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Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
Published on: June 17, 2012
Patterns of metabolite changes identified from large-scale gene perturbations in Arabidopsis using a genome-scale
Taehyong Kim1, Kate Dreher1, Ricardo Nilo-Poyanco1
1Department of Plant Biology, Carnegie Institution for Science, Stanford, California 94305 (T.K., K.D., R.N.-P., S.Y.R.);Department of Biotechnology, Yonsei University, Seoul 120-749, South Korea (I.L.); Genome Center, University of California, Davis, California 95616 (O.F.); M. J. Murdock Metabolomics Laboratory, Institute of Biological Chemistry, Washington State University, Pullman, Washington 99164 (B.M.L.); Center for Metabolic Biology, Department of Biochemistry, Biophysics, and Molecular Biology (B.J.N.), and Department of Genetics, Development, and Cell Biology (E.S.W.), Iowa State University, Ames, Iowa 50011; Plant Biology Division, The Samuel Roberts Noble Foundation, Ardmore, Oklahoma 73401 (L.S.); andDivision of Biology, Kansas State University, Manhattan, Kansas 66506 (R.W.).
Abstract:
Metabolomics enables quantitative evaluation of metabolic changes caused by genetic or environmental perturbations. However, little is known about how perturbing a single gene changes the metabolic system as a whole and which network and functional properties are involved in this response. To answer this question, we investigated the metabolite profiles from 136 mutants with single gene perturbations of functionally diverse Arabidopsis (Arabidopsis thaliana) genes. Fewer than 10 metabolites were changed significantly relative to the wild type in most of the mutants, indicating that the metabolic network was robust to perturbations of single metabolic genes. These changed metabolites were closer to each other in a genome-scale metabolic network than expected by chance, supporting the notion that the genetic perturbations changed the network more locally than globally. Surprisingly, the changed metabolites were close to the perturbed reactions in only 30% of the mutants of the well-characterized genes. To determine the factors that contributed to the distance between the observed metabolic changes and the perturbation site in the network, we examined nine network and functional properties of the perturbed genes. Only the isozyme number affected the distance between the perturbed reactions and changed metabolites. This study revealed patterns of metabolic changes from large-scale gene perturbations and relationships between characteristics of the perturbed genes and metabolic changes.
