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

Author

Listed:
  • Jason Ernst

    (Broad Institute of MIT and Harvard
    MIT Computer Science and Artificial Intelligence Laboratory)

  • Pouya Kheradpour

    (Broad Institute of MIT and Harvard
    MIT Computer Science and Artificial Intelligence Laboratory)

  • 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
    MIT Computer Science and Artificial Intelligence Laboratory)

  • 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
    Howard Hughes Medical Institute, Massachusetts General Hospital and Harvard Medical School
    Center for Systems Biology and Center for Cancer Research, Massachusetts General Hospital)

  • Timothy Durham

    (Broad Institute of MIT and Harvard)

  • Manolis Kellis

    (Broad Institute of MIT and Harvard
    MIT Computer Science and Artificial Intelligence Laboratory)

  • Bradley E. Bernstein

    (Broad Institute of MIT and Harvard
    Howard Hughes Medical Institute, Massachusetts General Hospital and Harvard Medical School
    Center for Systems Biology and Center for Cancer Research, Massachusetts General Hospital)

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.

Suggested Citation

  • 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 & Mano, 2011. "Mapping and analysis of chromatin state dynamics in nine human cell types," Nature, Nature, vol. 473(7345), pages 43-49, May.
  • Handle: RePEc:nat:nature:v:473:y:2011:i:7345:d:10.1038_nature09906
    DOI: 10.1038/nature09906
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