Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/23988
Appears in Collections:Aquaculture Journal Articles
Peer Review Status: Refereed
Title: Genomic prediction of host resistance to sea lice in farmed Atlantic salmon populations
Authors: Tsai, Hsin Y
Hamilton, Alastair
Tinch, Alan E
Guy, Derrick R
Bron, James
Taggart, John
Gharbi, Karim
Stear, Michael
Matika, Oswald
Pong-Wong, Ricardo
Bishop, Stephen C
Houston, Ross D
Contact Email: j.b.taggart@stir.ac.uk
Issue Date: 29-Jun-2016
Publisher: BioMed Central
Citation: Tsai HY, Hamilton A, Tinch AE, Guy DR, Bron J, Taggart J, Gharbi K, Stear M, Matika O, Pong-Wong R, Bishop SC & Houston RD (2016) Genomic prediction of host resistance to sea lice in farmed Atlantic salmon populations, Genetics Selection Evolution, 48 (1), Art. No.: 47.
Abstract: Background 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 ~33K 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 (0.5to33K) and compare it to that of pedigree-based prediction; and (iv) evaluate the accuracy of prediction in closely and distantly related animals.  Results Heritability of host resistance was significant (0.22to0.33) 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 ~5K within populations, although higher SNP density was advantageous for cross-population prediction.  Conclusions 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.
Type: Journal Article
URI: http://hdl.handle.net/1893/23988
DOI Link: http://dx.doi.org/10.1186/s12711-016-0226-9
Rights: © The Author(s) 2016 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Affiliation: University of Edinburgh
Landcatch Natural Selection Ltd
Landcatch Natural Selection Ltd
Landcatch Natural Selection Ltd
Aquaculture
Aquaculture
University of Edinburgh
University of Glasgow
University of Edinburgh
University of Edinburgh
University of Edinburgh
University of Edinburgh

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