Mining Candidate Genes for Kernel-Related Traits and General Combining Ability in Maize Based on Multi-Locus Genome-Wide Association Studies

Kernel-related traits are important agronomic traits that have a significant impact on maize yield, and the general combining ability (GCA) is one of the most crucial factors in maize breeding. Analyzing the genetic basis of kernel traits and their GCA is essential for maize yield improvement. In this study, a natural population including 205 inbred lines and an F1 population comprising 400 hybrids derived from four testers (Mo17, Zheng58, Chang7-2, and E28) were planted at two locations for two consecutive years, and four kernel-related traits were measured. A genome-wide association study (GWAS) was conducted using six multi-locus methods with 76,492 single-nucleotide polymorphism (SNP) markers to detect the SNPs related to four kernel-related traits and the corresponding GCA. A total of 66 and 52 SNPs significantly associated with kernel-related traits and the GCA were identified based on the threshold value of the logarithm of odds (LOD) = 3.0, respectively. Among them, eight SNPs related to the kernel traits and eight SNPs related to the GCA were simultaneously identified by using at least three methods. Finally, a total of 75 candidate genes were identified within the interval of the SNPs co-detected, of which 46 were annotated. The genes and significant SNPs identified in this study will deepen the understanding of the genetic foundation of kernel-related traits and GCAs, and also serve as molecular tools for improving kernel-related traits in maize.