Biochemical And Genetical Bases Of Rice Metabolome

Plant metabolites are crucial for both plant life and human nutrition. Despite recent advance in metabolomics, natural variation and the underlying genetic control of plant metabolome remain largely unknown.Liquid chromatography–mass spectrometry(LC-MS)-based metabolomics has been facilitated by the construction of MS2 spectral tag(MS2T) library from the total scan ESI MS/MS data, and the development of widely targeted metabolomics method using MS/MS data gathered from authentic standards. Here, a novel strategy called stepwise multiple ion monitoring-enhanced product ions(stepwise MIM-EPI) was developed to construct the MS2 T library, in which stepwise MIM was used as survey scans to trigger the acquisition of EPI. A total number of 698(almost) non-redundant metabolites with MS2 spectra were obtained, of which 135 metabolites were identified/annotated. Integrating the data gathered from our MS2 T library and other available multiple reaction monitoring(MRM) information, a widely targeted metabolomics method was developed to quantify 277 metabolites, including some phytohormones. Evaluation the dehydration responses and natural variations of these metabolites in rice leaf not only suggested the coordinated regulation of abscisic acid(ABA) with metabolites such as serotonin derivative(s), polyamine conjugates under drought stress, and also revealed some C-glycosylated flavones as the potential markers for the discrimination of indica and japonica rice subspecies. The new MS2 T library construction and widely targeted metabolomics strategy could be used as a tool for rice functional genomics.To explore the genetic control of plant metabolome, we performed a genetical genomics analysis of the rice metabolome which provided high resolution for over 2800 quantitative trait loci(QTL) for 900 metabolites. Distinct and overlapped accumulation was observed and complex genetic regulation of metabolism was revealed in two different tissues. Data mining has associated 24 candidate genes with various m QTLs, including ones controlling and/or regulating important morphological traits and biological processes, and the corresponding pathways were reconstructed by updating in vivo functions of previously identified and newly assigned genes. This study demonstrated a powerful tool and provided vast amount of high-quality data for understanding plant metabolome which may help bridge the gap between the genome and phenome.To further elucidate the genetic and biochemical bases of natural variation of rice metabolome, we report a comprehensive profiling for 840 metabolites and a further metabolic genome-wide association study(m GWAS) 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. Significant heterogeneity was observed in natural variation of metabolites and their underlying genetic architectures associated with different subspecies of rice. Data mining revealed 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 5 candidate genes. Our study provides insights into genetic and biochemical bases of rice metabolome and can be used as a powerful complementary tool to classical phenotypic traits mapping for rice improvement.