Genotype Imputation To Improve the Cost-Efficiency of Genomic Selection in Farmed Atlantic Salmon

Abstract

Genomic selection uses genome-wide marker information to predict breeding values for traits of economic interest, and is more accurate than pedigree-based methods. The development of high density SNP arrays for Atlantic salmon has enabled genomic selection in selective breeding programs, alongside high-resolution association mapping of the genetic basis of complex traits. However, in sibling testing schemes typical of salmon breeding programs, trait records are available on many thousands of fish with close relationships to the selection candidates. Therefore, routine high density SNP genotyping may be prohibitively expensive. One means to reducing genotyping cost is the use of genotype imputation, where selected key animals (e.g., breeding program parents) are genotyped at high density, and the majority of individuals (e.g., performance tested fish and selection candidates) are genotyped at much lower density, followed by imputation to high density. The main objectives of the current study were to assess the feasibility and accuracy of genotype imputation in the context of a salmon breeding program. The specific aims were: (i) to measure the accuracy of genotype imputation using medium (25 K) and high (78 K) density mapped SNP panels, by masking varying proportions of the genotypes and assessing the correlation between the imputed genotypes and the true genotypes; and (ii) to assess the efficacy of imputed genotype data in genomic prediction of key performance traits (sea lice resistance and body weight). Imputation accuracies of up to 0.90 were observed using the simple two-generation pedigree dataset, and moderately high accuracy (0.83) was possible even with very low density SNP data (250 SNPs). The performance of genomic prediction using imputed genotype data was comparable to using true genotype data, and both were superior to pedigree-based prediction. These results demonstrate that the genotype imputation approach used in this study can provide a cost-effective method for generating robust genome-wide SNP data for genomic prediction in Atlantic salmon. Genotype imputation approaches are likely to form a critical component of cost-efficient genomic selection programs to improve economically important traits in aquaculture.

Advances in genetic improvement for salmon and trout aquaculture: the Chilean situation and prospects

“…However, the use of genotyping strategies exploiting a combination of low‐ and medium‐ density SNP panels and genotype imputation have proven effective in increasing selection accuracy compared to PBLUP while minimizing the costs of genotyping, thus representing a cost‐effective alternative for the implementation of GS in aquaculture species (Tsai et al . ; Yoshida et al . 2018b).…”

“…Although there is null published information about objective economical appraisal of the implementation of GS in aquaculture breeding programmes, the development and implementation of effective genotype imputation strategies will promote the establishment of cost‐effective GS for traits that are difficult to measure in selection candidates (Tsai et al . ; Yoshida et al . 2018b).…”

“…For instance, the requirement of a large training population, consisting of thousands of individuals with phenotypes and genotypes, and the cost of genotyping a large number of candidates to achieve an appropriate selection intensity are most likely prohibitively expensive. However, the use of genotyping strategies exploiting a combination of low-and medium-density SNP panels and genotype imputation have proven effective in increasing selection accuracy compared to PBLUP while minimizing the costs of genotyping, thus representing a cost-effective alternative for the implementation of GS in aquaculture species (Tsai et al 2017;Yoshida et al 2018b). The increase in accuracy of selection provided by GS for resistance to P. salmonis, sea lice and other important diseases, will be of major commercial benefit to the Chilean salmon farming industry.…”

“…For instance, GS increased selection accuracy compared to traditional pedigree-based selection in salmon and trout. Although there is null published information about objective economical appraisal of the implementation of GS in aquaculture breeding programmes, the development and implementation of effective genotype imputation strategies will promote the establishment of cost-effective GS for traits that are difficult to measure in selection candidates (Tsai et al 2017;Yoshida et al 2018b). Moreover, the identification of functional causative variants, also called quantitative trait nucleotides (QTN), will maximize genomic prediction accuracies (P erez-Enciso et al 2015) within and across populations, decreasing the need to obtain phenotypes for each generation and population (i.e.…”

Future directions in breeding for disease resistance in aquaculture species

“…the offspring) at very-low density, but impute to high density -a technique that is relatively commonplace in terrestrial livestock breeding (e.g. Wellmann et al, 2013) and has shown promise in Atlantic salmon breeding (Tsai et al, 2017).…”