Plant metabolites are important to world food security in terms of maintaining sustainable yield and providing food with enriched phytonutrients. Here we report comprehensive profiling of 840 metabolites and a further metabolic genome-wide association study based on ∼6.4 million SNPs obtained from 529 diverse accessions of Oryza sativa. We identified hundreds of common variants influencing numerous secondary metabolites with large effects at high resolution. We observed substantial heterogeneity in the natural variation of metabolites and their underlying genetic architectures among different subspecies of rice. Data mining identified 36 candidate genes modulating levels of metabolites that are of potential physiological and nutritional importance. As a proof of concept, we functionally identified or annotated five candidate genes influencing metabolic traits. Our study provides insights into the genetic and biochemical bases of rice metabolome variation and can be used as a powerful complementary tool to classical phenotypic trait mapping for rice improvement.
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We appreciate the critical reading and helpful comments on the manuscript made by C. Martin from John Innes Centre, UK and Q. Zhang from Huazhong Agricultural University, China. We thank W. Yan for kindly providing 148 varieties from a mini-core subset of the US Department of Agriculture rice gene bank. This work was supported by the Major State Basic Research Development Program of China (973 Program) (number 2013CB127001), the National High Technology R&D Program of China (863 Program) (numbers 2012AA10A303 and 2012AA10A304), the National Natural Science Foundation of China (numbers 31070267 and 31100962) and the Program for New Century Excellent Talents in University of Ministry of Education in China (NCET-09-0401). We are also thankful for support from the Ministry of Science and Technology (numbers 2010CB125901 and 2011CB100304).
The authors declare no competing financial interests.
Supplementary Figures 1-15 and Supplementary Tables 6, 7 and 23. (PDF 16370 kb)
Metabolite reporting checklist and recommendations for LC-MS (XLSX 11 kb)
The (almost) non-redundant MS2T library of rice leaf (XLSX 124 kb)
Scheduled MRM (multiple reaction monitoring) transitions for widely targeted metabolite analysis in rice leaf (XLSX 147 kb)
The list of collected 529 rice accessions (XLSX 84 kb)
Data matrix of 840 metabolites in 524 accessions of rice germplasms (including repeat1 and repeat2) (XLSX 10486 kb)
The list of total 2,947 significant SNPs detected in at least one of the populations (XLSX 267 kb)
The list of 634 loci detected in at least one of the populations (XLSX 56 kb)
The list of 551 lead SNPs that were repeatedly detected (XLSX 110 kb)
The list of 356 loci that were repeatedly detected (XLSX 77 kb)
The full lists of significant associations of metabolic GWAS (mGWAS) (XLSX 4949 kb)
The full lists of significant associations of metabolic GWAS (mGWAS) (XLSX 19291 kb)
Manhattan plots of 356 loci that were repeatedly detected (XLSX 39 kb)
Results of analysis of two-locus interactions (XLSX 205 kb)
Statistics of significant loci on the chromosomes (XLSX 16 kb)
The list of significant loci detected in indica and japonica subspecies (XLSX 58 kb)
The list of significant loci detected for subspecies differentiation metabolites in indica and japonica subspecies (XLSX 21 kb)
The full list of identified or annotated metabolites that were supported by GWAS (XLSX 40 kb)
The full list of candidate genes (XLSX 20 kb)
Metabolic profiling of transgenic lines overexpressing the candidate genes (XLSX 47 kb)
The results of overlap between GWAS loci and mQTL (XLSX 24 kb)
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Chen, W., Gao, Y., Xie, W. et al. Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism. Nat Genet 46, 714–721 (2014). https://doi.org/10.1038/ng.3007
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