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SYSTEMS BIOLOGY, MOLECULAR BIOLOGY, AND GENE REGULATION

Gene and Metabolite Regulatory Network Analysis of Early Developing Fruit Tissues Highlights New Candidate Genes for the Control of Tomato Fruit Composition and Development^{1,[C],[W],[OA]}

INRA-UMR 619 Biologie du Fruit, Centre de Bordeaux, F–33140 Villenave d'Ornon, France (F.M., A.M., V.G., J.P., M.M., C.D., S.B., D.R., C.R., M.L.-C.); Université de Bordeaux, UMR 619 Biologie du Fruit, F–33140 Villenave d'Ornon, France (F.M., A.M., V.G., J.P., M.M., C.D., S.B., D.R., C.R., M.L.-C.); Pôle Métabolome-Fluxome, IFR 103, INRA de Bordeaux, F–33140 Villenave d'Ornon, France (M.M., C.D., S.B.); Institute of Food Research, Norwich Research Park, Colney, Norwich NR4 7UA, United Kingdom (G.L.G., I.C., M.D.); and EPCA, ISM, UMR 5255, CNRS-Université Bordeaux 1, F–24000 Perigueux, France (J.-L.G.)

Variations in early fruit development and composition may have major impacts on the taste and the overall quality of ripe tomato (Solanum lycopersicum) fruit. To get insights into the networks involved in these coordinated processes and to identify key regulatory genes, we explored the transcriptional and metabolic changes in expanding tomato fruit tissues using multivariate analysis and gene-metabolite correlation networks. To this end, we demonstrated and took advantage of the existence of clear structural and compositional differences between expanding mesocarp and locular tissue during fruit development (12–35 d postanthesis). Transcriptome and metabolome analyses were carried out with tomato microarrays and analytical methods including proton nuclear magnetic resonance and liquid chromatography-mass spectrometry, respectively. Pairwise comparisons of metabolite contents and gene expression profiles detected up to 37 direct gene-metabolite correlations involving regulatory genes (e.g. the correlations between glutamine, bZIP, and MYB transcription factors). Correlation network analyses revealed the existence of major hub genes correlated with 10 or more regulatory transcripts and embedded in a large regulatory network. This approach proved to be a valuable strategy for identifying specific subsets of genes implicated in key processes of fruit development and metabolism, which are therefore potential targets for genetic improvement of tomato fruit quality.

The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Martine Lemaire-Chamley (martine.lemaire{at}bordeaux.inra.fr).

^[C] Some figures in this article are displayed in color online but in black and white in the print edition.

^[W] The online version of this article contains Web-only data.

^[OA] Open Access articles can be viewed online without a subscription.

www.plantphysiol.org/cgi/doi/10.1104/pp.108.133967

^* Corresponding author; e-mail martine.lemaire{at}bordeaux.inra.fr.

Received December 10, 2008; accepted January 10, 2009; published January 14, 2009.