ArticleGenetics, selection, evolution : GSE2024
Accuracy of genomic prediction using multiple Atlantic salmon populations.
Article in Genetics, selection, evolution : GSE, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genome-wide association analysis using multiple Atlantic salmon populations.Genetics, selection, evolution : GSE · 2025Pooled it
- Integrating Epistatic Interactions into Genomic Prediction of Growth and Fillet Fat Content in Common Carp.International journal of molecular sciences · 2026Article
- Investigating the genetic basis of susceptibility to amoebic gill disease and idiopathic gill lesions in Atlantic salmon populations using field data.Genetics, selection, evolution : GSE · 2026Article
- Genomic Prediction for Growth-Related Traits in Golden Pompano (Evolutionary applications · 2025Article
- Genomic selection for resistance to one pathogenic strain ofFrontiers in genetics · 2024Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundThe accuracy of genomic prediction is partly determined by the size of the reference population. In Atlantic salmon breeding programs, four parallel populations often exist, thus offering the opportunity to increase the size of the reference set by combining these populations. By allowing a reduction in the number of records per population, multi-population prediction can potentially reduce cost and welfare issues related to the recording of traits, particularly for diseases. In this study, we evaluated the accuracy of multi- and across-population prediction of breeding values for resistance to amoebic gill disease (AGD) using all single nucleotide polymorphisms (SNPs) on a 55K chip or a selected subset of SNPs based on the signs of allele substitution effect estimates across populations, using both linear and nonlinear genomic prediction (GP) models in Atlantic salmon populations. In addition, we investigated genetic distance, genetic correlation estimated based on genomic relationships, and persistency of linkage disequilibrium (LD) phase across these populations.
resultsThe genetic distance between populations ranged from 0.03 to 0.07, while the genetic correlation ranged from 0.19 to 0.99. Nonetheless, compared to within-population prediction, there was limited or no impact of combining populations for multi-population prediction across the various models used or when using the selected subset of SNPs. The estimates of across-population prediction accuracy were low and to some extent proportional to the genetic correlation estimates. The persistency of LD phase between adjacent markers across populations using all SNP data ranged from 0.51 to 0.65, indicating that LD is poorly conserved across the studied populations.
conclusionsOur results show that a high genetic correlation and a high genetic relationship between populations do not guarantee a higher prediction accuracy from multi-population genomic prediction in Atlantic salmon.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.