Genome-Wide Dna Methylation Profiling Using Infinium ® Assay

DNA甲基化 生物 甲基化 基因组 仿形(计算机编程) 分子生物学 DNA分析 基因表达谱 遗传学 DNA 计算生物学 基因 基因表达 操作系统 计算机科学
作者
Marina Bibikova,Jennie Le,Bret Barnes,Shadi Saedinia-Melnyk,Lixin Zhou,Richard Shen,Kevin L. Gunderson
出处
期刊:Epigenomics [Future Medicine]
卷期号:1 (1): 177-200 被引量:610
标识
DOI:10.2217/epi.09.14
摘要

AIMS: Bisulfite sequence analysis of individual CpG sites within genomic DNA is a powerful approach for methylation analysis in the genome. The major limitation of bisulfite-based methods is parallelization. Both array and next-generation sequencing technology are capable of addressing this bottleneck. In this report, we describe the application of Infinium® genotyping technology to analyze bisulfite-converted DNA to simultaneously query the methylation state of over 27,000 CpG sites from promoters of consensus coding sequences (CCDS) genes. MATERIALS & METHODS: We adapted the Infinium genotyping assay to readout an array of over 27,000 pairs of CpG methylation-specific query probes complementary to bisulfite-converted DNA. Two probes were designed to each CpG site: a 'methylated' and an 'unmethylated' query probe. The probe design assumed that all underlying CpG sites were 'in phase' with the queried CpG site due to their close proximity. Bisulfite conversion was performed with a modified version of the Zymo EZ DNA Methylation™ kit. RESULTS: We applied this technology to measuring methylation levels across a panel of 14 different human tissues, four Coriell cell lines and six cancer cell lines. We observed that CpG sites within CpG islands (CGIs) were largely unmethylated across all tissues (~80% sites unmethylated, β < 0.2), whereas CpG sites in non-CGIs were moderately to highly methylated (only ~12% sites unmethylated, β < 0.2). Within CGIs, only approximately 3-6% of the loci were highly methylated; in contrast, outside of CGIs approximately 25-40% of loci were highly methylated. Moreover, tissue-specific methylation (variation in methylation across tissues) was much more prevalent in non-CGIs than within CGIs. CONCLUSION: Our results demonstrate a genome-wide scalable array-based methylation readout platform that is both highly reproducible and quantitative. In the near future, this platform should enable the analysis of hundreds of thousands to millions of CpG sites per sample.

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