Abstract
BackgroundThe genetic architecture of complex traits in farmed animal populations is of interest from a scientific and practical perspective. The use of genetic markers to predict the genetic merit (breeding values) of individuals is commonplace in modern farm animal breeding schemes. Recently, high density SNP arrays have become available for Atlantic salmon, which facilitates genomic prediction and association studies using genome-wide markers and economically important traits. The aims of this study were (i) to use a high density SNP array to investigate the genetic architecture of weight and length in juvenile Atlantic salmon; (ii) to assess the utility of genomic prediction for these traits, including testing different marker densities; (iii) to identify potential candidate genes underpinning variation in early growth.ResultsA pedigreed population of farmed Atlantic salmon (n = 622) were measured for weight and length traits at one year of age, and genotyped for 111,908 segregating SNP markers using a high density SNP array. The heritability of both traits was estimated using pedigree and genomic relationship matrices, and was comparable at around 0.5 and 0.6 respectively. The results of the GWA analysis pointed to a polygenic genetic architecture, with no SNPs surpassing the genome-wide significance threshold, and one SNP associated with length at the chromosome-wide level. SNPs surpassing an arbitrary threshold of significance (P < 0.005, ~ top 0.5 % of markers) were aligned to an Atlantic salmon reference transcriptome, identifying 109 SNPs in transcribed regions that were annotated by alignment to human, mouse and zebrafish protein databases. Prediction of breeding values was more accurate when applying genomic (GBLUP) than pedigree (PBLUP) relationship matrices (accuracy ~ 0.7 and 0.58 respectively) and 5,000 SNPs were sufficient for obtaining this accuracy increase over PBLUP in this specific population.ConclusionsThe high density SNP array can effectively capture the additive genetic variation in complex traits. However, the traits of weight and length both appear to be very polygenic with only one SNP surpassing the chromosome-wide threshold. Genomic prediction using the array is effective, leading to an improvement in accuracy compared to pedigree methods, and this improvement can be achieved with only a small subset of the markers in this population. The results have practical relevance for genomic selection in salmon and may also provide insight into variation in the identified genes underpinning body growth and development in salmonid species.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2117-9) contains supplementary material, which is available to authorized users.
Highlights
The genetic architecture of complex traits in farmed animal populations is of interest from a scientific and practical perspective
Summary statistics and heritability The final dataset used for the Genome-wide association studies (GWAS) consisted of ~ 112 K QC-filtered single nucleotide polymorphism (SNP) successfully genotyped in 622 fish with weight and length measurements taken approximately 1 year post-hatching
Genome-wide association analysis To determine which individual SNPs were associated with weight and length, a GWAS was performed on all markers
Summary
The genetic architecture of complex traits in farmed animal populations is of interest from a scientific and practical perspective. High density SNP arrays have become available for Atlantic salmon, which facilitates genomic prediction and association studies using genome-wide markers and economically important traits. The aims of this study were (i) to use a high density SNP array to investigate the genetic architecture of weight and length in juvenile Atlantic salmon; (ii) to assess the utility of genomic prediction for these traits, including testing different marker densities; (iii) to identify potential candidate genes underpinning variation in early growth. Genome-wide association studies (GWAS) are employed to assess the association between DNA sequence variants (typically SNPs) dispersed throughout the genome and complex traits of interest. Abundant GWAS have been conducted on human [4] and terrestrial livestock species [5, 6], resulting in the discovery of several genes and underlying mutations affecting traits of medical and economic importance. A high density publicly available SNP chip containing ~132 K verified SNP markers was developed [10] and gives the opportunity to apply GWAS at a resolution previously not possible in salmon
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