College of Agronomy, Shenyang Agricultural University, Shenyang, Liaoning 110866, China.
The Key Laboratory of Maize Biology and Genetic Breeding in Arid Area of Northwest Region, Yangling, Shaanxi 712100, China.
J Agric Food Chem. 2024 Sep 11;72(36):20182-20193. doi: 10.1021/acs.jafc.4c04683. Epub 2024 Aug 28.
The primary objective in contemporary maize breeding is to pursue high quality alongside high yield. Deciphering the genetic basis of natural variation in starch, protein, oil, and fiber contents is essential for manipulating kernel composition, thereby enhancing the kernel quality and meeting growing demands. Here, we identified 12 to 88 statistically significant loci associated with kernel composition traits through a genome-wide association study (GWAS) using a panel of 212 diverse inbred lines. A regional association study pinpointed numerous causal candidate genes at these loci. Coexpression and protein-protein interaction network analyses of candidate genes revealed several causal genes directly or indirectly involved in the metabolic processes related to kernel composition traits. Subsequent mutant experiment revealed that nonsense mutations in affect starch, protein, and fiber content, whereas nonsense mutations in affect starch, protein, and oil content. These findings provide valuable guidance for improving kernel quality in maize breeding efforts.
当代玉米育种的主要目标是追求高产和优质。解析淀粉、蛋白质、油和纤维含量的自然变异的遗传基础对于操纵籽粒组成至关重要，从而提高籽粒品质，满足不断增长的需求。在这里，我们通过对 212 个不同自交系的群体进行全基因组关联研究（GWAS），鉴定出 12 到 88 个与籽粒组成性状显著相关的统计显著位点。区域关联研究在这些位点上确定了许多候选基因。候选基因的共表达和蛋白质-蛋白质相互作用网络分析揭示了一些直接或间接参与与籽粒组成性状相关的代谢过程的候选基因。随后的突变实验表明， 中的无意义突变影响淀粉、蛋白质和纤维含量，而 中的无意义突变影响淀粉、蛋白质和油含量。这些发现为在玉米育种工作中提高籽粒品质提供了有价值的指导。
