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A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis

Abstract

DNA methylation is an indispensible epigenetic modification required for regulating the expression of mammalian genomes. Immunoprecipitation-based methods for DNA methylome analysis are rapidly shifting the bottleneck in this field from data generation to data analysis, necessitating the development of better analytical tools. In particular, an inability to estimate absolute methylation levels remains a major analytical difficulty associated with immunoprecipitation-based DNA methylation profiling. To address this issue, we developed a cross-platform algorithm—Bayesian tool for methylation analysis (Batman)—for analyzing methylated DNA immunoprecipitation (MeDIP) profiles generated using oligonucleotide arrays (MeDIP-chip) or next-generation sequencing (MeDIP-seq). We developed the latter approach to provide a high-resolution whole-genome DNA methylation profile (DNA methylome) of a mammalian genome. Strong correlation of our data, obtained using mature human spermatozoa, with those obtained using bisulfite sequencing suggest that combining MeDIP-seq or MeDIP-chip with Batman provides a robust, quantitative and cost-effective functional genomic strategy for elucidating the function of DNA methylation.

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Figure 1: Calibration of the Batman model against MeDIP-chip data.
Figure 2: Comparison of Batman-analyzed MeDIP-chip data with bisulfite-PCR sequencing data from the Human Epigenome Project.
Figure 3: Mapping quality and genomic coverage of the MeDIP-seq data.
Figure 4: Comparison of Batman-analyzed MeDIP-seq data with bisulfite-PCR sequencing data from the Human Epigenome Project.
Figure 5: Genomic coverage and web display of the MeDIP-seq data.

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Acknowledgements

T.A.D., E.M.T., L.B., K.L.H., D.K.J., M.M.M., H.L., T.J.P.H., S.B., D.J.T., R.D. were supported by the Wellcome Trust. V.K.R. was supported by the Barts and The London Charitable Trust, and a C.J. Martin Fellowship from the National Health and Medical Research Council, Australia. S.G., N.J. and M.H. were supported by an EU grant (High-throughput Epigenetic Regulatory Organization in Chromatin (HEROIC), LSHG-CT-2005-018883) under the 6th Framework Program to S.B. (M.H.) and E.B. (S.G., N.J.). N.P.T., J.C.M. and S.T. were supported by grant C14303/A8646 from Cancer Research UK.

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Authors and Affiliations

Authors

Contributions

T.A.D. co-conceived the study, wrote the Batman algorithm, co-analyzed data and co-wrote the paper; V.K.R. co-conceived the study, performed the bulk of the experimental work, co-analyzed data, co-wrote the paper and provided overall project management; D.J.T. performed the Illumina Genome Analyzer sequencing; H.L. performed the maq analysis; P.F., E.K., S.G., N.J. and J.H. performed some data analysis and designed the Ensembl web display for the data reported here; E.M.T., L.B. and M.H. performed experimental work; K.L.H. and D.K.J. assisted with array design; N.P.T. and J.C.M. performed preliminary array analysis; M.M.M. supplied materials; E.B., T.J.P.H., R.D. and S.T. provided intellectual input; S.B. co-conceived the study, co-wrote the paper and provided overall project management. T.A.D. and V.K.R. contributed equally to this work.

Corresponding authors

Correspondence to Thomas A Down, Vardhman K Rakyan or Stephan Beck.

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Figures 1–6, Tables 1–3 (PDF 943 kb)

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Down, T., Rakyan, V., Turner, D. et al. A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis. Nat Biotechnol 26, 779–785 (2008). https://doi.org/10.1038/nbt1414

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