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Systematic Identification and Analysis of Cell-state-associated cisregulatory Elements Using Statistical Approaches

Abstract

Recent genome-wide studies have significantly advanced our understanding of the non-coding genome in higher eukaryotes. Here we developed a novel computational method to systematically identify cell-state-associated cis-regulatory elements for more than 300 cell and tissue types from human and mouse. Our method identified strong enrichment of associated enhancers with immune cells. We found that the cis-regulatory elements associated with more cell and tissue types exhibit certain genomic features, including longer length, higher conservation score and enrichment of CpG-islands. We identified enriched transcription factor (TF) motifs within the enhancers associated with each cell and tissue type. We also found that the single nucleotide polymorphisms (SNPs) identified by the Genome-Wide Association Study (GWAS) are particularly enriched in the cell-state-associated enhancers. Furthermore, we analyzed the association between human diseases and various cell and tissue types, and found that sclerosis diseases are associated with diverse immune-associated tissues and mature immune cells. Finally, we estimated enhancer-promoter signal correlations and identified enhancers exhibiting conserved correlations between human and mouse.

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