PMID- 28148220 OWN - NLM STAT- MEDLINE DCOM- 20170223 LR - 20181113 IS - 1297-9686 (Electronic) IS - 0999-193X (Print) IS - 0999-193X (Linking) VI - 49 IP - 1 DP - 2017 Feb 1 TI - Genomic selection models double the accuracy of predicted breeding values for bacterial cold water disease resistance compared to a traditional pedigree-based model in rainbow trout aquaculture. PG - 17 LID - 10.1186/s12711-017-0293-6 [doi] LID - 17 AB - BACKGROUND: Previously, we have shown that bacterial cold water disease (BCWD) resistance in rainbow trout can be improved using traditional family-based selection, but progress has been limited to exploiting only between-family genetic variation. Genomic selection (GS) is a new alternative that enables exploitation of within-family genetic variation. METHODS: We compared three GS models [single-step genomic best linear unbiased prediction (ssGBLUP), weighted ssGBLUP (wssGBLUP), and BayesB] to predict genomic-enabled breeding values (GEBV) for BCWD resistance in a commercial rainbow trout population, and compared the accuracy of GEBV to traditional estimates of breeding values (EBV) from a pedigree-based BLUP (P-BLUP) model. We also assessed the impact of sampling design on the accuracy of GEBV predictions. For these comparisons, we used BCWD survival phenotypes recorded on 7893 fish from 102 families, of which 1473 fish from 50 families had genotypes [57 K single nucleotide polymorphism (SNP) array]. Naive siblings of the training fish (n = 930 testing fish) were genotyped to predict their GEBV and mated to produce 138 progeny testing families. In the following generation, 9968 progeny were phenotyped to empirically assess the accuracy of GEBV predictions made on their non-phenotyped parents. RESULTS: The accuracy of GEBV from all tested GS models were substantially higher than the P-BLUP model EBV. The highest increase in accuracy relative to the P-BLUP model was achieved with BayesB (97.2 to 108.8%), followed by wssGBLUP at iteration 2 (94.4 to 97.1%) and 3 (88.9 to 91.2%) and ssGBLUP (83.3 to 85.3%). Reducing the training sample size to n = ~1000 had no negative impact on the accuracy (0.67 to 0.72), but with n = ~500 the accuracy dropped to 0.53 to 0.61 if the training and testing fish were full-sibs, and even substantially lower, to 0.22 to 0.25, when they were not full-sibs. CONCLUSIONS: Using progeny performance data, we showed that the accuracy of genomic predictions is substantially higher than estimates obtained from the traditional pedigree-based BLUP model for BCWD resistance. Overall, we found that using a much smaller training sample size compared to similar studies in livestock, GS can substantially improve the selection accuracy and genetic gains for this trait in a commercial rainbow trout breeding population. FAU - Vallejo, Roger L AU - Vallejo RL AD - National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, USA. roger.vallejo@ars.usda.gov. FAU - Leeds, Timothy D AU - Leeds TD AD - National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, USA. FAU - Gao, Guangtu AU - Gao G AD - National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, USA. FAU - Parsons, James E AU - Parsons JE AD - Troutlodge, Inc., P.O. Box 1290, Sumner, WA, USA. FAU - Martin, Kyle E AU - Martin KE AD - Troutlodge, Inc., P.O. Box 1290, Sumner, WA, USA. FAU - Evenhuis, Jason P AU - Evenhuis JP AD - National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, USA. FAU - Fragomeni, Breno O AU - Fragomeni BO AD - Animal and Dairy Science Department, University of Georgia, Athens, GA, USA. FAU - Wiens, Gregory D AU - Wiens GD AD - National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, USA. FAU - Palti, Yniv AU - Palti Y AD - National Center for Cool and Cold Water Aquaculture, Agricultural Research Service, United States Department of Agriculture, Kearneysville, WV, USA. LA - eng PT - Journal Article DEP - 20170201 PL - France TA - Genet Sel Evol JT - Genetics, selection, evolution : GSE JID - 9114088 RN - 0 (Genetic Markers) SB - IM MH - Animals MH - Bacterial Infections/genetics/microbiology MH - Bayes Theorem MH - *Breeding MH - *Cold Temperature MH - Disease Resistance/*genetics MH - Fish Diseases/*genetics/microbiology MH - Genetic Markers MH - Genomics/methods MH - *Models, Genetic MH - Oncorhynchus mykiss/*genetics MH - *Pedigree MH - Phenotype MH - Polymorphism, Single Nucleotide MH - Quantitative Trait Loci MH - Reproducibility of Results MH - *Selection, Genetic PMC - PMC5289005 EDAT- 2017/02/06 06:00 MHDA- 2017/02/24 06:00 PMCR- 2017/02/01 CRDT- 2017/02/03 06:00 PHST- 2016/07/15 00:00 [received] PHST- 2017/01/25 00:00 [accepted] PHST- 2017/02/03 06:00 [entrez] PHST- 2017/02/06 06:00 [pubmed] PHST- 2017/02/24 06:00 [medline] PHST- 2017/02/01 00:00 [pmc-release] AID - 10.1186/s12711-017-0293-6 [pii] AID - 293 [pii] AID - 10.1186/s12711-017-0293-6 [doi] PST - epublish SO - Genet Sel Evol. 2017 Feb 1;49(1):17. doi: 10.1186/s12711-017-0293-6.