Literature DB >> 20627893

Bisulfite Patch PCR enables multiplexed sequencing of promoter methylation across cancer samples.

Katherine Elena Varley1, Robi David Mitra.   

Abstract

Aberrant DNA methylation frequently occurs at gene promoters during cancer progression. It is important to identify these loci because they are often misregulated and drive tumorigenesis. Bisulfite sequencing is the most direct and highest resolution assay for identifying aberrant promoter methylation. Recently, genomic capture methods have been combined with next-generation sequencing to enable genome-scale surveys of methylation in individual samples. However, it is challenging to validate candidate loci identified by these approaches because an efficient method to bisulfite sequence more than 50 differentially methylated loci across a large number of samples does not exist. To address this problem, we developed Bisulfite Patch PCR, which enables highly multiplexed bisulfite PCR and sequencing across many samples. Using this method, we successfully amplified 100% of 94 targeted gene promoters simultaneously in the same reaction. By incorporating sample-specific DNA barcodes into the amplicons, we analyzed 48 samples in a single run of the 454 Life Sciences (Roche) FLX sequencer. The method requires small amounts of starting DNA (250 ng) and does not require a shotgun library construction. The method was highly specific; 90% of sequencing reads aligned to targeted loci. The targeted promoters were from genes that are frequently mutated in breast and colon cancer, and the samples included breast and colon tumor and adjacent normal tissue. This approach allowed us to identify nine gene promoters that exhibit tumor-specific DNA methylation defects that occur frequently in colon and breast cancer. We also analyzed single nucleotide polymorphisms to observe DNA methylation that accumulated on specific alleles during tumor development. This method is broadly applicable for studying DNA methylation across large numbers of patient samples using next-generation sequencing.

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Year:  2010        PMID: 20627893      PMCID: PMC2928506          DOI: 10.1101/gr.101212.109

Source DB:  PubMed          Journal:  Genome Res        ISSN: 1088-9051            Impact factor:   9.043


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