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Apple breeding programs worldwide have usually been using a few recurrent parents for decades, which has resulted in a narrow genetic base in elite populations. In this context, genotypes from genetic resources that contain rare favourable alleles could be used to broaden the genetic base of elite material. Genomic selection could then be an appealing approach in order to efficiently harness this diversity in a pre-breeding program. The aim of this work was to explore the value of genomic selection in such programs in apple. We first explored the benefits of combining genetic resources and elite material into a single, diverse training set that could be used in multiple contexts and obtained moderate to high predictive abilities in doing so. We then simulated two pre-breeding schemes and showed that genomic selection could lead to a higher genetic gain per unit of time than using phenotypic selection and increases in the mean frequency of rare alleles. The results from this work suggest that genomic selection could help improve the efficiency of pre-breeding programs in apple.

On Zoom ONLY :https://inrae-fr.zoom.us/j/97270996206?pwd=cURVczZ1WWVIdE9VWHFZbjVOTUFRUT09
ID: 972 7099 6206
Code : 5vy#!NpAVg