遗传 ›› 2011, Vol. 33 ›› Issue (2): 100-108.doi: 10.3724/SP.J.1005.2011.00100

• 综述 • 上一篇    下一篇

全基因组关联研究的深度分析策略

权晟, 张学军   

  1. 安徽医科大学皮肤病研究所, 合肥 230032
  • 收稿日期:2010-08-16 修回日期:2010-10-19 出版日期:2011-02-20 发布日期:2011-02-25
  • 通讯作者: 张学军 E-mail:ayzxj@vip.sina.com
  • 基金资助:

    国家“863”计划项目(编号:2007AA02Z161)资助

Research strategies for the next step of genome-wide association study

QUAN Cheng, ZHANG Xue-Jun   

  1. Institute of Dermatology of Anhui Medical University, Hefei 230032, China
  • Received:2010-08-16 Revised:2010-10-19 Online:2011-02-20 Published:2011-02-25
  • Contact: ZHANG Xue-Jun E-mail:ayzxj@vip.sina.com

摘要: 2005年至今, 全基因组关联研究(Genome-wide association study, GWAS)发现了大量复杂疾病/性状相关变异。近来, 科学家们关注的焦点又集中在了如何利用GWAS数据进行深入分析, 期待发现更多复杂疾病/性状的易感基因。一些新的策略和方法已经被尝试应用到复杂疾病/性状GWAS的后续研究中, 例如深入分析GWAS数据; 鉴定新的复杂疾病/性状易感基因/位点; 国际合作和Meta分析; 易感区域精细定位及测序; 多种疾病共同易感基因研究; 以及基因型填补, 基于通路的关联分析, 基因-基因、基因-环境交互作用和上位研究等。这些策略和方法的应用弥补了经典GWAS的一些不足之处, 进一步推动了人类对复杂疾病/性状遗传机制的认识。文章对上述研究的策略、方法以及所面临的问题和挑战进行了综述, 为读者描绘了GWAS后期工作的一个简要框架。

关键词: 全基因组关联研究, 复杂疾病, 性状, 易感基因

Abstract: Since 2005, genome-wide association studies (GWAS) have yielded an unprecedented number of complex dis-eases/traits-associated variants. Recently, scientists have focused on performing further analysis by utilizing the ge-nome-wide genotyping data to identify more susceptibility genes of complex diseases/traits. Many strategies and methods have been applied in the following GWAS, such as screening other new susceptibility genes/loci for complex diseases/traits, international collaboration and meta-analysis, fine mapping and resequencing, studies on shared susceptibility genes in dif-ferent diseases, imputation methods, pathway analysis, gene-gene and gene-environment interaction, and epistasis study and so on. The application of these strategies and methods compensates the limitation of the traditional GWAS and provides new insights into genetics basis of complex diseases/traits. We reviewed these strategies and methods, as well as their diffi-culty and challenge. Meanwhile, we presented a brief framework of GWAS next step to readers.

Key words: genome-wide association studies, complex diseases, traits, susceptibility gene