Biology subjects

Liu, Y.

Publications and source records attributed to Liu, Y..

At least 631 records · Page 35Linked to original sources

bioRxiv2025

NAT10 Suppresses RNA Sensing Induced IFN-β Transactivation to Promote Viral Infection via Interfering with IRF3 Activities

Cells can sense invading viruses and trigger type I interferons (IFN-/{beta}) to evoke antiviral innate immune response. Induction of IFNs needs to be fine-tuned to achieve the antiviral consequence while avoiding severe disruption of host cell homeostasis. Here, we reported that NAT10, the acetyltransferase of histone and N4-acetylcytidine (ac4C) RNA modification, promotes infection of RNA viruses via regulation of type I IFN signaling. Depletion of NAT10 increased the expression of IFN-{beta} and interferon-stimulated genes (ISGs) upon stimulation of type I IFN antiviral signaling, while it impaired viral replication. NAT10 dynamically associated with the IFN-{beta} promotor and negatively regulated IRF3 through modulation of long non-coding RNAs (lncRNAs) that inhibit IRFs. Consistently, the small molecule inhibitor of NAT10, Remodelin, increased IFN-{beta} expression while inhibiting viral infections. Overall, our findings indicated that NAT10 is a negative regulator of type I IFN signaling, suggesting its potential as a target of antiviral treatment.

microbiology↗

bioRxiv2025

Dominance of plasticity in wind-pollinated trees' flowering time response to temperature

Climate change is shifting the flowering phenology of wind-pollinated trees, leading to longer pollen seasons and heightened allergy risks. Accurately forecasting these phenological shifts requires a clear understanding of the underlying mechanisms and variations in the sensitivity of phenology to temperature. Here, we investigated the temperature sensitivity of flowering phenology in 74 wind-pollinated tree species across the US using long-term herbarium records spanning over a century. We found consistent phenological responses to spring temperature variations over space and over time in 77% of species, indicating that these long-lived trees can rely primarily on plasticity to cope with temperature variation across different regions. Sensitivity estimates were consistent across both century-scale and decadal time scales, challenging the previous understanding of declines. Interspecific variations in sensitivity exhibited a strong phylogenetic signal, indicating evolutionary conservatism in phenological responses among related species. Together, these findings shed light on the magnitude, mechanism, trend, and variability of temperature sensitivity of wind-pollinated tree flowering phenology. Our results improve the mechanistic basis for forecasting phenological shifts and their downstream effects on airborne pollen and allergen exposure under ongoing climate change.

ecology↗

bioRxiv2025

Pleistocene demographic histories dominate contemporary genomic diversity in a continental radiation of Himalayan-Hengduan songbirds

While population genetic theory expects genetic diversity to scale predictably with population size, mounting empirical evidence has challenged this fundamental prediction. This striking inconsistency has prompted a paradigm shift in our understanding of the determinants of genetic diversity, driving increased efforts to disentangle the relative contributions of Pleistocene demography and linked selection. Here, based on systematic sampling and a unified analytical pipeline, we de novo assembled genomes for 120 songbird species breeding in the Himalayas-Hengduan Mountains (HHMs) and conducted population genomic analysis to examine the drivers of their genomic diversity. We observed a 6.5-fold variation in genome-wide heterogeneity and a 16.4-fold variation nucleotide diversity and across species. Notably, these measures of genomic diversity showed no correlation with recent population dynamics, current population size, or other contemporary factors--such as natural selection, elevational distribution, or life-history traits. Instead, historical demography strongly predicted genetic diversity, with ancestral population size during the late Pleistocene emerging as the sole correlate: larger ancestral sizes consistently coincided with higher diversity. These findings underscore the critical influence of historical demography on contemporary genetic diversity in natural populations--an insight essential for designing effective conservation strategies.

genetics↗

bioRxiv2025

Leveraging Large Language Models for Redundancy-Aware Pathway Analysis and Deep Biological Interpretation

Extracting coherent, biologically meaningful insights from vast, complex multi-omics data remains challenging. Currently, pathway enrichment analysis serves as a cornerstone for the functional interpretation of such data. However, conventional approaches often suffer from extensive functional redundancy caused by shared molecular components and overlapping pathway definitions across databases. This redundancy can obscure key biological signals and compromise the interpretability of pathway enrichment results. Here, we present MAPA (Functional Module Identification and Annotation for Pathway Analysis Results Using Large Language Models [LLM]), an open-source computational framework that resolves redundancy and enhances pathway analysis result interpretation. MAPA computes functional similarity between pathways using LLM-based text embeddings, enabling comparison across different databases. It constructs pathway similarity networks and identifies functional modules via community detection algorithms. Crucially, MAPA employs LLMs for automated functional annotation, integrating Retrieval-Augmented Generation (RAG) to generate comprehensive and real-time biological summaries and reduce hallucinations. Benchmarking demonstrated MAPAs superior performance: the biotext embedding similarity showed a large effect size (Cliffs {delta} = 0.96) compared with the Jaccard index ({delta} = 0.73), and module identification achieved high accuracy (Adjusted Rand Index [ARI] = 0.95) versus existing methods (ARI = 0.23-0.33). Human expert evaluation confirmed that MAPAs annotations match expert-quality interpretations. Finally, a multi-omics aging case study illustrates that MAPA uncovers coherent functional modules and generates insights extending beyond conventional pathway analyses. Collectively, MAPA represents a significant advance in redundancy-aware pathway analysis, transforming pathway enrichment results from fragmented lists into biologically coherent narratives. By leveraging the capabilities of LLMs, MAPA offers researchers a robust, scalable tool for deriving deep mechanistic insights from complex and vast multi-omics datasets, marking a new direction for AI-driven bioinformatics.

bioinformatics↗

bioRxiv2025

Analysis of the phosphorylation networks characterizing distinct phenotypic states in glioblastoma cell Populations

Cancer cells, including the most aggressive brain cancer, glioblastoma, can exhibit a high degree of phenotypic plasticity. However, it is not well understood whether and how distinct phenotypic states might be associated with or driven by specific signaling processes. Here, we use a novel approach to the identification of phenotype-specific signaling networks in cells undergoing the Go-or-Grow switch in populations of GBM cell lines. We find that the transition to invasive spread may be associated with the onset of DNA damage response, cell cycle arrest, and activation of the AKT-mTOR signaling. We reconstructed the large-scale signaling networks, revealing integration of diverse pathways and possible feedback interactions mediating phenotypic stability. We further show that phosphorylation outcomes may be preferentially mediated by 14-3-3 proteins, previously implicated in stress response and control of the cell cycle. Finally, we demonstrate that the phenotype-specific phospho-site signatures have predictive power for disease-free patient survival. This study paves the way for a more comprehensive understanding of phenotypic plasticity in GBM and other aggressive cancers.

systems biology↗

bioRxiv2025

CRISPR/Cas14a Combined with RPA for Visual Detection of Marek's Disease Virus

Mareks disease (MD), a highly contagious avian immunosuppressive disorder caused by the -herpesvirus MDV-1, poses a significant threat to poultry health. The development of rapid visual detection methods capable of distinguishing epidemic MDV-1 strains from vaccine strains is crucial for early disease warning, vaccine efficacy evaluation, and precise disease control. We developed a novel isothermal detection system that integrates recombinase polymerase amplification (RPA) with CRISPR/Cas14a technology for the visual identification of epidemic MDV-1 strains. This method operates at a constant temperature of 37{degrees}C and allows for either real-time analysis or endpoint visual readout without the need for complex instrumentation. Our results showed no cross-reactivity with Newcastle disease virus (NDV), infectious bursal disease virus (IBDV), MDV-1 vaccine strains, or herpesvirus of turkeys (HVT). Plasmid DNA standards were used to determine the sensitivity of the assay and the detection limit was 24.6 copies/L. Clinical evaluation using 24 field samples confirmed that the method successfully identified all MDV-positive cases, demonstrating its diagnostic reliability. In conclusion, we have developed a rapid, instrument-free, and highly specific nucleic acid detection platform for MDV-1 by combining the sensitivity of RPA with the specificity of CRISPR/Cas14a technology, offering promising potential for field-based diagnostics and disease surveillance. IMPORTANCEMareks disease virus (MDV-1) is a highly contagious and economically important avian pathogen. Existing diagnostic methods are unable to reliably distinguish between epidemic and vaccine strains in field settings, which hampers effective surveillance and evaluation of vaccination programs. To address this challenge, we developed a portable isothermal detection assay that combines recombinase polymerase amplification (RPA) with CRISPR/Cas14a technology. This approach enables highly sensitive (24.6 copies/L) and specific visual detection of epidemic MDV-1 strains without cross-reactivity with vaccine strains or related viruses. The assay demonstrated 100% agreement with reference methods when validated using clinical samples. As a cost-effective and instrument-free method, it offers a practical solution for rapid on-site diagnosis, facilitating enhanced outbreak control and improved poultry health management globally.

molecular biology↗

bioRxiv2025

A molecularly defined basalo-prefrontal-thalamic circuit regulates sensory and affective dimensions of pain

Both the medial prefrontal cortex (mPFC) and thalamus have been implicated in pain regulation. However, the roles of the mPFC-thalamus connection in pain and how the mPFC modulates nociceptive processing remain unclear. Here, we show that the mPFC neurons projecting to thalamus, marked by Foxp2 expression, are deactivated in both acute and chronic pain in male mice. Persistent inactivation of the mPFC Foxp2+ neurons enhances nociceptive sensitivity, while their activation alleviates multiple aspects of pain. Circuit-specific manipulations revealed that the projections to parataenial nucleus, mediodorsal and ventromedial thalamus differentially modulate sensory and affective pain. Additionally, the mPFC Foxp2+ neurons receive cholinergic input from the basal forebrain, particularly the horizonal diagonal band (HDB). Notably, activation of the 4{beta}2-containing nicotinic acetylcholine receptor in mPFC exerts antinociceptive effects in Foxp2+ neuron-dependent manner. Together, our study defines an HDB[->]mPFCFoxp2[->]thalamus circuit essential for sensory and affective pain modulation and underscores the therapeutic potential of targeting mPFC cholinergic signaling in chronic pain management.

neuroscience↗

bioRxiv2025

Identification and quantification of alternative polyadenylation sites in single cell RNA-seq data using scPAISO

AbstractsAlternative polyadenylation (APA) is a critical posttranscriptional mechanism that generates transcriptomic diversity through the production of mRNA isoforms with distinct 3 UTRs or coding sequences. Current APA analysis based on single-cell RNA sequencing (scRNA-seq) for establishing cell type-specific APA landscapes primarily rely on Read2 data, which lacks precise cleavage site (CS) information. This limitation restricts their ability to achieve precise de novo mapping of polyadenylation sites (PASs). Here, we present single-cell PolyAdenylation ISOform quantification (scPAISO), a computational pipeline designed for de novo identification of PAS and quantification of PAS isoforms in scRNA-seq data, by leveraging the often-discarded Read1 from 3 tag-based scRNA-seq protocols. Unlike existing tools, scPAISO directly captures mRNA 3 end cleavage sites, enabling superior performance in motif enrichment (stronger AAUAAA signal) and peak precision (sharper PAS peaks). Moreover, the smaller peak widths enhance the spatial resolution, enabling more accurate detection of closely spaced PASs in the genome. By integrating Read1 and Read2 data, scPAISO achieves isoform-level quantification with an assignment accuracy exceeding 95%. We demonstrate the robustness of scPAISO in identifying PASs and quantifying APA events across diverse biological contexts, including hematopoiesis, systemic sclerosis (SSc), and mouse tissues. We identified stage-specific 3 UTR lengthening in hematopoietic progenitors, global 3 UTR remodeling in SSc and tissue-specific polyadenylation (PA) preference along with RNA-binding proteins in mice. Overall, scPAISO represents a significant advancement in the analysis of APA at single-cell resolution and provides a powerful tool for exploring the regulatory landscape of APA, offering new insights into transcriptome complexity and gene regulation in both health and disease.

bioinformatics↗

bioRxiv2025

NicheScope: Identifying Multicellular Niches and Niche-Regulated Cell States in Spatial Transcriptomics

The functional state of a cell is intrinsically linked to its local microenvironment, or cell niche, a complex milieu formed by multiple interacting cell types. Deciphering how these multicellular niches regulate cell states is fundamental to understanding tissue biology and disease mechanisms, yet remains challenging with current computational approaches. Here, we present NicheScope, a computational framework for transcriptome-wide identification and characterization of Multicellular Niches (MCNs) and their corresponding Niche-Regulated Cell States (NRCSs) from spatial transcriptomics data. NicheScope operates on the principle that a cells transcriptional state is associated with its local multicellular composition. It employs a robust statistical approach to jointly model neighborhood composition and transcriptome-wide gene expression, enabling the simultaneous discovery of MCNs, defined by specific combinations of neighboring cell types, and their associated NRCSs, characterized by distinct gene programs. We demonstrate NicheScopes power and versatility across diverse tissues and platforms, including lymph node, lung adenocarcinoma, and head and neck cancer. NicheScope reproducibly dissected established tissue structures in lymph nodes across tissue regions and platforms, uncovered clinically relevant tumor cell-associated MCNs in lung adenocarcinoma, and revealed shared and condition-specific MCNs in primary and metastatic tumors. Our results establish NicheScope as a powerful, robust, scalable, and interpretable framework for dissecting the spatial and functional organization of complex tissues, providing new insights into multicellular coordination in health and disease.

bioinformatics↗

bioRxiv2025

Mid-zone hepatocytes trade proliferation for survival via Atf4-Chop axis in early acute liver injury

Hepatocytes undergo extensive proliferation to facilitate liver repair after injury, yet early adaptive changes prior to proliferation remain unclear. Here, we report that during early acetaminophen (APAP)-induced liver injury, hepatocytes exhibit transient proliferation suppression that is most pronounced in mid-zone hepatocytes, consistent with zonal APAP metabolism. While spatial transcriptomics (ST) provided robust evidence for this arrest in the mid-zone, support for a similar arrest in pericentral hepatocytes was limited. Integrating ST with immunohistochemistry and functional studies, we identified a unique mid-zone stress-response program centered on the Atf4-Chop axis, which suppresses proliferation via the cell cycle inhibitor Btg2. Together, our findings support a model in which mid-zone hepatocytes transiently prioritize stress adaptation over proliferation, thereby preserving regenerative capacity for subsequent liver repair.

pharmacology and toxicology↗

bioRxiv2025

LieOTAlign: A Differentiable Protein Structure Alignment Framework Combining Optimal Transport and Lie Algebra

The comparison of protein structures is fundamental to understanding biological function and evolutionary relationships. Existing methods, while powerful, often rely on heuristic search algorithms and non-differentiable scoring functions, which limits their direct integration into end-to-end deep learning pipelines. This paper introduces LieOTAlign1, a novel and fully differentiable protein structure alignment framework built on the mathematical principles of Lie algebra and Optimal Transport (OT). LieOTAlign represents rigid body transformations within the Lie algebra of SE(3), which intrinsically preserves the geometric validity of rotations and translations during optimization. We formulate the alignment task as an optimal transport problem, seeking the most efficient mapping between two protein structures. This approach leads to a differentiable version of the TM-score, the Sinkhorn score, which is derived from the entropically regularized OT solution computed via the Sinkhorn algorithm. The entire LieOTAlign pipeline is differentiable, enabling the use of gradient-based optimizers like AdamW to maximize structural similarity. Benchmarking against the official TM-align on the RPIC dataset shows that LieOTAlign can identify longer, topologically significant alignments, achieving higher TM-scores. While the current RMSD is higher, LieOTAlign provides a powerful and flexible framework for protein structure alignment, paving the way for its integration into next-generation deep learning models for diverse bioinformatics challenges.

bioinformatics↗

bioRxiv2025

Regional and Temporal Changes in Early Structural Remodeling Following Myocardial Infarction via Semi-Automatic Image Analysis

Reperfusion therapy, the restoration of blood flow following a myocardial infarction (MI), is one of the most effective treatment strategies. Unlike early reperfusion therapy, differences in infarct size or collagen content have not been reported in late reperfusion therapy. To evaluate the spatial-temporal effects of late reperfusion therapy, we conducted multimodal imaging of histologic sections of rat myocardium following permanent coronary artery occlusion or three hours of occlusion. Semi-automatic partitioning identified the infarct core, infarct border, and healthy periphery regions from label-free liquid crystal based polarized light microscopy (PolScope) images taken throughout the first 5 days of healing. Associated brightfield and standard polarized light microscopy images of hematoxylin-eosin or Picrosirius Red stained sections were also used to determine cellular and collagen fiber densities, respectively. Even when we consider multiple definitions for the vulnerable infarct border, its size decreased faster in late reperfusion therapy samples. Temporal patterns in collagen density also indicated late reperfusion led to a more rapid progression through the necrotic phase of healing (when the infarct is vulnerable to rupture) and earlier progression to the fibrotic phase of healing (when the infarct stabilizes). Notably, we also observed a broader region of provisional non-collagenous matrix in late reperfusion samples during the necrotic phase of healing. Together these findings suggest late reperfusion therapy accelerates healing and potentially changes the spatial pattern of provisional matrix deposition during the period the heart is most susceptible to rupture events.

pathology↗

bioRxiv2025

Structural insights on the ligand selectivity of the mouse trace amine-associated receptor TAAR7e

Trace amine-associated receptors (TAARs), a subclass of G protein-coupled receptors involved in detecting volatile amines, are co-expressed with odorant receptors in the main olfactory epithelium. Although many behaviorally relevant amines have been identified for olfactory TAARs, the molecular mechanisms underlying their selectivity for amines with varying carbon chain lengths and degrees of amine substitution remain unclear. In this study, we used mTAAR7e as a model to investigate these mechanisms. Homology modeling revealed a conserved ligand-binding pocket, supported by sequence-structure covariance analysis across TAARs. Structure-activity relationship profiling revealed key chemical determinants integral to mTAAR7e-mediated odorant recognition and provided, for the first time, a structural explanation for its selective preference toward longer carbon chains and tertiary amines. Computationally predicted interactions between mTAAR7e and the representative ligand N,N-dimethylcyclohexylamine (DMCHA) were validated through site-directed mutagenesis. Furthermore, conformational dynamics of mTAAR7e during receptor activation were characterized, providing insights into activation-related structural rearrangements. Together, these findings offer novel insights into the molecular logic of TAAR ligand selectivity and may advance our understanding of how TAARs mediate both olfactory and systemic aminergic signaling.

molecular biology↗

bioRxiv2025

High-throughput 3D super-resolution ultrasound imaging

Capturing fast hemodynamics in deep organs is essential for understanding microvascular regulation of organ responses to physiological demands and pathological stress. However, non-invasive three-dimensional (3D) imaging of these microscale processes remains challenging due to trade-offs between spatial resolution, imaging speed, and penetration depth. Here, we present fluctuation-based high-order super-resolution acoustic microscope (FLAME), a tracking-free 3D ultrasound imaging technology capable of fast microvascular angiography and flow measurement. Using as few as 30 volumes, FLAME improves 3D ultrasound resolution by 8-fold ([~]50 m) and shortens data acquisition time by over two orders of magnitude, from tens of seconds to tens of milliseconds, compared with conventional tracking-based super-resolution approaches1-6. This high-throughput capability supports high-fidelity imaging of tissue functions under flexible experimental settings. FLAME achieves an unprecedented 3D super-resolution frame rate of [~]40 Hz, capturing transient hemodynamic responses to various physiological and pathological stimuli in different mouse organs, from the microvascular level to the whole-body scale. With open-sourced implementation, FLAME provides an accessible platform for real-time, in-depth hemodynamic monitoring across diverse biomedical applications and clinical translation.

bioengineering↗

bioRxiv2025

KICDB: A Causality-Oriented Multi-Omics Database for Kinase Inhibitor-Induced Cardiotoxicity

BackgroundKinase inhibitors (KIs) are mainstays of targeted cancer therapy, but their clinical utility is frequently limited by cardiotoxicity. A systematic resource to explore the underlying causal mechanisms is urgently needed. MethodsWe present the KICDB (Kinase Inhibitor Cardiotoxicity Database), a comprehensive and interactive web server. KICDB is built upon a framework integrating large-scale transcriptomics meta-analysis with causal inference. ResultsThis database centralizes the findings from a comprehensive meta-analysis of 26 kinase inhibitors (KIs) across 7 studies (n=5291) identified 8,907 significant gene expression changes in human cardiomyocytes. To establish causality, we performed a two-pronged Mendelian randomization (MR) analysis testing hundreds of downstream genes and a panel of 43 key kinase proteins against 46 cardiovascular outcomes. This large-scale analysis revealed 26 significant causal associations, implicating novel molecular mediators in KI-induced cardiotoxicity. ConclusionsKICDB serves as a valuable and accessible platform for the cardio-oncology community. By integrating transcriptomic signatures with causal inference data, the database empowers researchers to formulate mechanistic hypotheses, accelerate biomarker validation, and guide the design of future cardioprotective strategies. URL: https://zhang-lab-database.shinyapps.io/KICDB/ Key PointsO_LIWe developed KICDB, a comprehensive and publicly accessible web server, to systematically investigate the causal mechanisms of KI-induced cardiotoxicity. C_LIO_LIKICDB integrates a large-scale meta-analysis of transcriptomic data from 26 KIs with a robust Mendelian randomization (MR) framework to move beyond correlation and infer causality. C_LIO_LIThe analysis identified 8,907 significant gene expression changes and 26 significant causal associations between KI-associated genes and 46 cardiovascular outcomes. C_LI

bioinformatics↗

bioRxiv2025

Dynamic connectivities of plant metacommunities at a millennial time-scale: the Beringia testbed

Ecological connectivity shapes ecosystem responses to climate change and is thought to underpin stability, yet its millennial-scale dynamics remain poorly resolved. We asked how spatial and temporal connectivity of plant metacommunities changed over the last 40 ka and which processes drove it. We analysed and compiled plant sedimentary DNA from 20 lake cores across Beringia (Siberia, Alaska) to investigate community dynamics and, for a high-resolution subset, applied beta- and zeta-diversity to track connectivity. Vegetation changed coherently across the glacial-Holocene transition, with trait shifts mirroring functional composition. Connectivity peaked during the late MIS3 and Last Glacial Maximum--likely aided by the Bering Land Bridge, mass effects and facilitation--collapsed during the Deglacial with rapid turnover, and rebounded in the Holocene as shrub and boreal communities expanded. Temporal zeta within sites exceeded spatial zeta, indicating strong local persistence and resilience. Tundra sites uninvaded by forest maintained continuous species pools. Overall, these patterns underscore the value of a metacommunity perspective for assessing millennial-scale connectivity changes.

ecology↗

bioRxiv2025

IsoPairFinder: A tool for biochemical pathway discovery using stable isotope tracing metabolomics

SummaryThe functional annotation of microbial genes lags far behind genome sequencing, leaving critical gaps in our knowledge of metabolic pathways. While integrating genetic manipulation with stable isotope tracing (SIT) metabolomics holds promise for pathway discovery, existing tools lack specialized capabilities for gene perturbation experiments. To address this need, we developed IsoPairFinder, a computational tool that identifies pathway intermediates by analyzing paired unlabeled (12C) and isotope-labeled (13C) metabolomics data from gene-edited microbes. By prioritizing substrate-specific feature pairs, IsoPairFinder efficiently prioritizes biologically relevant intermediates. Implemented as an open-source R package and integrated into the GNPS2 ecosystem, IsoPairFinder provides an accessible platform for the research community to accelerate novel pathway discovery and validation. Availability and implementationIsoPairFinder is freely available as an open-source R package (https://github.com/DoddLab/IsoPairFinder) and as a web-based workflow in the GNPS2 ecosystem (https://gnps2.org/workflowinput?workflowname=isopairfinder_nextflow_workflow). Comprehensive tutorials are provided at https://doddlab.github.io/IsoPairFinder_Tutorials. These implementations support both command-line and graphical analysis workflows. Contactddodd2@stanford.edu Supplementary informationSupplementary information is available at Bioinformatics online.

bioinformatics↗

bioRxiv2025

Angptl5 restricts primitive hematopoiesis by modulating retinoic acid signaling in zebrafish

Homeostasis is essential for hematopoiesis, and its dysregulation can lead to severe pathological conditions. Retinoic acid (RA) is a key regulator that exerts concentration-dependent effects on both embryonic and adult hematopoiesis. However, the mechanisms that modulate RA signaling in hematopoietic processes remain poorly understood. Using zebrafish as a model, we identified angiopoietin-like protein 5 (Angptl5) as a critical regulator of hematopoietic homeostasis. Loss of Angptl5 function resulted in myeloid hyperplasia in the anterior lateral plate mesoderm (ALPM) and anterior expansion of erythroid progenitors in the posterior lateral plate mesoderm (PLPM)-- phenotypes consistent with attenuated RA signaling. Molecular analyses confirmed impaired RA signaling in angptl5{Delta}10/{Delta}10 mutants, and exogenous RA supplementation fully rescued the hematopoietic defects. Mechanistically, we found that Angptl5 transcriptionally activates retinol dehydrogenase dhrs9 through its interaction with Integrin 6l{beta}5. Our findings establish Angptl5 as a novel and essential regulator of embryonic hematopoiesis and reveal a previously unrecognized mechanism controlling hematopoietic homeostasis. These insights position Angptl5 as a potential therapeutic target for hematological disorders.

developmental biology↗