Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice

• Published in: Nature communications Vol. 5; no. 1; p. 5087
• Main Authors: Yang, Wanneng, Guo, Zilong, Huang, Chenglong, Duan, Lingfeng, Chen, Guoxing, Jiang, Ni, Fang, Wei, Feng, Hui, Xie, Weibo, Lian, Xingming, Wang, Gongwei, Luo, Qingming, Zhang, Qifa, Liu, Qian, Xiong, Lizhong
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 08.10.2014; Nature Publishing Group; Nature Pub. Group
• Subjects: 38/43; 49/47; 49/56; 631/1647/1513; 631/449/1870; 631/61/447/8; Genetic Variation; Genome, Plant - genetics; Genome-Wide Association Study; High-Throughput Screening Assays - methods; Humanities and Social Sciences; multidisciplinary; Optical Imaging; Oryza - genetics; Oryza - physiology; Phenotype; Quantitative Trait Loci - genetics; Science; Science (multidisciplinary); Tomography, X-Ray Computed
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/ncomms6087

Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1 . Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits. Next-generation sequencing technology has made the generation of huge amounts of genetic data possible, but phenotype characterization remains slow and difficult. Here the authors develop a high-throughput phenotyping facility for rice that is able to accurately identify and characterize traits related to morphology, biomass and yield.