Biology subjects

Zhang, H.

Publications and source records attributed to Zhang, H..

At least 343 records · Page 19Linked to original sources

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↗

bioRxiv2025

The Secreted Metabolite Isopentenyladenine from Faecalibacterium prausnitzii Mitigates Gut Inflammation

Colonic microbiome dysbiosis is correlated with inflammatory bowel disease (IBD), and depletion of the commensal bacterium Faecalibacterium prausnitzii (F. prausnitzii) is routinely observed in the metagenomic analyses of IBD patient microbiome samples. F. prausnitzii is likely beneficial to hosts, as oral administration of F. prausnitzii strain A2-165 has anti-inflammatory properties in murine models of colitis. Previous studies attribute the anti-inflammatory effects of F. prausnitzii A2-165 to production of the short-chain fatty acid butyrate, as well as a 15 kDa protein known as microbial anti-inflammatory molecule (MAM). Here, we verified that oral dosing of strain A2-165 protects against DSS-induced murine colitis and further show the aqueous-soluble secreted fraction of overnight cultures from a collection of F. prausnitzii strain inhibit inflammatory signatures, including the activation of the hosts NF-{kappa}B pathway, production of IL-8, and differentiation of naive T cells into the TH17 lineage. We find that MAM is secreted in extracellular vesicles; however, MAM-containing vesicles do not have anti-inflammatory properties in our collection of assays and suggests that MAM is likely not a direct contributor. Untargeted and targeted mass spectrometry metabolomics analyses on the soluble anti-inflammatory secretome yielded several unique F. prausnitzii metabolites, including isopentenyladenine. We demonstrated isopentenyladenine independently modulates host cellular signaling and immune responses and suggests this newly identified metabolite with human immunomodulatory properties may be useful towards the discovery of IBD-focused therapeutics.

microbiology↗

bioRxiv2025

Frataxin deficiency drives cardiac dysfunction and transcriptional dysregulation in Friedreich ataxia iPSC model

Friedreich ataxia (FRDA) is a progressive neuromuscular degenerative disorder caused by GAA repeat expansions in the FXN gene, leading to frataxin deficiency and multisystem pathology. Cardiomyopathy is the leading cause of mortality in individuals with FRDA. To investigate the cellular and molecular mechanisms underlying FRDA-associated cardiac dysfunction, we employed induced pluripotent stem cell (iPSC) lines derived from three individuals with FRDA, each paired with an isogenic control line generated through CRISPR/Cas9-mediated excision of the pathogenic GAA repeat expansion. Correction of the mutation restored FXN expression to levels comparable to healthy donor iPSCs, and all lines differentiated efficiently into cardiomyocytes. Functional analysis revealed significant contractile abnormalities in FRDA cardiomyocytes and multicellular cardiac microtissues, including prolonged contraction and relaxation times and faster beating rates, consistent with clinical observations of cardiac contractile dysfunction. FRDA cardiomyocytes also exhibited pathological features such as increased cell size, irregular calcium transients, elevated mitochondrial reactive oxygen species levels, increased mitochondrial fission and increased cell death. These phenotypes were exacerbated by pathological levels of iron supplementation in culture media, highlighting the heightened sensitivity of frataxin-deficient cardiomyocytes to iron-induced metabolic stress. RNA sequencing revealed a distinct transcriptional profile associated with frataxin deficiency. MEG3 and PCDHGA10 were consistently dysregulated across all three FRDA-iPSC lines and may represent early molecular markers of FRDA cardiomyopathy. Together, these findings establish a robust human iPSC model of FRDA cardiomyopathy that captures early disease phenotypes and reveals novel molecular targets. This preclinical human model provides valuable insight into the pathogenesis of FRDA and provides a platform for developing early-stage therapeutic interventions.

pathology↗

bioRxiv2025

Lipid Droplets of Human Carotid Atherosclerotic Plaques: Cholesteryl Arachidonate Core and Cytoskeletal Fibrotic Cover

Lipid droplets (LDs) within atherosclerotic plaques are central to cardiovascular disease, yet their molecular composition remains largely unknown. More than 20 years experiences of developing LD purification method allowed us recently to successfully purify LDs from atherosclerotic plaques of patients undergoing carotid artery surgery, including three types, soft (lipid), mixed, and hard (calcified). In addition, the subpopulations of large LDs and small LDs were purified and studied, respectively. We report the first comprehensive proteo-lipidomic analysis of these LDs. Unexpectedly, about 19.3% of the plaque LD proteins belonged to cytoskeleton, while the content of lipid metabolism enzymes on plaque LDs was low. Our results show that the compositions of lipids and proteins were similar between two population LDs. Compared to soft (lipid) plaque LDs, LDs from mixed and hard (calcified) plaques had fewer metabolic enzymes and more cytoskeletal proteins. Lipidomics of the LD core uncovered an unexpected enrichment of polyunsaturated fatty acid cholesteryl esters (PUFA-CEs), which constituted 88.3% of all cholesterol esters. Notably, esters of the pro-inflammatory precursor arachidonic acid (AA) were among the most abundant species (16.5%). In addition, plaque LD were uniquely enriched in phospholipids including phosphatidic acid (PA), phosphatidylethanolamine plasmagens (PE-P), sphingomyelin (SM), and phosphatidylserine (PS). Our findings redefine the plaque LD as a dual-function "bad" organelle: a metabolically inert container for cholesterol ester, coated with cytoskeletons, and a massive reservoir for inflammatory precursors.

cell biology↗

bioRxiv2025

Validation of Solvent Proteome Profiling for Antimalarial Drug Target Deconvolution

Malaria remains a global health threat, with rising drug resistance accelerating the urgent need for new therapeutics. Target elucidation is a critical step in antimalarial drug discovery, enabling a deeper understanding of the molecular mechanisms of action of both existing and novel compounds. This study validates solvent-induced proteome profiling (SPP) as a proteomics-based approach for identifying drug-protein interactions in Plasmodium falciparum. SPP detects shifts in protein stability induced by ligand binding, allowing the identification of drug target/s without the need for compound modifications. Here, we successfully generated solvent denaturation curves for the P. falciparum proteome, and demonstrated the utility of SPP with five antimalarial compounds: pyrimethamine, atovaquone, cipargamin, MMV1557817 and OSM-S-106. In addition to measuring each compounds impact across the full denaturation curve, investigating protein levels at individual solvent percentages preserved specific stability changes that would otherwise be masked in pooled analyses performed by integral SPP. This strategy was critical for the identification of the cipargamin target, non-SERCA-type Ca2+-transporting P-ATPase (PfATP4). Notably, we propose live-cell treatment SPP as a novel approach, demonstrating its ability to identify the validated target of pyrimethamine, bifunctional dihydrofolate reductase-thymidylate synthase (PfDHFR), with high specificity. We also introduced the novel one-pot mixed-drug SPP which enables the evaluation of multiple drugs within a single lysate and experimental setup. This alternative method simplifies the experimental workflow and includes positive controls to affirm the performance of the experiment. Overall, this study demonstrates that SPP can be successfully applied in both lysates and live cells to elucidate drug targets in P. falciparum, as well as providing additional information regarding the mechanisms of drug action, offering insights for the optimisation of existing antimalarials and the development of novel therapies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/670428v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@b83c75org.highwire.dtl.DTLVardef@1895f23org.highwire.dtl.DTLVardef@1c51ba0org.highwire.dtl.DTLVardef@198c822_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2025

Structure-based Generation of a Secondary Nucleation Inhibitor in alpha-Synuclein Aggregation Using a Conditional Diffusion Model

The process of -synuclein aggregation results in the formation of amyloid fibrils, which accumulate in the brain of patients affected by Parkinsons disease. Among possible therapeutic strategies to cure this disease, one approach is based on the development of compounds capable of inhibiting -synuclein aggregation. An effective inhibition could be achieved by blocking the nucleation sites on the surface of the amyloid fibrils that are responsible for their autocatalytic proliferation. Here, we report a strategy based on deep learning to achieve this goal, which uses an E(3)-equivariant conditional diffusion model. By using this approach, we designed and tested experimentally candidate small molecules. We found that one of these small molecules acts as a potent inhibitor of secondary nucleation in -synuclein aggregation. These results provide evidence that generative diffusion models offer effective tools for drug design.

biophysics↗

bioRxiv2025

Recombinant proteasome provides new avenues for anti-malarial drug development.

The Plasmodium falciparum 20S proteasome (Pf20S) has emerged as a promising antimalarial target. Development of therapeutics to this target has previously relied on native purifications of Pf20S, which is challenging and has limited the scope of previous efforts. Here, we report an effective recombinant Pf20S platform to facilitate drug discovery. Proteasome assembly was carried out in insect cells by co-expressing all fourteen subunits along with the essential chaperone homolog, Ump1. Unexpectedly, the isolated proteins consisted of both a mature and an immature complex. Cryo-EM analysis of the immature complexes revealed structural insights detailing how Ump1 and the propeptides of the {beta}2 and {beta}5 subunits coordinate {beta}-ring assembly, which differ from human and yeast homologs. Biochemical validation confirmed that {beta}1, {beta}2, and {beta}5 subunits of the mature proteasome were catalytically active. Clinical proteasome inhibitors, bortezomib, carfilzomib and marizomib were potent but lacked Pf20S selectivity. However, the tripeptide-epoxyketone J-80 inhibited Pf20S {beta}5 with an IC50 of 22.4 nM and 90-fold selectivity over human {beta}5. Structural studies using cryo-EM elucidated the basis for the selective binding of J-80. Further evaluation of novel Pf20S-selective inhibitors such as the reversible TDI-8304 and irreversible analogs, 8304-vinyl sulfone and 8304-epoxyketone, confirmed their potency and selectivity over the human constitutive proteasome. This recombinant Pf20S platform facilitates detailed biochemical and structural studies, accelerating the development of selective antimalarial therapeutics.

biochemistry↗

bioRxiv2025

Protein Function Prediction via Contig-Aware Multi-Level Feature Integration

Proteins play a central role in biological processes, and accurately predicting their functions is crucial for biomedical research. While computational methods have advanced significantly, most approaches rely solely on sequence or structure, neglecting critical inter-protein relationships, such as the topological arrangement of coding sequences (CDSs) within contigs. To address this gap, we propose CAML, a novel deep learning model that integrates intra-protein features including sequence and predicted structure with inter-protein features capturing functional linkages among CDSs in contigs. Specifically, CAML employs a Graph Isomorphism Network (GIN) to extract structural features from predicted protein contact graphs and ESM-2 for sequence embeddings. Additionally, it leverages kmer frequencies and a Bidirectional Long Short-Term Memory (BiLSTM) network to model functional relationships among colocalized CDSs within contigs, capturing operon-like associations. Extensive experiments demonstrate that CAML outperforms the state-of-the-art methods in accuracy, precision, recall and F1-score, achieving improvements of 11.24%, 12.43%, 13.59%, and 13.30%, respectively over the second-best model. Ablation studies further confirm the critical contribution of CAMLs multi-level biological feature integration in enhancing functional annotation accuracy. Our study demonstrates the importance of integrating structural, sequential, and CDSs topological features for accurate protein function prediction, providing a robust computational framework for genomics research.

bioinformatics↗

bioRxiv2025

RESM: Capturing sequence and structure encoding of RNAs by mapped transfer learning from ESM (evolutionary scale modeling) protein language model

RNA sequences exhibit lower evolutionary conservation than proteins due to their informationally constrained four-letter alphabet, compared to the 20-letter code of proteins. More limited information makes unsupervised learning of structural and functional evolutionary patterns more challenging from single RNA sequences. We overcame this limitation by mapping RNA sequences to pseudo-protein sequences to allow effective transfer training from a protein language model (protein Evolution-Scale Model 2, protESM-2). The resulting RNA ESM (RESM) outperforms 12 existing RNA language models in zero-shot prediction, not only in sequence classification but also in RNA secondary structure and RNA-RNA interaction prediction. Further supervised fine-tuning demonstrates RESMs generalizability and superior performance over the existing models compared across multiple downstream tasks, including mRNA ribosome loading efficiency and gene expression prediction, despite RESM being trained exclusively on noncoding RNAs. Moreover, RESM can generalize to unseen sequences beyond its 1,024-nucleotide training limit, achieving 81.3% improvement over state-of-the-art methods in supervised secondary structure prediction for RNAs up to 4,000 nucleotides, limited only by the available GPU memory, while providing >1000-fold speedup compared to MSA-based approaches. RESM provides a robust foundation for deciphering RNA sequence-structure-function relationships, with broad implications for RNA biology.

bioinformatics↗

bioRxiv2025

Bottlebrush Polymer Conjugates for Enhanced Antisense Oligonucleotide Therapy in Myotonic Dystrophy Type 1

Oligonucleotides are a promising genetic medicine for myotonic dystrophy type 1 (DM1), the most common adult-onset muscular dystrophy. However, poor muscle distribution of nucleic acid drugs after systemic administration has hindered drug development, and no curative treatment exists. Additionally, DM1 pathology requires drug localization to the nucleus, where pathogenic mutant RNA is trapped, posing challenges after endocytosis and endosomal escape. Here, we show that a locked nucleic acid oligonucleotide targeting mutant CUGexp RNA tracts, conjugated to a bottlebrush polymer, exhibited improved muscle distribution and potent correction of DM1-associated splicing at low nanomolar doses in a DM1 mouse model. Significant improvements in myotonia, body weight, and grip strength were observed. The conjugates were well tolerated after 12 weeks of weekly intravenous dosing. These results suggest that bottlebrush polymer bioconjugates may overcome key limitations of traditional antisense drugs for muscular dystrophies, with the potential as potent, durable, and cost-efficient DM1 therapies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/668589v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@e3961corg.highwire.dtl.DTLVardef@194225dorg.highwire.dtl.DTLVardef@5c470dorg.highwire.dtl.DTLVardef@3cc46a_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

OmniCellAgent: Towards AI Co-Scientists for Scientific Discovery in Precision Medicine

Real-world biomedical scientific discovery operates as an iterative lifecycle integrating four core pillars: the targeted identification and analysis of question-specific omics datasets; the context-aware interpretation of molecular data using rich biomedical prior knowledge database; comprehensive literature reviews; and the subjective creativity and expert intuition of human scientists. Together, these pillars drive robust evidence synthesis and novel hypothesis generation. The recently reported AI agents support automated omics analysis and literature review, which typically require users to predefine and curate disease-specific datasets, which is a process that remains challenging and time-consuming. In this study, we present OmniCellAgent, a novel multi-agent AI framework built on large-scale single-cell RNA sequencing (scRNA-seq) datasets, and can autonomously retrieve and analyze disease and control-related scRNAseq datasets of diverse cell types across tissues and conditions. Moreover, it incorporates a biomedical prior knowledge and literature review agents, and disease domain-specific expert agents to systematically annotate omic data-derived targets. By aggregating evidence across agents, the framework generates structured analytical reports and potential scientific hypotheses. We evaluated OmniCellAgent across multiple disease settings, demonstrating its ability to identify relevant datasets, generate omic data analysis results, and produce structured reports and scientific hypotheses. Our findings demonstrate that multi-agent AI systems lower the technical barriers to omics-driven research, thereby accelerating scientific discovery and hypothesis generation in biomedical research and precision medicine. The source code is publicly available at: https://github.com/FuhaiLiAiLab/OmniCellAgent.

bioinformatics↗

bioRxiv2025

Population genomics of the endangered scaly-foot snail defines conservation units amid deep-sea mining threats in Indian Ocean vents

Hydrothermal vents in the Indian Ocean face imminent deep-sea mining, yet lack baseline high-resolution connectivity data for their endemic fauna. We present the first population genomic study of the endangered scaly-foot snail (Chrysomallon squamiferum), an iconic species distributed across three vent biogeographic provinces. Analysing 125 individuals from eight vent fields using 14 million single-nucleotide polymorphisms, we identify five genetic groups that warrant recognition as evolutionarily significant units. Demographic modelling reveals critical contributions from extinct or unsampled phantom populations to the contemporary genetic structure. Together with physical ocean modelling, we show that the deep currents drive asymmetric south-to-north gene flows, while transform faults act as dispersal barriers. We propose Longqi-Duanqiao fields on the Southwest Indian Ridge and Wocan field on the Carlsberg Ridge as two isolated populations prioritised for protection. Given its exceptional adaptations, wide distribution, and public recognition, the scaly-foot snail is well-positioned to serve as both a flagship and umbrella species to ensure the survival of a broader suite of vent biodiversity. As the International Seabed Authority finalises its Mining Code in 2025, our findings provide essential genomic evidence to mitigate the impacts of mining on genetic diversity and inform transboundary conservation strategies for this vulnerable ecosystem.

ecology↗

bioRxiv2025

An absolute quantification atlas of small non-coding RNAs across diverse mammalian tissues and cell lines

The low quantitative accuracy of conventional small noncoding RNA sequencing (sncRNA-seq) methods due to extensive ligation bias commonly limits functional investigation of microRNAs (miRNAs) and PIWI-interacting RNAs (piRNAs). Here, we develop 4NBoost, a single-tube sncRNA-seq protocol designed to minimize bias in the estimated absolute quantification of miRNA and piRNA transcripts through the incorporation of quantitative exogenous RNA spike-ins. With 4NBoost, we profile sncRNA expression across 20 murine tissues, 18 macaque tissues, and 24 widely used cell lines, as well as 4 Arabidopsis tissues, to establish a comprehensive quantitative reference atlas. Compared with existing small RNA databases, our data reveal substantial biases in miRNA abundance, strand selection, and tissue-specific expression at both individual and family levels. To further extend its utility, we employ machine learning to model and correct biases in conventional datasets, effectively recovering ground truth transcript abundances. All 4NBoost data and the accompanying bias-correction model are freely available via SmRNAQuant (http://wulg-lab.sibcb.ac.cn/SmRNAQuant/), a web-based repository for exploring sncRNA expression. Together, the 4NBoost, bias-correction model, and SmRNAQuant provide powerful resources to advance sncRNA research.

genomics↗

bioRxiv2025

Intracranial Insights into the Developing Neural Basis of Moral Punishment

Third-party punishment (TPP) is a critical component of social regulation and justice, in-tegrating moral reasoning and emotional salience. However, the neural developmental basis underpinning this complex process remains largely unknown. Using rare intracranial stereo-electroencephalography (SEEG) in 14 children and 17 adults, we investigated the developing neural circuits of TPP. We found that broad-band gamma activity in the amygdala and ventromedial prefrontal cortex (vmPFC) encodes inferred intentions, with different patterns across age groups. Furthermore, the vmPFC, insula, and inferior parietal lobule (IPL) integrate punishment efficacy, also showing significant developmental differences. Combining task and resting state functional connectivity analyses, we further found age-dependent interactions among the amygdala-insula and IPL-vmPFC neural couplings during decision-making. These findings provide valuable intracranial evidence that the maturation of moral decision-making stems from the developmental refinement of subcortical-cortical circuits that integrate emotional and cognitive evaluations, explaining the shift from intuitive decisions in children to context-sensitive judgments in adults.

neuroscience↗

bioRxiv2025

Coiled-coil interactions drive ectopic condensation of overexpressed MAD1 to promote mitotic slippage in cancer cells

The mitotic checkpoint protein MAD1 is significantly overexpressed in several cancers, weakening the checkpoint and promoting mitotic slippage. Overexpressed MAD1 forms ectopic foci in mitotic cells, yet the biophysical nature of these foci and their contributions to mitotic slippage remain unclear. Here, we report that MAD1 foci are phase-separated condensates that shorten the mitotic duration by sequestering checkpoint proteins. Our biophysical quantifications reveal that MAD1 ectopic foci in mitotic cells exhibit dynamic condensate properties rather than those of a solid aggregate. Using an inducible phase separation assay in live cells, we show that MAD1 phase separation is driven by interactions between its coiled-coil and disordered domains at the N-terminus. We decouple the contributions of condensation from concentration by inducing the formation of MAD1 ectopic condensates in mitotic cells with low levels of MAD1, demonstrating that the condensation process directly drives mitotic slippage. Mechanistically, the MAD1 ectopic condensate traps the diffusive pool of MAD2, an interaction partner of MAD1, thereby weakening the MAD2 conversion cycle necessary for a robust mitotic checkpoint. Our work illustrates a loss of function caused by ectopic condensates in MAD1-overexpressed cancer cells.

cell biology↗

bioRxiv2025

HBMAP: Bayesian inference of neural circuits from DNAbarcoded projection mapping

Decoding how the brain routes information through its precise, long-range wiring remains a central challenge in neuroscience. Barcode-based mapping of axonal projections allows brain-wide, high-throughput investigation of projections at single-neuron resolution offering a powerful solution. However, principled methods for statistical analysis of barcode count data that can detect common projection rules and effectively integrate datasets across subjects are lacking. To address these issues, we developed a model-based clustering approach through hierarchical Bayesian mixtures which we call hierarchical Bayesian mapping of axonal projections (HBMAP). We show that the inferred model accurately reflects the features of the data and allows simultaneous identification of projection patterns and characterization of uncertainty that accounts for subject variability. Our study presents the first Bayesian approach to barcode-based projection mapping, offering a general solution for this class of data.

neuroscience↗

bioRxiv2025

Population-level super-pangenome reveals genome evolution and empowers precision breeding in watermelon

Pangenomes are increasingly critical for harnessing crop genetic diversity, yet their resolution and utility are often limited by insufficient sampling of high-quality genome assemblies. Here, we report a population-level watermelon super-pangenome constructed from 138 reference-grade assemblies, including 135 newly generated near-gapless genomes representing all seven watermelon species. The super-pangenome captures approximately one million structural variants (SVs), enabling accurate variant genotyping across ~900 watermelon accessions and substantially expanding variant discovery both across and within species. Broader sampling within the pangenome provides insights into genome evolution among watermelon species and sheds light on the origin of cultivated watermelon. SV-inclusive genome-wide association studies enhance trait mapping resolution and identify a copy number variation upstream of ClFCI1 that regulates flesh color intensity in a dosage-dependent manner. Leveraging this comprehensive variation map, we developed high-accuracy genomic prediction models for 18 agronomic traits. Together, our findings and genomic resources establish a foundational framework for dissecting complex traits and accelerating precision breeding in watermelon, while offering a valuable model for SV-resolved pangenomics in crop species.

plant biology↗

bioRxiv2025

Integrated small and long RNA sequencing in single oocytes reveals piRNA-mediated transposon repression during human oogenesis

The piwi-interacting RNA (piRNA) pathway plays a pivotal role in controlling transposable element (TE) activity, which is crucial for the developmental competence of gametogenesis. Although piRNAs have been studied in golden hamsters and other representative mammals, little is known about the relationship between distinct piRNA populations and their regulatory effects on TEs in human oocytes. In this study, we simultaneously profiled small and long RNA transcriptomes in individual human oocytes across four developmental stages. piRNAs, especially PIWIL3-associated short piRNAs (short-piRNAs), are the predominant small non-coding RNAs during human oogenesis. A marked increase in short-piRNAs after the primordial follicle stage coincided with a global downregulation of TE expression, particularly LINE-1 (L1) and endogenous retroviruses (ERVs). On the other hand, PIWIL1- and PIWIL2-associated long piRNAs (long-piRNAs) were correlated with the silencing of certain specific ERV subfamilies. Genomic-context analyses revealed that highly productive piRNA clusters have evolved asymmetric antisense insertion bias toward L1 and ERVs, contributing to TE families-specific regulation. Our findings highlight the global effect of piRNA-mediated TEs repression, with short-piRNAs acting as the primary and broad-spectrum suppressors, and long-piRNAs providing coordinated ERV-specific silencing. In summary, this study provides a valuable dataset of small and long RNA co-expression landscapes in developing human oocytes and offers insights into the coordinated yet distinct roles of different PIWI/piRNA classes in repressing TEs during human oogenesis.

genomics↗