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复杂疾病的遗传易感基因区域的精细定位

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  • 1. 广西医科大学附属肿瘤医院介入治疗科, 南宁 530021;
    2. 军事医学科学院放射与辐射医学研究所, 北京蛋白质组学研究中心, 蛋白质组学国家重点实验室, 北京 102206;
    3. 蛋白质药物国家工程研究中心, 北京 102206;
    4. 国家蛋白质科学中心(北京), 北京 102206
宋庆峰, 硕士研究生, 专业方向:复杂疾病的遗传易感性。Tel: 0771-5332738; E-mail: qfsong2010@hotmail.com

收稿日期: 2013-05-08

  修回日期: 2013-09-24

  网络出版日期: 2013-12-20

基金资助

国家自然科学基金项目(编号:81222027; 30901707; 30901231)和北京市科技新星计划项目(编号:2010B006)资助

Fine mapping of complex disease susceptibility loci

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  • 1. Interventional Radiology Department of Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, China; 
    2. State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, Beijing 102206, China; 
    3. National Engineering Research Center for Protein Drugs, Beijing 102206, China; 
    4. National Center for Protein Sciences in Beijing, Beijing 102206, China

Received date: 2013-05-08

  Revised date: 2013-09-24

  Online published: 2013-12-20

摘要

以单核苷酸多态性(Single-nucleotide polymorphism, SNP)为遗传标记, 采用全基因组关联研究(Genome-wide association studies, GWAS)的策略, 已经在660多种疾病(或性状)中发现了3800多个遗传易感基因区域。但是, 其中最显著关联的遗传变异或致病性的遗传变异位点及其生物学功能并不完全清楚。这些位点的鉴定有助于阐明复杂疾病的生物学机制, 以及发现新的疾病标记物。后GWAS时代的主要任务之一就是通过精细定位研究找到复杂疾病易感基因区域内最显著关联的易感位点或致病性的易感位点并阐明其生物学功能。针对常见变异, 可通过推断或重测序增加SNP密度, 寻找最显著关联的SNP位点, 并通过功能元件分析、表达数量性状位点(Expression quantitative trait locus, eQTL)分析和单体型分析等方法寻找功能性的SNP位点和易感基因。针对罕见变异, 则可采用重测序、罕见单体型分析、家系分析和负荷检验等方法进行精细定位。文章对这些策略和所面临的问题进行了综述。

本文引用格式

宋庆峰, 张红星, 马亦龙, 周钢桥 . 复杂疾病的遗传易感基因区域的精细定位[J]. 遗传, 2014 , 36(1) : 2 -10 . DOI: 10.3724/SP.J.1005.2014.00002

Abstract

Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers have identified more than 3800 susceptibility loci for more than 660 diseases or traits. However, the most significantly associated variants or causative variants in these loci and their biological functions have remained to be clarified. These causative variants can help to elucidate the pathogenesis and discover new biomarkers of complex diseases. One of the main goals in the post-GWAS era is to identify the causative variants and susceptibility genes, and clarify their functional aspects by fine mapping. For common variants, imputation or re-sequencing based strategies were implemented to increase the number of analyzed variants and help to identify the most significantly associated variants. In addition, functional element, expression quantitative trait locus (eQTL) and haplotype analyses were performed to identify functional common variants and susceptibility genes. For rare variants, fine mapping was carried out by re-sequencing, rare haplotype analysis, family-based analysis, burden test, etc.This review summarizes the strategies and problems for fine mapping.

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