Trends in Plant Science
Potential of metabolomics as a functional genomics tool
Section snippets
Biological relevance
For a holistic understanding of the biological behavior of a complex system, it is essential to follow, as unambiguously as possible, the response of an organism to a conditional perturbation at the transcriptome, proteome and metabolome levels 12, 13. These three levels of expression profiling provide a complete picture of the RNAs, proteins and metabolites that enable one to: infer relevant associations between macromolecules; identify functional linkages between phenotypic expressions; and
Comprehensiveness
The enormous biochemical diversity displayed in the plant kingdom is estimated to exceed 200 000 different metabolites [16]. It is therefore in plants that large-scale, comprehensive metabolite profiling meets its greatest challenge – a challenge that provides the impetus for cutting-edge technological developments. Various experimental approaches are currently being pursued to profile and determine the chemical identity of plant metabolites (Box 1). The need for multiple technologies reflects
Current limitations of metabolomics and comparison with other functional genomics approaches
Metabolomics could benefit from a more comprehensive coverage. This is also true for other functional genomics technologies. For example, Heiko Schoof et al. proposed that the Arabidopsis genome contains ∼28 000 genes, of which 50% have been successfully annotated [19], a percentage likely to increase rapidly [20]. The comprehensiveness of genomic databases facilitates the functional characterization of mRNAs in a transcriptomic approach. But the accuracy and completeness of nucleotide
Future directions for metabolomics
Our goal is to promote plant metabolomics as a valuable functional genomics tool that provides a comprehensive characterization of the biochemical phenotype of a plant. The realization of this goal will require improved technology for the determination of metabolites in complex plant tissues and the integration and dissemination of metabolomics research data. To integrate and disseminate metabolomics research data, a metabolomics information standard should help to ensure that metabolite data
Implementation of future steps
Many of the details for the suggested common actions, outlined in sections (i–iii) above, still need to be established for effective implementation. For example, generation of online libraries with retention indices not only requires the willingness of individual laboratories to contribute, but also requires mutual agreement on the technical details of such libraries, including chromatographic columns and the development of retention time indices standards. Detailed input for the common
Acknowledgements
We thank Richard A. Dixon, Maarten Koornneef, Sander van der Krol and Corey Broeckling for reading the text and valuable suggestions. The Samuel Roberts Noble Foundation is acknowledged for its financial support (R.J.B. and L.W.S.).
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