Genome wide association study for resistance to Caligus rogercresseyi in Atlantic salmon (Salmo salar L.) using a 50K SNP genotyping array

Correa, Katharina; Lhorente, Jean Paul; Bassini, Liane N.; López, María Eugenia; Génova, Alex Di; Maass, Alejandro; Davidson, William S.; Yáñez, José M.

doi:10.1016/j.aquaculture.2016.04.008

Cited by 81 publications

(88 citation statements)

References 28 publications

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“…Therefore, the two phenotypes used in the current study were sea lice counts and body weight, as described in Tsai et al (2016a). Both these traits have been shown in previous studies to be heritable, but with a predominantly polygenic genetic architecture (Ødegård et al 2014; Tsai et al 2015, 2016a; Correa et al 2016). The sea lice count data were transformed to account for a positively skewed distribution, using the approach of Gjerde et al (2011), as described previously for these data (Tsai et al 2016a).…”

Section: Methodsmentioning

confidence: 99%

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

Tsai

Matika

Edwards

et al. 2017

G3 Genes|Genomes|Genetics

104

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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.

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Section: Methodsmentioning

confidence: 99%

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

Tsai

Matika

Edwards

et al. 2017

G3 Genes|Genomes|Genetics

104

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“…Here, genomic regions harboring collagen alpha-1XIII chain gene (coda1) were identified in both comparisons. There is evidence that collagen genes may be involved in the response of Atlantic salmon to sea lice as initiators of inflammatory cytokine signaling (Castillo-Briceño et al, 2009;Correa et al, 2016;Krasnov, Skugor, Todorcevic, Glover, & Nilsen, 2012). Therefore, this gene might be involved in the immune response to cope with specific diseases present in aquaculture environment and may be a relevant target of selection.…”

Section: Parallel Genomic Regions Detected As Being Putatively Undementioning

confidence: 99%

Comparing genomic signatures of domestication in two Atlantic salmon (Salmo salar L.) populations with different geographical origins

López

Benestan

Moore

et al. 2018

Evolutionary Applications

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Selective breeding and genetic improvement have left detectable signatures on the genomes of domestic species. The elucidation of such signatures is fundamental for detecting genomic regions of biological relevance to domestication and improving management practices. In aquaculture, domestication was carried out independently in different locations worldwide, which provides opportunities to study the parallel effects of domestication on the genome of individuals that have been selected for similar traits. In this study, we aimed to detect potential genomic signatures of domestication in two independent pairs of wild/domesticated Atlantic salmon populations of Canadian and Scottish origins, respectively. Putative genomic regions under divergent selection were investigated using a 200K SNP array by combining three different statistical methods based either on allele frequencies (LFMM, Bayescan) or haplotype differentiation (Rsb). We identified 337 and 270 SNPs potentially under divergent selection in wild and hatchery populations of Canadian and Scottish origins, respectively. We observed little overlap between results obtained from different statistical methods, highlighting the need to test complementary approaches for detecting a broad range of genomic footprints of selection. The vast majority of the outliers detected were population‐specific but we found four candidate genes that were shared between the populations. We propose that these candidate genes may play a role in the parallel process of domestication. Overall, our results suggest that genetic drift may have override the effect of artificial selection and/or point toward a different genetic basis underlying the expression of similar traits in different domesticated strains. Finally, it is likely that domestication may predominantly target polygenic traits (e.g., growth) such that its genomic impact might be more difficult to detect with methods assuming selective sweeps.

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“…It has been observed that Caligus primarily affects Atlantic salmon ( Salmo salar and rainbow trout ( Oncorhynchus mykiss ), while coho salmon ( Oncorhynchus kisutch ) has an innate lower susceptibility to the parasite 6 . The clinical signs attributed to infection by sea lice include skin lesions, osmotic imbalance and greater susceptibility to bacterial and viral infections through the suppression of immune responses by damage to the skin of the host 7 .…”

Section: Introductionmentioning

confidence: 99%

Genome-scale comparative analysis for host resistance against sea lice between Atlantic salmon and rainbow trout

Cáceres

Barría

Christensen

et al. 2019

Preprint

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Genome wide association study for resistance to Caligus rogercresseyi in Atlantic salmon (Salmo salar L.) using a 50K SNP genotyping array

Cited by 81 publications

References 28 publications

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

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

Comparing genomic signatures of domestication in two Atlantic salmon (Salmo salar L.) populations with different geographical origins

Genome-scale comparative analysis for host resistance against sea lice between Atlantic salmon and rainbow trout

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