A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis

作者：Down Thomas A; Rakyan Vardhman K^*; Turner Daniel J; Flicek Paul; Li Heng; Kulesha Eugene; Graf Stefan; Johnson Nathan; Herrero Javier; Tomazou Eleni M; Thorne Natalie P; Backdahl Liselotte; Herberth Marlis; Howe Kevin L; Jackson David K; Miretti Marcos M; Marioni John C; Birney Ewan; Hubbard Tim J P; Durbin Richard; Tavare Simon; Beck Stephan

来源：Nature Biotechnology, 2008, 26(7): 779-785.

DOI：10.1038/nbt1414

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.

• 出版日期2008-7