Quantitative comparison of genome-wide DNA methylation mapping technologies.
Quantitative comparison of genome-wide DNA methylation mapping technologies.
复制标题
DOI：
10.1038/nbt.1681
复制
发表时间：
2010-10
影响因子：
46.9
通讯作者：
中科院分区：
文献类型：
--
作者：
DNA甲基化是哺乳动物基因调控的关键组成部分，也是表观遗传标记最经典的例子。DNA甲基化模式在有丝分裂过程中可遗传且随时间稳定，但它们会因细胞分化、疾病和环境影响而发生显著变化。已经开发了几种在基因组规模上进行DNA甲基化分析的方法。在此，我们在两对样本上对其中四种方法进行了基准测试，比较了它们检测DNA甲基化差异的准确性和能力。结果表明，所有评估的方法（MeDIP - seq：甲基化DNA免疫沉淀，MethylCap - seq：亲和纯化捕获甲基化DNA，RRBS：简化代表性亚硫酸氢盐测序，以及Infinium HumanMethylation27检测）都能产生准确的DNA甲基化数据。然而，这些方法在检测样本对之间差异甲基化区域的能力上有所不同。我们强调了这四种方法的优缺点，并为表观基因组病例对照研究的设计提供了实用的建议。
DNA methylation is a key component of mammalian gene regulation and the most classical example of an epigenetic mark. DNA methylation patterns are mitotically heritable and stable over time, but they undergo considerable changes in response to cell differentiation, diseases and environmental influences. Several methods have been developed for DNA methylation profiling on a genomic scale. Here, we benchmark four of these methods on two sample pairs, comparing their accuracy and power to detect DNA methylation differences. The results show that all evaluated methods (MeDIP-seq: methylated DNA immunoprecipitation, MethylCap-seq: methylated DNA capture by affinity purification, RRBS: reduced representation bisulfite sequencing, and the Infinium HumanMethylation27 assay) produce accurate DNA methylation data. However, these methods differ in their ability to detect differentially methylated regions between pairs of samples. We highlight strengths and weaknesses of the four methods and give practical recommendations for the design of epigenomic case-control studies.
登录
查看更多内容
影响因子：
64.8
作者：
Heintzman, Nathaniel D.;Hon, Gary C.;Hawkins, R. David;Kheradpour, Pouya;Stark, Alexander;Harp, Lindsey F.;Ye, Zhen;Lee, Leonard K.;Stuart, Rhona K.;Ching, Christina W.;Ching, Keith A.;Antosiewicz-Bourget, Jessica E.;Liu, Hui;Zhang, Xinmin;Green, Roland D.;Lobanenkov, Victor V.;Stewart, Ron;Thomson, James A.;Crawford, Gregory E.;Kellis, Manolis;Ren, Bing
通讯作者：
Ren, Bing
影响因子：
64.8
作者：
通讯作者：
--
影响因子：
14.9
作者：
Bock C;Walter J;Paulsen M;Lengauer T
通讯作者：
Lengauer T
影响因子：
11.2
作者：
Caldwell, GM;Jones, C;Morton, DG
通讯作者：
Morton, DG
影响因子：
7
作者：
Brunner, Alayne L.;Johnson, David S.;Myers, Richard M.
通讯作者：
Myers, Richard M.