Deciphering long-range chromatin interactions is critical for understanding temporal and tissue-specific gene expression regulated by cis- and trans-acting factors. By combining the chromosome conformation capture (3C) and biotinylated dCas9 system, we previously established a method CAPTURE-3C-seq to unbiasedly identify high-resolution and locus-specific long-range DNA interactions. Here we present the statistical model and a flexible pipeline, C3S, for analysing CAPTURE-3C-seq or similar experimental data from raw sequencing reads to significantly interacting chromatin loci. C3S provides all steps for data processing, quality control and result illustration. It can automatically define the bin size based on the binding peak of the dCas9-targeted regions. Furthermore, it supports the analysis of intra- and inter-chromosomal interactions for different mammalian cell types. We successfully applied C3S across multiple datasets in human K562 cells and mouse embryonic stem cells (mESC) for detecting known and new chromatin interactions at multiple scales. Integrative and topological analysis of the interacted loci at the human β-globin gene cluster provides new insights into mechanisms in developmental gene regulation and network structure in local chromosomal architecture. Furthermore, computational results in mESCs reveal a role for chromatin interacting loops between enhancers and promoters in regulating alternative transcripts of the pluripotency gene OCT4.
Chen, Yong; Wang, Yunfei; Liu, Xin; Xu, Jian; and Zhang, Michael Q, "Model-based analysis of chromatin interactions from dCas9-Based CAPTURE-3C-seq." (2020). Faculty Scholarship for the College of Science & Mathematics. 177.
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Yong Chen, Yunfei Wang, Xin Liu, Jian Xu, and Michael Q. Zhang. (2020). Model-based analysis and pipeline of dCas9 Capture-3C-Seq data. PLOS ONE, July 2020. 15(7): e0236666. https://doi.org/10.1371/journal.pone.0236666