CpG站点
DNA甲基化
照明菌甲基化试验
亚硫酸氢盐测序
甲基化DNA免疫沉淀
亚硫酸氢盐
生物
甲基化
差异甲基化区
分子生物学
表观遗传学
基因分型
遗传学
DNA
计算生物学
基因
基因表达
基因型
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]
日期:2009-10-01
卷期号:1 (1): 177-200
被引量:548
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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