Understanding variation in transcription factor binding by modeling transcription factor genome-epigenome interactions.
Understanding variation in transcription factor binding by modeling transcription factor genome-epigenome interactions.
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DOI：
10.1371/journal.pcbi.1003367
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发表时间：
2013
影响因子：
4.3
通讯作者：
Zhong S
中科院分区：
文献类型：
--
作者：
Chen CC;Xiao S;Xie D;Cao X;Song CX;Wang T;He C;Zhong S
尽管基因组数据集呈爆炸式增长，但研究基因调控的表观基因组机制的方法仍然很原始。在这里，我们提出了一种基于模型的方法来系统分析调节转录因子-DNA 结合的表观基因组功能。基于统计力学的第一原理，该模型考虑了表观基因组修饰与顺式调控模块之间的相互作用，该模块包含以任何配置排列的多个结合位点。我们在小鼠胚胎干 (mES) 细胞中编制了全面的表观基因组数据集，包括 DNA 甲基化（MeDIP-seq 和 MRE-seq）、DNA 羟甲基化 (5-hmC-seq) 和组蛋白修饰 (ChIP-seq)。我们发现了转录因子（TF）与表观基因组修饰的特定组合的相关性，我们将其称为表观基因组基序。表观基因组基序解释了为什么一些 TF 似乎具有源自体内 (ChIP-seq) 和体外实验的不同 DNA 结合基序。理论分析表明表观基因组可以调节转录噪音并增强弱 TF 结合位点的协同性。 ChIP-seq 数据表明，弱 TF 结合位点的表观基因组结合亲和力增强可以在 mES 细胞中发挥作用。我们从理论上证明，表观基因组应该抑制两个人中含有 SNP 的结合位点上 TF 结合的差异。使用个人数据，我们确定了 H3K4me2/H3K9ac 与包含 SNP 的结合位点中 NFκB 结合的个人差异程度之间存在很强的关联，这可以解释为什么某些 SNP 在 TF 结合上引入的个人差异比其他 SNP 小得多。总之，该模型提供了一种分析表观基因组修饰功能的强大方法。该模型被实施到开源程序 APEG（Epigenome 和 Genome 的亲和力预测，http://systemsbio.ucsd.edu/apeg）中。我们开发了一种基于模型的方法来系统分析调节转录因子-DNA 结合的表观基因组功能。我们假设存在 TF 特异性表观基因组基序，这可以解释为什么一些 TF 似乎具有来自体内和体外实验的不同 DNA 结合基序。理论结果表明表观基因组可以调节转录噪音并增强弱 TF 结合位点的协同性。对现有数据的初步分析表明，弱 TF 结合位点的表观基因组结合亲和力增强可能是 mES 细胞中广泛的调节机制。此外，利用个人数据，我们发现H3K4me2/H3K9ac与含SNP结合位点的NFκB结合的个体差异程度之间存在很强的关联，这表明表观基因组减弱两个个体中含SNP结合位点的TF结合差异的理论机制可能有助于将基因组变异与表型变异联系起来。因此，该模型提供了一种分析表观基因组修饰功能的强大方法。
Despite explosive growth in genomic datasets, the methods for studying epigenomic mechanisms of gene regulation remain primitive. Here we present a model-based approach to systematically analyze the epigenomic functions in modulating transcription factor-DNA binding. Based on the first principles of statistical mechanics, this model considers the interactions between epigenomic modifications and a cis-regulatory module, which contains multiple binding sites arranged in any configurations. We compiled a comprehensive epigenomic dataset in mouse embryonic stem (mES) cells, including DNA methylation (MeDIP-seq and MRE-seq), DNA hydroxymethylation (5-hmC-seq), and histone modifications (ChIP-seq). We discovered correlations of transcription factors (TFs) for specific combinations of epigenomic modifications, which we term epigenomic motifs. Epigenomic motifs explained why some TFs appeared to have different DNA binding motifs derived from in vivo (ChIP-seq) and in vitro experiments. Theoretical analyses suggested that the epigenome can modulate transcriptional noise and boost the cooperativity of weak TF binding sites. ChIP-seq data suggested that epigenomic boost of binding affinities in weak TF binding sites can function in mES cells. We showed in theory that the epigenome should suppress the TF binding differences on SNP-containing binding sites in two people. Using personal data, we identified strong associations between H3K4me2/H3K9ac and the degree of personal differences in NFκB binding in SNP-containing binding sites, which may explain why some SNPs introduce much smaller personal variations on TF binding than other SNPs. In summary, this model presents a powerful approach to analyze the functions of epigenomic modifications. This model was implemented into an open source program APEG (Affinity Prediction by Epigenome and Genome, http://systemsbio.ucsd.edu/apeg). We developed a model-based approach to systematically analyze the epigenomic functions in modulating transcription factor-DNA binding. We postulated the existence of TF-specific epigenomic motifs, which could explain why some TFs appeared to have different DNA binding motifs derived from in vivo and in vitro experiments. The theoretical results suggested that the epigenome can modulate transcriptional noise and boost the cooperativity of weak TF binding sites. A preliminary analysis of the existing data suggested that epigenomic boost of binding affinities in weak TF binding sites could be a widespread regulatory mechanism in mES cells. Moreover, using personal data, we identified strong associations between H3K4me2/H3K9ac and the degree of individual differences in NFκB binding in SNP-containing binding sites, suggesting the theoretical mechanism for epigenome to attenuate the TF binding differences on SNP-containing binding sites in two individuals may contribute to link genomic variation to phenotypic variation. Thus, this model presents a powerful approach to analyze the functions of epigenomic modifications.
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影响因子：
64.8
作者：
Ernst, Jason;Kheradpour, Pouya;Mikkelsen, Tarjei S.;Shoresh, Noam;Ward, Lucas D.;Epstein, Charles B.;Zhang, Xiaolan;Wang, Li;Issner, Robbyn;Coyne, Michael;Ku, Manching;Durham, Timothy;Kellis, Manolis;Bernstein, Bradley E.
通讯作者：
Bernstein, Bradley E.
影响因子：
9.9
作者：
Fakhouri, Walid D.;Ay, Ahmet;Sayal, Rupinder;Dresch, Jacqueline;Dayringer, Evan;Arnosti, David N.
通讯作者：
Arnosti, David N.
影响因子：
30.8
作者：
He, Housheng Hansen;Meyer, Clifford A.;Shin, Hyunjin;Bailey, Shannon T.;Wei, Gang;Wang, Qianben;Zhang, Yong;Xu, Kexin;Ni, Min;Lupien, Mathieu;Mieczkowski, Piotr;Lieb, Jason D.;Zhao, Keji;Brown, Myles;Liu, X. Shirley
通讯作者：
Liu, X. Shirley
DOI：
10.1126/science.1183621
发表时间：
2010-04-09
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Kasowski M;Grubert F;Heffelfinger C;Hariharan M;Asabere A;Waszak SM;Habegger L;Rozowsky J;Shi M;Urban AE;Hong MY;Karczewski KJ;Huber W;Weissman SM;Gerstein MB;Korbel JO;Snyder M
通讯作者：
Snyder M
影响因子：
64.8
作者：
Gertz, Jason;Siggia, Eric D.;Cohen, Barak A.
通讯作者：
Cohen, Barak A.