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Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications


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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Figure 1: CpG coverage by each method.
Figure 2: Comparison of bisulfite-based methods.
Figure 3: Comparison of methylated DNA enrichment methods.
Figure 4: Comparison of all methods.
Figure 5: Integrative method increases methylome coverage and enables identification of a DMR.
Figure 6: Allelic DNA methylation, histone methylation and gene expression in ESCs.


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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.

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Authors and Affiliations



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.

Corresponding author

Correspondence to Joseph F Costello.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Tables 2, 4, 5 and 8 and Supplementary Figs. 1–18 (PDF 3818 kb)

Supplementary Table 1

Primer designs for bisulfite pyrosequencing. See Excel spreadsheet Supplementary_Table_1.xls. (XLS 33 kb)

Supplementary Table 3

Bisulfite data for Supplementary Figure 12. (XLS 118 kb)

Supplementary Table 6

Genome-wide catalogue of CpG island regions exhibiting overlapping MeDIP-seq (methylated) signals and MRE-seq (unmethylated) signals. (XLS 223 kb)

Supplementary Table 7

Validation of known and putative DMRs by bisulfite, PCR, cloning and sequencing. (XLS 250 kb)

Supplementary Table 9

Details of the comparison of genomic variation between pairs of assays to determine allele-specific epigenetic states. (XLS 409 kb)

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Harris, R., Wang, T., Coarfa, C. et al. Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications. Nat Biotechnol 28, 1097–1105 (2010).

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