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24, chemin de Borde Rouge -Auzeville - CS52627 31326 Castanet Tolosan cedex - France

Last update: May 2021

From the cow to poplar tree, from bees to wheat, how does genomic selection work?

For 10 years, in dairy cattle, "classical" selection has been put aside for genomic selection. This evolution has allowed more rapid progress and a considerable reduction in the cost of selection. Since then, it has been applied to an ever increasing number of animal and plant species and has spiked interest in many others.

Depuis plus de 10 ans, chez les bovins laitiers, la sélection ‘classique’ a laissé place à la sélection génomique. Cette évolution a permis des progrès plus rapides et une réduction considérable du coût de la sélection. Elle est depuis mise en œuvre dans un nombre croissant d’espèces animales ou végétales et suscite un intérêt très clair pour de nombreuses autres.

Genomic selection is a generic method that can be applied to all animal and plant species. But is it applied in the same way to all species? What are the main arguments that incite breeders to adopt this technology? How do the biological characteristics and the organisation of the selection programmes in different species influence the choice of breeders?

The R2D2 network supported by the INRAE SELGEN metaprogram has been interested in different methodological questions pertaining to genomic selection. The specificity of this network is to bring together scientists working on a wide range of animal and plant species: bees, dairy and beef cattle, goats, horses, sheep, fish, pigs, poultry, apricot trees, wheat, corn, popler trees, pinasters, fodder plants, peas, apple trees, rice, tomatoes, vines ...Seventy-five scientists from various horizons (INRAE BAP (Biology of Plant Improvements), GA (Animal Genetics), EcoDiv (Ecology and Biodiversity) and EcoSocio (Economy and Social Sciences) Divisions, IFREMER, CIRAD and SYSAAF, geneticists and economists participated in the network.

The comparison amongst all these species has shown that genomic selection can be developed very differently in selection programs. This cross-cutting analysis showed three main implementation logics called bricks and that can possibly be combined together.

Brick A: Adding gentoyping to improve the precision of genetic prediction values
Brick B: Replace the phenotyping by genotyping to shorten the selection cycles or increase selection intensity
Brick C: Mieux choisir les parents pour réaliser de meilleurs croisements ou pour préserver la diversité génétique

For more information

INRAE Press Release