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Accurate genomic predictions for BCWD resistance in rainbow trout are achieved using low‐density SNP panels: Evidence that long‐range LD is a major contributing factor
Author(s) -
Vallejo Roger L.,
Silva Rafael M. O.,
Evenhuis Jason P.,
Gao Guangtu,
Liu Sixin,
Parsons James E.,
Martin Kyle E.,
Wiens Gregory D.,
Lourenco Daniela  A. L.,
Leeds Timothy D.,
Palti Yniv
Publication year - 2018
Publication title -
journal of animal breeding and genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.689
H-Index - 51
eISSN - 1439-0388
pISSN - 0931-2668
DOI - 10.1111/jbg.12335
Subject(s) - snp , biology , rainbow trout , quantitative trait locus , single nucleotide polymorphism , genetics , linkage disequilibrium , best linear unbiased prediction , population , selection (genetic algorithm) , genotype , gene , fish <actinopterygii> , computer science , fishery , demography , artificial intelligence , sociology
Previously accurate genomic predictions for Bacterial cold water disease (BCWD) resistance in rainbow trout were obtained using a medium‐density single nucleotide polymorphism (SNP) array. Here, the impact of lower‐density SNP panels on the accuracy of genomic predictions was investigated in a commercial rainbow trout breeding population. Using progeny performance data, the accuracy of genomic breeding values (GEBV) using 35K, 10K, 3K, 1K, 500, 300 and 200 SNP panels as well as a panel with 70 quantitative trait loci (QTL)‐flanking SNP was compared. The GEBVs were estimated using the Bayesian method BayesB, single‐step GBLUP (ssGBLUP) and weighted ssGBLUP (wssGBLUP). The accuracy of GEBVs remained high despite the sharp reductions in SNP density, and even with 500 SNP accuracy was higher than the pedigree‐based prediction (0.50–0.56 versus 0.36). Furthermore, the prediction accuracy with the 70 QTL‐flanking SNP (0.65–0.72) was similar to the panel with 35K SNP (0.65–0.71). Genomewide linkage disequilibrium (LD) analysis revealed strong LD ( r 2  ≥ 0.25) spanning on average over 1 Mb across the rainbow trout genome. This long‐range LD likely contributed to the accurate genomic predictions with the low‐density SNP panels. Population structure analysis supported the hypothesis that long‐range LD in this population may be caused by admixture. Results suggest that lower‐cost, low‐density SNP panels can be used for implementing genomic selection for BCWD resistance in rainbow trout breeding programs.

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