International Journal of Molecular Sciences (Jan 2023)

A Systemic Investigation of Genetic Architecture and Gene Resources Controlling Kernel Size-Related Traits in Maize

  • Cheng Wang,
  • Huangai Li,
  • Yan Long,
  • Zhenying Dong,
  • Jianhui Wang,
  • Chang Liu,
  • Xun Wei,
  • Xiangyuan Wan

DOI
https://doi.org/10.3390/ijms24021025
Journal volume & issue
Vol. 24, no. 2
p. 1025

Abstract

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Grain yield is the most critical and complex quantitative trait in maize. Kernel length (KL), kernel width (KW), kernel thickness (KT) and hundred-kernel weight (HKW) associated with kernel size are essential components of yield-related traits in maize. With the extensive use of quantitative trait locus (QTL) mapping and genome-wide association study (GWAS) analyses, thousands of QTLs and quantitative trait nucleotides (QTNs) have been discovered for controlling these traits. However, only some of them have been cloned and successfully utilized in breeding programs. In this study, we exhaustively collected reported genes, QTLs and QTNs associated with the four traits, performed cluster identification of QTLs and QTNs, then combined QTL and QTN clusters to detect consensus hotspot regions. In total, 31 hotspots were identified for kernel size-related traits. Their candidate genes were predicted to be related to well-known pathways regulating the kernel developmental process. The identified hotspots can be further explored for fine mapping and candidate gene validation. Finally, we provided a strategy for high yield and quality maize. This study will not only facilitate causal genes cloning, but also guide the breeding practice for maize.

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