Mapping and Analysis of Chromatin State Dynamics in Nine Human Cell Types
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Kellis_Mapping and analysis.pdf
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1.4 MB
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Author(s)
Ernst, Jason
Kheradpour, Pouya
Mikkelsen, Tarjei Sigurd
Shoresh, Noam
Ward, Lucas D.
Epstein, Charles B.
Zhang, Xiaolan
Wang, Li
Issner, Robbyn
Coyne, Michael J.
Date Issued
March 2011
Journal
Nature
Publisher
Nature Publishing Group
Citation
Ernst, Jason et al. “Mapping and Analysis of Chromatin State Dynamics in Nine Human Cell Types.” Nature 473.7345 (2011): 43–49.
Version
Author's final manuscript
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.
MIT Department
Lincoln Laboratory
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. School of Science
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1038/nature09906
