By taking the advantages of development of sequencing technology, the genome sequences of several plant species have been revealed: these include Arabidopsis thaliana [1], Oryza sativa (rice) [2], Populus trichocarpa (poplar) [3], Vitis vinifera (grapevine) [4], and Sorghum bicolor (sorghum) (http://www.phytozome.net/ sorghum). However, even in Arabidopsis, which is most extensively investigated in terms of gene function, only half the genes have been functionally annotated based on sequence similarity to known genes, and the function of only about 11% has been confirmed with evidence [5]. Therefore, the identification of the function of unknown genes is currently a major subject in plant genomics. Analyses of the changes in plants in which specific genes are either overexpressed (gain-of-function experiment) or knocked out (loss-of-function experiment) are generally used for decoding the functions of genes. Systematic analyses of the transcriptome and metabolome, in particular, correlating the expression pattern of genes with the accumulation pattern of metabolites, could be an excellent way for deducing the functions of genes, even if these engineered plants do not show apparent phe-notypic alternation [6–9].
In plants, a large number of genes involved in primary and secondary metabolism are present to form multigene families, for example, in Arabidopsis, 30 terpene synthase genes, 272 cytochrome P450 genes, 107 glycosyltransferase genes, and 130 ABC protein genes [10]. These genes are believed to be involved in the synthesis, modification, degradation, and/or transport of particular metabolites in plants. Compared with the model plant Arabidopsis, the situation is more complicated in the case of other plants, even if their genome sequences are available, because of the lack of feasible genetic resources for functional investigation such as large mutant panels and full-length cDNA collections. The integration of metabolic profiles with gene expression profiles can provide hints for the identification of functions of unknown metabolic genes, regardless of model or nonmodel plants. With the recent advances of sophisticated bioinformatics tools and analytical technology, the systems biology approach becomes more realistic to solve biological problems. In this chapter, the functional genomics study of combining transcriptome and metab-olome is discussed, leading to the development of plant systems biology.
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Saito, K. (2009). Plant Functional Genomics Based on Integration of Metabolomics and Transcriptomics: Toward Plant Systems Biology. In: Nakanishi, S., Kageyama, R., Watanabe, D. (eds) Systems Biology. Springer, Tokyo. https://doi.org/10.1007/978-4-431-87704-2_14
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DOI: https://doi.org/10.1007/978-4-431-87704-2_14
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