Summary Starch is the most abundant storage carbohydrate in maize kernels and provides calories for humans and other animals as well as raw materials for various industrial applications. Decoding the genetic basis of natural variation in kernel starch content is needed to manipulate starch quantity and quality via molecular breeding to meet future needs. Here, we identified 50 unique single quantitative trait loci (QTLs) for starch content with 18 novel QTLs via single linkage mapping, joint linkage mapping and a genome‐wide association study in a multi‐parent population containing six recombinant inbred line populations. Only five QTLs explained over 10% of phenotypic variation in single populations. In addition to a few large‐effect and many small‐effect additive QTLs, limited pairs of epistatic QTLs also contributed to the genetic basis of the variation in kernel starch content. A regional association study identified five non‐starch‐pathway genes that were the causal candidate genes underlying the identified QTLs for starch content. The pathway‐driven analysis identified ZmTPS9, which encodes a trehalose‐6‐phosphate synthase in the trehalose pathway, as the causal gene for the QTL qSTA4−2, which was detected by all three statistical analyses. Knockout of ZmTPS9 increased kernel starch content and, in turn, kernel weight in maize, suggesting potential applications for ZmTPS9 in maize starch and yield improvement. These findings extend our knowledge about the genetic basis of starch content in maize kernels and provide valuable information for maize genetic improvement of starch quantity and quality.

Summary The nutritional traits of maize kernels are important for human and animal nutrition, and these traits have undergone selection to meet the diverse nutritional needs of humans. However, our knowledge of the genetic basis of selecting for kernel nutritional traits is limited. Here, we identified both single and epistatic quantitative trait loci (QTLs) that contributed to the differences of oil and carotenoid traits between maize and teosinte. Over half of teosinte alleles of single QTLs increased the values of the detected oil and carotenoid traits. Based on the pleiotropism or linkage information of the identified single QTLs, we constructed a trait–locus network to help clarify the genetic basis of correlations among oil and carotenoid traits. Furthermore, the selection features and evolutionary trajectories of the genes or loci underlying variations in oil and carotenoid traits revealed that these nutritional traits produced diverse selection events during maize domestication and improvement. To illustrate more, a mutator distance–relative transposable element (TE) in intron 1 of DXS2, which encoded a rate‐limiting enzyme in the methylerythritol phosphate pathway, was identified to increase carotenoid biosynthesis by enhancing DXS2 expression. This TE occurs in the grass teosinte, and has been found to have undergone selection during maize domestication and improvement, and is almost fixed in yellow maize. Our findings not only provide important insights into evolutionary changes in nutritional traits, but also highlight the feasibility of reintroducing back into commercial agricultural germplasm those nutritionally important genes hidden in wild relatives.

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Zinc (Zn) deficiency is one of the most common micronutrient disorders in cereal plants, greatly impairing crop productivity and nutritional quality. Identifying the genes associated with Zn deficiency tolerance is the basis for understanding the genetic mechanism conferring tolerance. In this study, the K22×BY815 and DAN340×K22 recombination inbred line (RIL) populations, which were derived from Zn-inefficient and Zn-efficient inbred lines, were utilized to detect the quantitative trait loci (QTLs) associated with Zn deficiency tolerance and to further identify candidate genes within these loci. The BLUP (Best Linear Unbiased Prediction) values under Zn-deficient condition (-Zn) and the ratios of the BLUP values under Zn deficient condition to the BLUP values under Zn-sufficient condition (-Zn/CK) were used to perform linkage mapping. In QTL analysis, 21 QTLs and 33 QTLs controlling the Zn score, plant height, shoot and root dry weight, and root-to-shoot ratio were detected in the K22×BY815 population and the DAN340×K22 population, explaining 5.5–16.6% and 4.2–23.3% of phenotypic variation, respectively. In addition, seventeen candidate genes associated with the mechanisms underlying Zn deficiency tolerance were identified in QTL colocalizations or the single loci, including the genes involved in the uptake, transport, and redistribution of Zn (ZmIRT1, ZmHMAs, ZmNRAMP6, ZmVIT, ZmNAS3, ZmDMAS1, ZmTOM3), and the genes participating in the auxin and ethylene signal pathways (ZmAFBs, ZmIAA17, ZmETR, ZmEIN2, ZmEIN3, ZmCTR3, ZmEBF1). Our findings will broaden the understanding of the genetic structure of the tolerance to Zn deficiency in maize.