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势能景观确定了表观基因组的信息论本质。

Potential energy landscapes identify the information-theoretic nature of the epigenome.

作者信息

Jenkinson Garrett, Pujadas Elisabet, Goutsias John, Feinberg Andrew P

机构信息

Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.

Whitaker Biomedical Engineering Institute, Johns Hopkins University, Baltimore, Maryland, USA.

出版信息

Nat Genet. 2017 May;49(5):719-729. doi: 10.1038/ng.3811. Epub 2017 Mar 27.

Abstract

Epigenetics is the study of biochemical modifications carrying information independent of DNA sequence, which are heritable through cell division. In 1940, Waddington coined the term "epigenetic landscape" as a metaphor for pluripotency and differentiation, but methylation landscapes have not yet been rigorously computed. Using principles from statistical physics and information theory, we derive epigenetic energy landscapes from whole-genome bisulfite sequencing (WGBS) data that enable us to quantify methylation stochasticity genome-wide using Shannon's entropy, associating it with chromatin structure. Moreover, we consider the Jensen-Shannon distance between sample-specific energy landscapes as a measure of epigenetic dissimilarity and demonstrate its effectiveness for discerning epigenetic differences. By viewing methylation maintenance as a communications system, we introduce methylation channels and show that higher-order chromatin organization can be predicted from their informational properties. Our results provide a fundamental understanding of the information-theoretic nature of the epigenome that leads to a powerful approach for studying its role in disease and aging.

摘要

表观遗传学是对携带独立于DNA序列信息的生化修饰的研究,这些修饰可通过细胞分裂遗传。1940年,沃丁顿创造了“表观遗传景观”一词,作为多能性和分化的隐喻,但甲基化景观尚未得到严格计算。利用统计物理学和信息论的原理,我们从全基因组亚硫酸氢盐测序(WGBS)数据中推导出表观遗传能量景观,这使我们能够使用香农熵在全基因组范围内量化甲基化随机性,并将其与染色质结构相关联。此外,我们将样本特异性能量景观之间的 Jensen-Shannon 距离视为表观遗传差异的一种度量,并证明了其在辨别表观遗传差异方面的有效性。通过将甲基化维持视为一个通信系统,我们引入了甲基化通道,并表明可以从其信息特性预测高阶染色质组织。我们的结果提供了对表观基因组信息论本质的基本理解,从而产生了一种研究其在疾病和衰老中作用的强大方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3eae/5565269/f7bd401fade3/nihms852360f1.jpg

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