Analysis of DNA methylation patterns relies increasingly on sequencing-based profiling methods. The four most frequently used sequencing-based technologies are the bisulfite-based methods MethylC-seq and reduced representation bisulfite sequencing (RRBS), and the enrichment-based techniques methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylated DNA binding domain sequencing (MBD-seq). We applied all four methods to biological replicates of human embryonic stem cells to assess their genome-wide CpG coverage, resolution, cost, concordance and the influence of CpG density and genomic context. The methylation levels assessed by the two bisulfite methods were concordant (their difference did not exceed a given threshold) for 82% for CpGs and 99% of the non-CpG cytosines. Using binary methylation calls, the two enrichment methods were 99% concordant and regions assessed by all four methods were 97% concordant. We combined MeDIP-seq with methylation-sensitive restriction enzyme (MRE-seq) sequencing for comprehensive methylome coverage at lower cost. This, along with RNA-seq and ChIP-seq of the ES cells enabled us to detect regions with allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression.

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We would like to thank the US National Institutes of Health (NIH) Roadmap Epigenomics Program; sponsored by the National Institute on Drug Abuse (NIDA) and the National Institute of Environmental Health Sciences (NIEHS). J.F.C. and M.H. are supported by NIH grant 5U01ES017154-02. A. Milosavljevic is supported by NIH grant 5U01DA025956-02. A. Meissner and B.E.B. are supported by NIH grant 6U01ES017155-02. J.R.E. and B.R. are supported by NIH grant 5U01ES017166-02. R.P.N. was supported by NIH T32 CA108462-04 and F32CA141799. S.L.D. was supported by CIRM TB1-01190. S.D.F. was supported by NIH T32 CA108462-06. B.E.J. was supported by NIH T32 GM008568. M.A.M. is a Terry Fox Young Investigator and a Michael Smith Senior Research Scholar. We thank Z. Zhang and H. Li for modifying the ZOOM algorithm for bisulfite alignments.

Author information


  1. Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA.

    • R Alan Harris
    • , Cristian Coarfa
    • , Robert A Waterland
    •  & Aleksandar Milosavljevic
  2. Center for Genome Sciences and Systems Biology, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA.

    • Ting Wang
    • , Xin Zhou
    • , Kevin J Forsberg
    •  & Junchen Gu
  3. Brain Tumor Research Center, Department of Neurosurgery, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California, USA.

    • Raman P Nagarajan
    • , Chibo Hong
    • , Sara L Downey
    • , Brett E Johnson
    • , Shaun D Fouse
    • , Adam Olshen
    •  & Joseph F Costello
  4. Genome Sciences Centre, BC Cancer Agency, Vancouver, British Columbia, Canada.

    • Allen Delaney
    • , Yongjun Zhao
    • , Marco A Marra
    •  & Martin Hirst
  5. Center for Biomolecular Science and Engineering, University of California, Santa Cruz, California, USA.

    • Tracy Ballinger
    •  & David Haussler
  6. Department of Pharmacology and the Genome Center, University of California-Davis, Davis, California, USA.

    • Lorigail Echipare
    • , Henriette O'Geen
    •  & Peggy J Farnham
  7. Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, California, USA.

    • Ryan Lister
    • , Mattia Pelizzola
    •  & Joseph R Ecker
  8. Division of Biostatistics, Dan L. Duncan Cancer Center, Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas, USA.

    • Yuanxin Xi
    •  & Wei Li
  9. Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.

    • Charles B Epstein
    • , Bradley E Bernstein
    • , Hongcang Gu
    • , Christoph Bock
    • , Andreas Gnirke
    •  & Alexander Meissner
  10. Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.

    • Bradley E Bernstein
  11. Center for Cancer Research, Massachusetts General Hospital, Boston, Massachusetts, USA.

    • Bradley E Bernstein
  12. Ludwig Institute for Cancer Research, University of California San Diego, La Jolla, California, USA.

    • R David Hawkins
    •  & Bing Ren
  13. Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, California, USA.

    • Bing Ren
  14. Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA.

    • Wen-Yu Chung
    •  & Michael Q Zhang
  15. Department of Molecular and Cell Biology, Center for Systems Biology, University of Texas at Dallas, Dallas, Texas, USA.

    • Wen-Yu Chung
    •  & Michael Q Zhang
  16. Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, USA.

    • Christoph Bock
    •  & Alexander Meissner
  17. Harvard Stem Cell Institute, Cambridge, Massachusetts, USA.

    • Christoph Bock
    •  & Alexander Meissner
  18. Max Planck Institute for Informatics, Saarbrücken, Germany.

    • Christoph Bock
  19. USDA/ARS Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA.

    • Robert A Waterland


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J.F.C., R.A.H., T.W., M.H., M.A.M. and A. Milosavljevic conceived and designed the experiments. R.P.N., C.H., S.L.D., B.E.J., S.D.F., Y.Z. and M.H. performed the MeDIP, MRE and bisulfite sequencing experiments. R.A.W. and X.Z. designed and performed pyrosequencing and data analyses. H.G., C.B., A.G. and A. Meissner9 performed and analyzed RRBS. L.E., H.O., P.J.F., B.E.B., C.B.E., R.D.H. and B.R. performed and analyzed Chip-seq experiments. R.L., M.P. and J.R.E. analyzed MethylC-seq data and performed Bowtie aligner testing. R.A.H., T.W., K.J.F., J.G., C.C., M.H., X.Z., A.D. and A.O. performed data analysis. T.W., T.B. and D.H. developed MeDIP and methyl-sensitive restriction enzyme scoring algorithms and performed coverage analyses including repetitive sequence analyses. Y.X., W.-Y.C., R.L., M.Q.Z. and W.L. compared bisulfite sequence aligners. J.F.C., R.A.H., M.H., T.W., R.P.N. and R.A.W. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Joseph F Costello.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Tables 2, 4, 5 and 8 and Supplementary Figs. 1–18

Excel files

  1. 1.

    Supplementary Table 1

    Primer designs for bisulfite pyrosequencing. See Excel spreadsheet Supplementary_Table_1.xls.

  2. 2.

    Supplementary Table 3

    Bisulfite data for Supplementary Figure 12.

  3. 3.

    Supplementary Table 6

    Genome-wide catalogue of CpG island regions exhibiting overlapping MeDIP-seq (methylated) signals and MRE-seq (unmethylated) signals.

  4. 4.

    Supplementary Table 7

    Validation of known and putative DMRs by bisulfite, PCR, cloning and sequencing.

  5. 5.

    Supplementary Table 9

    Details of the comparison of genomic variation between pairs of assays to determine allele-specific epigenetic states.

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