Research abstract

Article abstract


Nature Biotechnology 27, 361 - 368 (2009)
Published online: 29 March 2009 | Corrected online: 8 May 2009 | doi:10.1038/nbt.1533



There is a Corrigenda (May 2009) associated with this Article.

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

Madeleine P Ball1,2,7, Jin Billy Li1,2,7, Yuan Gao3,4, Je-Hyuk Lee1,2, Emily M LeProust5, In-Hyun Park6, Bin Xie3, George Q Daley6 & George M Church1,2


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 approx10,000 bisulfite padlock probes to profile approx7,000 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 approx1.4 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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  1. Department of Genetics, Harvard Medical School, Cambridge, Massachusetts, USA.
  2. Broad Institute of MIT and Harvard University, Cambridge, Massachusetts, USA.
  3. Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia, USA.
  4. Department of Computer Science, Virginia Commonwealth University, Richmond, Virginia, USA.
  5. Genomics Solution Unit, Agilent Technologies Inc., Santa Clara, California, USA.
  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.
  7. These authors contributed equally to this work.

Correspondence to: George M Church1,2 e-mail: gmc@harvard.edu

Correspondence to: Jin Billy Li1,2,7 e-mail: jli@genetics.med.harvard.edu

* 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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