Beyond pathways: genetic dissection of tocopherol content in maize kernels by combining linkage and association analyses

Abstract

SummaryAlthough tocopherols play an important role in plants and animals, the genetic architecture of tocopherol content in maize kernels has remained largely unknown. In this study, linkage and association analyses were conducted to examine the genetic architecture of tocopherol content in maize kernels. Forty‐one unique quantitative trait loci (QTLs) were identified by linkage mapping in six populations of recombinant inbred lines (RILs). In addition, 32 significant loci were detected via genome‐wide association study (GWAS), 18 of which colocalized with the QTLs identified by linkage mapping. Fine mapping of a major QTL validated the accuracy of GWAS and QTL mapping results and suggested a role for nontocopherol pathway genes in the modulation of natural tocopherol variation. We provided genome‐wide evidence that genes involved in fatty acid metabolism, chlorophyll metabolism and chloroplast function may affect natural variation in tocopherols. These findings were confirmed through mutant analysis of a particular gene from the fatty acid pathway. In addition, the favourable alleles for many of the significant SNPs/QTLs represented rare alleles in natural populations. Together, our results revealed many novel genes that are potentially involved in the variation of tocopherol content in maize kernels. Pyramiding of the favourable alleles of the newly elucidated genes and the well‐known tocopherol pathway genes would greatly improve tocopherol content in maize.

An allele of ZmPORB2 encoding a protochlorophyllide oxidoreductase promotes tocopherol accumulation in both leaves and kernels of maize

“…Three recombinant inbred line (RIL) populations, including F 10 RILs generated by crossing Zong3 and Yu8701 (ZY) and then selfing, F 6 RILs from the hybrid of K22/CI7 (KC), and F 9 RILs whose parental lines are B73and BY804 (BB), containing 170-188 lines (Pan et al, 2016), were genotyped with high-density SNPs and phenotyped in two environments, respectively. A major QTL, qVE5, for c-tocopherol and total tocopherol content in kernel was mapped to chromosome 5 in all three populations in multiple environments (Table S1 and Figure S1; Wang et al, 2018). qVE5 accounted for a large proportion of phenotypic variation in each RIL population ranging from 9.75% in BB to 42.47% in KC population for c-tocopherol content (Table S1).…”

“…ZmVTE4 (c-tocopherol methyltransferase) has been identified through genome-wide and candidate gene association analysis and two markers within ZmVTE4 were developed (Li et al, 2012;Lipka et al, 2013). Recently, many QTLs have been identified using large-scale QTL mapping and some candidate genes were identified, including several genes involved in and outside the known tocopherol biosynthetic pathways (Diepenbrock et al, 2017;Wang et al, 2018). In this study, a major QTL (qVE5) affecting tocopherol content in the maize kernel was identified by linkage analysis in three bi-parental mapping populations.…”

Genome-Wide Association Studies Reveal the Genetic Basis of Fertility Restoration of CMS-WA and CMS-HL in xian/indica and aus Accessions of Rice (Oryza sativa L.)

“…The durable high temperature and humidity in Wuhan during the growing season exerted great pressure to the fate of developing and developed pollens, which resulted in the unrepeatable detection of many association signals in two different years, especially for those minor loci (Tables 1 and 2). Therefore, a combination of GWAS and linkage mapping would be better in mining Rf genes, which would provide not only an overview of the genetic basis, but also a high resolution of functional genes (Deng et al 2017, Wang et al 2018.…”

Crop metabolomics: from diagnostics to assisted breeding

“…Under this section we highlight recent papers showing direct links between basic metabolism knowledge with the understanding of two very complex traits such as yield and quality. Recent studies combined metabolite profiling and genetic analyses in crop species identified dozens of genomic regions associated with variations in the contents of Brassica seeds glucosinolates (Feng et al 2012), rice seed lipids (Ying et al 2012), maize grain carotenoids (Owens et al 2014) and tocochromanols (Lipka et al 2013;Diepenbrock et al 2017;Wang et al 2018) and hundreds of not linked loci for variations in the contents of intermediate compounds from primary and secondary metabolic pathways.…”