BackgroundPreviously, 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.MethodsWe 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]. Naïve 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.ResultsThe 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.ConclusionsUsing 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-017-0293-6) contains supplementary material, which is available to authorized users.

h As global aquaculture fish production continues to expand, an improved understanding of how environmental factors interact in fish health and production is needed. Significant advances have been made toward economical alternatives to costly fishmealbased diets, such as grain-based formulations, and toward defining the effect of rearing density on fish health and production. Little research, however, has examined the effects of fishmeal-and grain-based diets in combination with alterations in rearing density. Moreover, it is unknown whether interactions between rearing density and diet impact the composition of the fish intestinal microbiota, which might in turn impact fish health and production. We fed aquacultured adult rainbow trout (Oncorhynchus mykiss) fishmeal-or grain-based diets, reared them under high-or low-density conditions for 10 months in a single aquaculture facility, and evaluated individual fish growth, production, fin indices, and intestinal microbiota composition using 16S rRNA gene sequencing. We found that the intestinal microbiotas were dominated by a shared core microbiota consisting of 52 bacterial lineages observed across all individuals, diets, and rearing densities. Variations in diet and rearing density resulted in only minor changes in intestinal microbiota composition despite significant effects of these variables on fish growth, performance, fillet quality, and welfare. Significant interactions between diet and rearing density were observed only in evaluations of fin indices and the relative abundance of the bacterial genus Staphylococcus. These results demonstrate that aquacultured rainbow trout can achieve remarkable consistency in intestinal microbiota composition and suggest the possibility of developing novel aquaculture strategies without overtly altering intestinal microbiota composition.

The TNF superfamily (TNFSF) of proteins are cytokines involved in diverse immunological and developmental pathways. Little is known about their evolution or expression in lower vertebrate species. Bioinformatic searches of Zebrafish, Tetraodon, and Fugu genome and other teleost expressed sequence tag databases identified 44 novel gene sequences containing a TNF homology domain. This work reveals the following: 1) teleosts possess orthologs of BAFF, APRIL, EDA, TWEAK, 4-1BBL, Fas ligand, LIGHT, CD40L, RANKL, and possibly TL1A; 2) the BAFF-APRIL subfamily is enriched by a third member, BALM, unique to fish; 3) orthologs of lymphotoxins ␣ and ␤ were not clearly identified in teleosts and are substituted by a related ligand, TNF-New; 4) as many as four TRAIL-like genes are present in teleosts, as compared with only one in mammals; and 5) T cell activation ligands OX40L, CD27L, CD30L, and GITRL were not identified in any fish species. Finally, we characterize mRNA expression of TNFSF members CD40L, LIGHT, BALM, APRIL, Fas ligand, RANKL, TRAIL-like, and TNF-New in rainbow trout, Oncorhynchus mykiss, immune and nonimmune tissues. In conclusion, we identified a total of 14 distinct TNFSF members in fishes, indicating expansion of this superfamily before the divergence of bony fish and tetrapods, ϳ360 -450 million years ago. Based on these findings, we extend a model of TNFSF evolution and the coemergence of the vertebrate adaptive immune system.

Selective breeding of animals for increased innate resistance offers an attractive strategy to control disease in agriculture. However, this approach is limited by an incomplete knowledge of the heritability, duration, and mechanism(s) of resistance, as well as the impact of selection on the immune response to unrelated pathogens. Herein, as part of a rainbow trout broodstock improvement program, we evaluated factors involved in resistance against a bacterial disease agent, Flavobacterium psychrophilum. In 2005, 71 full-sibling crosses, weighing an average of 2.4 g, were screened, and resistant and susceptible crosses were identified. Naive cohorts were evaluated at 10 and 800 g in size, and most maintained their original relative resistant or susceptible phenotypes, indicating that these traits were stable as size increased >300-fold. During the course of these studies, we observed that the normalized spleen weights of the resistant fish crosses were greater than those of the susceptible fish crosses. To test for direct association, we determined the spleen-somatic index of 103 fish crosses; created high, medium, and low spleen-index groups; and determined survival following challenge with F. psychrophilum or Yersinia ruckeri. Consistent with our previous observations, trout with larger spleen indices were significantly more resistant to F. psychrophilum challenge; however, this result was pathogen-specific, as there was no correlation of spleen size with survival following Y. ruckeri challenge. To our knowledge, this is the first report of a positive association between spleen size and disease resistance in a teleost fish. Further evaluation of spleen index as an indirect measure of disease resistance is warranted.

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 ≥ 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.

The objectives of this study were to estimate the heritabilities for and genetic correlations among resistance to bacterial cold-water disease and growth traits in a population of rainbow trout (Oncorhynchus mykiss). Bacterial cold-water disease, a chronic disease of rainbow trout, is caused by Flavobacterium psychrophilum. This bacterium also causes acute losses in young fish, known as rainbow trout fry syndrome. Selective breeding for increased disease resistance is a promising strategy that has not been widely used in aquaculture. At the same time, improving growth performance is critical for efficient production. At the National Center for Cool and Cold Water Aquaculture, reducing the negative impact of diseases on rainbow trout culture and improving growth performance are primary objectives. In 2005, when fish averaged 2.4 g, 71 full-sib families were challenged with F. psychrophilum and evaluated for 21 d. Overall survival was 29.3% and family rates of survival varied from 1.5 to 72.5%. Heritability of postchallenge survival, an indicator of disease resistance, was estimated to be 0.35 +/- 0.09. Body weights at 9 and 12 mo posthatch and growth rate from 9 to 12 mo were evaluated on siblings of the fish in the disease challenge study. Growth traits were moderately heritable, from 0.32 for growth rate to 0.61 for 12-mo BW. Genetic and phenotypic correlations between growth traits and resistance to bacterial cold-water disease were not different from zero. These results suggest that genetic improvement can be made simultaneously for growth and bacterial cold-water disease resistance in rainbow trout by using selective breeding.

A family-based selection program was initiated at the National Center for Cool and Cold Water Aquaculture in 2005 to improve resistance to bacterial cold water disease (BCWD) in rainbow trout. The objective of this study was to estimate response to 2 generations of selection. A total of 14,841 juvenile fish (BW = 3.1 g; SD = 1.1 g) from 230 full-sib families and 3 randomly mated control lines were challenged intraperitoneally with Flavobacterium psychrophilum, the bacterium that causes BCWD, and mortalities were observed for 21 d. Selection was applied to family EBV derived from a proportional-hazards frailty (animal) model while constraining rate of inbreeding to

Bacterial cold water disease (BCWD) causes significant economic losses in salmonid aquaculture, and traditional family-based breeding programs aimed at improving BCWD resistance have been limited to exploiting only between-family variation. We used genomic selection (GS) models to predict genomic breeding values (GEBVs) for BCWD resistance in 10 families from the first generation of the NCCCWA BCWD resistance breeding line, compared the predictive ability (PA) of GEBVs to pedigree-based estimated breeding values (EBVs), and compared the impact of two SNP genotyping methods on the accuracy of GEBV predictions. The BCWD phenotypes survival days (DAYS) and survival status (STATUS) had been recorded in training fish (n = 583) subjected to experimental BCWD challenge. Training fish, and their full sibs without phenotypic data that were used as parents of the subsequent generation, were genotyped using two methods: restriction-site associated DNA (RAD) sequencing and the Rainbow Trout Axiom® 57 K SNP array (Chip). Animal-specific GEBVs were estimated using four GS models: BayesB, BayesC, single-step GBLUP (ssGBLUP), and weighted ssGBLUP (wssGBLUP). Family-specific EBVs were estimated using pedigree and phenotype data in the training fish only. The PA of EBVs and GEBVs was assessed by correlating mean progeny phenotype (MPP) with mid-parent EBV (family-specific) or GEBV (animal-specific). The best GEBV predictions were similar to EBV with PA values of 0.49 and 0.46 vs. 0.50 and 0.41 for DAYS and STATUS, respectively. Among the GEBV prediction methods, ssGBLUP consistently had the highest PA. The RAD genotyping platform had GEBVs with similar PA to those of GEBVs from the Chip platform. The PA of ssGBLUP and wssGBLUP methods was higher with the Chip, but for BayesB and BayesC methods it was higher with the RAD platform. The overall GEBV accuracy in this study was low to moderate, likely due to the small training sample used. This study explored the potential of GS for improving resistance to BCWD in rainbow trout using, for the first time, progeny testing data to assess the accuracy of GEBVs, and it provides the basis for further investigation on the implementation of GS in commercial rainbow trout populations.