通过整合性表观遗传学来调节人类疾病的基因组电路
Carles A Boix1,2,3, Benjamin T James1,2, Yongjin P Park1,2,4
1Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
Nature
|February 4, 2021
概括
一个大型的表观基因图集EpiMap注释了与人类疾病相关的非编码遗传变异. 该资源揭示了复杂的特征变性,并确定了疾病基因发现的组织特异性调节元素.
科学领域:
- 基因组学
- 表观遗传学
- 人类疾病遗传学
背景情况:
- 大多数人类疾病的基因位置都在非编码区域,有不完整的基因调节注释.
- 由于这些局限性,了解人类疾病的分子基础是一个重大挑战.
研究的目的:
- 介绍一个全面的表观基因地图资源EpiMap.
- 标注与人类特征和疾病相关的遗传位置.
- 调查复杂特征的复杂性.
主要方法:
- 在800个样本中生成了10,000个表观基因地图.
- 定义的染色体状态,增强剂,调节模块和向基因.
- 使用EpiMap资源注释了3万个与特征相关的遗传位点.
主要成果:
- 预测了与特征相关的组织,因果变异,以及为30,000个位点的候选目标基因.
- 将多因素特征划分为特定组织的促成因素.
- 揭示了广泛的变性,其中常常涉及多种变体,增强剂,基因和组织.
结论:
- 密集,高分辨率的表观遗传学注释对于复杂的特征调查至关重要.
- EpiMap为了解人类疾病的遗传结构提供了宝贵的资源.
- 这些发现突出了复杂的特征和疾病关联的复杂调节网络.
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