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PubMed2026

Detecting Meiotic Crossing-Overs in Maize Using Chromatin Immunoprecipitation-Sequencing (ChIP-seq).

During meiosis, homologous chromosomes engage in reciprocal exchanges of segments in a process known as crossing over (CO). About 85% of CO events in maize are products of the class I pathway. Class I COs are interference-sensitive, meaning that the formation of one CO reduces the likelihood of another CO forming close by. This protocol describes a chromatin immunoprecipitation-sequencing (ChIP-seq)-based method for mapping meiotic COs in maize, using an antibody against MutL Homolog 3 (MLH3), a key component of the class I CO pathway. CO sites are determined by Illumina sequencing of DNA isolated from MLH3-associated chromatin fragments. Traditionally, COs have been identified through genetic mapping, which relies on the segregation of genetic markers in the progeny of hybrid plants. However, conventional genetic mapping provides limited resolution and requires large numbers of progeny individuals. The MLH3 ChIP-seq approach enables direct detection of COs, providing high-resolution and genome-wide coverage, including genome regions with low DNA sequence polymorphism, which are inaccessible to genetic CO mapping. Furthermore, MLH3 ChIP-seq enables screening of thousands of CO events, greatly accelerating the analysis and reducing its cost. This protocol can also be used to examine any chromatin-bound meiotic proteins and adapted to studying chromatin-associated proteins in somatic cells.

Journal Article↗

PubMed2026

ChIP-seq profiling identifies diapause-regulated H3K27me3 targets in the fat body of Culex pipiens.

Culex pipiens, a principal vector of significant arboviruses, survives winter through diapause, a hormonally controlled inactive phase that enhances endurance under severe cold circumstances. Recent data suggests that epigenetic processes, namely histone post-translational modifications (hPTMs), play a crucial role in regulating seasonal dormancy. Prior studies from our laboratory indicated a decrease in the methylation of Histone 3 (H3K27me3) in diapausing fat body tissue, associated with elevated expression of the histone demethylase UTX. Nonetheless, the precise genomic areas impacted by these chromatin alterations remained unidentified. We used chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) to delineate the genome-wide distribution of H3K27me3 across fat body chromatin in diapausing (D) and non-diapausing (ND) female Cx. pipiens. Notably, the higher signal at transcription start sites (TSSs) reflects localized redistribution rather than a global decrease, as diapausing fat bodies retain less H3K27me3 overall but concentrate it at promoters. To investigate the functional significance of these chromatin alterations, we confirmed a number of target loci via ChIP-qPCR and assessed gene expression with qRT-PCR. We identified many critical genes that were markedly increased in diapausing mosquitoes, exhibiting an inverse relation to H3K27me3 enrichment. Our data demonstrates different H3K27me3 chromatin landscapes between diapausing and non-diapausing Cx. pipiens, corroborating a hypothesis of selective, locus-specific repression in the non-diapause state and its targeted removal during diapause to permit activation of dormancy-associated genes. These results suggest that chromatin remodeling is a core driver of the diapause switch.

Animals↗

PubMed2026

Improved spike-in normalization clarifies the relationship between active histone modifications and transcription.

Spike-in normalization enables quantitative analysis of chromatin immunoprecipitation sequencing (ChIP-seq) signal. Here we introduce a robust dual spike-in normalization approach for ChIP-seq (ChIP-wrangler), optimize parameters and verify its accuracy in quantifying changes in ChIP-seq signal and detecting technical artifacts. We use ChIP-wrangler to revisit recent claims that active histone marks depend on transcription. We show that acute depletion of RNA polymerase II (RNAPII) has a modest impact on H3K27ac levels, with only 6% of peaks significantly changing after RNAPII depletion, indicating that histone acetylation maintenance is not entirely dependent on ongoing transcription. Promoters and enhancers are differentially affected, with 82% of decreasing acetylation peaks located at promoter-distal elements with enhancer-related motifs. ChIP-wrangler provides increased rigor and 'guardrails' for successful spike-in normalization and, as applied here, refines the understanding of crosstalk between RNAPII activity and transcription-associated histone marks.

Histones↗

PubMed2026

Age-associated chromatin repression of Hippo-Yap signaling drives oogonial stem cell decline in chicken.

Oogonial stem cells (OSCs) are a type of reproductive germline stem cell present in the ovaries of adult animals after birth. They have been proposed to contribute to follicle renewal and could be associated with reproductive longevity, yet the molecular mechanism contribute to OSC malfunction during aging in chicken remain unclear. Here, we show that OSC number and proliferative capacity decline significantly from pre-laying to late-laying stages, accompanied by increased follicular atresia. RNA-seq analysis revealed a global reduction in transcriptional activity in aged OSCs. ChIP-seq demonstrated elevated H3K27me3 deposition, particularly at promoter regions, which correlated with repression of proliferation-related genes in the Hippo pathway including YAP1 and TEAD1. Pharmacological inhibition of H3K27me3 reduced repressive chromatin marks, restored Hippo pathway gene expression, and significantly enhanced OSC proliferation. Conversely, YAP1 knockdown attenuated proliferation-associated gene expression. These findings indicate that age-dependent H3K27me3 accumulation suppresses OSC proliferation through epigenetic repression of the Hippo-YAP axis, providing mechanistic insight into ovarian aging and a potential strategy to extend the laying cycle in poultry.

Animals↗

PubMed2025

Chromatin Immunoprecipitation for Standard, Rare, or Weakly Binding Proteins.

Various proteins interact with specific genome regions, playing crucial roles in gene regulation. Chromatin Immunoprecipitation (ChIP) is the most commonly used method to study protein-DNA interactions in vivo. By combining ChIP with high-throughput sequencing, ChIP-seq allows for studying the genome-wide localization of proteins. Although several ChIP protocols are available for plant tissues, they are primarily designed for histone modifications and abundant proteins with high DNA-binding affinity, which are considered as the "standard targets." Here we describe a ChIP protocol for plant tissues not only optimized for the standard targets but also adapted for proteins with low abundances or weak DNA-binding ability. Successful execution of the protocol enables reliable generation of DNA templates for quantitative PCR or libraries for next-generation sequencing, which makes it an effective tool for analyzing genomic interactions of a wide range of proteins.

Chromatin Immunoprecipitation↗

PubMed2026

Charting host structural variations in cervical cancer by long-read sequencing pinpoints a functional deletion in PIAS1.

Host structural variations (SVs) are critical in cancer development but their landscape and interaction with HPV integration in cervical carcinogenesis remain unclear. In this study, we performed Nanopore long-read sequencing on five HPV-positive cervical cancer tissues and two cell lines to profile host SVs. We identified thousands of SVs and statistically demonstrated their significant enrichment in genomic windows ±25 to ±50 kb from HPV integration sites. Cross-sample analysis revealed 60 shared SVs, including a recurrent deletion within the PIAS1 gene. Multi-omics integration (Hi-C, H3K27ac ChIP-seq, and TCGA data) showed that this deletion is associated with reduced PIAS1 expression, disruption of local topologically associating domains, advanced pathological tumor stage, and poorer overall survival. Functional assays confirmed that PIAS1 deficiency inhibits cervical cancer cell proliferation and migration. Our findings identify a PIAS1 deletion as a candidate driver event, and underscore the pivotal role of host genomic instability in HPV-associated oncogenesis.

Cervical cancer↗

PubMed2026

Oncogene SETDB1's dual role: driving tumor progression and immune escape.

Oncogene SETDB1, an H3K9 methyltransferase, drives tumorigenesis in various cancers. Using endometrial cancer (EC) as a model, we discovered SETDB1's dual mechanisms in driving EC tumorigenesis and mediating immune evasion. SETDB1 knockout (SETDB1-/-) tumor-bearing mice exhibited prolonged survival up to 100 days. Transcriptomic profiling of SETDB1-/- EC cells revealed decreased oncogene expression and increased tumor suppressor gene expression, which indicates that SETDB1 intrinsically promotes EC proliferation by regulating these downstream genes. SETDB1 repressed repeat elements and the interferon pathway, mediating immune evasion extrinsically by inhibiting anti-tumor macrophage infiltration. ChIP-seq analysis showed SETDB1 binding at pericentromeric regions on many chromosomes and numerous ZNFs. Loss of SETDB1 resulted in abnormal cell division. SETDB1-/- tumors displayed reduced proliferation markers (Ki67, pHH3) and increased macrophage infiltration. Mechanistically, SETDB1 promotes CD47 (a don't-eat-me signal) and represses CCL5 and CXCL9 (macrophage and T-cell recruiting chemokines), contributing to immune evasion. M1-like macrophages killed more SETDB1-/- cells in co-culture. Additionally, SETDB1 knockout in mouse EC cells reduced tumor growth in C57BL/6 mice, with increased macrophage and CD4 + T-cell infiltration. Our results indicate that elevated SETDB1 and its targets can predict higher tumor grade and worse survival, suggesting that targeting SETDB1 could be a promising therapeutic strategy for EC.

Animals↗

PubMed2026

Evolution and domestication-trait associations of ultra-long centromere haplotypes in pepper plants.

Centromeric and pericentromeric regions of most eukaryotic genomes are highly repetitive and strongly recombination-suppressed, confounding efforts to resolve genetic variation, population structure and phenotypic associations. Pepper (Capsicum annuum) centromeres are nearly devoid of satellite repeats, facilitating assembly and population-level comparison of centromeric regions. Here we integrate 9 near-complete genome assemblies, CENH3 ChIP-seq profiles from 26 diverse accessions, and resequencing and phenotypic data from ~400 cultivated and wild accessions to investigate population-level diversity and phenotypic relevance of pepper peri/centromeric regions. Functional centromere positions are largely fixed on 8 of 12 chromosomes, whereas the remaining 4 carry distinct centromeric epialleles shaped mainly by centromere repositioning and pericentromeric inversions. Pepper centromeres are embedded within ultra-long centromere-spanning haplotype (cenhap) blocks, ranging from 29.8 to 112.9 Mb and collectively covering 23.96% of the genome; each block contains only 1-4 major haplotypes. Some cenhaps may act as supergene-like units and are strongly associated with fruit traits, probably because recombination-suppressed intervals harbour multiple fruit-related genes, including OFP and F-box genes. F2 segregation assays further reveal transmission distortion of chromosomes carrying alternative cenhaps. Together, these findings highlight peri/centromeric regions as underrecognized reservoirs of agronomically important variation.

Centromere↗

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

ChromCall: assigning chromatin status to defined genomic regions using epigenomic profiling data.

MOTIVATION: Chromatin regulation is crucial for modulating gene expression and cellular function by altering DNA accessibility. Defining and understanding chromatin regulation across diverse biological conditions, including health and disease, requires quantification of both the presence and enrichment level of diverse DNA-binding factors and chromatin modifications across defined genomic regions. Existing approaches mainly rely on peak-based or genome-wide models, which identify high-signal regions but do not annotate chromatin status at predefined functional genomic regions, such as promoters or enhancers. This lack of region-based annotation limits downstream comparative and integrative analyses across multiple factors and datasets, prompting us to create ChromCall. RESULTS: ChromCall is an R package for region-based chromatin enrichment analysis that provides a robust and extensible foundation for transparent and reproducible epigenomic profiling at predefined genomic regions. We applied ChromCall to ChIP-seq data from glioblastoma (GBM) brain tumours and found that the promoters of genes implicated in treatment resistance are significantly more likely to exhibit a combination of histone marks associated with phenotypic plasticity. This highlights a potential novel mechanism of therapeutic escape in these deadly tumours. AVAILABILITY AND IMPLEMENTATION: The R package is available on https://github.com/GliomaGenomics/ChromCall and the version used in this paper is archived at https://doi.org/10.5281/zenodo.19580967.

Chromatin↗

PubMed2026

Causal circuit tracing reveals distinct computational architectures in single-cell foundation models: inhibitory dominance, biological coherence, and cross-model convergence.

MOTIVATION: Sparse autoencoders (SAEs) decompose foundation-model activations into interpretable features, but the model-internal causal interactions between those features (i.e. what ablating one feature does to the others, as distinct from the biological causal structure of the underlying cells)-and how those model-internal relationships relate to biological structure-are uncharacterized in single-cell foundation models. RESULTS: We introduce model-internal causal circuit tracing-zeroing one SAE feature at a source layer and measuring the resulting change in all downstream SAE features, for each of 120 source features-and apply it to Geneformer V2-316M and scGPT whole-human across four conditions (96 892 ablation-derived edges, 80 191 forward passes). On annotation-selected source features, edges share GO/KEGG/Reactome/STRING/TRRUST ontology terms at 50.9%-68.5%, a 2.9-6.2× enrichment over a configuration-preserving permutation null (P<.002); on 20 randomly sampled source features this attenuates to 21.5%-26.3%-still 2.5-3.1× above null-quantifying the annotation-selection contribution. Inhibitory dominance (fraction of ablation edges with d<0, i.e. source activation supports downstream target) is 65.5%-89.4%. scGPT produces larger raw per-edge effects (mean |d|=1.40 versus 1.05); after feature-share normalization, Geneformer is stronger (paired gene-pair ratio 0.64 on 33 301 shared pairs). Cross-model consensus yields 1142 architecture-invariant domain pairs (ordered pairs of GO biological-process categories "A→B" each connected by at least one ablation edge in both models; 10.6× enrichment over permutation null; P<.001). Circuit edge magnitude explains <1% of the variance in marginal driver-gene coexpression on the same cells (R2=0.010, n=31 176): the graph encodes structure beyond bivariate correlation. Against a matched-cell-type ENCODE ChIP-seq prior, circuit-predicted transcription factor (TF)→target pairs are enriched 2.06× (Fisher OR 5.84), markedly higher than 1.12× against TRRUST; direct ChIP-seq-supported target pairs show 10-30× larger CRISPRi sign-bias-corrected excess than indirect pairs. Gene-level CRISPRi validation on Replogle K562 and the noncancer RPE1 arm (and a true primary-T-cell control from Shifrut E, Carnevale J, Tobin V et al. Genome-wide CRISPR screens in primary human T cells reveal key regulators of immune function. Cell 2018; 175: 1958-71.e15) after sign-bias correction shows excess over baseline of +0.03 and +0.35 percentage points on K562 and RPE1, respectively (baseline already 52%-56% from sign marginals); effect-magnitude Spearman correlations ρ≈0. Bootstrap and per-cell-type stability (N∈{50,100,200}; B cell, CD4 + T, macrophage) give Pearson r≥0.97 on shared edges with 100% sign agreement; edge Jaccard grows monotonically with sample size. The circuit graph is therefore highly reproducible as an effect-size map, cell type specific in edge identity, consistent with coexpression encoding, and weakly but detectably enriched for ChIP-seq-supported direct regulatory edges. AVAILABILITY AND IMPLEMENTATION: https://github.com/Biodyn-AI/bio-sae-circuits (Python). Archival DOI: 10.5281/zenodo.19,633,166 (Zenodo).

Humans↗

PubMed2026

ChromBERT-tools: a versatile toolkit for context-specific regulatory representations of transcription regulators across different cell types.

SUMMARY: Representations that encode the genome-wide regulatory behavior of transcription regulators provide a foundation for flexible transcription modeling and in silico regulatory analysis. Existing regulator representations are commonly derived from gene co-expression, motif annotations, or static protein features, which capture useful but limited aspects of regulator identity but do not directly model how regulators participate in region-specific regulatory programs across the genome. ChromBERT addresses this gap by learning context-aware regulatory representations from large-scale ChIP-seq data. However, routine bioinformatics applications require lightweight, accessible, and modular tools for generating, adapting, and interpreting these representations in user-defined biological contexts. Here, we present ChromBERT-tools, a user-oriented toolkit built upon ChromBERT that converts its regulatory representation framework into practical workflows for customizable analysis across cellular contexts. ChromBERT-tools provides command-line interfaces and Python APIs organized into three functional layers: representation generation, predictive modeling, and regulatory interpretation. The representation generation layer produces representations of genomic regions and transcription regulators. The predictive modeling layer fine-tunes ChromBERT for genome-wide regulatory activity prediction through classification or regression tasks, with optimized implementation to reduce running time and computational resource requirements. The regulatory interpretation layer supports inference of the context-specific roles of cis-regulatory elements and transcription regulators. These modules can be used independently or integrated into end-to-end workflows, enabling flexible analyses across diverse datasets. ChromBERT-tools lowers the barrier to applying context-specific regulatory representations in routine genomic analyses. AVAILABILITY AND IMPLEMENTATION: ChromBERT-tools is freely available at https://github.com/TongjiZhanglab/ChromBERT-tools, with documentation at https://chrombert-tools.readthedocs.io/en/latest/. A frozen archival snapshot is available on Zenodo under DOI: 10.5281/zenodo.20094206.

Software↗

PubMed2026

Chiron3D: an interpretable deep learning framework for understanding the DNA code of chromatin looping.

MOTIVATION: Three-dimensional folding of the genome into structures such as chromatin loops is essential for gene regulation. Current experimental methods for mapping these structures, like Hi-C and HiChIP, are labor-intensive and require repeated assays to test hypothesized mutation effects. This motivates the need for predictive approaches that reveal the sequence determinants of chromatin loops. RESULTS: In this work, we present a novel and interpretable computational pipeline for predicting CTCF-mediated chromatin loops. We propose Chiron3D, a DNA-only model trained in a cell-type specific manner to predict CTCF HiChIP contact maps. By leveraging pre-trained embeddings from a foundation model, our approach is competitive with baselines that take CTCF ChIP-seq as additional input, while enabling nucleotide-level attribution to the input DNA sequence. Using our framework, we provide likely mechanistic insights into the physical control of loop dynamics. Specifically, we find that the strength of the loop extrusion anchorage site is largely governed by the amount and binding affinity of CTCF sites at the boundaries. Furthermore, we reveal that loop stability is regulated by the amount of intra-loop CTCF binding sites, where fewer intra-loop sites are associated with greater loop stability. Using targeted, single-nucleotide edit simulations with Chiron3D, we show that both loop strength and stability can be precisely controlled. Together, these results provide novel mechanistic insights into the physical control of genome organization and highlight the potential of decoding the DNA sequence logic in silico. AVAILABILITY: The Chiron3D pipeline is made available at https://github.com/BoevaLab/Chiron3D.

Chromatin↗

PubMed2026

ATX1-COMPASS-like complex participates in the bud dormancy release of tree peony by regulating H3K4me3 modification.

Bud dormancy release in woody plants is crucial for survival, regrowth, flowering, and fruiting. Tree peony (Paeonia suffruticosa), an important ornamental and economic plant, undergoes bud endodormancy in winter, and sufficient chilling duration and exogenous gibberellins (GAs) can effectively break the dormancy. However, the epigenetic regulation mechanism remains poorly understood. Here, immunoblotting revealed that H3K4me3, but not H3K4me1 or H3K4me2, was associated with chilling- and GA3-induced dormancy release. Chromatin immunoprecipitation sequencing (ChIP-seq) combined with RNA-seq results revealed that H3K4me3 enriched near transcription start sites (TSS). H3K4me3 enrichment genes (HEGs) and differentially expressed genes (DEGs) were commonly enriched in KEGG pathways, such as plant hormone signal transduction and MAPK signaling. The expression patterns of these marker genes, such as EARLY BUD-BREAK 3 (PsEBB3), CYCLIND3.1 (PsCYCD3.1), CYCLIND3.3 (PsCYCD3.3), and β-1,3-glucanase 6 (PsBG6), were correlated with their H3K4me3 enrichment and were validated by chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR). Four COMPASS-like component homologs and one histone methyltransferase were screened; among them, PsWDR5a, PsRBL, PsASH2R, and PsATX1 were upregulated by prolonged chilling and GA3 treatments. Yeast two-hybrid (Y2H), yeast three-hybrid (Y3H), luciferase complementation (LCA), and co-immunoprecipitation (Co-IP) analyses revealed that PsRBL interacts with PsWDR5a and PsASH2R as a bridge. PsATX1 was confirmed as an H3K4me3 methyltransferase and interacted with PsWDR5a and PsRBL to form the PsATX1-COMPASS-like complex using Y2H, LCA, and Co-IP assays. Functional analyses showed that PsWDR5a, PsRBL, PsASH2R, and PsATX1 significantly promoted budburst by elevating genomic H3K4me3 levels. Our findings provide insights into the epigenetic regulation of dormancy transitions in woody perennials.

Histones↗

PubMed2026

MCM10 and RECQL4 have cooperative and redundant roles in activating the CMG helicase during the replication initiation.

DNA replication initiation requires activation of the CMG helicase to establish the replisome. This process involves the extrusion of single-stranded DNA (ssDNA) from the central channel of MCM double hexamers, allowing the two CMG helicases to pass each other; however, the factors that mediate this process in human cells remain unclear. We show that degron-mediated depletion of either MCM10 or RECQL4 alone causes mild replication defects, whereas simultaneous depletion of both proteins severely impairs CMG activation. ChIP-seq analyses demonstrate that RECQL4 localizes to replication initiation zones (IZs) independently of MCM10, whereas MCM10 recruitment to IZs is enhanced upon RECQL4 depletion, consistent with partially redundant roles during CMG activation. Rescue experiments further indicate that RECQL4 cooperates with MCM10 through direct interaction, and that their ssDNA-binding activity underlies their functional overlap. We propose that MCM10 and RECQL4 act cooperatively and redundantly to promote CMG activation.

CMG activation↗

PubMed2026

Polycomb protein ZmEMF1a restricts endosperm proliferation and directs differentiation via stage-specific H2Aub1 and H3K27me3 landscapes in maize.

Polycomb group (PcG) proteins serve as pivotal epigenetic repressors that govern the transcriptional programs underlying cell growth and differentiation. However, their functional roles in maize endosperm remain largely unexplored. Here, we characterize the recessive maize small-kernel mutant sks1, which exhibits persistent endosperm cell hyperproliferation and compromised cell expansion during grain filling. Map-based cloning reveals that SKS1 encodes ZmEMF1a, a PcG protein that physically interacts with subunits of both PRC1 and PRC2. Integrated ChIP-seq and RNA-seq analyses were performed to investigate its epigenetic regulatory functions. ZmEMF1a orchestrates a stage-specific epigenetic regulatory program: it predominantly mediates H3K27me3 deposition at 6 d after pollination (DAP), while coordinately regulating the deposition of both H3K27me3 and H2Aub1 at 10 DAP. Loss of ZmEMF1a leads to ectopic hyperproliferation of differentiated endosperm tissues, specifically the basal endosperm transfer layer (BETL) and aleurone (AL), as well as elevated vitamin B content in the endosperm. Collectively, these findings establish ZmEMF1a as an epigenetic regulator that balances endosperm proliferation, cell fate specification, and nutrient accumulation through stage-specific histone modifications, thereby offering promising targets for enhancing maize yield and nutritional quality.

H2Aub1↗

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

FOXC2 and WT1 regulate transcriptional reprogramming during the podocyte response to injury.

Transcriptional reprogramming has an important role in kidney glomerular disease. Using in vivo murine models of podocyte injury, we studied the roles of the FOXC2 and WT1 transcription factors (TFs) in podocyte injury. Podocytes are a crucial cell type of glomeruli, the filtration units of each nephron. Podocyte injury is often the incipient event leading to chronic kidney disease. It is well established that the TFs FOXC2 and WT1 are required in podocytes to maintain the glomerular filtration barrier. Their role in the response to injury is less well understood. Here, we tested the hypothesis that FOXC2 and WT1 act together to mediate transcriptional reprogramming in response to podocyte injury. Similarly to that of WT1, genome-wide FOXC2 binding to target genes is dynamic during the course of injury, initially increasing, but late in injury there is a dramatic decrease in FOXC2 expression and in its binding to target genes. Podocyte-specific inactivation of FoxC2 or Wt1 in adult mice limits the transcriptional response to injury. Correlating FOXC2 and WT1 ChIP-seq analyses demonstrated that they co-bind many genes expressed in podocytes. Thus, reprogramming the transcriptome involves dynamic changes in the binding of FOXC2 and WT1 to their target genes during a reparative injury response.

Animals↗