Precise regulation of gene expression is integral in development. Emerging studies have highlighted that super-enhancers (SEs), which are clusters of multiple enhancers, play critical roles in regulating cell type-specific gene expression via 3D chromatin, thereby defining the cellular identities of given cells. Here we provide optimized bioinformatics pipelines to identify SEs and 3D chromatin contacts. Our pipelines encompass the processing of chromatin immunoprecipitation sequencing (ChIP-seq) data to identify SEs and the processing of genome-wide chromosome conformation capture (Hi-C) data. We can then infer long-range chromatin contacts between SEs and other genomic regions. This integrative computational approach, which can be applied to CUT&RUN and CUT&Tag, alternative technologies to ChIP-seq, allows us to identify genomic locations of SEs and their 3D genome configuration, whereby multiple SEs act in concert. We show an analysis of mouse spermatogenesis as an example of this application.
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