Detecting differential DNA methylation from sequencing of bisulfite converted DNA of diverse species.
Detecting differential DNA methylation from sequencing of bisulfite converted DNA of diverse species.
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DOI：
10.1093/bib/bbx077
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发表时间：
2019-01-18
影响因子：
9.5
通讯作者：
Yi SV
中科院分区：
文献类型：
--
作者：
Huh I;Wu X;Park T;Yi SV
DNA甲基化是基因组DNA的表观遗传修饰中研究最广泛的一种。近年来，亚硫酸氢盐转化的DNA的测序，特别是通过下一代测序技术，已成为研究DNA甲基化的广泛流行的方法。这种方法可以很容易地应用于各种物种，大大扩展了DNA甲基化研究的范围，超出了传统研究的人类和小鼠系统。与基因组甲基化谱日益丰富的同时，已经开发了许多统计工具来检测生物条件之间的差异甲基化基因座（DML）或差异甲基化区域（DMR）。我们讨论和总结了目前可用的工具来检测从测序的亚硫酸氢盐转化的DNA的DMLs和DMR的几个关键属性。然而，大多数为DML/DMR分析开发的统计工具仅使用哺乳动物数据集进行了验证，而对无脊椎动物或植物DNA甲基化数据的分析则不那么优先。我们证明，非哺乳动物物种的基因组甲基化谱往往是高度不同的哺乳动物物种的蜜蜂和人类的例子。然后，我们将讨论如何在数据属性的差异可能会影响统计分析。基于这些差异，我们提供了三个具体的建议，以提高使用目前可用的统计工具时，无脊椎动物数据的DML和DMR分析的功率和准确性。这些考虑应该有助于对不同物种的DNA甲基化进行系统和可靠的分析，从而促进我们对DNA甲基化的理解。
DNA methylation is one of the most extensively studied epigenetic modifications of genomic DNA. In recent years, sequencing of bisulfite-converted DNA, particularly via next-generation sequencing technologies, has become a widely popular method to study DNA methylation. This method can be readily applied to a variety of species, dramatically expanding the scope of DNA methylation studies beyond the traditionally studied human and mouse systems. In parallel to the increasing wealth of genomic methylation profiles, many statistical tools have been developed to detect differentially methylated loci (DMLs) or differentially methylated regions (DMRs) between biological conditions. We discuss and summarize several key properties of currently available tools to detect DMLs and DMRs from sequencing of bisulfite-converted DNA. However, the majority of the statistical tools developed for DML/DMR analyses have been validated using only mammalian data sets, and less priority has been placed on the analyses of invertebrate or plant DNA methylation data. We demonstrate that genomic methylation profiles of non-mammalian species are often highly distinct from those of mammalian species using examples of honey bees and humans. We then discuss how such differences in data properties may affect statistical analyses. Based on these differences, we provide three specific recommendations to improve the power and accuracy of DML and DMR analyses of invertebrate data when using currently available statistical tools. These considerations should facilitate systematic and robust analyses of DNA methylation from diverse species, thus advancing our understanding of DNA methylation.
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在多因素全基因组亚硫酸盐测序实验中，使用β-二项式回归进行高精度差甲基化分析。
影响因子：
3
作者：
Dolzhenko E;Smith AD
通讯作者：
Smith AD
影响因子：
64.5
作者：
Calarco JP;Borges F;Donoghue MT;Van Ex F;Jullien PE;Lopes T;Gardner R;Berger F;Feijó JA;Becker JD;Martienssen RA
通讯作者：
Martienssen RA
影响因子：
9.5
作者：
Adusumalli, Swarnaseetha;Omar, Mohd Feroz Mohd;Benoukraf, Touati
通讯作者：
Benoukraf, Touati
DOI：
10.1016/0005-2787(75)90193-8
发表时间：
1975-01-01
期刊：
BIOCHIMICA ET BIOPHYSICA ACTA
影响因子：
--
作者：
GUSEINOV, VA;VANYUSHIN, BF
通讯作者：
VANYUSHIN, BF
影响因子：
12.3
作者：
Akalin A;Kormaksson M;Li S;Garrett-Bakelman FE;Figueroa ME;Melnick A;Mason CE
通讯作者：
Mason CE