000 02449nab a22004577a 4500
999 _c30900
_d30900
001 G99593
003 MX-TxCIM
005 20201201161424.0
008 121211b |||p||p||||||| |z||| |
022 _a1476-4687 (Revista en electrónico)
022 0 _a0028-0836
024 8 _ahttps://doi.org/10.1038/ncomms4438
040 _aMX-TxCIM
041 0 _aEn
100 1 _aWeiwei Wen
245 1 0 _aMetabolome-based genome-wide association study of maize kernel leads to novel biochemical insights
260 _c2014
500 _aPeer-review: Yes - Open Access: Yes | http://ip-science.thomsonreuters.com/cgi-bin/jrnlst/jlresults.cgi?PC=MASTER&ISSN=0028-0836
500 _aPeer review
500 _aOpen Access
520 _aPlants 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.
536 _aGenetic Resources Program
546 _aEnglish
591 _aNature|CIMMYT Informa No. 1919
594 _aCLIH01
595 _aCSC
650 1 0 _aBiological Sciences
650 7 _aPlant sciences
_91214
_2AGROVOC
650 7 _91130
_aGenetics
_2AGROVOC
650 7 _91853
_aQuantitative Trait Loci
_2AGROVOC
650 7 _98948
_aMetabolites
_2AGROVOC
700 1 _aDong Li,
_ecoaut.
700 1 _aHaijun Liu,
_ecoaut.
700 1 _9398
_aJianbing Yan
700 1 _aJie Liu,
_ecoaut.
700 1 _aJie Luo,
_ecoaut.
700 1 _aWei Chen,
_ecoaut.
_92613
700 1 _aWenqiang Li,
_ecoaut.
700 1 _aXiang Li,
_ecoaut.
700 1 _aYanqiang Gao,
_ecoaut.
700 1 _9764
_aHuihui Li
_gGenetic Resources Program
_8CLIH01
773 0 _tNature
_gv. 5, p. 3438
856 4 _uhttps://hdl.handle.net/10883/19739
_yOpen Access through DSpace
942 _cJA
_2ddc
_n0