Strategies to improve the accuracy and reduce costs of genomic prediction in aquaculture species.

ABSTRACT: Genomic selection (GS) has great potential to increase genetic gain in aquaculture breeding; however, its implementation is hindered owing to high genotyping cost and the large number of individuals to genotype. This study investigated the efficiency of genomic prediction in four aquaculture species. In total, 749 to 1481 individuals with records for disease resistance and growth traits were genotyped using SNP arrays ranging from 12K to 40K. We compared the prediction accuracies and bias of breeding values obtained from BLUP, genomic BLUP (GBLUP), Bayesian mixture (BayesR), weighted GBLUP (WGBLUP), and genomic feature BLUP (GFBLUP). For GFBLUP, the genomic feature matrix was constructed based on prior information from genome-wide association studies. Fivefold cross-validation was performe

SUBMITTER: Song H 

PROVIDER: S-EPMC9046917 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature