environments, have evolved under natural and artificial selection to suit their living conditions and meet human needs. In arid and semi-arid regions, they provide valuable resources through economically important traits such as meat, milk, and wool production, contributing significantly to both economy and ecology. However, research on gene function, adaptive evolution, and molecular mechanisms underlying complex traits in Bactrian camels remains limited, constraining the full utilization of their breeding potential and conservation efforts.To address this gap, we performed whole-genome resequencing (WGS) on 35 domesticated Bactrian camels from the Chinese Sunite local population and integrated this data with publicly available WGS data from 112 Asian Bactrian camels. Our comprehensive analysis revealed significant genetic differences and genomic features between wild and domesticated Bactrian camels. We further integrated 27 epigenomic (ATAC-seq) and transcriptomic (RNA-seq) datasets from eight biologically important tissues of four Bactrian camels, along with skeletal muscle scRNA-seq and scATAC data. This allowed us to identify tissue-specific genes, regulatory elements, and genes under positive selection.Our integrated analysis identified target genes and their upstream regulatory elements, including potential regulatory transcription factors, with a focus on positively selected regions in Bactrian camel muscle tissue. We constructed regulatory pathways from key SNPs to regulatory elements to genes, and for the first time, identified regulatory elements in major tissues of the Bactrian camel genome. Our results also summarized the single-cell transcriptional landscape of Bactrian camel skeletal muscle, revealing cellular heterogeneity and genetic expression patterns across two developmental stages.This comprehensive regulatory element map provides a valuable resource for genetic and genomic studies in Bactrian camels. It reveals key regulatory networks, important genes, and regulatory elements influencing muscle development, as well as potentially significant functional variants affecting meat production traits. These findings will provide crucial data support for future genetic improvement and breeding efforts in Bactrian camels.

genetics↗

bioRxiv2025

An electrostatic repulsion model of centromere organisation

During cell division, chromosomes reorganise into compact bodies in which centromeres localise precisely at the chromatin surface1-4 to enable kinetochore-microtubule interactions essential for genome segregation5-8. The physical principles guiding this centromere positioning remain unknown. Here, we reveal that human core centromeres are directed to the chromatin surface by repulsion of centromere-associated proteins - independent of condensin-mediated loop extrusion and microtubule engagement. Using cellular perturbations, biochemical reconstitution, and multiscale molecular dynamics simulations, we show that chromatin surface localisation emerges from repulsion between condensed chromatin and both the kinetochore and the highly negatively charged centromere protein, CENP-B. Together, these elements form a centromeric region composed of two domains with opposing affinities, one favouring integration within the mitotic chromosome and the other favouring exposure to the surrounding cytoplasm, thereby driving surface positioning. Tethering synthetic negatively charged proteins to chromatin was sufficient to recapitulate this surface localisation in cells and in vitro, indicating that electrostatic repulsion is a key determinant of surface localisation. These findings demonstrate that centromere layering is not hardwired by chromatin folding patterns but instead emerges from phase separation in chromatin. Our work uncovers electrostatic polarity as a general and programmable mechanism to spatially organise chromatin.

cell biology↗

bioRxiv2025

Mapping early PRC2 nucleation sites upon Suz12 reintroduction reveals features of de novo Polycomb recruitment

Polycomb domains safeguard cell identity by maintaining lineage-specific chromatin states enriched in repressive histone modifications, preserving the epigenetic memory of cell lineages. While Polycomb Repressive Complex 2 (PRC2) can re-establish its occupancy after perturbation, the mechanisms that guide de novo Polycomb recruitment remain unclear. To address this, we engineered an auxin-inducible degradation system to reversibly deplete and reintroduce the endogenous PRC2 core subunit Suz12 in mouse embryonic stem cells (mESCs). Genome-wide profiling at an early recovery time point revealed [~]1,100 PRC2 nucleation sites, characterized by rapid Suz12 and histone H3K27me3 re-accumulation with strong signal, with minimal impact on gene expression. These sites were significantly enriched at bivalent promoters, coinciding with unmethylated CpG islands and chromatin states associated with developmental regulation, and were largely conserved in differentiated cells. Motif analysis identified G/C-rich DNA sequences associated with E2F and zinc-finger proteins, alongside strong co-occupancy with MTF2 and JARID2, two PRC2 cofactors previously implicated in Polycomb targeting. Notably, a subset of nucleation sites overlapped with long-range chromatin interaction anchors in histone H3K27me3 HiChIP datasets. These findings reveal that PRC2 de novo nucleation sites are associated with a combination of chromatin states, DNA sequence features, cofactor co-occupancy and spatial genome organization, suggesting that epigenetic memory can be re-established through defined genomic and chromatin features. Author summaryPolycomb group proteins are key epigenetic regulators that silence gene expression by establishing and dispersing repressive chromatin domains marked by histone modifications such as histone H3K27me3 and H2AK119ub1 and are critical for defining cell identity. During differentiation, Polycomb domains are dynamically redistributed, implying a mechanism for de novo targeting to specific loci. How the Polycomb Repressive Complex 2 (PRC2) is initially recruited to these nucleation sites and which features stabilize its binding remain poorly understood. To explore this, we studied the characteristics of the de novo recruitment sites of PRC2 in mouse embryonic stem cells (mESCs) using an auxin-inducible degradation (AID) system targeting PRC2 to deplete and reintroduce the core subunit Suz12. We identified recruitment sites after complete clearance of the histone H3K27me3 through ChIP-seq at a very early time point after Suz12 reintroduction. Most nucleation sites were located at bivalent promoters of developmental genes and correlated with unmethylated CpG islands. Motif analysis revealed over-represented sequences and accessory partners such as MTF2 and JARID2, along with long-range chromatin interactions. These nucleation sites were also conserved in differentiated cells, highlighting their potential role in developmental regulation. Our study provides insight into how Polycomb domains are established and how epigenetic memory is maintained in stem cells.

molecular biology↗

bioRxiv2025

Comprehensive analysis of metabolic reprogramming-related gene signaturesmetabolic reprogramming related gene signature for predicting ovarian cancer prognosis, immune landscape, and potential treatment options

Ovarian cancer (OV) is the most lethal gynecologic malignancy. Metabolic reprogramming is a distinctive feature of cancer and is associated with tumorigenesis and progression. It could be a potential therapeutic target for cancer treatments and a biomarker for assessing cancer prognosis. In this study, we identified metabolic reprogramming-related differentially expressed genes (MRRDEGs) in OV through differential gene expression analysis and conducted a comprehensive characterization of these MRRDEGs. Based on the MRRDEGs, we constructed an effective prognostic risk model including five model genes for OV. The risk score was a valid independent prognostic factor that could more accurately predict the survival of OV patients. It could classify OV patients into distinct risk groups with significant differences in survival. We observed significant differences between risk groups in biological pathway activity, immune cell infiltration patterns, and immunotherapy responses. Specifically, the low-risk group demonstrated superior immunotherapy response compared to the high-risk group. These findings significantly advance our understanding of the relationship between metabolic reprogramming and OV pathogenesis, progression, prognosis, and immunotherapy response, laying a foundation for developing novel biomarkers and therapeutic targets in the future and providing an important reference for the formulation of precision medicine strategies.

bioinformatics↗

bioRxiv2025

An integrated multi-tissue atlas of epigenomic landscapes and regulatory elements in the bovine genome

Deciphering the regulatory syntax of the genome is essential to understand the genetic and molecular architecture of complex traits, as most trait-associated variants lie in non-coding regions. Yet, functional annotation of the bovine genome remains limited, hindering our ability to unravel the mechanisms underpinning complex traits of economic and ecological importance in cattle. Here, we present a comprehensive epigenetic atlas comprising 1,138 genome-wide epigenetic profiles, including chromatin accessibility, six histone modifications, CCCTC-binding factor (CTCF) transcription factor binding, DNA methylation, chromatin conformation, and transcriptomes across 53 adult tissues, five fetal tissues, and seven primary cell types. This atlas-level data enables us to annotate around 45% of the genome as putative regulatory elements exhibiting tissue- or cell-specific regulatory activity. Leveraging sequence-to-function deep learning models, we discovered 301 sequence motifs and predicted the functional impact of genetic variants through in silico mutagenesis, thereby facilitating the decoding of the regulatory syntax of the cattle genome and fine-mapping of GWAS loci for 22 complex traits. Cross-species analysis further revealed evolutionarily conserved features of regulatory architecture and provided evolutionary insights into complex traits and diseases in humans. Together, this atlas offers a foundational resource for advancing cattle functional genomics, sustainable breeding, and studies of regulatory evolution.

genomics↗