Chromatin marks identify critical cell types for fine mapping complex trait variants.
Chromatin marks identify critical cell types for fine mapping complex trait variants.
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DOI：
10.1038/ng.2504
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发表时间：
2013-02
期刊：
影响因子：
30.8
通讯作者：
Raychaudhuri, Soumya
中科院分区：
文献类型：
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作者：
Trynka, Gosia;Sandor, Cynthia;Han, Buhm;Xu, Han;Stranger, Barbara E.;Liu, X. Shirley;Raychaudhuri, Soumya
如果性状相关变异改变了调控区域，那么它们应该属于相关细胞类型的染色质标记。然而，目前还不清楚在许多标记中，哪一个在定义与疾病相关的细胞类型和精细定位变体方面最有用。我们假设信息标记是表型细胞类型特异性的;也就是说，与相同性状相关的SNP可能与相同细胞类型中的标记重叠。我们检查了15个染色质标记，发现那些突出活跃的基因调控是表型细胞类型特异性的。组蛋白H3赖氨酸4位的三甲基化（H3 K4 me 3）是最具表型细胞类型特异性的（P < 1 × 10−6），这是由变体和标记的共定位而不是基因邻近性驱动的（P < 0.001）。H3 K4 me 3峰与肝脏中血浆低密度脂蛋白浓度的37个SNP重叠（P < 7 × 10−5），CD 4+调节性T细胞内类风湿性关节炎的31个SNP（P = 1 × 10−4），胰岛细胞中2型糖尿病的67个SNP（P = 0.003）和肝脏（P = 0.003），和14个SNPs的神经精神疾病的神经元组织（P = 0.007）。我们展示了细胞类型特异性H3 K4 me 3峰如何告知相关SNP的精细映射以识别因果变异。
If trait-associated variants alter regulatory regions, then they should fall within chromatin marks in relevant cell types. However, it is unclear which of the many marks are most useful in defining cell types associated with disease and fine mapping variants. We hypothesized that informative marks are phenotypically cell type specific; that is, SNPs associated with the same trait likely overlap marks in the same cell type. We examined 15 chromatin marks and found that those highlighting active gene regulation were phenotypically cell type specific. Trimethylation of histone H3 at lysine 4 (H3K4me3) was the most phenotypically cell type specific (P < 1 × 10−6), driven by colocalization of variants and marks rather than gene proximity (P < 0.001). H3K4me3 peaks overlapped with 37 SNPs for plasma low-density lipoprotein concentration in the liver (P < 7 × 10−5), 31 SNPs for rheumatoid arthritis within CD4+ regulatory T cells (P = 1 × 10−4), 67 SNPs for type 2 diabetes in pancreatic islet cells (P = 0.003) and the liver (P = 0.003), and 14 SNPs for neuropsychiatric disease in neuronal tissues (P = 0.007). We show how cell type–specific H3K4me3 peaks can inform the fine mapping of associated SNPs to identify causal variation.
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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.
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Bernstein, Bradley E.
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影响因子：
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通讯作者：
Seielstad, Mark
影响因子：
30.8
作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
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影响因子：
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