Abstract
Multiparallel analyses of mRNA and proteins are central to today's functional genomics initiatives. We describe here the use of metabolite profiling as a new tool for a comparative display of gene function. It has the potential not only to provide deeper insight into complex regulatory processes but also to determine phenotype directly. Using gas chromatography/mass spectrometry (GC/MS), we automatically quantified 326 distinct compounds from Arabidopsis thaliana leaf extracts. It was possible to assign a chemical structure to approximately half of these compounds. Comparison of four Arabidopsis genotypes (two homozygous ecotypes and a mutant of each ecotype) showed that each genotype possesses a distinct metabolic profile. Data mining tools such as principal component analysis enabled the assignment of “metabolic phenotypes” using these large data sets. The metabolic phenotypes of the two ecotypes were more divergent than were the metabolic phenotypes of the single-loci mutant and their parental ecotypes. These results demonstrate the use of metabolite profiling as a tool to significantly extend and enhance the power of existing functional genomics approaches.
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Acknowledgements
This project was funded by the Max-Planck-Society. We thank Frank Kose, Una Griebel, and Antje Feller for their support in carrying out laboratory and computer work, Urte Schlüter for providing C24 WT and sdd1-1 mutant plants, and Megan McKenzie for revising the manuscript.
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Fiehn, O., Kopka, J., Dörmann, P. et al. Metabolite profiling for plant functional genomics. Nat Biotechnol 18, 1157–1161 (2000). https://doi.org/10.1038/81137
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DOI: https://doi.org/10.1038/81137
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