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将表观基因组学融入对生物医学见解的理解中。

Integrating Epigenomics into the Understanding of Biomedical Insight.

作者信息

Han Yixing, He Ximiao

机构信息

Mouse Cancer Genetics Program, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD, USA.; Present address: Genetics and Biochemistry Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.

Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.; Present address: Department of Medical Genetics, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.

出版信息

Bioinform Biol Insights. 2016 Dec 4;10:267-289. doi: 10.4137/BBI.S38427. eCollection 2016.

Abstract

Epigenetics is one of the most rapidly expanding fields in biomedical research, and the popularity of the high-throughput next-generation sequencing (NGS) highlights the accelerating speed of epigenomics discovery over the past decade. Epigenetics studies the heritable phenotypes resulting from chromatin changes but without alteration on DNA sequence. Epigenetic factors and their interactive network regulate almost all of the fundamental biological procedures, and incorrect epigenetic information may lead to complex diseases. A comprehensive understanding of epigenetic mechanisms, their interactions, and alterations in health and diseases genome widely has become a priority in biological research. Bioinformatics is expected to make a remarkable contribution for this purpose, especially in processing and interpreting the large-scale NGS datasets. In this review, we introduce the epigenetics pioneering achievements in health status and complex diseases; next, we give a systematic review of the epigenomics data generation, summarize public resources and integrative analysis approaches, and finally outline the challenges and future directions in computational epigenomics.

摘要

表观遗传学是生物医学研究中发展最为迅速的领域之一,高通量下一代测序(NGS)的普及凸显了过去十年间表观基因组学发现的加速进程。表观遗传学研究染色质变化导致的可遗传表型,而DNA序列不发生改变。表观遗传因子及其相互作用网络调控几乎所有基本生物学过程,错误的表观遗传信息可能导致复杂疾病。全面了解表观遗传机制、它们的相互作用以及在健康和疾病基因组中的改变已成为生物学研究的当务之急。预计生物信息学将为此做出显著贡献,尤其是在处理和解释大规模NGS数据集方面。在本综述中,我们介绍表观遗传学在健康状况和复杂疾病方面的开创性成就;接下来,我们对表观基因组学数据生成进行系统综述,总结公共资源和整合分析方法,最后概述计算表观基因组学面临的挑战和未来方向。

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