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      Metabolome-genome-wide association study dissects genetic architecture for generating natural variation in rice secondary metabolism

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          Abstract

          Plants produce structurally diverse secondary (specialized) metabolites to increase their fitness for survival under adverse environments. Several bioactive compounds for new drugs have been identified through screening of plant extracts. In this study, genome-wide association studies (GWAS) were conducted to investigate the genetic architecture behind the natural variation of rice secondary metabolites. GWAS using the metabolome data of 175 rice accessions successfully identified 323 associations among 143 single nucleotide polymorphisms (SNPs) and 89 metabolites. The data analysis highlighted that levels of many metabolites are tightly associated with a small number of strong quantitative trait loci (QTLs). The tight association may be a mechanism generating strains with distinct metabolic composition through the crossing of two different strains. The results indicate that one plant species produces more diverse phytochemicals than previously expected, and plants still contain many useful compounds for human applications.

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          MassBank: a public repository for sharing mass spectral data for life sciences.

          Hisayuki Horai, Masanori Arita, Shigehiko Kanaya … (2010)
          MassBank is the first public repository of mass spectra of small chemical compounds for life sciences (<3000 Da). The database contains 605 electron-ionization mass spectrometry (EI-MS), 137 fast atom bombardment MS and 9276 electrospray ionization (ESI)-MS(n) data of 2337 authentic compounds of metabolites, 11 545 EI-MS and 834 other-MS data of 10,286 volatile natural and synthetic compounds, and 3045 ESI-MS(2) data of 679 synthetic drugs contributed by 16 research groups (January 2010). ESI-MS(2) data were analyzed under nonstandardized, independent experimental conditions. MassBank is a distributed database. Each research group provides data from its own MassBank data servers distributed on the Internet. MassBank users can access either all of the MassBank data or a subset of the data by specifying one or more experimental conditions. In a spectral search to retrieve mass spectra similar to a query mass spectrum, the similarity score is calculated by a weighted cosine correlation in which weighting exponents on peak intensity and the mass-to-charge ratio are optimized to the ESI-MS(2) data. MassBank also provides a merged spectrum for each compound prepared by merging the analyzed ESI-MS(2) data on an identical compound under different collision-induced dissociation conditions. Data merging has significantly improved the precision of the identification of a chemical compound by 21-23% at a similarity score of 0.6. Thus, MassBank is useful for the identification of chemical compounds and the publication of experimental data. 2010 John Wiley & Sons, Ltd.
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            Mass spectral molecular networking of living microbial colonies.

            J. Watrous, P. Roach, T Alexandrov … (2012)
            Integrating the governing chemistry with the genomics and phenotypes of microbial colonies has been a "holy grail" in microbiology. This work describes a highly sensitive, broadly applicable, and cost-effective approach that allows metabolic profiling of live microbial colonies directly from a Petri dish without any sample preparation. Nanospray desorption electrospray ionization mass spectrometry (MS), combined with alignment of MS data and molecular networking, enabled monitoring of metabolite production from live microbial colonies from diverse bacterial genera, including Bacillus subtilis, Streptomyces coelicolor, Mycobacterium smegmatis, and Pseudomonas aeruginosa. This work demonstrates that, by using these tools to visualize small molecular changes within bacterial interactions, insights can be gained into bacterial developmental processes as a result of the improved organization of MS/MS data. To validate this experimental platform, metabolic profiling was performed on Pseudomonas sp. SH-C52, which protects sugar beet plants from infections by specific soil-borne fungi [R. Mendes et al. (2011) Science 332:1097-1100]. The antifungal effect of strain SH-C52 was attributed to thanamycin, a predicted lipopeptide encoded by a nonribosomal peptide synthetase gene cluster. Our technology, in combination with our recently developed peptidogenomics strategy, enabled the detection and partial characterization of thanamycin and showed that it is a monochlorinated lipopeptide that belongs to the syringomycin family of antifungal agents. In conclusion, the platform presented here provides a significant advancement in our ability to understand the spatiotemporal dynamics of metabolite production in live microbial colonies and communities.
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              Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism.

              Wei Chen, Yanqiang Gao, Weibo Xie … (2014)
              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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                Author and article information

                Journal
                Journal ID (nlm-ta): Plant J
                Journal ID (iso-abbrev): Plant J
                Journal ID (publisher-id): tpj
                Title: The Plant Journal
                Publisher: Blackwell Publishing Ltd (Oxford, UK )
                ISSN (Print): 0960-7412
                ISSN (Electronic): 1365-313X
                Publication date (Print): January 2015
                Publication date (Electronic): 29 September 2014
                Volume: 81
                Issue: 1
                Pages: 13-23
                Affiliations
                [1 ]RIKEN Center for Sustainable Resource Science 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Japan
                [2 ]Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University 1-5 Yamadaoka, Suita, Osaka, Japan
                [3 ]National Institute of Agrobiological Sciences 2-1-2 Kannondai, Tsukuba, Ibaraki, Japan
                [4 ]Graduate School of Pharmaceutical Sciences, Chiba University Inohana 1-8-1, Chuo-ku, Chiba, Japan
                Author notes
                *For correspondence (e-mail ksaito@ 123456faculty.chiba-u.jp ).
                [†]

                Present address: NARO Institute of Crop Science, 2-1-18 Kannondai, Tsukuba, Ibaraki, Japan.

                Article
                DOI: 10.1111/tpj.12681
                PMC ID: 4309412
                PubMed ID: 25267402
                SO-VID: 52bfc3f1-7cee-419a-afb8-9649fe8a10b1
                Copyright © © 2014 The Authors The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.
                License:

                This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                Date received : 24 May 2014
                Date revision received : 19 September 2014
                Date accepted : 19 September 2014
                Categories
                Subject: Original Articles

                ScienceOpen disciplines: Plant science & Botany
                Keywords: oryza sativa,secondary metabolites,metabolome analysis,genome-wide association study,natural variation
                Data availability:
                ScienceOpen disciplines: Plant science & Botany
                Keywords: oryza sativa, secondary metabolites, metabolome analysis, genome-wide association study, natural variation

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