title: Genome wide association and genomic prediction for growth traits in juvenile farmed Atlantic salmon using a high density SNP array.
abstract: BACKGROUND
  The 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.
  
  
  RESULTS
  A 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.
  
  
  CONCLUSIONS
  The 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.
authors.affiliation: The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, Edinburgh, UK. hsin-yuan.tsai@roslin.ed.ac.uk.
authors.forename: Hsin-Yuan
authors.initials: HY
authors.lastname: Tsai
authors.affiliation: Landcatch Natural Selection Ltd., 15 Beta Centre, Stirling University Innovation Park, Stirling, FK9 4NF, UK. Alastair.Hamilton@hendrix-genetics.com.
authors.forename: Alastair
authors.initials: A
authors.lastname: Hamilton
authors.affiliation: Landcatch Natural Selection Ltd., 15 Beta Centre, Stirling University Innovation Park, Stirling, FK9 4NF, UK. Alan.Tinch@hendrix-genetics.com.
authors.forename: Alan E
authors.initials: AE
authors.lastname: Tinch
authors.affiliation: Landcatch Natural Selection Ltd., 15 Beta Centre, Stirling University Innovation Park, Stirling, FK9 4NF, UK. Derrick.Guy@hendrix-genetics.com.
authors.forename: Derrick R
authors.initials: DR
authors.lastname: Guy
authors.affiliation: Edinburgh Genomics, Ashworth Laboratories, King's Buildings, The University of Edinburgh, Edinburgh, EH9 3JT, UK. Karim.Gharbi@ed.ac.uk.
authors.forename: Karim
authors.initials: K
authors.lastname: Gharbi
authors.affiliation: Institute of Biodiversity, Animal Health & Comparative Medicine, University of Glasgow, Bearsden Road, Glasgow, G61 1QH, UK. Michael.Stear@glasgow.ac.uk.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Stear
authors.affiliation: The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, Edinburgh, UK. Oswald.Matika@roslin.ed.ac.uk.
authors.forename: Oswald
authors.initials: O
authors.lastname: Matika
authors.affiliation: The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, Edinburgh, UK. Stephen.Bishop@roslin.ed.ac.uk.
authors.forename: Steve C
authors.initials: SC
authors.lastname: Bishop
authors.affiliation: The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, Edinburgh, UK. Ross.Houston@roslin.ed.ac.uk.
authors.forename: Ross D
authors.initials: RD
authors.lastname: Houston
mesh_terms: D000818:Animals; D017756:Aquaculture; D001947:Breeding; D005819:Genetic Markers / Q000235:genetics; D055106:Genome-Wide Association Study; D023281:Genomics; D006801:Humans; D051379:Mice; D020411:Oligonucleotide Array Sequence Analysis; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D020317:Salmo salar / Q000235:genetics* / Q000254:growth & development*; D014158:Transcription, Genetic
chemical_list: D005819:Genetic Markers