FN Archimer Export Format
PT J
TI Optimization of Genomic Selection to Improve Disease Resistance in Two Marine Fishes, the European Sea Bass (Dicentrarchus labrax) and the Gilthead Sea Bream (Sparus aurata)
BT 
AF Griot, Ronan
   Allal, Francois
   Phocas, Florence
   Brard-Fudulea, Sophie
   Morvezen, Romain
   Haffray, Pierrick
   François, Yoannah
   Morin, Thierry
   Bestin, Anastasia
   Bruant, Jean-Sébastien
   Cariou, Sophie
   Peyrou, Bruno
   Brunier, Joseph
   Vandeputte, Marc
AS 1:1,2,3;2:3;3:2;4:1;5:1;6:1;7:1;8:4;9:1;10:5;11:5;12:6;13:6;14:2,7;
FF 1:;2:PDG-RBE-MARBEC-LAAAS;3:;4:;5:;6:;7:;8:;9:;10:;11:;12:;13:;14:;
C1 SYSAAF, Station LPGP/INRAE, Campus de Beaulieu, Rennes, France
   Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France
   MARBEC, Univ. Montpellier, Ifremer, CNRS, IRD, Palavas-les-Flots, France
   ANSES, Ploufragan-Plouzané-Niort Laboratory, Viral Fish Diseases Unit, National Reference Laboratory for Regulated Fish Diseases, Technopôle Brest-Iroise, Plouzané, France
   Ferme Marine du Douhet, La Brée Les Bains, France
   Ecloserie Marine de Gravelines-Ichtus, Gravelines, France
   MARBEC, Univ. Montpellier, Ifremer, CNRS, IRD, Palavas-les-Flots, France
C2 SYSAAF, FRANCE
   UNIV PARIS SACLAY, FRANCE
   IFREMER, FRANCE
   ANSES, FRANCE
   FERME MARINE DOUHET, FRANCE
   ECLOSERIE MARINE GRAVELINES-ICHTUS, FRANCE
   INRAE, FRANCE
SI PALAVAS
SE PDG-RBE-MARBEC-LAAAS
UM MARBEC
IN WOS Ifremer UMR
   WOS Cotutelle UMR
   DOAJ
   copubli-france
   copubli-p187
   copubli-univ-france
IF 4.772
TC 11
UR https://archimer.ifremer.fr/doc/00718/83039/87977.pdf
   https://archimer.ifremer.fr/doc/00718/83039/87978.tif
   https://archimer.ifremer.fr/doc/00718/83039/87979.gif
   https://archimer.ifremer.fr/doc/00718/83039/87980.docx
   https://archimer.ifremer.fr/doc/00718/83039/88924.pdf
LA English
DT Article
DE ;genomic selection;dicentrarchus labrax;Sparus aurata;disease resistance;aquaculture
AB Disease outbreaks are a major threat to the aquaculture industry, and can be controlled by selective breeding. With the development of high-throughput genotyping technologies, genomic selection may become accessible even in minor species. Training population size and marker density are among the main drivers of the prediction accuracy, which both have a high impact on the cost of genomic selection. In this study, we assessed the impact of training population size as well as marker density on the prediction accuracy of disease resistance traits in European sea bass (Dicentrarchus labrax) and gilthead sea bream (Sparus aurata). We performed a challenge to nervous necrosis virus (NNV) in two sea bass cohorts, a challenge to Vibrio harveyi in one sea bass cohort and a challenge to Photobacterium damselae subsp. piscicida in one sea bream cohort. Challenged individuals were genotyped on 57K–60K SNP chips. Markers were sampled to design virtual SNP chips of 1K, 3K, 6K, and 10K markers. Similarly, challenged individuals were randomly sampled to vary training population size from 50 to 800 individuals. The accuracy of genomic-based (GBLUP model) and pedigree-based estimated breeding values (EBV) (PBLUP model) was computed for each training population size using Monte-Carlo cross-validation. Genomic-based breeding values were also computed using the virtual chips to study the effect of marker density. For resistance to Viral Nervous Necrosis (VNN), as one major QTL was detected, the opportunity of marker-assisted selection was investigated by adding a QTL effect in both genomic and pedigree prediction models. As training population size increased, accuracy increased to reach values in range of 0.51–0.65 for full density chips. The accuracy could still increase with more individuals in the training population as the accuracy plateau was not reached. When using only the 6K density chip, accuracy reached at least 90% of that obtained with the full density chip. Adding the QTL effect increased the accuracy of the PBLUP model to values higher than the GBLUP model without the QTL effect. This work sets a framework for the practical implementation of genomic selection to improve the resistance to major diseases in European sea bass and gilthead sea bream. 
PY 2021
PD JUN
SO Frontiers In Genetics
SN 1664-8021
PU Frontiers Media SA
VL 12
UT 000678372100001
DI 10.3389/fgene.2021.665920
ID 83039
ER

EF