Biology subjects

Yu, H.

Publications and source records attributed to Yu, H..

At least 145 records · Page 8Linked to original sources

bioRxiv2025

Aromatic Patch in WhiB-Like Transcription Factors Facilitates Primary Sigma Factor Interaction in Mycobacterium tuberculosis

WhiB-like (Wbl) family proteins are a unique family of iron-sulfur ([4Fe-4S]) cluster-bound transcription factors found exclusively in Actinobacteria and actinobacteriophages, including the notoriously persistent pathogen Mycobacterium tuberculosis (Mtb). Despite their critical roles in cell development, stress response and antibiotic resistance, the mechanisms of gene regulation by the Wbl family proteins are not fully understood due to the lack of a canonical DNA-binding motif in most Wbl proteins. Here, we present structural and biochemical evidence demonstrating that all Mtb Wbl proteins bind to the same site in the conserved region 4 of the primary sigma 70 factor facilitated by a previously unrecognized structural motif, the aromatic patch, in the Wbl family. Our phylogenetic findings provide compelling evidence for a complex evolutionary relationship of Wbls between actinobacteria and the associated phages. Together, this work fills a critical gap in our understanding of the function, mechanism and evolutionary origin of Wbls.

biochemistry↗

bioRxiv2025

Impact of trait measurement error on quantitative genetic analysis of computer vision derived traits

BackgroundQuantitative genetic analysis of image- or video-derived phenotypes is increasingly being performed for a wide range of traits. Pig body weight values estimated by a conventional approach or a computer vision system can be considered as two different measurements of the same trait, but with different sources of phenotyping error. Previous studies have shown that trait measurement error, defined as the difference between manually collected phenotypes and image-derived phenotypes, can be influenced by genetics, suggesting that the error is systematic rather than random and is more likely to lead to misleading quantitative genetic analysis results. Therefore, we investigated the effect of trait measurement error on genetic analysis of pig body weight (BW). ResultsCalibrated scale-based and image-based BW showed high coefficients of determination and goodness of fit. Genomic heritability estimates for scale-based and image-based BW were mostly identical across growth periods. Genomic heritability estimates for trait measurement error were consistently negligible, regardless of the choice of computer vision algorithm. In addition, genome-wide association analysis revealed no overlap between the top markers identified for scale-based BW and those associated with trait measurement error. Overall, the deep learning-based regressions outperformed the adaptive thresholding segmentation methods. ConclusionsThis study showed that manually measured scale-based and image-based BW phenotypes yielded the same quantitative genetic results. We found no evidence that BW trait measurement error could be influenced, at least in part, by genetic factors. This suggests that trait measurement error in pig BW does not contain systematic errors that could bias downstream genetic analysis.

genetics↗

bioRxiv2025

Post-replicative initial expression of the cell fate regulator PAX6 during neuroectoderm differentiation

The development of multicellular organisms requires precise coordination between cell division and differentiation. Cell division generates the necessary number of cells, while differentiation creates distinct cell identities, forming tissues and organs. The transcription factors SOX2 and PAX6 specify neuroepithelial cells, the earliest neural progenitor cells (NPCs) during brain development. How lineage specification is coordinated with the cell cycle is not fully understood. Here, we show that PAX6 expression occurs during a narrow time window--between 48 and 72 hours--after neural induction of human embryonic stem cells (ESCs). Flow cytometry analyses and time-lapse imaging further show that PAX6 expression starts during the G2 phase of the cell cycle. We identify a novel 500-bp PAX6 promoter that drives its G2-specific expression. PAX6 expression is independent of known regulators of cell-cycle-dependent transcription, suggesting the existence of a novel mechanism. S-phase block by hydroxyurea prevents PAX6 expression and differentiation into NPC. Thus, NPC fate specification is coupled to cell cycle progression and occurs after the completion of DNA replication. This post-replicative lineage commitment ensures the creation of two daughter cells of identical cell fate following cell division.

cell biology↗

bioRxiv2025

Cryo-EM structure of DNA-unbound human MCM2-7 complex reveals new disease-relevant regulation

Chromatin loading of the hexameric replicative helicase MCM2-7 complex requires coordinated interactions with the origin recognition complex (ORC), CDC6, and CDT1. MCM2-7 not bound to DNA forms a single hexamer (SH) with an open DNA entry gate. Two MCM2-7 SHs are loaded sequentially to form the double hexamer (DH) that encircles the DNA duplex. Activated MCM2-7 then unwinds DNA and initiates DNA replication. Our cryo-electron microscopy analyses show that a fraction of human MCM2-7 without DNA exists as DH. Unexpectedly, we find that the MCM3 winged helix domain (WHD) docks on MCM2 in both DNA-free DH and SH, creating a safety latch across the DNA entry gate to block DNA entry into the central channel. The safety latch can be opened by ORC-CDC6 binding. Disrupting this latch by designed or human disease-related mutations of MCM3 causes replication defects and DNA damage checkpoint activation. Our findings uncover a new regulated step in MCM2-7 loading with implications for human diseases.

biophysics↗

bioRxiv2025

Venus-MAXWELL: Efficient Learning of Protein-Mutation Stability Landscapes using Protein Language Models

In-silico prediction of protein mutant stability, measured by the difference in Gibbs free energy change ({Delta}{Delta}G), is fundamental for protein engineering. Current sequence-to-label methods typically employ the two-stage pipeline: (i) encoding mutant sequences using neural networks (e.g., transformers), followed by (ii) the {Delta}{Delta}G regression from the latent representations. Although these methods have demonstrated promising performance, their dependence on specialized neural network encoders significantly increases the complexity. Additionally, the requirement to individually compute latent representations for each mutant site negatively impacts computational efficiency and poses the risk of overfitting. This work proposes the Venus-MO_SCPLOWAXWELLC_SCPLOW framework, which reformulates mutation {Delta}{Delta}G prediction as a sequence-to-landscape task. In Venus-MO_SCPLOWAXWELLC_SCPLOW, mutations of a protein and their corresponding {Delta}{Delta}G values are organized into a landscape matrix, allowing our framework to learn the {Delta}{Delta}G landscape of a protein with a single forward and backward pass during training. Besides, to facilitate future works, we also curated a large-scale {Delta}{Delta}G dataset with strict controls on data leakage and redundancy to ensure robust evaluation. Venus-MO_SCPLOWAXWELLC_SCPLOW is compatible with multiple protein language models and enables these models for accurate and efficient {Delta}{Delta}G prediction. For example, when integrated with the ESM-IF, Venus-MO_SCPLOWAXWELLC_SCPLOW achieves higher accuracy than ThermoMPNN with 10x faster in inference speed (despite having 50x more parameters than ThermoMPNN). The training codes, model weights, and datasets are publicly available at https://github.com/ai4protein/Venus-MAXWELL.

bioinformatics↗

bioRxiv2025

Peptides alleviate cognitive impairment by inhibiting and disassembling amyloid-beta aggregates in Alzheimer disease

Alzheimers disease (AD) is a devasting neurodegenerative disorder characterized by {beta}-amyloid formation, further exacerbated by RIPK1/RIPK3 necrosome-induced programmed necrosis (necroptosis). We previously showed that the RIPK1/RIPK3 necrosome forms a functional amyloid complex using its RIP homotypic interaction motifs (RHIMs). Here, we discovered that the core RIPK1/RIPK3 necrosome shares strikingly structural similarity to the C-terminal region of {beta}-amyloid (A{beta}42), and the RHIM-derived tetrapeptides (IQIG or VQVG) directly inhibit A{beta} aggregation, disassemble preformed A{beta} fibrils (PFFs), and reduce RIPK1 polymerization. Also, the peptides exhibit effective membrane permeability and could reduce A{beta}40 or A{beta}42-induced neural death and TNF-induced necroptosis in SH-SY5Y cells. IQIG and VQVG injected by ICV increase learning and memory abilities by reducing A{beta} plaques and hyperphosphorylated tau in the cortex and hippocampus of APP/PS1 double-transgenic mice. Mechanistically, the peptides directly interact with A{beta} to block A{beta} aggregation and alleviate microglia-mediated neuroinflammation. Strikingly, single-cell RNA sequencing revealed that the peptides-treated AD transgenic mice restored neuronal homeostasis with increased GABAergic neurons and decreased glutamatergic neurons. Furthermore, total cell-cell interaction strength increased while the AD risk gene Apoe expression decreased in the specific oligodendrocyte subtype of peptides-treated AD mice. Thus, our findings revealed that the peptides could improve cognition and memory capabilities and serve as promising structural templates for potential drugs against AD.

neuroscience↗

bioRxiv2025

Fish remain high in selenium long after mountaintop coal mines close

Mountaintop removal (MTR) coal mining generates large volumes of waste rock. Weathering of this waste rock releases selenium, which can bioaccumulate to levels that can harm, and even extirpate, downstream fish communities. This is well demonstrated in ecosystems impacted by active MTR operations; however, less is known about the long-term impacts after coal mines close. Here we show that MTR coal mines still present an acute threat to downstream fish populations, decades after mining ends. Crowsnest Lake (Alberta, Canada) receives runoff from the Tent Mountain Coal Mine, which closed in the 1980s and part of which was certified reclaimed. Fish in Crowsnest Lake contain tissue selenium concentrations (5-26 {micro}g/g dry weight) that exceed guidelines and rival fish selenium levels downstream of active MTR operations. This is despite lake water selenium concentrations ([≤]2 {micro}g/L) that are below water quality guidelines intended to protect fish. The clinical signs of selenium poisoning in fish are similar to the symptoms of Whirling Disease, which was first detected in the Crowsnest basin in 2016 making this the first aquatic system to be impacted by both stressors. This finding demonstrates that the biological impacts of MTR coal mining can persist long after mining operations end, and it suggests that any further coal mine development may well push the Crowsnest fishery beyond sustainability. SynopsisFish in Crowsnest Lake, Alberta, are high in selenium sourced from an abandoned mountaintop removal coal mine.

ecology↗

bioRxiv2025

Humans underestimate their body mass in microgravity: evidence from reaching movements during spaceflight

Astronauts consistently exhibit slower movements in microgravity, even during tasks requiring rapid responses. The sensorimotor mechanisms underlying this general slowing remain debated. Two hypotheses have been proposed: either the sensorimotor system adopts a conservative control strategy for safety and postural stability, or the system underestimates body mass due to reduced inputs from proprioceptive receptors. To dissociate these opinions, we studied twelve taikonauts aboard the China Space Station performing a classical hand-reaching task. Compared to their pre-flight performance and to an age-matched control group, participants showed increased movement durations and altered kinematic profiles in microgravity. Model-based analyses of motor control parameters revealed that these changes stemmed from reduced initial force generation in the feedforward control phase followed by compensatory feedback-based corrections. These findings providing support for the body mass underestimation hypothesis while being inconsistent with the strategic slowing hypothesis. Importantly, the sensory estimate of bodily property in microgravity is biased but immune from sensorimotor adaptation, calling for an extension of existing theories of motor learning.

neuroscience↗

bioRxiv2025

Computational Assessment of Circularization Impact on Saxitoxin G-quadruplex Aptamer Performance

Although high-affinity and high-specificity aptamers can be obtained by SELEX (Systematic Evolution of Ligands by Exponential Enrichment), and have good activity in vitro, their performance in vivo is poor. This is mainly because of the degradation of linear nucleic acids by nucleases in body fluids and the difficulty of maintaining stable 3D structures in complex body fluid environments, which seriously hinders the clinical application of aptamers. This makes circular aptamers, which can resist degradation and are more stable in complex body fluid environments, an attractive option. However, the cyclization process may have a considerable impact on the structure of the original linear aptamer, and blind cyclization may lead to a decrease in its affinity. Here, we developed a new method to guide the cyclization of saxitoxin (STX) aptamers based on molecular computation, and verified the activity of circular aptamers through bioactivity experiments to further verify the authenticity and reliability of our methods. Consistent with the computational analysis, although circularization disrupts the G4 structure, circular aptamer not only has a higher affinity than the linear one but also provides certain protection to mice and greatly prolongs their survival, which proves the accuracy and reliability of the circular structure designed by our computational method. Our findings provide important ideas for better guidance in the design of circular aptamers and demonstrate their great potential in therapeutic applications.

biochemistry↗

bioRxiv2025

Antibody Binding and Neutralizing Targets within the Predicted Structure of the Poxvirus Multiprotein Entry-Fusion Complex

The increased incidence of mpox emphasizes a need for new and improved vaccines. Poxviruses rely on a highly conserved but poorly characterized 11-protein entry-fusion complex (EFC), providing numerous potential targets. Here, we demonstrate that antibodies induced by six of 10 EFC proteins are neutralizing. Protein targets of the neutralizing and non-neutralizing antibodies are located within discrete regions of a model of the EFC predicted by AlphaFold3. Two newly identified targets, A16 and G9, at the apex of the EFC induced cross-neutralizing orthopoxvirus antibodies and protected female mice against a lethal VACV infection. Unexpectedly, antibodies to A16 and G9 were not detected following infection by attenuated or pathogenic VACV, likely due to physical sequestration of the proteins in the viral membrane. Our findings provide a model for the physical, immunogenic and antigenic structure of the EFC, new immunogens for incorporation into recombinant vaccines and suggest a novel poxvirus immune evasion strategy. 150 words.

microbiology↗

bioRxiv2025

Increasing Stemness Drives Prostate Cancer Progression, Plasticity, Therapy Resistance and Poor Patient Survival

BackgroundCancer progression is often accompanied by dedifferentiation and acquisition of stem cell-like properties (stemness). In prostate cancer (PCa), lineage plasticity and therapy resistance remain major clinical challenges, yet a unified quantitative transcriptomic framework connecting stemness, androgen receptor (AR) signaling, castration resistance, and disease progression across the PCa continuum is lacking. MethodsWe integrated 87,339 transcriptomic profiles from 33 preclinical and clinical datasets spanning the PCa continuum from normal prostate and treatment-naive primary PCa (Pri-PCa) to PCa treated with neoadjuvant ADT (nADT) and metastatic castration-resistant PCa (mCRPC), with single-cell RNA-seq analyses encompassing 115,197 cells. Cancer stemness was quantified using a transcriptome-derived mRNA-based Stemness Index (mRNAsi; hereafter Stemness), and a 12-gene PCa-Stem signature was developed to capture PCa-specific stemness. Stemness, PCa-Stem, canonical AR activity (c_AR-A), castration-reprogrammed AR activity (cr_AR-A), RB1-loss, PTEN-loss, and MYC activity signatures were quantified across cohorts. Functional validation included MYC inhibition and representative PCa-Stem signature gene depletion in PCa models. Clinical prognostic significance was evaluated in independent patient cohorts. ResultsThe Stemness score and c_AR-A increased concordantly during early prostate tumorigenesis but diverged with PCa progression: as Gleason grade increased, c_AR-A declined while Stemness continually increased. mCRPC exhibited the highest Stemness and lowest c_AR-A, a pattern recapitulated in Pten/Rb1/Trp53-deficient mouse models. Global Stemness increased progressively across the PCa continuum, was enriched in aggressive PAM50-LumB and PCS1 subtypes, associated with proliferative and lineage plasticity programs, and predicted poor patient survival. The newly derived 12-gene PCa-Stem signature provided a PCa-specific molecular representation of Stemness and tracked disease progression and poor patient survival. Network analyses identified a coordinated mitotic regulatory program linking MYC activity, RB1-loss, cr_AR-A, and the PCa-Stem signature. Spatial and single-cell transcriptomic analyses localized the PCa-Stem program to lineage plasticity-related epithelial cells and demonstrated progressive expansion of PCa-Stem epithelial cells during PCa progression. Functional perturbation of representative PCa-Stem signature genes, as well as genetic and pharmacological MYC inhibition, consistently suppressed Stemness-associated phenotypes in diverse PCa models. ConclusionsCancer Stemness quantitatively captures PCa aggressiveness, lineage plasticity, treatment resistance, disease progression, and poor patient survival. cr_AR-A, RB1 loss, and MYC activation cooperate to reinforce the high-Stemness state and therapy resistance in mCRPC. Collectively, our work establishes a trajectory-integrated transcriptomic framework defining cancer Stemness as a quantifiable molecular and clinical determinant of PCa aggressiveness, lineage plasticity, disease progression, therapy resistance and patient survival.

cancer biology↗

bioRxiv2025

High-resolution reconstruction of cell-type specific transcriptional regulatory processes from bulk sequencing samples

Biological systems exhibit remarkable heterogeneity, characterized by intricate interplay among diverse cell types. Resolving the regulatory processes of specific cell types is crucial for delineating developmental mechanisms and disease etiologies. While single-cell sequencing methods such as scRNA-seq and scATAC-seq have revolutionized our understanding of individual cellular functions, adapting bulk genome-wide assays to achieve single-cell resolution of other genomic features remains a significant technical challenge. Here, we introduce Deep-learning-based DEconvolution of Tissue profiles with Accurate Interpretation of Locus-specific Signals (DeepDETAILS), a novel quasi-supervised framework to reconstruct cell-type-specific genomic signals with base-pair precision. DeepDETAILS core innovation lies in its ability to perform cross-modality deconvolution using scATAC-seq reference libraries for other bulk datasets, benefiting from the affordability and availability of scATAC-seq data. DeepDETAILS enables high-resolution mapping of genomic signals across diverse cell types, with great versatility for various omics datasets, including nascent transcript sequencing (such as PRO-cap and PRO-seq) and ChIP-seq for chromatin modifications. Our results demonstrate that DeepDETAILS significantly outperformed traditional statistical deconvolution methods. Using DeepDETAILS, we developed a comprehensive compendium of high-resolution nascent transcription and histone modification signals across 39 diverse human tissues and 86 distinct cell types. Furthermore, we applied our compendium to fine-map risk variants associated with Primary Sclerosing Cholangitis (PSC), a progressive cholestatic liver disorder, and revealed a potential etiology of the disease. Our tool and compendium provide invaluable insights into cellular complexity, opening new avenues for studying biological processes in various contexts.

bioinformatics↗

bioRxiv2025

CanASM: A comprehensive database for genome-wide allele-specific DNA methylation identification and annotation in cancer

Allele-specific DNA methylation (ASM) provides critical insights into the complex genetic and epigenetic mechanisms regulating gene transcription. Emerging evidence suggests that ASM is particularly enriched in gene enhancer regions, and recent studies have demonstrated that ASM is increased in cancer tissues compared with normal tissues. Despite the increasing recognition of ASM as a potential biomarker in tumorigenesis, systematic resources dedicated to identifying and annotating ASMs in cancer contexts remain limited. In this study, we developed CanASM (https://bioinfor.nefu.edu.cn/CanASM/), the first comprehensive database specifically designed to identify and annotate ASM in cancer. In CanASM, ASM sites identified from bisulfite sequencing data across 31 cancer types and their matched normal tissue samples are cataloged. Importantly, CanASM includes extensive regulatory annotations for ASMs, including associated genes, cis-regulatory elements and transcription factor binding colocalizations, transcription factor affinity changes, etc. Users can query and explore ASMs using various parameters, such as single-nucleotide variations (SNVs), chromosomal coordinates, and gene names. The current version of CanASM includes 5,003,877 unique SNV-CpG pairs, including 3,056,776 index SNVs, of which 2,634,406 are single-nucleotide polymorphisms (SNPs), and 4,157,508 CpGs. With an intuitive interface for browsing, querying, analyzing, and downloading, CanASM serves as a valuable resource for researchers investigating cancer-associated genetic variations and epigenetic regulation in cancer. Author summaryIdentifying target genes and regulatory mechanisms of cancer-associated genetic variants remains a major challenge in the post-GWAS era. Existing databases like Pancan-meQTL and ASMdb have contributed to uncovering the role of genetic variants in cancer by linking DNA variations to methylation. However, they lack comprehensive regulatory annotations for such sites and rely solely on genomic proximity for target gene prediction, overlooking distal interactions. Our analysis using 3D interaction data reveals that over 94.8% of ASMs exhibit distal regulatory relationships, emphasizing their critical role in cancer epigenetics. Furthermore, these databases cover a limited number of cancer types (Pancan-meQTL: 23, ASMdb: 8). To address these limitations, we developed CanASM, a database that provides ASMs identified from BS-seq data for 31 human cancers, along with multidimensional regulatory annotations for ASM sites. This includes target genes, cis-regulatory elements (enhancers, ATAC-seq regions, insulators, 3D interactions, CpG islands), TFBSs, and GWAS cancer trait associations. Additionally, CanASM offers three interactive tools for analyzing TF binding affinity changes, predicting ASM target genes through 3D interactions, and identifying cell marker variations. As a comprehensive resource for SNV-driven epigenetic regulation in cancer, CanASM is helpful for in-depth research in cancer genetics and epigenetics.

bioinformatics↗

bioRxiv2025

Comprehensive Atomic-Scale 3D Viral-Host Protein Interactomes Enable Dissection of Key Mechanisms and Evolutionary Processes Underlying Viral Pathogenesis

Viral-human protein interactions are critical for viral replication and modulation of the host immune response. Structural modeling of these interactions is vital for developing effective antiviral therapies and vaccines. However, 99% of experimentally determined binary host-viral interactions currently lack structural information. We aimed to address this gap by leveraging computational protein structure prediction methods. Using extensive benchmarking, we found AlphaFold to be the most accurate structure prediction model for host-pathogen protein interactions. We then predicted the structures of 11,666 binary protein interactions across 33 viral families and created the most comprehensive atomic-scale 3D viral-host protein interactomes till date (https://3d-viralhuman.yulab.org). By integrating these interactomes with genetic variation data, we identified population-specific signatures of selection on variants coding for interfaces of viral-human interactions. We also found that viral interaction interfaces were less conserved than non-interface regions, a striking trend that is opposite to what is observed for host interfaces, suggesting different evolutionary pressures. Systematic analyses of interface sharing between host and viral proteins binding to the same host protein revealed mutation rate-dependent differences in interface mimicry. Similar mutation rate-dependent differences were seen in the interface sharing between viral proteins binding to a host protein. We also found that the patterns of E6 protein binding to KPNA2 differed between high- and low-risk oncogenic human papillomaviruses (HPVs), and clustering based on these binding patterns allowed the classification of HPVs with unknown oncogenic risk. Our interface mimicry analyses also unveiled a novel mechanism by which herpes simplex virus-1 UL37 suppresses the antiviral immune response through disruption of the TRAF6-MAVS signalosome interaction. Overall, our comprehensive 3D viral interactomes provide a resource at unprecedented scale and resolution that will enable researchers to explore how variation and signatures of selection influence viral interactions and disease progression. This tool also facilitates the identification of conserved and unique interaction patterns across viruses, empowering researchers to generate testable hypotheses and ultimately accelerate the discovery of novel therapeutic targets and intervention strategies.

systems biology↗

bioRxiv2025

Cortactin regulates metastatic dormancy of circulating tumor cells by suppressing mTOR-dependent senescence

Metastatic dormancy often refers to the stable cell cycle arrest of disseminated tumor cells (DTCs) at distant sites. However, whether circulating tumor cells (CTCs) in the blood microenvironment can enter a dormant state prior to extravasation and becoming DTCs remains unclear. Using patient-derived melanoma CTC lines and animal explant models (CDX), we identified a previously unrecognized role of the cytoskeletal regulator cortactin (encoded by CTTN) in controlling mTOR/p53-dependent senescence and metastatic dormancy. Cortactin was localized to Rab7-postive endosomes and engaged in late endosomal tethering and homeostasis. The depletion of cortactin resulted in the accumulation of aberrantly enlarged late endosomal aggregates that were positive for Rab7 and mTOR. The mTOR protein complex was accumulated and activated within these abnormal vesicular structures, leading to robust p53 activation through phosphorylation at serine (S) 15 and S33 sites. Consequently, melanoma CTCs underwent G0/G1 cell cycle arrest and entered cellular senescence. This unusual oncogene-induced senescence (OIS) mechanism was characterized by SASP upregulation, {beta}-galactosidase activity, depletion of Ki-67 and Lamin B1, and elevated mitochondrial ROS (mtROS) levels. Notably, a positive feedback loop between p53 and mtROS was essential for maintaining stable senescence in CTCs. In preclinical CDX mouse models, we developed a sequential therapeutic strategy combining cortactin depletion with anti-Bcl-xL senolytic drugs. Such "One-two punch" treatment strategy effectively eliminated viable CTCs and suppressed metastatic tumor growth in vivo. Thus, targeting cortactin to induce CTC senescence, followed by senolytic therapy, may represent a promising strategy to block CTC-mediated metastatic progression.

cancer biology↗

bioRxiv2025

Comprehensive Evaluation of Diverse Massively Parallel Reporter Assays to Functionally Characterize Human Enhancers Genome-wide

Massively parallel reporter assays (MPRAs) and self-transcribing active regulatory region sequencing (STARR-seq) have revolutionized enhancer characterization by enabling high-throughput functional assessment of regulatory sequences. Here, we systematically evaluated six MPRA and STARR-seq datasets generated in the human K562 cell line and found substantial inconsistencies in enhancer calls from different labs that are primarily due to technical variations in data processing and experimental workflows. To address these variations, we implemented a uniform enhancer call pipeline, which significantly improved cross-assay agreement. While increasing sequence overlap thresholds enhanced concordance in STARR-seq assays, cross-assay consistency in LentiMPRA was strongly influenced by assay-specific factors. Notably, our results show that LentiMPRA exhibits a strong preference for promoter-associated sequences rather than enhancers. Functional validation using candidate cis-regulatory elements (cCREs) confirmed that epigenomic features such as chromatin accessibility and histone modifications are strong predictors of enhancer activity. Importantly, our study validated transcription as a critical hallmark of active enhancers, demonstrating that highly transcribed regions exhibit significantly higher active rates across assays. Furthermore, we show that transcription enhances the predictive power of epigenomic features, enabling more accurate and refined enhancer annotation. Our study provides a comprehensive framework for integrating different enhancer datasets and underscores the importance of accounting for assay-specific biases when interpreting enhancer activity. These findings refine enhancer identification using massively parallel reporter assays and improve the functional annotation of the human genome.

genomics↗

bioRxiv2025

Genome-wide association studies reveal novel loci associated with carcass and body measures in goats (Capra hircus)

Elucidating the genetic architecture of local goat populations is crucial for improving breeding strategies and conservation efforts. In southwestern China, there are numerous local goat resources, featuring rich phenotypic and genetic variations. Nevertheless, in-depth research on their production performance is scarce. Therefore, in this study, whole-genome 7x resequencing was performed on 776 individuals of six goat breeds (Dazu Black Goat, Yudong Black Goat, Banjiao Goat, Hechuan White Goat, Chuandong White Goat, and Youzhou Black Goat) in Chongqing to deeply investigate their population structure, genetic relationships, and heritability, and to identify significant genes related to growth traits and carcass traits. The mapping of significant genes for growth and carcass traits identified novel genetic loci, including a significant association at position 63,248,396 within ASIP on chromosome 13, which was linked to both traits, indicating a potential pleiotropic effect. Additional candidate genes for growth traits included CXCL14, PTGFR, and DPYD (body weight); CCSER1, HMCN1, and MYOM1 (body length); MALRD1 and ASIP (withers height); and MEIS2 and NLRC5 (chest circumference). For carcass traits, key candidate genes included ASIP, ATP5G1, COX3 and BCAR3. Functional enrichment analysis highlighted the calcium signaling pathway, glycan biosynthesis, and cytokine receptor interactions as key biological pathways influencing these traits. These findings provide novel insights into the genetic mechanisms underlying economically important traits in Chongqing local goats. The identification of ASIP as a pleiotropic gene, along with other newly discovered loci, offers valuable targets for genetic improvement and selective breeding programs, enhancing the productivity and sustainability of local goat populations.

genomics↗

bioRxiv2025

H3K4me3 instructs transcription at intergenic active regulatory elements

Mammalian genomes undergo pervasive transcription in both genic and intergenic regions. Tri-methylation of histone H3 lysine 4 (H3K4me3) is a deeply conserved and functionally important histone modification enriched at transcriptionally active promoters, where it facilitates RNA polymerase activity. H3K4me3 is also commonly found in intergenic regions, where its role is poorly understood. We interrogated the role of H3K4me3 at intergenic regulatory elements by using epigenetic editing to efficiently deposit H3K4me3 at intergenic loci. We find that H3K4me3 instructs RNA polymerase activity and is actively remodeled at intergenic regions, shedding light on these important but poorly understood regions of the genome.

genetics↗