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Title Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights
 
Names Weiwei Wen
Dong Li
Xiang Li
Yanqiang Gao
Wenqiang Li
Huihui Li
Jie Liu
Haijun Liu
Wei Chen
Jie Luo
Jianbing Yan
Date Issued 2014 (iso8601)
Abstract Plants produce a variety of metabolites that have a critical role in growth and development. Here we present a comprehensive study of maize metabolism, combining genetic, metabolite and expression profiling methodologies to dissect the genetic basis of metabolic diversity in maize kernels. We quantify 983 metabolite features in 702 maize genotypes planted at multiple locations. We identify 1,459 significant locus–trait associations (P≤1.8 × 10−6) across three environments through metabolite-based genome-wide association mapping. Most (58.5%) of the identified loci are supported by expression QTLs, and some (14.7%) are validated through linkage mapping. Re-sequencing and candidate gene association analysis identifies potential causal variants for five candidate genes involved in metabolic traits. Two of these genes were further validated by mutant and transgenic analysis. Metabolite features associated with kernel weight could be used as biomarkers to facilitate genetic improvement of maize.
Genre Article
Access Condition Open Access
Identifier 2041-1723