Differential analysis of chromatin accessibility and gene expression profiles identifies cis-regulatory elements in rat adipose and muscle
Chromatin accessibility is a key factor influencing gene expression. We optimized the Omni-ATAC-seq protocol and used it together with RNA-seq to investigate cis-regulatory elements in rat white adipose and skeletal muscle, two tissues with contrasting metabolic functions. While promoter accessibili...
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Veröffentlicht in: | Genomics (San Diego, Calif.) Calif.), 2021-11, Vol.113 (6), p.3827-3841 |
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Zusammenfassung: | Chromatin accessibility is a key factor influencing gene expression. We optimized the Omni-ATAC-seq protocol and used it together with RNA-seq to investigate cis-regulatory elements in rat white adipose and skeletal muscle, two tissues with contrasting metabolic functions. While promoter accessibility correlated with RNA expression, integration of the two datasets identified tissue-specific differentially accessible regions (DARs) that predominantly localized in intergenic and intron regions. DARs were mapped to differentially expressed (DE) genes enriched in distinct biological processes in each tissue. Randomly selected DE genes were validated by qPCR. Top enriched motifs in DARs predicted binding sites for transcription factors (TFs) showing tissue-specific up-regulation. The correlation between differential chromatin accessibility at a given TF binding motif and differential expression of target genes further supported the functional relevance of that motif. Our study identified cis-regulatory regions that likely play a major role in the regulation of tissue-specific gene expression in adipose and muscle.
•Ruptor-ATAC method probes the chromatin landscape in rat white adipose and muscle.•We identify tissue-specific chromatin accessible regions in adipose and muscle.•Differentially accessible regions are predominantly intronic and intergenic.•Differentially accessible regions map to genes with a wide range in expression levels.•Tissue-specific transcription factors are inferred from ATAC-seq and RNA-seq data. |
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ISSN: | 0888-7543 1089-8646 |
DOI: | 10.1016/j.ygeno.2021.09.013 |