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全基因组表观遗传学数据有助于理解疾病易感性关联研究。

Genome-wide epigenetic data facilitate understanding of disease susceptibility association studies.

机构信息

Department of Biochemistry and Molecular Biology and Center for Comparative Genomics and Bioinformatics, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16801, USA.

出版信息

J Biol Chem. 2012 Sep 7;287(37):30932-40. doi: 10.1074/jbc.R112.352427. Epub 2012 Sep 5.

Abstract

Complex traits such as susceptibility to diseases are determined in part by variants at multiple genetic loci. Genome-wide association studies can identify these loci, but most phenotype-associated variants lie distal to protein-coding regions and are likely involved in regulating gene expression. Understanding how these genetic variants affect complex traits depends on the ability to predict and test the function of the genomic elements harboring them. Community efforts such as the ENCODE Project provide a wealth of data about epigenetic features associated with gene regulation. These data enable the prediction of testable functions for many phenotype-associated variants.

摘要

复杂性状(如疾病易感性)部分由多个遗传位点的变异决定。全基因组关联研究可以识别这些位点,但大多数与表型相关的变异位于编码区之外,可能参与调控基因表达。了解这些遗传变异如何影响复杂性状,取决于预测和测试携带这些变异的基因组元件功能的能力。ENCODE 项目等社区努力提供了大量与基因调控相关的表观遗传特征数据。这些数据使许多与表型相关的变异的可测试功能得以预测。

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