Format

Send to

Choose Destination
See comment in PubMed Commons below
Nat Biotechnol. 2008 Jul;26(7):779-85. doi: 10.1038/nbt1414.

A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis.

Author information

1
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

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.

PMID:
18612301
PMCID:
PMC2644410
DOI:
10.1038/nbt1414
[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Nature Publishing Group Icon for PubMed Central
    Loading ...
    Support Center