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Published on January 14, 2009; 10.1104/pp.108.133967

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Received December 10, 2008
Accepted January 10, 2009

Gene and metabolite regulatory network analysis of early developing fruit tissues highlights new candidate genes for the control of tomato fruit composition and development

Fabien Mounet , Annick Moing , Virginie Garcia , Johann Petit , Michael Maucourt , Catherine Deborde , Stephane Bernillon , Gwenaelle Le Gall , Ian Colquhoun , Marianne Defernez , Jean-Luc Giraudel , Dominique Rolin , Christophe Rothan , and Martine Lemaire-Chamley *

INRA - UMR 619 Biologie du Fruit, Centre de Bordeaux, F-33140 Villenave d‘Ornon, France; Universite de Bordeaux, UMR 619 Biologie du Fruit, F-33140 Villenave d’Ornon, France; Pole Metabolome-Fluxome, IFR 103, INRA de Bordeaux, F-33140 Villenave d‘Ornon, France; Institute of Food Research, Norwich Research Park, Colney, Norwich NR4 7UA, UK; EPCA, ISM, UMR 5255, CNRS-Universite Bordeaux 1, F-24000 Perigueux, France

* Corresponding author; email: martine.lemaire{at}bordeaux.inra.fr.

Variations in early fruit development and composition may have major impacts on the taste and the overall quality of ripe tomato (Solanum lycopersicum L.) 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 to 35 days post anthesis – DPA). Transcriptome and metabolome analyses were carried out respectively with tomato microarrays and analytical methods including proton NMR and LC-MS. Pair-wise 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.






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