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PubMed2025

Improved cohesin HiChIP protocol and bioinformatic analysis for robust detection of chromatin loops and stripes.

Chromosome Conformation Capture (3 C) methods, including Hi-C (a high-throughput variation of 3 C), detect pairwise interactions between DNA regions, enabling the reconstruction of chromatin architecture in the nucleus. HiChIP is a modification of the Hi-C experiment that includes a chromatin immunoprecipitation (ChIP) step, allowing genome-wide identification of chromatin contacts mediated by a protein of interest. In mammalian cells, cohesin protein complex is one of the major players in the establishment of chromatin loops. We present an improved cohesin HiChIP experimental protocol. Using comprehensive bioinformatic analysis, we show that a dual chromatin fixation method compared to the standard formaldehyde-only method, results in a substantially better signal-to-noise ratio, increased ChIP efficiency and improved detection of chromatin loops and architectural stripes. Additionally, we propose an automated pipeline called nf-HiChIP ( https://github.com/SFGLab/hichip-nf-pipeline ) for processing HiChIP samples starting from raw sequencing reads data and ending with a set of significant chromatin interactions (loops), which allows efficient and timely analysis of multiple samples in parallel, without requiring additional ChIP-seq experiments. Finally, using advanced approaches for biophysical modelling and stripe calling we generate accurate loop extrusion polymer models for a region of interest and provide a detailed picture of architectural stripes, respectively.

Chromatin↗

PubMed2026

dcHiChIP: a comprehensive Nextflow-based pipeline for multiscale analysis of chromatin architecture from HiChIP data.

MOTIVATION: Despite the growing use of HiChIP to investigate protein-directed chromatin architecture, a comprehensive and reproducible pipeline for analysing these datasets-from raw reads to multiscale 3D genome features-remains lacking. Existing tools often focus on isolated components, such as loop calling or matrix generation, but fall short in integrating structural annotation, functional enrichment, and spatial modeling within a unified framework. To address this gap, we developed dcHiChIP, a modular, scalable Nextflow-based workflow that streamlines the analysis of HiChIP data, enabling both routine processing and in-depth exploration of chromatin organization and regulatory interactions. RESULTS: dcHiChIP enables robust and reproducible analysis of HiChIP datasets across multiple scales of chromatin architecture. It accepts raw sequencing data as input and generates high-quality loop calls, domain annotations, and 3D genome models. It also performs functional annotation and motif enrichment analyses. Applied to benchmark CTCF HiChIP datasets, dcHiChIP identifies major chromatin architectural features such as TADs/CCDs, A/B compartments, and chromatin stripes, and offers efficient, end-to-end execution with support for batch processing and workflow resumability. AVAILABILITY: dcHiChIP is publicly available on GitHub at https://github.com/SFGLab/dcHiChIP, with documentation at https://sfglab.github.io/dcHiChIP/. The software version used in this study is archived at Zenodo: https://doi.org/10.5281/zenodo.22030542.

Chromatin↗

PubMed2025

HiChIP for Plant Tissues.

While most epigenomics studies are based on a linear view of genome organization, the necessity to take the three-dimensional chromatin folding into account to understand transcriptional regulation is now clearly recognized. In the past years, approaches combining proximity-based ligation with high-throughput sequencing have opened the way to study long/short-range chromatin interactions and, thus, to analyze 3D chromatin organization. Among them, HiChIP, a protein-based method to capture chromatin interactions, gave rise to the most comprehensive view of the chromatin contacts involving specific chromatin components in a given system. Here, we describe a detailed procedure to produce HiChIP libraries starting from plant tissues.

Chromatin↗

PubMed2025

Deciphering estrogen receptor alpha-driven transcription in human endometrial stromal cells via transcriptome, cistrome, and integration with chromatin landscape.

OBJECTIVE: To investigate estrogen receptor gene 1 (ESR1) and estrogen-driven transcription in human endometrial stromal cells. DESIGN: RNA sequencing (RNA-seq) and Cleavage Under Targets and Release Using Nuclease (Cut&Run) were performed on telomerase-immortalized human endometrial stromal cells with Clustered Regularly Interspaced Short Palindromic Repeats-mediated ESR1 activation. Hi-C-based chromatin architecture analysis (H3K27ac HiChIP) was conducted in primary endometrial stromal cells. SUBJECTS: Biopsies from two healthy, reproductive-aged volunteers with regular menstrual cycles and no history of gynecological malignancies. EXPOSURE: The ESR1-activated and control endometrial stromal cells were treated with estradiol (E2) or vehicle. Primary endometrial stromal cells were treated with vehicle or a decidualization cocktail. MAIN OUTCOME MEASURES: Differential gene expression analysis (RNA-seq) identified ligand-independent and -dependent ESR1 activity. Cut&Run profiled ESR1 genomic binding in ESR1-activated cells. H3K27ac HiChIP mapped hormone-induced changes in chromatin looping in primary cells. RESULTS: Among seven tested guide RNAs (gRNA), the ESR1-3 gRNA induced robust ESR1 activation and restored E2 responsiveness. Bulk RNA-seq revealed both ligand-dependent and -independent ESR1 transcriptional programs regulating inflammation, proliferation, and cancer-related pathways. Notably, 72% of differentially expressed genes overlapped with genes active in human endometrial tissue during the proliferative estrogen-dominant phase, supporting their physiological relevance. The Cut&Run-seq identified genome-wide ESR1 binding sites, with most binding sites located at distal regulatory elements. Integration of Cut&Run data with H3K27ac HiChIP chromatin loops linked distal ESR1 binding sites to gene promoters, including genes involved in decidualization (e.g., FOXO1) and endometrial cancer (e.g., ERRFI1, NRIP1, and EPAS1). Functional assays showed that ESR1 promotes cell viability and, in the presence of E2, enhances migration. CONCLUSION: The CRISPR-mediated ESR1 activation restores estrogen responsiveness in endometrial stromal cells. Combined transcriptomic, cistromic, and chromatin architecture analyses reveal ESR1's role in regulating decidualization and inflammation-related gene networks, with relevance to endometrial pathologies including endometrial cancer. This model serves as a powerful tool to study estrogen signaling in endometrial stromal cell biology and related pathologies.

Humans↗

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↗

PubMed2025

Integrative Genomic, Transcriptomic and Epigenomic Analysis Reveals cis-regulatory Contributions to High-altitude Adaptation in Tibetan Pigs.

The Qinghai-Tibet Plateau, characterized by its extreme environmental conditions, presents significant challenges to life, making it an ideal region for studying adaptation and evolution. Tibetan pigs, known for their high genetic diversity and exceptional adaptability to high altitudes, serve as excellent models for investigating high-altitude adaptation. While previous studies have extensively identified genetic determinants associated with high-altitude adaptation, the molecular mechanisms, particularly cis-regulatory patterns, remain poorly understood. Here, we conducted a selective sweep analysis using 484 genomes from Chinese and Western pig breeds across various altitudes, revealing 38.56 Mb of genomic regions under selection in Tibetan pigs. Enrichment analysis identified the lung as the primary functional tissue involved in high-altitude adaptation, supported by tissue-specific transcriptional and regulatory patterns observed between Tibetan and Meishan pigs (low altitude). By integrating genomic, RNA-seq, ATAC-seq, and H3K27ac HiChIP data, we constructed comprehensive enhancer-promoter regulatory maps of candidate genes and pinpointed promising genetic determinants associated with high-altitude adaptation, including SNPs in EPAS1, KLF13, SPRED1, and CFD. These loci were predicted to influence chromatin accessibility and the interactions of regulatory elements, with altered binding strength of relevant transcription factors. Further in vitro experiments confirmed that these loci function as allele-specific enhancers, modulating the expression of target genes. Our findings elucidate the regulatory basis of high-altitude adaptation in Tibetan pigs and provide valuable insights for exploring hypoxia-related diseases in livestock and humans.

Animals↗

PubMed2025

Systematic decoding of functional enhancer connectomes and risk variants in human glioma.

Genetic and epigenetic variations contribute to the progression of glioma, but the mechanisms underlying these effects, particularly for enhancer-associated genetic variations in non-coding regions, still remain unclear. Here we performed high-throughput CRISPR interference screening to identify pro-tumour enhancers in glioma cells. By integrating genome-wide H3K27ac HiChIP data, we identified the target genes of these pro-tumour enhancers and revealed the essential role of enhancer connectomes in promoting glioma progression. Through systematic analysis of enhancers carrying glioma risk-associated single-nucleotide polymorphisms (SNPs), we found that these SNPs can promote glioma progression through the enhancer connectome. Using CRISPR-Cas9-mediated enhancer interference and SNP editing, we demonstrated that glioma-specific enhancer carrying the risk SNP rs2297440 regulates SOX18 expression by specifically recruiting transcription factor MEIS1 binding, thereby contributing to glioma progression. Our study sheds light on the molecular mechanisms underlying glioma susceptibility and provides potential therapeutic targets to treat glioma.

Humans↗

PubMed2025

AQuA Tools: clear and reliable BEDPE operations for 3D genomics.

MOTIVATION: The genome interacts with itself within the volume of the cell nucleus to process information. These interactions mediate signal integration, gene regulation, and cell identity. The identification of new therapeutic targets from non-coding disease-associated variants relies critically on correctly assigning variants to genes through 3D interactions. Experimental techniques in 3D genomics, such as HiC and HiChIP, allow the mapping of interactions through sequencing. Bioinformatics for 3D genomics contends primarily with contact matrices that contain interaction frequencies for all possible element pairs, and BEDPE files that store element pairs that interact. Whereas the tools available for processing linear genomic data are mature, operating on contact matrices and BEDPE files remains cumbersome, opaque, and error-prone, as researchers have had to shoehorn tools originally designed for linear data. A genome arithmetic designed from the ground up for 3D genomics does not yet exist. RESULTS: We present AQuA Tools, a suite of shell- and R-based command-line tools that provide a set of core operations on contact matrices and BEDPE files motivated by key questions in population genetics, cancer research, and precision medicine. We have designed our core operations to be clear, reliable, intuitive and versatile. Core operations can be chained together along with standard UNIX commands. Our goal is to make AQuA Tools easy for the novice to learn and the go-to choice for power users. We hope our tools will motivate more researchers to use 3D genomic data in their projects. AVAILABILITY AND IMPLEMENTATION: We provide and maintain AQuA Tools at https://github.com/axiotl/aqua-tools.

Genomics↗

PubMed2025

Mapping early PRC2 nucleation sites upon Suz12 reintroduction reveals features of de novo Polycomb recruitment.

Polycomb domains safeguard cell identity by maintaining lineage-specific chromatin states enriched in repressive histone modifications, preserving the epigenetic memory of cell lineages. While Polycomb Repressive Complex 2 (PRC2) can re-establish its occupancy after perturbation, the mechanisms that guide de novo Polycomb recruitment remain unclear. To address this, we engineered an auxin-inducible degradation system to reversibly deplete and reintroduce the endogenous PRC2 core subunit Suz12 in mouse embryonic stem cells (mESCs). Genome-wide profiling at an early recovery time point revealed ~1,100 PRC2 nucleation sites, characterized by rapid Suz12 and histone H3K27me3 re-accumulation with strong signal, with minimal impact on gene expression. These sites were significantly enriched at bivalent promoters, coinciding with unmethylated CpG islands and chromatin states associated with developmental regulation, and were largely conserved in differentiated cells. Motif analysis identified G/C-rich DNA sequences associated with E2F and zinc-finger proteins, alongside strong co-occupancy with MTF2 and JARID2, two PRC2 cofactors previously implicated in Polycomb targeting. Notably, a subset of nucleation sites overlapped with long-range chromatin interaction anchors in histone H3K27me3 HiChIP datasets. These findings reveal that PRC2 de novo nucleation sites are associated with a combination of chromatin states, DNA sequence features, cofactor co-occupancy and spatial genome organization, suggesting that epigenetic memory can be re-established through defined genomic and chromatin features.

Epigenetic memory↗

PubMed2025

Defining three dimensional chromatin structures of pediatric and adolescent B cells using primary B cell and EBV-immortalized B cell reference genomes.

BACKGROUND/PURPOSE: Knowledge of the 3D genome is essential to elucidate genetic mechanisms driving autoimmune diseases. The 3D genome is distinct for each cell type, and it is uncertain whether cell lines faithfully recapitulate the 3D architecture of primary human cells or whether developmental aspects of the pediatric immune system require use of pediatric samples. We undertook a systematic analysis of B cells and B cell lines to compare 3D genomic features encompassing risk loci for juvenile idiopathic arthritis (JIA), systemic lupus (SLE), and type 1 diabetes (T1D). METHODS: We isolated B cells from four healthy individuals, ages 9-17. HiChIP was performed using a CTCF antibody, and CTCF peaks were called within each sample separately. Peaks observed in all four samples were identified. CTCF loops were called within the pediatric samples using three CTCF peak datasets: 1) self-called CTCF consensus peaks called within the pediatric samples, 2) ENCODE's publicly available GM12878 CTCF ChIP-seq peaks, and 3) ENCODE's primary B cell CTCF ChIP-seq peaks from two adult females. Differential looping was assessed within the pediatric samples and each of the three peak datasets. RESULTS: The number of consensus peaks called in the pediatric samples was similar to that identified in ENCODE's GM12878 and primary B cell datasets. We observed < 1% of loops that demonstrated significantly differential looping between peaks called within the pediatric samples themselves and when called using ENCODE GM12878 peaks. Significant looping differences were even fewer when comparing loops of the pediatric called peaks to those of the ENCODE primary B cell peaks. When querying loops found in juvenile idiopathic arthritis, type 1 diabetes, or systemic lupus erythematosus risk haplotypes, we observed significant differences in only 2.2%, 1.0%, and 1.3% loops, respectively, when comparing peaks called within the pediatric samples and ENCODE GM12878 dataset. The differences were even less apparent when comparing loops called with the pediatric vs ENCODE adult primary B cell peak datasets. CONCLUSION: The 3D chromatin architecture in B cells is similar across pediatric, adult, and EBV-transformed cell lines. This conservation of 3D structure includes regions encompassing autoimmune risk haplotypes. Thus, even for pediatric autoimmune diseases, publicly available adult B cell and cell line datasets may be sufficient for assessing effects exerted in the 3D genomic space.

Humans↗