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The myoblast-to-adipocyte trans-differentiation model is crucial for studying the regulatory mechanisms underlying ectopic fat deposition and cell fate determination. However, the comprehensive dynamics of chromatin accessibility and interactions during this process remain largely unexplored. To address this, we performed an integrative analysis of bulk and single-cell multi-omics data (ATAC-seq, RNA-seq), and Hi-C data on an adipogenesis model in C2C12 myoblasts. Our findings revealed significant reprogramming of chromatin accessibility driven by adipogenic lineage-specific transcription factors (TFs), particularly Cebps and Stats, during trans-differentiation. Notably, 63.46% of the distal open chromatin regions with increased accessibility were shared between myogenesis and adipogenesis. Further joint analysis with Hi-C data suggests that these pre-established enhancers in myoblasts undergo a "regulatory redirection," shifting their influence from myogenic to adipogenic genes-a phenomenon we termed "enhancer snatch." This model was validated by knocking out a "snatched" enhancer (Enhancer-R/L), which was found to be a critical regulator of both Rbl1 and Lbp expression. Overall, our study uncovers a mechanism that pre-established enhancers in original cell lineage are predominantly utilized by lineage-specific TFs during chromatin reprogramming, thereby altering cell's differentiation trajectory.
Pubmed ID: 41258103
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Web tool to search, sort, analyze, visualize and download data of interest. Along with providing details of the ontologies, gene products and annotations, features a BLAST search, Term Enrichment and GO Slimmer tools, the GO Online SQL Environment and a user help guide.Used at the Gene Ontology (GO) website to access the data provided by the GO Consortium. Developed and maintained by the GO Consortium.
View all literature mentionsSoftware package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.
View all literature mentionsA software library for analyzing DNase-seq data.
View all literature mentionsA tool for mapping and performing quality control on Hi-C data.
View all literature mentionsData analysis service that predicts functions of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. The utility of GREAT extends to data generated for transcription-associated factors, open chromatin, localized epigenomic markers and similar functional data sets, and comparative genomics sets. Platform: Online tool
View all literature mentionsA powerful toolset for genome arithmetic allowing one to address common genomics tasks such as finding feature overlaps and computing coverage. Bedtools allows one to intersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g., intersect two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line.
View all literature mentionsSoftware tools for Motif Discovery and next-gen sequencing analysis. Used for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets. Collection of command line programs for unix style operating systems written in Perl and C++.
View all literature mentionsBioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.
View all literature mentionsHuman and mouse genome annotation project which aims to identify all gene features in the human genome using computational analysis, manual annotation, and experimental validation.
View all literature mentionsSoftware package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
View all literature mentionsSoftware as R package designed for QC, analysis, and exploration of single cell RNA-seq data. Enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data.
View all literature mentionsPython based tools to process, visualize and analyse high-throughput sequencing data, such as ChIP-seq, RNA-seq or MNase-seq. Implemented within Galaxy framework. Used to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches.
View all literature mentionsSoftware tool as a function in R to draw clustered heatmaps for better control over graphical parameters.
View all literature mentionsSoftware tool as optimized and flexible pipeline for Hi-C data processing. Used to process Hi-C data, from raw fastq files, paired end Illumina data, to normalized contact maps.
View all literature mentionsSoftware package for detection and handling of doublets/multiplets in single cell sequencing data.
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