Genome-wide mapping of nucleosome positioning and DNA methylation within individual DNA molecules

  1. Peter A. Jones1,6,7
  1. 1Department of Urology, Department of Biochemistry and Molecular Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California 90033, USA;
  2. 2USC Epigenome Center and Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California 90033, USA;
  3. 3Genetic, Molecular and Cellular Biology Program, Keck School of Medicine, University of Southern California, Los Angeles, California 90033, USA;
  4. 4Department of Preventive Medicine, University of Southern California, Los Angeles, California 90033, USA
    1. 5 These authors contributed equally to this work.

    2. 6 These authors contributed equally to this work.

    Abstract

    DNA methylation and nucleosome positioning work together to generate chromatin structures that regulate gene expression. Nucleosomes are typically mapped using nuclease digestion requiring significant amounts of material and varying enzyme concentrations. We have developed a method (NOMe-seq) that uses a GpC methyltransferase (M.CviPI) and next generation sequencing to generate a high resolution footprint of nucleosome positioning genome-wide using less than 1 million cells while retaining endogenous DNA methylation information from the same DNA strand. Using a novel bioinformatics pipeline, we show a striking anti-correlation between nucleosome occupancy and DNA methylation at CTCF regions that is not present at promoters. We further show that the extent of nucleosome depletion at promoters is directly correlated to expression level and can accommodate multiple nucleosomes and provide genome-wide evidence that expressed non-CpG island promoters are nucleosome-depleted. Importantly, NOMe-seq obtains DNA methylation and nucleosome positioning information from the same DNA molecule, giving the first genome-wide DNA methylation and nucleosome positioning correlation at the single molecule, and thus, single cell level, that can be used to monitor disease progression and response to therapy.

    Footnotes

    • 7 Corresponding authors

      E-mail bberman{at}usc.edu

      E-mail pjones{at}med.usc.edu

    • [Supplemental material is available for this article.]

    • Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.143008.112.

    • Received May 11, 2012.
    • Accepted August 16, 2012.

    This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported License), as described at http://creativecommons.org/licenses/by-nc/3.0/.

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