Identification of genetic variants associated with maize flowering time using an extremely large multi-genetic background population

Plant J. 2016 Jun;86(5):391-402. doi: 10.1111/tpj.13174. Epub 2016 Jun 20.


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.

Keywords: flowering time; genome-wide association study (GWAS); linkage analysis; maize (Zea mays L.); nested association mapping (NAM).

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Breeding
  • Flowers / genetics
  • Flowers / physiology
  • Genetic Background
  • Genetic Linkage
  • Genetic Variation*
  • Genome-Wide Association Study*
  • Phenotype
  • Polymorphism, Single Nucleotide
  • Time Factors
  • Zea mays / genetics*
  • Zea mays / physiology