title: Genomic prediction of host resistance to sea lice in farmed Atlantic salmon populations.
abstract: Sea lice have significant negative economic and welfare impacts on marine Atlantic salmon farming. Since host resistance to sea lice has a substantial genetic component, selective breeding can contribute to control of lice. Genomic selection uses genome-wide marker information to predict breeding values, and can achieve markedly higher accuracy than pedigree-based methods. Our aim was to assess the genetic architecture of host resistance to sea lice, and test the utility of genomic prediction of breeding values. Individual lice counts were measured in challenge experiments using two large Atlantic salmon post-smolt populations from a commercial breeding programme, which had genotypes for ~33 K single nucleotide polymorphisms (SNPs). The specific objectives were to: (i) estimate the heritability of host resistance; (ii) assess its genetic architecture by performing a genome-wide association study (GWAS); (iii) assess the accuracy of predicted breeding values using varying SNP densities (0.5 to 33 K) and compare it to that of pedigree-based prediction; and (iv) evaluate the accuracy of prediction in closely and distantly related animals.
  
  
  
  Heritability of host resistance was significant (0.22 to 0.33) in both populations using either pedigree or genomic relationship matrices. The GWAS suggested that lice resistance is a polygenic trait, and no genome-wide significant quantitative trait loci were identified. Based on cross-validation analysis, genomic predictions were more accurate than pedigree-based predictions for both populations. Although prediction accuracies were highest when closely-related animals were used in the training and validation sets, the benefit of having genomic-versus pedigree-based predictions within a population increased as the relationships between training and validation sets decreased. Prediction accuracy reached an asymptote with a SNP density of ~5 K within populations, although higher SNP density was advantageous for cross-population prediction.
  
  
  
  Host resistance to sea lice in farmed Atlantic salmon has a significant genetic component. Phenotypes relating to host resistance can be predicted with moderate to high accuracy within populations, with a major advantage of genomic over pedigree-based methods, even at relatively sparse SNP densities. Prediction accuracies across populations were low, but improved with higher marker densities. Genomic selection can contribute to lice control in salmon farming.
authors.affiliation: The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG, 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.
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.
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.
authors.forename: Derrick R
authors.initials: DR
authors.lastname: Guy
authors.affiliation: Institute of Aquaculture, University of Stirling, Stirling, FK9 4LA, UK.
authors.forename: James E
authors.initials: JE
authors.lastname: Bron
authors.affiliation: Institute of Aquaculture, University of Stirling, Stirling, FK9 4LA, UK.
authors.forename: John B
authors.initials: JB
authors.lastname: Taggart
authors.affiliation: Edinburgh Genomics, Ashworth Laboratories, King's Buildings, University of Edinburgh, Edinburgh, EH9 3JT, UK.
authors.forename: Karim
authors.initials: K
authors.lastname: Gharbi
authors.affiliation: Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Bearsden Road, Glasgow, G61 1QH, UK.
authors.forename: Michael
authors.initials: M
authors.lastname: Stear
authors.affiliation: The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG, 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, UK.
authors.forename: Ricardo
authors.initials: R
authors.lastname: Pong-Wong
authors.affiliation: The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, EH25 9RG, 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, UK.
authors.forename: Ross D
authors.initials: RD
authors.lastname: Houston
mesh_terms: D000818:Animals; D017756:Aquaculture; D001947:Breeding; D033342:Copepoda; D060467:Disease Resistance / Q000235:genetics*; D005393:Fish Diseases / Q000235:genetics* / Q000469:parasitology; D055106:Genome-Wide Association Study; D005838:Genotype; D008957:Models, Genetic; D020412:Multifactorial Inheritance; D010375:Pedigree; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D020317:Salmo salar / Q000235:genetics* / Q000469:parasitology