SEARCH · PubMed Health

Results for “ATAC-seq”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed2026

Integrative ATAC-seq and RNA-seq analysis reveals lactation performance between Sewa sheep and East Friesian sheep.

Lactation performance is a pivotal economic trait in sheep production, yet its underlying epigenetic regulatory mechanisms remain poorly understood. In the present study, we integrated ATAC-seq and RNA-seq to compare chromatin accessibility landscapes and transcriptomic in mammary gland tissues from Sewa sheep (SWS) and East Friesian sheep (EFS). Histological characterization revealed that SWS exhibited significantly smaller mammary acini area, smaller lipid droplet area, and reduced lipid droplet diameter compared to EFS. ATAC-seq analysis identified 15,902 differentially accessible regions (DARs) between the two breeds, with motif enrichment analysis uncovering key transcription factors potentially governing lactation traits. RNA-seq analysis revealed 1,163 differentially expressed genes (DEGs), which were involved in lactation regulation. Integrated analysis identified 441 overlapping genes, and enriched in glycolysis/gluconeogenesis (e.g., PGAM1, ENO1) and pyruvate metabolism (e.g., ACACA, ACSS1, ACYP1). Collectively, our study provides new insights into the epigenetic regulatory mechanisms underlying lactation performance differences in sheep.

Animals↗

PubMed2026

Alignment-free integration of single-nucleus ATAC-seq across species with sPYce.

Changes in gene regulation largely contribute to differences in cellular identities and phenotypes between species. Single-nucleus assays for transposase-accessible chromatin with sequencing (snATAC-seq) are an efficient strategy to identify putative gene regulatory elements and provide new insight into evolutionary divergence of regulatory programmes. However, no dedicated framework exists to integrate and compare snATAC-seq data across species, while methods designed for single-cell gene expression data have serious limitations. Here we present sPYce, a cross-species snATAC-seq integration method that relies on sequence composition similarities through k-mer histograms of regulatory regions, removing the need for genome alignments to anchor data from different species. sPYce can embed datasets from multiple species into the same mathematical space and permits further downstream analysis steps. We benchmarked sPYce against existing approaches on two publicly available datasets spanning more than 160 myr of evolution, showing that it successfully uncovers conserved cellular programmes while preserving biologically relevant species-specific differences. By comparing cerebellar development in mice and opossums, sPYce identifies regulatory divergence in granule cell differentiation programmes, particularly driven by nuclear factor 1. As an easy-to-use, alignment-free cross-species snATAC-seq integration approach, sPYce opens new perspectives to compare gene regulatory evolution across species.

Animals↗

PubMed2026

Trichoderma reesei Nsd3 transcription factor: pleiotropic roles in development, stress response, secondary metabolism, and cellulase production.

Trichoderma reesei is known for its ability to secrete high amounts of cellulases, enzymes of fundamental importance in generating products from lignocellulosic biomass. Diverse signaling pathways and transcription factors (TFs) control the cellulolytic repertoire in T. reesei to ensure correct adaptation to the environment. Here, we analyzed RNA-Seq data and identified a new potential regulator of cellulase production in T. reesei: a novel TF named Nsd3, a homolog of NsdC from Aspergilli. Deletion of nsd3 reduced vegetative growth and conidiation on solid medium. Phenotypic characterization of the Δnsd3 strain showed that it is more sensitive to osmotic stress, but more resistant to cell wall and oxidative stresses. Our results showed that Nsd3 is a repressor of cellulase expression by directly regulating key genes in the cellulolytic pathway, an unreported role for this TF in fungi. Loss of nsd3 leads to a faster and more robust induction of cellulolytic genes, and higher cellulase and hemicellulase activities. Transcriptional profiling by RNA-Seq, chromatin accessibility profiling by ATAC-Seq, and protein-DNA interaction assays showed that sugar transporters are important targets of Nsd3 during cellulase expression regulation. Combined with microscopy and gene expression analyses, the ATAC-Seq data also highlighted Nsd3 as a central regulator of cell wall remodeling and organization. Furthermore, the transcriptomics also showed that Nsd3 regulates genes involved in secondary metabolism. These results showed that Nsd3 regulates several physiological processes and provide novel insights into the regulatory system of cellulases in T. reesei that can be used in the design of high-performance strains for biorefinery.IMPORTANCETrichoderma reesei is a key player in the production of hydrolytic enzymes for the degradation of lignocellulose biomass, and transcription factors are important targets for genetic engineering to construct cellulase-hyperproducing strains. Here, we identified the transcription factor Nsd3 and characterized its role as a regulator of cellulase production in T. reesei. We applied two powerful genomics methods (transcriptome sequencing and chromatin accessibility sequencing) to unravel the global role of Nsd3 and its regulatory mechanism. Nsd3 participates in various biological processes in T. reesei, including cell wall remodeling, calcium metabolism, and secondary metabolism, in addition to regulating the expression of sugar transporters. Protein-DNA interaction assays demonstrate that Nsd3 acts through important genes to regulate cellulase expression, including ace4, crt1, stp1, and cel1b. Our study provides mechanistic insights about how Nsd3 regulates diverse physiological processes in T. reesei. This work also applied ATAC-Seq for the first time to study chromatin accessibility in T. reesei.

ATAC-Seq↗

PubMed2026

How negative sampling shapes the performance of transcription factor binding site prediction models.

MOTIVATION: Transcription factors (TFs) are key players in gene regulation and development, where they activate and repress gene expression through DNA binding. Predicting transcription factor binding sites (TFBSs) has long been an active area of research, with many deep learning methods developed to tackle this problem. These models are often trained on TF ChIP-seq data, which is generally seen as only providing positive samples. The choice of datasets and negative sampling techniques is a critical yet often overlooked aspect of this work. RESULTS: In this study, we investigate the impact of different negative sampling techniques on TFBS prediction performance. We create high-quality test datasets based on ChIP-seq and ATAC-seq data, where true negatives can be identified as positions that are accessible but not bound by the TF in question. We then train models using various negative sampling techniques, including genomic sampling, shuffling, dinucleotide shuffling, neighborhood sampling, and cell line specific sampling, simulating cases where matching ATAC-seq data is not available. Our results show that, generally, metrics calculated on training datasets give inflated performance scores. Of the tested techniques, genomic sampling of negatives based on similarity to the positives performed by far the best, although still not reaching the performance of baseline models trained on high-quality datasets. Models trained on dinucleotide shuffled negatives performed poorly, despite being a common practice in the field. Our findings highlight the importance of carefully selecting negative sampling techniques for TFBS prediction, as they can significantly impact model performance and the interpretation of results. AVAILABILITY AND IMPLEMENTATION: The code used in this study is available at https://github.com/NatanTourne/TFBS-negatives (DOI: 10.5281/zenodo.18007567).

Binding Sites↗

PubMed2026

DNA-aware evaluation and debiasing of sequence-to-function models.

MOTIVATION: Genome sequence-to-function (S2F) models are widely used to interpret base-resolution functional genomics assays. Most S2F models are trained and evaluated against observed counts and profile-shapes using statistical objectives and fidelity metrics. These choices are well motivated, but they are DNA-independent. At the same time, experimental measurements arise from DNA-dependent assays with distinct characteristics. This mismatch motivates a complementary DNA-aware evaluation of S2F-predicted and experimental functional genomic tracks. RESULTS: We study DNA-dependency of experimental and S2F-predicted tracks using track-conditional genome language models (cgLMs). cgLMs predict masked nucleotides from a conditioning track under controlled DNA visibility. Across ATAC-seq and TF ChIP-seq peaks from GM12878 and K562, cgLM-probing reveals a consistent masked DNA-decodability gap between many experimental and S2F-predicted tracks. In particular, single-task (e.g. BPNet) and multi-task (e.g. AlphaGenome) S2F-predicted tracks enabled cgLMs to recover masked nucleotides with significantly higher accuracy and confidence than matched experimental tracks. Analyses of nonpeak and dinucleotide-shuffled sequences show that this gap is not confined to peaks and is not captured by standard DNA-agnostic profile-shape fidelity metrics alone. ChromBPNet Tn5-denoised predictions were an exception and behaved closer to the experimental regime, suggesting that staged training may reduce the gap. We then convert this diagnostic into a critic-derived objective, DNA-dependency matching (DDM), using a frozen multi-headed cgLM critic. We introduce Critic-Guided Profile-Shape Editing (CGPSE), a preliminary post hoc debiasing framework for frozen S2F models. In GM12878 ATAC-seq, CGPSE partially reduces the masked DNA-decodability gap for AlphaGenome and BPNet predictions, while exposing a tradeoff with profile-shape fidelity. AVAILABILITY AND IMPLEMENTATION: https://github.com/li-lab-mcgill/dna-aware-s2f-eval.

DNA↗

PubMed2026

Disentangling covariate effects on single-cell-resolved epigenomes with DeepDive.

Understanding the effects of individual biological factors from single-cell-resolved epigenomic data is hindered by multicollinearity, particularly in human cohorts. We introduce DeepDive, a deep-learning framework designed to systematically disentangle known and unknown sources of variation in single-nucleus ATAC-seq data. DeepDive accurately reconstructs chromatin accessibility, outperforms state-of-the-art methods with incomplete covariate information, and robustly recovers true biological signals from even highly entangled covariates, unlocking counterfactual, "what-if," analyses. Applying DeepDive to pancreatic islet cells, we perform counterfactual analyses to prioritize covariates associated with a type 2 diabetes-linked beta-cell subtype and nominate transcription regulators. DeepDive offers a powerful and unbiased tool for mechanistic discovery in complex human disease cohorts.

disentanglement↗

PubMed2025

Exposure to zinc oxide nanoparticles inhibits preimplantation embryonic development by disrupting zygotic genome activation.

The potential adverse effects of zinc oxide nanoparticles (ZnONPs) on human reproductive health may arise from their increasing industrial and commercial applications. However, their effects on preimplantation embryonic development and the related molecular mechanisms are still not well understood. Here, we demonstrate that ZnONPs exposure exhibit toxicity to a critical developmental period in mice. We observed that sustained exposure to ZnONPs in vitro resulted in embryonic development arrest at the 2-cell stage. To identify the susceptible stage, we controlled experiments to treat embryos with ZnONPs in the different processes of early embryonic development and determined that ZnONPs mainly to affect 2-cell stage embryos. According to the RNA-seq and EU (5-ethynyl uridine) analysis, the transcriptional activity of minor ZGA genes increased in the late 2-cell embryos following ZnONPs exposure. Subsequently, we employed multi-omics assays, including CUT&Tag and ATAC-seq. We found that ZnONPs exposure led to increased enrichment of H3K27ac (Histone H3 acetylated lysine 27) in late 2-cell embryos and enhanced chromatin accessibility, which led to abnormal upregulation of minor zygotic genome activation (ZGA) genes. In addition, the direct occupancy of ZnONPs at H3K27ac modification sites was verified through pulldown and immunoprecipitation. In conclusion, our findings demonstrate that ZnONPs exposure disrupting minor ZGA by interfering with H3K27ac erasure on the embryonic genome and ultimately impairing the developmental potential of embryos.

Animals↗

PubMed2026

Evaluating the pathogenic significance of unique chromosomal variants in craniosynostosis using patient-derived induced pluripotent stem cells and mouse modelling.

PURPOSE: Unravelling causal links between unique structural/copy-number variants (SV/CNV) and associated phenotypes is essential for correct genetic counselling. We investigated two families in which patients with craniosynostosis had SV/CNV potentially dysregulating a fibroblast growth factor (FGF)-encoding gene; a 730 kb dup(4)(q21.21) including FGF5; and a complex 568 kb interspersed 13q12.11 duplication, located 841 kb from FGF9. METHODS: We combined bioinformatic predictions of altered topologically-associating domain (TAD) structure, with experimental analysis (RNA- and ATAC- [assay for transposase-accessible chromatin] sequencing) of patient induced pluripotent stem cell lines (iPSCs) differentiated to neural crest (NCC) and osteoprogenitor (OPC) identities. For the dup(4)(q21.21) we generated a mouse bearing an equivalent rearrangement using CRISPR-Cas9 targeting. RESULTS: TAD analysis suggested potential dysregulation of the FGF5/FGF9 gene by bringing it into a novel genomic milieu. The RNA- and ATAC-seq assays demonstrated FGF5/FGF9 upregulation (2.7-18x) and local opening of chromatin, in 3/4 cell lines. For the dup(4)(q21.21), a causal role was supported by the mouse model, whereas interpretation of the 13q12.11 SV is confounded by a co-existing FOXP2 pathogenic variant. CONCLUSION: Patient iPSC-differentiated NCC and OPC lines, combined with TAD-based modelling to generate testable functional hypotheses, provide valuable functional evidence when evaluating causation of unique SV/CNV in craniosynostosis.

copy-number variant↗

PubMed2026

Prdm15 deficiency perturbs hematopoietic stem and progenitor cell homeostasis.

The maintenance of homeostasis in hematopoietic stem and progenitor cells (HSPCs) is essential for the proper development of the entire hematopoietic system. However, the mechanisms underlying this regulatory equilibrium remain elusive. Here, we report that Prdm15 deficiency in HSPCs induces the accumulation of immature hematopoietic stem cells in mice. A series of transplantation assays shows that these cells display impaired reconstitution capacity and competitive fitness, which are associated with abnormal differentiation trajectories and transcriptional alterations identified by single-cell RNA sequencing. Mechanistically, integrated multi-omics analyses including ATAC-seq and CUT&Tag sequencing of HSPCs indicate that Prdm15 deficiency induces significant transcriptional and epigenetic alterations, particularly affecting the methyltransferase KMT2C and altering H3K4me1 and H3K27ac modifications at the promoters of hematopoietic developmental genes. Collectively, our findings establish PRDM15 as a critical epigenetic regulator of HSPCs, offering valuable insights into the molecular mechanisms underlying hematopoietic homeostasis.

Cell differentiation↗

PubMed2026

Rbp-Jκ controls NK cell late maturation and migration via chromatin landscape remodeling.

The transcriptional regulator Rbp-Jκ is a pivotal molecular switch in Notch signaling; however, its cell-intrinsic role in natural killer (NK) cell maturation and migration remains incompletely understood. Here, we demonstrate that NK cell-specific deletion of Rbp-Jκ (Ncr1iCre × Rbp-Jκfl/fl, Rbp-JκΔNK) impairs NK cell terminal maturation and migration, as evidenced by increased retention of NK cells in bone marrow, a reduced number of circulating NK cells and decreased expression of migration mediators (CD62L, S1pr5, and Cx3cr1). Despite exhibiting an activated phenotype, Rbp-Jκ-deficient NK cells fail to control B16F10 lung metastases in vivo because of impaired tissue mobilization. Multiomics (scRNA-seq/scATAC-seq, bulk ATAC-seq, and CUT&Tag) reveal that Rbp-Jκ orchestrates chromatin remodeling in NK cells, suppressing the expression of genes related to NK cell activation and cytotoxicity while promoting the expression of genes involved in ribosome and oxidative phosphorylation. Notably, Rbp-Jκ directly binds to the Kruppel-like factor 2 (Klf2) promoter, and loss of Rbp-Jκ reduces both the mRNA and protein levels of Klf2. Klf2 overexpression rescues the decreased expression of CD62L and CX3CR1 in Rbp-Jκ-deficient NK cells. The cooccupancy of Rbp-Jκ and Klf2 at shared genomic loci is confirmed by ChIP-qPCR. In summary, our study reveals that Rbp-Jκ acts as a master regulator of NK cell terminal maturation and tissue homing via chromatin reprogramming, with Klf2 acting as its critical downstream transcription factor.

Animals↗

PubMed2026

In vivo genome-wide CRISPR screens identify FOXR1 as a suppressor of CD8+ T cell antitumor immunity.

T cell dysfunction critically limits the efficacy of T cell-based immunotherapies in solid tumors, yet the intrinsic regulators of T cell dysfunction remain incompletely understood. Through an in vivo genome-wide CRISPR screen in tumor-infiltrating CD8+ T cells, we identified Forkhead Box R1 (FOXR1) as a potent transcriptional suppressor of CD8+ T cell effector functions. Genetic ablation of FOXR1 significantly enhanced cytokine production and cytotoxic capacity in both murine and human CD8+ T cells, whereas its overexpression impaired T cell activation and effector molecule expression. Mechanistically, multiomics integration of RNA-seq, CUT&Tag-seq, and ATAC-seq revealed that FOXR1 binds directly to promoter regions of key effector genes, including IL2, GZMB, and PRF1, and represses their expression. Importantly, FOXR1 deletion in human anti-CD19 CAR T cells improved their efficacy against solid tumors, demonstrating that FOXR1 is a checkpoint of T cell effector function and targeting FOXR1 is a promising strategy to enhance CAR T cell efficacy against solid tumors.

Animals↗

PubMed2026

Predicting gene-specific regulation with transcriptomic and epigenetic single-cell data.

MOTIVATION: Analysis of single cell ATAC-seq and RNA-seq data has allowed to gain unprecedented insights into gene regulation by allowing to define cell type-specific regulatory regions and their effects on gene expression. While powerful, such analysis is challenging due to the inherent sparsity of single cell data. RESULTS: We present a new approach, MetaFR, to learn gene-specific models that link open-chromatin variation from scATAC-seq data to gene expression from scRNA-seq. Using efficient regression trees, we illustrate that accurate expression prediction models can be learned on the single-cell or meta-cell level. Validation was done using fine-mapped eQTLs. Meta-cell models were found to outperform single-cell models for most genes. Comparison to the SOTA method SCARlink revealed advantages of MetaFR in terms of runtime and prediction performance. MetaFR thus allows time-efficient analysis and obtains reliable models of gene expression prediction, which can be used to study gene regulation in any organism for which scRNA-seq and scATAC-seq data is available. AVAILABILITY AND IMPLEMENTATION: MetaFR is available under https://github.com/SchulzLab/MetaFR.

Single-Cell Analysis↗

PubMed2026

DeepGeSeq: deep learning library for genomic sequence modeling and analysis.

MOTIVATION: Deep learning methods have demonstrated significant potential in genomics, enabling broad applications such as sequence activity prediction, regulatory rule identification, and variant effect quantification. However, their widespread adoption is often hindered by the steep computational learning curve required for model construction, training, and downstream biological interpretation. Here, we introduce DeepGeSeq, a user-friendly Deep-learning library tailored for Genomic Sequence modeling and analysis. RESULTS: By integrating state-of-the-art architectural modules, DeepGeSeq streamlines the entire deep learning workflow, requiring minimal user input via a simple configuration file and an intuitive agentic skill. We comprehensively validate the efficacy of DeepGeSeq through diverse case studies, encompassing pipeline verification using synthetic datasets, the reproduction and application of established models, and model fine-tuning coupled with biological interpretation on user-defined data. Furthermore, we demonstrate DeepGeSeq's versatility in domain-specific applications, including single-cell ATAC-seq modeling for cell-type clustering, and MPRA data modeling coupled with in silico saturation mutagenesis to dissect cis-regulatory elements. Ultimately, DeepGeSeq bridges the gap between computational complexity and biological discovery, providing an accessible resource that facilitates the development and broad application of deep learning methods in genomics research. AVAILABILITY AND IMPLEMENTATION: https://github.com/JiaqiLi1024/DeepGeSeq.

Deep Learning↗

PubMed2026

Multi-omics analysis of glucocorticoid receptor crosstalk with Type I and Type II inflammatory signaling in human airway smooth muscle cells.

Airway smooth muscle (ASM) dysfunction in obstructive airway disease is treated with glucocorticoids. Through RNA-seq analysis of cultured human ASM, we identified repressive effects of dexamethasone, a glucocorticoid, on the baseline expression of a subset of genes that are induced by either IL1B or IL13, which model Type I and Type II inflammation, respectively. ChIP-seq analysis of glucocorticoid receptor (GR) and the p65 subunit of NFkB occupancy indicated canonical motifs for both factors occur at sites of p65 occupancy but did not provide biochemical support for significant repressive tethering between GR and p65. Instead, ATAC-seq revealed significant chromatin remodeling and increased accessibility at binding motifs for the NFkB complex in association with dex + IL1B co-treatment in comparison to IL1B treatment alone. Our data support a competition-based primary repressive effect of glucocorticoids on both IL1B and IL13 signaling and provide evidence for transcriptional cooperation between GR and NFkB on a genome-wide basis in ASM, including at regulatory elements that control expression of anti-inflammatorygenes.

chromatin↗

PubMed2026

Multi-omics analysis identifies key genes and functional loci affecting teat number in American Large White and Landrace pigs and their application in optimizing genomic selection models.

BACKGROUND: Teat number is a crucial economic trait in pigs. It directly affects the ability of sows to lactate, which in turn influences the survival and health of piglets. The teat number of French Large White pigs is close to 16, while the teat number of American Large White and Landrace pigs is about 14. In order to improve the teat number of American Landrace and Large White pigs through molecular approaches and precise breeding techniques, we genotyped 2,131 American Landrace and 4,564 American Large White with teat number phenotype using a 50 K SNP chip. Then, the SNP-chip data was imputed to the level of whole-genome sequencing (iWGS). Based on iWGS data, we conducted GWAS to identify novel, significant SNPs associated with teat number and to incorporate them into genomic selection. RESULTS: In Landrace pigs, significant SNPs for TTN mapped to SSC2, SSC7, SSC8, and SSC14; the SSC8 and SSC14 effects are novel. LTN mapped to SSC7, RTN to SSC7 and SSC8. The lead SSC7 SNP explained 2.60% of TTN phenotypic variance. In Large White pigs, significant SNPs were detected on SSC7 and SSC10 for TTN; SSC7, SSC10, and SSC12 for LTN; and SSC7 and SSC10 for RTN. The most significant locus on SSC7 accounted for 2.99% of the phenotypic variance in TTN. Additionally, a multi-population meta-analysis detected significant novel SNPs for LTN on SSC1 and SSC8. By utilizing Bayesian fine mapping, the most precise QTL confidence interval on SSC7 for both TTN and RTN in Large White pigs was reduced to 40 kb. By integrating functional gene annotation with RNA-seq and ATAC-seq data from Erhualian and Bamaxiang pigs mammary placodes at embryonic day 26, we prioritized PTPN13, TRPV3, ZDHHC13, and BRD2 as novel candidate genes for teat number. We then incorporated the significant SNPs to GBLUP and benchmarked genomic-selection accuracy. In both breeds, fitting the top SNP as fixed maximized prediction for TTN and RTN, whereas treating all significant loci as an additional random effect optimized LTN. CONCLUSIONS: Our findings provide a theoretical basis for dissecting new key genes affecting teat number and for advancing molecular breeding of teat number in pigs.

Animals↗

PubMed2026

Quantitative trait loci mapping of gene expression and chromatin accessibility in primary fibroblasts reveals shared allelic effects between Latin American and European ancestries.

BACKGROUND: Quantitative Trait Locus (QTL) analysis of molecular data has identified genetic variants associated with traits such as gene expression, and colocalization of these functional QTL with GWAS risk loci has offered insights into the genetic basis of human disease. We employed gene expression (RNA-seq) and chromatin accessibility (ATAC-seq) obtained from human primary fibroblasts to investigate quantitative trait loci (QTLs) in cohorts ascertained for bipolar disorder of European (n = 150) and Latin American (n = 96) ancestries. RESULTS: Leveraging data from three countries of origin (The Netherlands, Colombia, Costa Rica) within our cohort, we characterized differences among individuals at the SNP, gene, and accessible-chromatin levels to compute ancestry-specific expression (e)QTLs and chromatin-accessibility (ca)QTLs. Across ancestries, we observed R2 ≥ 0.93 for eQTL effect sizes and R2 ≥ 0.95 for caQTLs, indicating a high degree of concordance. Integrating chromatin data with expression and genotype information enabled precise fine-mapping of eQTLs, yielding 203 genes with high-confidence (posterior probability > 90%) candidate regulatory pathways. In downstream analyses, transcriptome-wide (TWAS) and chromatin-wide (CWAS) association studies with brain- and skin-related GWAS identified 36 TWAS-significant genes and 77 CWAS-significant open chromatin regions. CONCLUSIONS: These findings underscore the shared genetic regulatory mechanisms across European and Latin American ancestries, while demonstrating that ancestry-specific reference panels enhance the accuracy of TWAS and CWAS in diverse populations. More broadly, this study highlights the value of paired multi-omic datasets from diverse cohorts for interpreting disease-associated genetic variation.

Humans↗

PubMed2026

SWI/SNF Alterations Define a Chromatin-Dependent Subtype of Urothelial Carcinoma.

PURPOSE: SWI/SNF (BAF) chromatin remodeling complex alterations are common in urothelial carcinoma, yet no biomarker-directed therapeutic strategies have been established for this population. We investigated whether BAF alterations delineate a biologically distinct, therapeutically actionable urothelial carcinoma subtype. EXPERIMENTAL DESIGN: We performed integrative genomic and transcriptomic analyses of 792 urothelial carcinoma tumors from the Oncology Research Information Exchange Network (ORIEN) and validated findings in the TCGA-BLCA cohort. Mechanistic studies incorporated RNA sequencing and ATAC-seq following histone deacetylase (HDAC) inhibition. Functional dependencies were assessed using patient-derived xenograft organoids and cell line models. Clinical relevance was explored in a biomarker-enriched investigator-initiated trial. RESULTS: Approximately half of urothelial carcinoma tumors exhibited BAF alterations, defining a previously unrecognized chromatin-altered molecular subtype characterized by activation of proliferative programs, loss of lineage identity, and altered metabolic signaling. This subtype was enriched for transcriptomic programs associated with HDAC inhibitor sensitivity and depleted of HDAC inhibitor resistance signatures. Mechanistically, HDAC inhibition induced widespread chromatin remodeling with reduced accessibility at AP-1 and TEAD-associated regions, and downregulation of E2F- and MYC-driven transcriptional networks. Functional studies confirmed enhanced HDAC inhibition sensitivity in ARID1A -mutated cell lines and a patient-derived organoid model. Early clinical observations demonstrated a durable responder treated with HDAC inhibitors and immunotherapy. CONCLUSIONS: BAF alterations define a chromatin-dependent tumor state in urothelial carcinoma that is selectively vulnerable to HDAC inhibition. Integrating genomic, epigenomic, functional, and early clinical evidence, these findings provide a rationale for biomarker-enriched clinical trials and HDAC inhibitor-based combination strategies in urothelial carcinoma.

Journal Article↗

PubMed2026

A latent activated olfactory stem cell state revealed by single-cell transcriptomic and epigenomic profiling.

The olfactory epithelium is one of the few regions of the nervous system that sustains neurogenesis throughout life. Its experimental accessibility makes it especially tractable for studying molecular mechanisms that drive neural regeneration in response to injury. In this study, we used single-cell sequencing to identify transcriptional and epigenetic processes involved in determining olfactory epithelial stem cell fate during injury-induced regeneration. By combining gene expression and accessible chromatin profiles of individual lineage-traced olfactory stem cells, we identified transcriptional heterogeneity among activated stem cells at a stage when cell fates are being specified. We further identified a subset of resting cells that appears poised for activation, characterized by accessible chromatin around silent genes prior to their expression in response to injury. These results provide evidence for a latent activated stem cell state in which a subset of quiescent olfactory epithelial stem cells are epigenetically primed to support injury-induced regeneration.

Animals↗