Arabidopsis 2010: Metabolomics: A Functional Genomics Tool for Deciphering Functions of Arabidopsis Genes in the Context of Metabolic and Regulatory Networks

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The long-term goal of this project is to establish a multiinstitutional, international consortium of labs that will develop metabolomics as a new functional genomics tool for elucidating the functions of Arabidopsis genes. In this 2-year pilot project the consortium will conduct the research that will test the feasibility of using metabolomics in deciphering functions of genes. The consortium will apply established metabolite-profiling platforms that together detect approximately 2,000 metabolites, of which about 900 are chemically defined. Studies will investigate the robustness of the Arabidopsis metabolome, and define conditions that minimize the environmental and developmental effects on the metabolome. Subsequently, the consortium will profile changes in the metabolome associated with knockout alleles in genes of unknown function. These metabolomics data will be integrated with additional functional genomics data (i.e., transcriptomic, proteomic and phenotypic characterizations) gathered in parallel 2010 projects, and in combination, these profiling data will generate new tools and resources for determining the function of the many Arabidopsis genes, whose functions are still undefined. All information generated from this project will be available at www.metabolomics2010.bb.iastate.edu.Broader Impacts: This project will validate the utility of metabolomics in deciphering the function of genes. This development will be a resource to the Arabidopsis research community in that it will facilitate the elucidation of functions for genes whose functions are currently unknown. The consortium of labs that are participating in this project will foster the coordinate international development of metabolomics as a tool in functional genomics. The project will facilitate the research-based training of undergraduate, graduate and post-graduate researchers at the interface between chemistry, biochemistry, genetics and bioinformatics to solve biological problems in postgenomic sciences.