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Olivier Martin

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SémIDEEV à GQE – Le Moulon


Salle de conférences de l’UMR
Ferme du Moulon – Gif-sur-Yvette

Mercredi 6  décembre  2017


Timothée FLUTRE
Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (AGAP), Montpellier

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Deciphering the genetic architecture of traits of interest in perennial fruit plants to speed-up selection :
a case study in grapevine

Cereals feed the world, but few would refuse a fruit at the end of a meal, and what about a glass of wine? Perennial fruit plants participate in diversifying human diet, yet orchards and vineyards are less and less diversified. For many such species, global production is dominated by a small number of cultivars, highly prized for their fruit quality. Nevertheless, they are often sensitive to various pathogens. Given the perenial life cycle combined with agriculture intensification, the few cultivars with a single resistance gene are quickly by-passed. As a result, current agronomic practices require frequent pesticide treatments. In such a context, breeding programs aim at pyramiding several resistance genes for a given pathogen while maintaining essential agronomic features as well as a certain level of fruit quality, leading to generation times of fifteen years.

To speed-up such programs, a multi-species project that I coordinate aims at assessing the feasibility of genomic selection. In the first part of my talk, I will present some results of this project, showing how genotyping-by-sequencing can be used on outbred crosses, and which prediction accuracy is reached depending on trait heritability. Furthermore, beyond the issue of pathogen resistance lies a bigger challenge, adaptation to climate change, which requires the study of a much wider diversity. In the second part of my talk, I will present preliminary results concerning the genetic architecture of various traits of interest based on the analysis of a structured diversity panel of grapevines. Most studies are performed on a trait-by-trait basis, ignoring genetic tradeoffs between traits. In the end, I hence will briefly present several directions to take advantage of genetic covariances when detecting QTLs or predicting breeding values.