Maize (Zea mays L.) is a multi-purpose row crop grown worldwide, which, over time, has often been bred for increased yield at the detriment of lower composition grain quality. Some knowledge of the genetic factors that affect quality traits has been discovered through the study of classical maize mutants; however, much of the underlying genetic control of these traits and the interaction between these traits remains unknown. To better understand variation that exists for grain compositional traits in maize, we evaluated 501 diverse temperate maize inbred lines in five unique environments and predicted 16 compositional traits (e.g., carbohydrates, protein, and starch) based on the output of near-infrared (NIR) spectroscopy. Phenotypic analysis found substantial variation for compositional traits and the majority of variation was explained by genetic and environmental factors. Correlations and trade-offs among traits in different maize types (e.g., dent, sweetcorn, and popcorn) were explored, and significant differences and meaningful correlations were detected. In total, 22.9–71.0% of the phenotypic variation across these traits could be explained using 2,386,666 single nucleotide polymorphism (SNP) markers generated from whole-genome resequencing data. A genome-wide association study (GWAS) was conducted using these same markers and found 72 statistically significant SNPs for 11 compositional traits. This study provides valuable insights in the phenotypic variation and genetic control underlying compositional traits that can be used in breeding programs for improving maize grain quality.

中文翻译：

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玉米多样性面板中籽粒组成变异的遗传控制

玉米（玉蜀黍L.) 是一种在世界范围内种植的多用途行作物，随着时间的推移，它经常被培育以提高产量，但损害了较低成分的谷物质量。通过对经典玉米突变体的研究，发现了一些影响品质性状的遗传因素的知识；然而，这些性状的许多潜在遗传控制以及这些性状之间的相互作用仍然未知。为了更好地了解玉米中存在的谷物组成性状变异，我们在五个独特的环境中评估了 501 个不同的温带玉米自交系，并根据近红外 (NIR) 的输出预测了 16 个组成性状（例如，碳水化合物、蛋白质和淀粉） ) 光谱学。表型分析发现组成性状的显着变异，大部分变异是由遗传和环境因素解释的。探索了不同玉米类型（例如，马齿、甜玉米和爆米花）中性状之间的相关性和权衡，并检测到了显着差异和有意义的相关性。总的来说，这些性状中 22.9-71.0% 的表型变异可以使用从全基因组重测序数据产生的 2,386,666 个单核苷酸多态性 (SNP) 标记来解释。使用这些相同的标记进行全基因组关联研究 (GWAS)，发现 11 个组成性状的 72 个具有统计学意义的 SNP。