Genomic Selection in AquacultureAquaculture Species

François Allal (1) , Nguyen Hong Nguyen

1 UMR MARBEC - MARine Biodiversity Exploitation and Conservation - MARBEC

To date, genomic prediction has been conducted in about 20 aquaculture species, with a preference for intra-family genomic selection (GS). For every trait under GS, the increase in accuracy obtained by genomic estimated breeding values instead of classical pedigree-based estimation of breeding values is very important in aquaculture species ranging from 15% to 89% for growth traits, and from 0% to 567% for disease resistance. Although the implementation of GS in aquaculture is of little additional investment in breeding programs already implementing sib testing on pedigree, the deployment of GS remains sparse, but could be boosted by adaptation of cost-effective imputation from low-density panels. Moreover, GS could help to anticipate the effect of climate change by improving sustainability-related traits such as production yield (e.g., carcass or fillet yields), feed efficiency or disease resistance, and by improving resistance to environmental variation (tolerance to temperature or salinity variation). This chapter synthesized the literature in applications of GS in finfish, crustaceans and molluscs aquaculture in the present and future breeding programs.

Mots clés: Aquaculture; Crustaceans; Genomic selection; Accuracy; Finfish; Genotype-by-environment; Molluscs

Domaines: Biodiversité et Ecologie; Milieux et Changements globaux

François Allal, Nguyen Hong Nguyen. Genomic Selection in AquacultureAquaculture Species. Ahmadi; Nourollah and Bartholomé; Jérôme. Complex Trait Prediction: Methods and Protocols, Springer US, pp.469--491, 2022, Methods in Molecular Biology, 978-1-07-162205-6. ⟨10.1007/978-1-0716-2205-6_17⟩. ⟨hal-03679217⟩