遗传 ›› 2014, Vol. 36 ›› Issue (11): 1099-1111.

• 综述 • 上一篇    下一篇

基于高通量测序的全基因组关联研究策略

周家蓬1,裴智勇1,2,陈禹保1,陈润生3   

  1. 1. 北京市计算中心
    2. 中国科学院北京基因组研究所
    3. 中国科学院生物物理研究所
  • 收稿日期:2014-03-31 修回日期:2014-09-19 出版日期:2014-11-20 发布日期:2014-10-28
  • 通讯作者: 裴智勇 E-mail:peizy@bcc.ac.cn
  • 基金资助:

    北科院海外人才项目;北科院海外人才项目;国自然面上项目;北自然重大项目;北京市计算中心萌芽计划项目

Strategies of genome-wide association study based on high-throughput sequencing

Jiapeng Zhou1, Zhiyong Pei1, 2, Yubao Chen1, Runsheng Chen3   

  • Received:2014-03-31 Revised:2014-09-19 Online:2014-11-20 Published:2014-10-28

摘要:

全基因组关联研究(Genome-wide association study, GWAS)是人类复杂疾病研究的重要组成部分之一,在群体水平检测全基因组范围的遗传变异与可观测性状间的遗传关联。传统的GWAS是以芯片(Array)技术获得高密度的遗传变异,尽管硕果累累,但也存在不少问题。如:所谓的“缺失的遗传力”,即利用关联分析检测达到全基因组水平显著的遗传变异位点只能解释小部分遗传力;在某些性状上不同研究的结果一致性较弱;显著关联的遗传变异位点的功能较难解释等。高通量测序技术,也称第二代测序(Next-generation sequencing, NGS)技术,可以快速、准确地产出高通量的变异位点数据,为解决以上问题提供了可行的方案。基于NGS技术的GWAS方法(NGS-GWAS),可在一定程度上弥补传统GWAS的不足。文章对NGS-GWAS策略和方法进行了系统性调研,提出了目前较为可行的NGS-GWAS的实施策略和方法,并对NGS-GWAS如何应用于个体化医疗(Personalized medicine, PM)进行了展望。

关键词: 全基因组关联研究, 第二代测序, 个体化医疗

Abstract:

Genome-wide association studies (GWASs) have been playing an important role on human complex diseases. Generally speaking, GWAS tries to detect the relationship between genome-wide genetic variants and measurable traits in the population level. Although fruitful, array-based GWASs still exist some problems, for example, the so-called “missing heritability”--significantly associated SNPs can only explain a small part of phenotypic variation. Other problems include that, in some traits, significantly associated SNPs in one study are hard to be repeated by other studies; and that the functions of significantly associated SNPs are often difficult to interpret. High-throughput sequencing, also known as next-generation sequencing (NGS), could be one of the most promising technologies to solve those problems by quickly producing accurate variations in a high-throughput way. NGS-based GWASs (NGS-GWAS), to some extent, provide a better solution compared with traditional array-based GWASs. We systematically review the strategies and methods for NGS-GWASs, pick out the most feasible and efficient strategies and methods for NGS-GWASs, and discuss their applications in personalized medicine.

Key words: genome-wide association study (GWAS), next-generation sequencing (NGS), personalized medicine (PM)