Linkage and association mapping in multi-parental populations reveal the genetic basis of carotenoid variation in maize kernels.

Carotenoids are indispensable to plants and critical components of the human diet. The carotenoid metabolic pathway is conserved across plant species, but our understanding of the genetic basis of carotenoid variation remains limited for the seeds of most cereal crops. To address this issue, we systematically performed linkage and association mapping for eight carotenoid traits using six recombinant inbred line (RIL) populations. Single linkage mapping (SLM) and joint linkage mapping (JLM) identified 77 unique additive QTLs and 104 pairs of epistatic QTLs. Among these QTLs, we identified 22 overlapping hotspots of additive and epistatic loci, highlighting the important contributions of some QTLs to carotenoid levels through additive or epistatic mechanisms. A genome-wide association study based on all RILs detected 244 candidate genes significantly associated with carotenoid traits, 23 of which were annotated as carotenoid pathway genes. Effect comparisons suggested that a small number of loci linked to pathway genes have substantial effects on carotenoid variation in our tested populations, but many loci not associated with pathway genes also make important contributions to carotenoid variation. We identified ZmPTOX as the causal gene for a QTL hotspot (Q10/JLM10/GWAS019); this gene encodes a putative plastid terminal oxidase that produces plastoquinone-9 used by two enzymes in the carotenoid pathway. Natural variants in the promoter and second exon of ZmPTOX were found to alter carotenoid levels. This comprehensive assessment of the genetic mechanisms underlying carotenoid variation establishes a foundation for rewiring carotenoid metabolism and accumulation for efficient carotenoid biofortification.

Genetic basis of kernel starch content decoded in a maize multi-parent population.

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.

Transcriptome analysis of near-isogenic lines provides molecular insights into starch biosynthesis in maize kernel.

Starch is the major component in maize kernels, providing a stable carbohydrate source for humans and livestock as well as raw material for the biofuel industry. Increasing maize kernel starch content will help meet industry demands and has the potential to increase overall yields. We developed a pair of maize near-isogenic lines (NILs) with different alleles for a starch quantitative trait locus on chromosome 3 (qHS3), resulting in different kernel starch content. To investigate the candidate genes for qHS3 and elucidate their effects on starch metabolism, RNA-Seq was performed for the developing kernels of the NILs at 14 and 21 d after pollination (DAP). Analysis of genomic and transcriptomic data identified 76 genes with nonsynonymous single nucleotide polymorphisms and 384 differentially expressed genes (DEGs) in the introgressed fragment, including a hexokinase gene, ZmHXK3a, which catalyzes the conversion of glucose to glucose-6-phosphate and may play a key role in starch metabolism. The expression pattern of all DEGs in starch metabolism shows that altered expression of the candidate genes for qHS3 promoted starch synthesis, with positive consequences for kernel starch content. These results expand the current understanding of starch biosynthesis and accumulation in maize kernels and provide potential candidate genes to increase starch content.

Genetic basis of maize kernel starch content revealed by high-density single nucleotide polymorphism markers in a recombinant inbred line population.

BACKGROUND: Starch from maize kernels has diverse applications in human and animal diets and in industry and manufacturing. To meet the demands of these applications, starch quantity and quality need improvement, which requires a clear understanding of the functional mechanisms involved in starch biosynthesis and accumulation. In this study, a recombinant inbred line (RIL) population was developed from a cross between inbred lines CI7 and K22. The RIL population, along with both parents, was grown in three environments, and then genotyped using the MaizeSNP50 BeadChip and phenotyped to dissect the genetic architecture of starch content in maize kernels. RESULTS: Based on the genetic linkage map constructed using 2,386 bins as markers, six quantitative trait loci (QTLs) for starch content in maize kernels were detected in the CI7/K22 RIL population. Each QTL accounted for 4.7% (qSTA9-1) to 10.6% (qSTA4-1) of the starch variation. The QTL interval was further reduced using the bin-map method, with the physical distance of a single bin at the QTL peak ranging from 81.7 kb to 2.2 Mb. Based on the functional annotations and prior knowledge of the genes in the top bin, seven genes were considered as potential candidate genes for the identified QTLs. Three of the genes encode enzymes in non-starch metabolism but may indirectly affect starch biosynthesis, and four genes may act as regulators of starch biosynthesis. CONCLUSIONS: A few large-effect QTLs, together with a certain number of minor-effect QTLs, mainly contribute to the genetic architecture of kernel starch content in our maize biparental linkage population. All of the identified QTLs, especially the large-effect QTL, qSTA4-1, with a small QTL interval, will be useful for improving the maize kernel starch content through molecular breeding.

A genome-wide association study of folates in sweet corn kernels.

Folate is commonly synthesized in natural plants and is an essential water-soluble vitamin of great importance inhuman health. Although the key genes involved in folate biosynthesis and transformation pathways have been identified in plants, the genetic architecture of folate in sweet corn kernels remain largely unclear. In this study, an association panel of 295 inbred lines of sweet corn was constructed. Six folate derivatives were quantified in sweet corn kernels at 20 days after pollination and a total of 95 loci were identified for eight folate traits using a genome-wide association study. A peak GWAS signal revealed that natural variation in ZmFCL, encoding a 5-formyltetrahydrofolate cyclo-ligase, accounted for 30.12% of phenotypic variation in 5-FTHF content. Further analysis revealed that two adjacent SNPs on the second exon resulting in an AA-to-GG in the gene and an Asn-to-Gly change in the protein could be the causative variant influencing 5-FTHF content. Meanwhile, 5-FTHF content was negatively correlated with ZmFCL expression levels in the population. These results extend our knowledge regarding the genetic basis of folate and provide molecular markers for the optimization of folate levels in sweet corn kernels.

Transcriptome Analysis Identifies Novel Genes Associated with Low-Temperature Seed Germination in Sweet Corn.

Typically, sweet corn, particularly sh2 sweet corn, has low seed vigor owing to its high sugar and low starch content, which is a major problem in sweet corn production, particularly at low temperatures. There is considerable variation in the germination rates among sweet corn varieties under low-temperature conditions, and the underlying mechanisms behind this phenomenon remain unclear. In this study, we screened two inbred sweet corn lines (tolerant line L282 and sensitive line L693) differing in their low-temperature germination rates; while no difference was observed in their germination rates at normal temperatures. To identify the specifically induced genes influencing the germination capacity of sweet corn at low temperatures, a transcriptome analysis of the two lines was conducted at both normal and low temperatures. Compared to the lines at a normal temperature, 3926 and 1404 differently expressed genes (DEGs) were identified from L282 and L693, respectively, under low-temperature conditions. Of them, 830 DEGs were common DEGs (cDEGs) that were identified from both L282 and L693, which were majorly enriched in terms of microtubule-based processes, histone H3-K9 modification, single-organism cellular processes, and carbohydrate metabolic processes. In addition, 3096 special DEGs (sDEGs), with 2199 upregulated and 897 downregulated, were detected in the tolerant line L282, but not in the sensitive line L693. These sDEGs were primarily related to plasma membranes and oxygen-containing compounds. Furthermore, electric conductivity measurements demonstrated that the membrane of L282 experienced less damage, which is consistent with its strong tolerance at low temperatures. These results expand our understanding of the complex mechanisms involved in the cold germination of sweet corn and provide a set of candidate genes for further genetic analysis.

Convergent selection of a WD40 protein that enhances grain yield in maize and rice.

A better understanding of the extent of convergent selection among crops could greatly improve breeding programs. We found that the quantitative trait locus KRN2 in maize and its rice ortholog, OsKRN2, experienced convergent selection. These orthologs encode WD40 proteins and interact with a gene of unknown function, DUF1644, to negatively regulate grain number in both crops. Knockout of KRN2 in maize or OsKRN2 in rice increased grain yield by ~10% and ~8%, respectively, with no apparent trade-offs in other agronomic traits. Furthermore, genome-wide scans identified 490 pairs of orthologous genes that underwent convergent selection during maize and rice evolution, and these were enriched for two shared molecular pathways. KRN2, together with other convergently selected genes, provides an excellent target for future crop improvement.