4.7 Article

Genome wide association analysis for yield related traits in maize

Journal

BMC PLANT BIOLOGY
Volume 22, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12870-022-03812-5

Keywords

Maize; Yield related trait; Genome-wide association study; Quantitative trait nucleotide; Marker-assisted selection

Categories

Funding

  1. Shandong Natural Science Foundation of China [ZR2020MC111]
  2. Key R&D project of Shandong Province [2021LZGC022]
  3. China Agriculture Research System of MOF and MARA [CARS-02-09]

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Using a large-scale investigation, this study identified 59 significantly associated genetic loci related to maize yield through genome-wide association analysis. These findings are important for understanding the genetic architecture of maize yield and genetic improvement of maize.
Background Understanding the genetic basis of yield related traits contributes to the improvement of grain yield in maize. Results Using 291 excellent maize inbred lines as materials, six yield related traits of maize, including grain yield per plant (GYP), grain length (GL), grain width (GW), kernel number per row (KNR), 100 kernel weight (HKW) and tassel branch number (TBN) were investigated in Jinan, in 2017, 2018 and 2019. The average values of three environments were taken as the phenotypic data of yield related traits, and they were statistically analyzed. Based on 38,683 high-quality SNP markers in the whole genome of the association panel, the MLM with PCA model was used for genome-wide association analysis (GWAS) to obtain 59 significantly associated SNP sites. Moreover, 59 significantly associated SNPs (P < 0.0001) referring to GYP, GL, GW, KNR, HKW and TBN, of which 14 SNPs located in yield related QTLs/QTNs previously reported. A total of 66 candidate genes were identified based on the 59 significantly associated SNPs, of which 58 had functional annotation. Conclusions Using genome-wide association analysis strategy to identify genetic loci related to maize yield, a total of 59 significantly associated SNP were detected. Those results aid in our understanding of the genetic architecture of maize yield and provide useful SNPs for genetic improvement of maize.

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