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Acta Agron Sin ›› 2016, Vol. 42 ›› Issue (07): 945-956.doi: 10.3724/SP.J.1006.2016.00945

• REVIEW •     Next Articles

Advances on Methodologies for Genome-wide Association Studies in Plants

FENG Jian-Ying1,WEN Yang-Jun1,ZHANG Jin1,ZHANG Yuan-Ming2,*   

  1. 1 State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China; 2 College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China?
  • Received:2015-07-08 Revised:2016-05-09 Online:2016-07-12 Published:2016-05-11
  • Contact: 章元明, E-mail: soyzhang@mail.hzau.edu.cn; Tel: 13505161564 E-mail:fengjianying@njau.edu.cn
  • Supported by:

    This work was supported by National Natural Science Foundation of China (31301004) and Fundamental Research Funds for the Central Universities (KJQN201422).

Abstract:

Genome-wide association studies (GWAS) have been widely used in human, animal and plant genetics, and many new approaches and their softwares have been developed in recent years. To make a better use of the GWAS methods in applied research, in this study we summarized the advances on methodologies and softwares for GWAS. First, LD score regression was introduced to investigate the effect of population structure on GWAS. Then, the main approaches and their softwares for GWAS in plants were reviewed, including a single-locus model, a multi-locus model, epistasis, and multiple correlated traits. Finally, we prospected the future developments in GWAS. It should be noted that, in real data analysis at present, the methodologies for genome-wide single-marker scan under polygenic background and population structure controls are widely used, and the corresponding results are complementary to those derived from non-parameter approaches with high false discovery rate. However, the future approaches for GWAS should be based on the multi-locus genetic model, QTN-by-environment interaction, epistatic detection and multivariate analysis. Our purpose was to provide beneficial information in theoretical and applied researches.

Key words: Genome-wide association study, Epistasis, mixed linear model, multi-locus model

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