Journal article
Identification of genetic variants associated with maize flowering time using an extremely large multi-genetic background population
The Plant journal : for cell and molecular biology, Vol.86(5), pp.391-402
06/2016
Handle:
https://hdl.handle.net/2376/102824
PMID: 27012534
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.
Metrics
18 Record Views
Details
- Title
- Identification of genetic variants associated with maize flowering time using an extremely large multi-genetic background population
- Creators
- Yong-Xiang Li - Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 10008, ChinaChunhui Li - Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 10008, ChinaPeter J Bradbury - Institute for Genomic Diversity, Cornell University, Ithaca, NY, 14853, USAXiaolei Liu - Huazhong Agricultural UniversityFei Lu - Institute for Genomic Diversity, Cornell University, Ithaca, NY, 14853, USACinta M Romay - Institute for Genomic Diversity, Cornell University, Ithaca, NY, 14853, USAJeffrey C Glaubitz - Institute for Genomic Diversity, Cornell University, Ithaca, NY, 14853, USAXun Wu - Chinese Academy of Agricultural SciencesBo Peng - Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 10008, ChinaYunsu Shi - Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 10008, ChinaYanchun Song - Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 10008, ChinaDengfeng Zhang - Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 10008, ChinaEdward S Buckler - United States Department of Agriculture-Agricultural Research Service, Ithaca, NY, 14853, USAZhiwu Zhang - Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99164, USAYu Li - Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 10008, ChinaTianyu Wang - Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, 10008, China
- Publication Details
- The Plant journal : for cell and molecular biology, Vol.86(5), pp.391-402
- Academic Unit
- Department of Crop and Soil Sciences
- Publisher
- England
- Identifiers
- 99900546638601842
- Language
- English
- Resource Type
- Journal article