Article | Published:

Targeted and genome-scale strategies reveal gene-body methylation signatures in human cells

Nature Biotechnology volume 27, pages 361368 (2009) | Download Citation

  • A Corrigendum to this article was published on 01 May 2009

This article has been updated

Abstract

Studies of epigenetic modifications would benefit from improved methods for high-throughput methylation profiling. We introduce two complementary approaches that use next-generation sequencing technology to detect cytosine methylation. In the first method, we designed 10,000 bisulfite padlock probes to profile 7,000 CpG locations distributed over the ENCODE pilot project regions and applied them to human B-lymphocytes, fibroblasts and induced pluripotent stem cells. This unbiased choice of targets takes advantage of existing expression and chromatin immunoprecipitation data and enabled us to observe a pattern of low promoter methylation and high gene-body methylation in highly expressed genes. The second method, methyl-sensitive cut counting, generated nontargeted genome-scale data for 1.4 million HpaII sites in the DNA of B-lymphocytes and confirmed that gene-body methylation in highly expressed genes is a consistent phenomenon throughout the human genome. Our observations highlight the usefulness of techniques that are not inherently or intentionally biased towards particular subsets like CpG islands or promoter regions.

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  • 08 May 2009

    In the version of this article initially published, the second affilliation for Yuan Gao was omitted: Department of Computer Science, Virginia Commonwealth University, Richmond, Virginia, USA. The affiliation has been added to the HTML and PDF versions of the article.

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Acknowledgements

We thank Kun Zhang for discussion throughout this work; Wei Lin for help with computational design; Andrew Chess and Ravid Straussman for discussion and critical reading of the manuscript; Harvard Biopolymers Facility for Solexa sequencing; and Harvard Partners Center for Genetics and Genomics for gene expression profiling. This work was supported by the NHGRI-Centers of Excellence in Genomic Science (to G.M.C.).

Author information

Author notes

    • Madeleine P Ball
    •  & Jin Billy Li

    These authors contributed equally to this work.

Affiliations

  1. Department of Genetics, Harvard Medical School, Cambridge, Massachusetts, USA.

    • Madeleine P Ball
    • , Jin Billy Li
    • , Je-Hyuk Lee
    •  & George M Church
  2. Broad Institute of MIT and Harvard University, Cambridge, Massachusetts, USA.

    • Madeleine P Ball
    • , Jin Billy Li
    • , Je-Hyuk Lee
    •  & George M Church
  3. Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia, USA.

    • Yuan Gao
    •  & Bin Xie
  4. Department of Computer Science, Virginia Commonwealth University, Richmond, Virginia, USA.

    • Yuan Gao
  5. Genomics Solution Unit, Agilent Technologies Inc., Santa Clara, California, USA.

    • Emily M LeProust
  6. Department of Medicine, Division of Pediatric Hematology Oncology, Children's Hospital Boston, and Dana-Farber Cancer Institute; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Karp Family Research Building 7214, Boston, Massachusetts, USA.

    • In-Hyun Park
    •  & George Q Daley

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Contributions

M.P.B., J.B.L. and G.M.C. conceived the study, designed the research and wrote the manuscript. M.P.B. and J.B.L. performed experiments and data analysis. Y.G. and B.X. carried out initial Solexa sequencing. J.-H.L. helped with culturing cell lines and isolating DNA/RNA. E.M.L. synthesized the padlock oligos. I.-H.P. and G.Q.D. generated the iPS cell lines.

Competing interests

E.M.L. is an employee of Agilent Technologies. G.M.C. is involved in eight next-generation sequencing companies. M.P.B., J.B.L. and G.M.C. are named as inventors on a patent application on technologies described in this article.

Corresponding authors

Correspondence to Jin Billy Li or George M Church.

Supplementary information

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    Supplementary Text and Figures

    Supplementary Figures 1–10; Supplementary Tables 2–5, 7,8

Text files

  1. 1.

    Supplementary Table 1

    BSPP data

  2. 2.

    Supplementary Table 6

    MSCC data

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DOI

https://doi.org/10.1038/nbt.1533

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