Résumé
The ANR DELICAS project will address the problem faced in sugarcane for identifying molecular markers with a strong effect on traits of agronomic interest. The genetic control of cane and sugar yield traits in sugarcane typically involves numerous QTLs with small individual effects (Hoarau et al. 2002; Aitken et al. 2006). The lack of markers has been so far one of the most important constraints to a wider contribution of genomics to sugarcane breeding and for the development of marker assisted selection in this crop. Phenotypic traits for production potential interact strongly with the environment, and represent the outcome of multiple processes difficult to measure and to tag at the genetic level. Plant growth modelling can describe yield formation dynamically as a set of interactive equations using only a small number of genotypic parameters. The different parameters participating in phenotype expression can be considered as synthetic component traits, presumably controlled by fewer genes than the complex agronomic traits and can be expected to be closer to gene or QTL effects, in the sense that Genotype x Environment `noise' is reduced (Hammer et al. 2002, Dingkuhn et al. 2005). In such a `heuristic' approach, parameter variation among genotypes can be interpreted as an expression of allelic diversity, and analyzed accordingly in QTL or association studies. Model assisted phenotyping has been applied to maize (Reymond et al. 2003) or peach tree (Quilot et al. 2004). The DELICAS project, which associates the breeding company eRcane and Cirad, aims at identifying molecular markers associated with genes implied in the elaboration of sugarcane yield by using ecophysiological models. To achieve the objectives of the project, we will: (i) elaborate methods and tools for model assisted ecophysiological phenotyping of sugarcane, and (ii) phenotype a core collection with two ecophysiological models, Mosicas (Martine, 2003) and EcoMeristem (Luquet et al. 2006), and detect associations between genetic markers and model parameters. (Résumé d'auteur)