Mapping and analysis of chromatin state dynamics in nine human cell types

Jason Ernst, Pouya Kheradpour, Tarjei S. Mikkelsen, Noam Shoresh, Lucas D. Ward, Charles B. Epstein, Xiaolan Zhang, Li Wang, Robbyn Issner, Michael Coyne, Manching Ku, Timothy Durham, Manolis Kellis () and Bradley E. Bernstein
Additional contact information
Jason Ernst: Broad Institute of MIT and Harvard
Pouya Kheradpour: Broad Institute of MIT and Harvard
Tarjei S. Mikkelsen: Broad Institute of MIT and Harvard
Noam Shoresh: Broad Institute of MIT and Harvard
Lucas D. Ward: Broad Institute of MIT and Harvard
Charles B. Epstein: Broad Institute of MIT and Harvard
Xiaolan Zhang: Broad Institute of MIT and Harvard
Li Wang: Broad Institute of MIT and Harvard
Robbyn Issner: Broad Institute of MIT and Harvard
Michael Coyne: Broad Institute of MIT and Harvard
Manching Ku: Broad Institute of MIT and Harvard
Timothy Durham: Broad Institute of MIT and Harvard
Manolis Kellis: Broad Institute of MIT and Harvard
Bradley E. Bernstein: Broad Institute of MIT and Harvard

Nature, 2011, vol. 473, issue 7345, 43-49

Abstract: Abstract Chromatin profiling has emerged as a powerful means of genome annotation and detection of regulatory activity. The approach is especially well suited to the characterization of non-coding portions of the genome, which critically contribute to cellular phenotypes yet remain largely uncharted. Here we map nine chromatin marks across nine cell types to systematically characterize regulatory elements, their cell-type specificities and their functional interactions. Focusing on cell-type-specific patterns of promoters and enhancers, we define multicell activity profiles for chromatin state, gene expression, regulatory motif enrichment and regulator expression. We use correlations between these profiles to link enhancers to putative target genes, and predict the cell-type-specific activators and repressors that modulate them. The resulting annotations and regulatory predictions have implications for the interpretation of genome-wide association studies. Top-scoring disease single nucleotide polymorphisms are frequently positioned within enhancer elements specifically active in relevant cell types, and in some cases affect a motif instance for a predicted regulator, thus suggesting a mechanism for the association. Our study presents a general framework for deciphering cis-regulatory connections and their roles in disease.

Date: 2011
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DOI: 10.1038/nature09906

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