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The key to sustainable sea lice control is in the genome.

The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar)

Overview
TitleThe use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar)
AuthorsCorrea K, Bangera R, Figueroa R, Lhorente JP, Yáñez JM
TypeJournal Article
Journal NameGenetics, selection, evolution : GSE
Volume49
Issue1
Year2017
Page(s)15
CitationCorrea K, Bangera R, Figueroa R, Lhorente JP, Yáñez JM. The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar). Genetics, selection, evolution : GSE. 2017 01 31; 49(1):15.

Abstract

<p>Sea lice infestations caused by Caligus rogercresseyi are a main concern to the salmon farming industry due to associated economic losses. Resistance to this parasite was shown to have low to moderate genetic variation and its genetic architecture was suggested to be polygenic. The aim of this study was to compare accuracies of breeding value predictions obtained with pedigree-based best linear unbiased prediction (P-BLUP) methodology against different genomic prediction approaches: genomic BLUP (G-BLUP), Bayesian Lasso, and Bayes C. To achieve this, 2404 individuals from 118 families were measured for C. rogercresseyi count after a challenge and genotyped using 37 K single nucleotide polymorphisms. Accuracies were assessed using fivefold cross-validation and SNP densities of 0.5, 1, 5, 10, 25 and 37 K. Accuracy of genomic predictions increased with increasing SNP density and was higher than pedigree-based BLUP predictions by up to 22%. Both Bayesian and G-BLUP methods can predict breeding values with higher accuracies than pedigree-based BLUP, however, G-BLUP may be the preferred method because of reduced computation time and ease of implementation. A relatively low marker density (i.e. 10 K) is sufficient for maximal increase in accuracy when using G-BLUP or Bayesian methods for genomic prediction of C. rogercresseyi resistance in Atlantic salmon.</p>
Properties
Additional details for this publication include:
Property NameValue
Journal CountryFrance
Publication TypeJournal Article
Language Abbreng
LanguageEnglish
Elocation10.1186/s12711-017-0291-8
DOI10.1186/s12711-017-0291-8
Journal AbbreviationGenet. Sel. Evol.
Publication Date2017 01 31
eISSN1297-9686
ISSN1297-9686
Publication ModelElectronic
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DatabaseAccession
PMID: PubMedPMID:28143593