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Last update: May 2021

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Axis 4: Selection and Innovation

Genomic selection in tomato

To sustain innovation and the valuation of the genetic resources in tomato, we initiated a genomic selection program in this species. As a first step, we studied the pattern of linkage disequilibrium in core collection of >200 accessions and its evolution across generations in several pedigrees. Then, we used genetic and phenotypic data from previous GWA experiment to conduct a cross validation experiment. We tested the effect of diverse parameters such as marker density or size of the training population on the accuracy to predict phenotypes of interest (Duangjit et al, 2017)

Relevant Publications

Zhao J, C Sauvage, F Bitton, M Causse (2021) Multiple haplotype-based analyses provide genetic and evolutionary insights into tomato fruit weight and composition. (2022) Hort Res

Bineau, E.; Rambla, J.L.; Priego-Cubero, S.; Hereil, A.; Bitton, F.; Plissonneau, C.; Granell, A.; Causse, M. 2021. Breeding Tomato Hybrids for Flavour: Comparison of GWAS Results Obtained on Lines and F1 Hybrids. Genes, 12, 1443.

Roth, M., H. Muranty, et al. (2020). Genomic prediction of fruit texture and training population optimization towards the application of genomic selection in apple. Horticulture Research 7(1): 148.

Nsibi, M., B. Gouble, et al. (2020). Adoption and Optimization of Genomic Selection To Sustain Breeding for Apricot Fruit Quality. G3: Genes|Genomes|Genetics 10(12): 4513-4529.

Duangjit J, M Causse, C Sauvage (2016) Efficiency of genomic selection for tomato fruit quality. Molecular Breeding doi:10.1007/s11032-016-0453-3

Prunus innovation

The conversion of our upstream research into innovation will be achieved by a tight collaboration with private partners. The objective is to ensure a transfer of activities, skills, tools and materials to develop multi-resistant varieties for regular and sustainable production. Thus, the activities of innovation of our team are focused on the development of markers for MAS and of pre-breeding materials, through the:

  • development of multi-character selection in low input production systems: optimization of schemes and methods of selection, genomic selection.
  • design of prototypes to 'protect' the resistances and to respond to multiple stresses (MAS), for example by introgressing target traits into resilient genotypes.

Relevant Publications

Laurens, F., Aranzana, M. J., Arus, Bassi, D., Bink, M., Bonany, J., Caprera, A., Corelli-Grappadelli, L., Costes, E., Durel, C. E., Mauroux, J.-B., Muranty, H., Nazzicari, Pascal, T., Patocchi, A., Peil, A., Quilot-Turion, Rossini, Stella, Troggio, M., Velasco, R., van de Weg, E. (2018). An integrated approach for increasing breeding efficiency in apple and peach in Europe. Horticulture Research, 5 (1).

Biscarini, F., Nazzicari, N., Bink, M., Arús, P., Aranzana, Verde, I., Micali, Pascal, T., Quilot-Turion, B., Lambert, P., da Silva Linge, Pacheco, I., Bassi, Stella, Rossini (2017). Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies. BMC Genomics, 18 (1).

Lambert, P., Campoy, J. A., Pacheco, I., Mauroux, J.-B., da Silva Linge, C., Micheletti, D., Bassi, D., Rossini, L., Dirlewanger, E., Pascal, T., Troggio, M., Aranzana, M. J., Patocchi, A., Arús, P. (2016). Identifying SNP markers tightly associated with six major genes in peach [Prunus persica (L.) Batsch] using a high-density SNP array with an objective of marker-assisted selection (MAS). Tree Genetics and Genomes, 12 (6), 121.