A multi-Ievel Omic approach of tomato fruit quality
2012
XU , Jiaxin (INRA , Montfavet (France). UR 1052 Génétique et Amélioration des Fruits et Légumes) | Pascual , Laura (INRA , Montfavet (France). UR 1052 Génétique et Amélioration des Fruits et Légumes) | Desplat , Nelly (INRA , Montfavet (France). UR 1052 Génétique et Amélioration des Fruits et Légumes) | Faurobert , Mireille (INRA , Montfavet (France). UR 1052 Génétique et Amélioration des Fruits et Légumes) | Gibon , Yves (INRA , Villenave D'Ornon (France). UMR 1332 Biologie du Fruit et Pathologie) | Moing , Annick (INRA , Villenave D'Ornon (France). UMR 1332 Biologie du Fruit et Pathologie) | Maucourt , Marise (Université de Bordeaux, Villenave d'Ornon(France). UMR1332 Biologie du Fruit et Pathologie) | Ballias , P. (Institut National de la Recherche Agronomique, Villenave d'Ornon(France). UMR1332 Biologie du Fruit et Pathologie) | Deborde , Cécile (Institut National de la Recherche Agronomique, Villenave d'Ornon(France). UMR1332 Biologie du Fruit et Pathologie) | Liang , Yan (Institut National de la Recherche Agronomique, Montfavet(France). UR1052, GAFL) | Bouchet , Jean-Paul (INRA , Montfavet (France). UR 1052 Génétique et Amélioration des Fruits et Légumes) | Brunel , Dominique (INRA , Evry (France). US 1279 Etude du Polymorphisme des Génomes Végétaux) | Lepaslier , Marie-Christine (Institut National de la Recherche Agronomique, Evry(France). UR1279, Unité Etude du Polymorphisme des Génomes Végétaux, CEA-Institut de Génomique-CNG) | Causse , Mathilde(auteur de correspondance) (INRA , Montfavet (France). UR 1052 Génétique et Amélioration des Fruits et Légumes)
Tomato fruit quality is an important trait for tomato consumers, but complex to improve due to the number ofcomponents involved and by their polygenic nature. ln order to decipher the genetic diversity and the inheritanceof fruit qua lity components at a global level, we conducted a large multi-Ievel omic experiment. A set of 8contrasted lines and 4 of their F1 hybrids were phenotyped for fruit development traits. Fruits were harvested andpericarp samples analysed at 2 stages (cell expansion and orange) and different scales: (1) primary andsecondary metabolome profiles, (2) activities of 28 enzymes involved in primary metabolism, (3) proteome profilesrevealed by 2D-PAGE and sequencing of 470 spots showing quantitative variations and (4) gene expressionanalysis by Digital Gene Expression. ln parallel, the 8 lines were resequenced and more than 3 millions SNPsidentified when aligned on the reference tomato genome.This experiment allowed us to address several questions: the range of variability for the metabolic traits andexpression data. Correlation networks can be constructed within and between levels of analysis to identifyregulatory networks. Diversity of chosen candidate genes can be analysed, relating the polymorphisms at thesequence levels with their expression. Some examples will be presented.
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