TY  - JA
AU  - Weiwei Wen
AU  - Dong Li
AU  - Haijun Liu
AU  - Jianbing Yan
AU  - Jie Liu
AU  - Jie Luo
AU  - Wei Chen
AU  - Wenqiang Li
AU  - Xiang Li
AU  - Yanqiang Gao
AU  - Huihui Li
TI  - Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights
SN  - 1476-4687
PY  - 2014///
KW  - Biological Sciences
KW  - Plant sciences
KW  - AGROVOC
KW  - Genetics
KW  - Quantitative Trait Loci
KW  - Metabolites
N1  - Peer-review: Yes - Open Access: Yes | http://ip-science.thomsonreuters.com/cgi-bin/jrnlst/jlresults.cgi?PC=MASTER&ISSN=0028-0836; Peer review; Open Access
N2  - 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
UR  - https://hdl.handle.net/10883/19739
T2  - Nature
DO  - https://doi.org/10.1038/ncomms4438
ER  -