Author
LI, YONG-XIANG - Chinese Academy Of Agricultural Sciences | |
LI, CHUNHUI - Chinese Academy Of Agricultural Sciences | |
Bradbury, Peter | |
LIU, XIAOLEI - Cornell University | |
ROMAY, CINTA - Cornell University | |
GLAUBITZ, JEFFREY - Cornell University | |
WU, XUN - Chinese Academy Of Agricultural Sciences | |
PENG, BO - Chinese Academy Of Agricultural Sciences | |
SHI, YUNSU - Chinese Academy Of Agricultural Sciences | |
SONG, YANCHUN - Chinese Academy Of Agricultural Sciences | |
ZHANG, DENGFENG - Chinese Academy Of Agricultural Sciences | |
Buckler, Edward - Ed | |
ZHANG, ZHIWU - Washington State University | |
LI, YU - Chinese Academy Of Agricultural Sciences | |
WANG, TIANYU - Chinese Academy Of Agricultural Sciences |
Submitted to: Plant Journal
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 3/18/2016 Publication Date: 6/20/2016 Citation: Li, Y., Li, C., Bradbury, P., Liu, X., Romay, C., Glaubitz, J., Wu, X., Peng, B., Shi, Y., Song, Y., Zhang, D., Buckler IV, E.S., Zhang, Z., Li, Y., Wang, T. 2016. Identification of genetic variants associated with maize flowering time using an extremely large multi-genetic background population. Plant Journal. 86(5):391-402. Interpretive Summary: Flowering time is arguably the most important trait involved in the adaptation of maize to a wide range of environments from the equator into Canada. Because of its importance, flowering time has been the subject of a number of genetic studies. In this research, a large collaboration between US and Chinese scientists, over 8000 maize inbred lines, representing a wide range of germplasm including lines adapted to both countries and to the tropics, were grown in environments in China and the US and genotyped with almost 1 million genetic markers. A genome-wide association study (GWAS) of the lines found almost 1000 associated markers, many located near a set of 220 genes thought to affect flowering time. When the associated SNPs were used to create a statistical model of flowering time, the resulting model accurately predicted flowering time in lines that were not used to create the model. Technical Abstract: Flowering time is one of the major adaptive traits in domestication of maize and an important selection criterion in breeding. To detect more maize flowering time variants we evaluated flowering time traits using an extremely large multi- genetic background population that contained more than 8000 lines under multiple Sino-United States environments. The population included two nested association mapping (NAM) panels and a natural association panel. Nearly 1 million single-nucleotide polymorphisms (SNPs) were used in the analyses. Through the parallel linkage analysis of the two NAM panels, both common and unique flowering time regions were detected. Genome wide, a total of 90 flowering time regions were identified. One-third of these regions were connected to traits associated with the environmental sensitivity of maize flowering time. The genome-wide association study of the three panels identified nearly 1000 flowering time-associated SNPs, mainly distributed around 220 candidate genes (within a distance of 1 Mb). Interestingly, two types of regions were significantly enriched for these associated SNPs - one was the candidate gene regions and the other was the approximately 5 kb regions away from the candidate genes. Moreover, the associated SNPs exhibited high accuracy for predicting flowering time. |