Abstract LB-133: Genome-wide differences in DNA methylation between tumor and normal adjacent tissue mapped by high-throughput sequencing of methyl-CPG binding domain based affinity-purified genomic fragments

Abstract

Abstract Aberrant DNA methylation is characteristic of many cancers and differences in methylation have been observed in a wide variety of genomic contexts; for example, both within “classic” promoter-associated CpG islands and also in distal, non-CpG island regions. Establishing a method to broadly and efficiently survey the methylation patterns genome-wide in matched tumor and normal genomic DNA and to elucidate differences in these “methylomes” is the objective of the work presented. The method combines the power of methyl-CpG binding domain (MBD) proteins to sensitively and selectively bind methylated DNA sequences with the coverage, precision, and accuracy provided by high-throughput sequencing. Notably, MBD-affinity capture can also be used to sub-fractionate genomic DNA based on its average methyl-CpG content. In parallel, patient-derived matched samples of fragmented genomic DNA from a breast tumor and normal adjacent tissue were enriched and fractionated based on their methyl-CpG content with a commercial MBD-based affinity reagent (see figure) and high-throughput sequencing libraries were prepared from each fraction. The libraries were sequenced at 50 bp read-length on a SOLiD 3 Plus system and mapped to the human reference genome. Peak analysis of the distribution of mapped reads permitted the discovery of hundreds of putative differentially methylation regions (DMRs). Differential methylation at a number of these positions was confirmed by bisulfite-sequencing. We conclude that such enrichment and fractionation, when coupled to high-throughput sequencing, can be used to efficiently survey the majority of DNA methylation marks within samples of genomic DNA and to discover genomic loci of differential methylation. We conclude that such enrichment and fractionation, when coupled to high-throughput sequencing, can be used to efficiently survey a large fraction of all DMRs between samples of genomic DNA and to discover genomic loci of differential methylation. These datasets can then be compared with ChIP-seq and/or RNA-seq data sets to begin to decipher the functional genomics and epigenomics of cancer. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr LB-133.