Genome-Wide Analysis and Genomic Prediction of Chilling Tolerance of Maize During Germination Stage Using Genotyping-by-Sequencing SNPs

Shiliang Cao (), Tao Yu, Gengbin Yang, Wenyue Li, Xuena Ma and Jianguo Zhang
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Shiliang Cao: Maize Research Institute of Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China
Tao Yu: Maize Research Institute of Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China
Gengbin Yang: Maize Research Institute of Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China
Wenyue Li: Maize Research Institute of Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China
Xuena Ma: Maize Research Institute of Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China
Jianguo Zhang: Maize Research Institute of Heilongjiang Academy of Agricultural Sciences, Harbin 150086, China

Agriculture, 2024, vol. 14, issue 11, 1-15

Abstract: Chilling injury during the germination stage (CIGS) of maize significantly hinders production, particularly in middle- and high-latitude regions, leading to slow germination, seed decay, and increased susceptibility to pathogens. This study dissects the genetic architecture of CIGS resistance expressed in terms of the relative germination rate (RGR) in maize through association mapping using genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs). A natural panel of 287 maize inbred lines was evaluated across multiple environments. The results revealed a broad-sense heritability of 0.68 for chilling tolerance, with 12 significant QTLs identified on chromosomes 1, 3, 5, 6, and 10. A genomic prediction analysis demonstrated that the rr-BLUP model outperformed other models in accuracy, achieving a moderate prediction accuracy of 0.44. This study highlights the potential of genomic selection (GS) to enhance chilling tolerance in maize, emphasizing the importance of training population size, marker density, and significant markers on prediction accuracy. These findings provide valuable insights for breeding programs aimed at improving chilling tolerance in maize.

Keywords: maize; chilling tolerance; germination; genomic prediction; SNP; association mapping (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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