title: 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.
authors.affiliation: Wellcome Trust Cancer Research UK Gurdon Institute, and Department of Genetics, University of Cambridge, Tennis Court Road, Cambridge CB2 1QR, UK. thomas.down@gurdon.cam.ac.uk
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Down
authors.forename: Vardhman K
authors.initials: VK
authors.lastname: Rakyan
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Turner
authors.forename: Paul
authors.initials: P
authors.lastname: Flicek
authors.forename: Heng
authors.initials: H
authors.lastname: Li
authors.forename: Eugene
authors.initials: E
authors.lastname: Kulesha
authors.forename: Stefan
authors.initials: S
authors.lastname: Gräf
authors.forename: Nathan
authors.initials: N
authors.lastname: Johnson
authors.forename: Javier
authors.initials: J
authors.lastname: Herrero
authors.forename: Eleni M
authors.initials: EM
authors.lastname: Tomazou
authors.forename: Natalie P
authors.initials: NP
authors.lastname: Thorne
authors.forename: Liselotte
authors.initials: L
authors.lastname: Bäckdahl
authors.forename: Marlis
authors.initials: M
authors.lastname: Herberth
authors.forename: Kevin L
authors.initials: KL
authors.lastname: Howe
authors.forename: David K
authors.initials: DK
authors.lastname: Jackson
authors.forename: Marcos M
authors.initials: MM
authors.lastname: Miretti
authors.forename: John C
authors.initials: JC
authors.lastname: Marioni
authors.forename: Ewan
authors.initials: E
authors.lastname: Birney
authors.forename: Tim J P
authors.initials: TJ
authors.lastname: Hubbard
authors.forename: Richard
authors.initials: R
authors.lastname: Durbin
authors.forename: Simon
authors.initials: S
authors.lastname: Tavaré
authors.forename: Stephan
authors.initials: S
authors.lastname: Beck
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D001499:Bayes Theorem; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D002874:Chromosome Mapping / Q000379:methods*; D004247:DNA / Q000235:genetics*; D019175:DNA Methylation; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*
chemical_list: D004247:DNA