Genome-wide association analysis of the resistance to infectious hematopoietic necrosis virus in two rainbow trout aquaculture lines confirms oligogenic architecture with several moderate effect quantitative trait loci.

Infectious hematopoietic necrosis (IHN) is a disease of salmonid fish that is caused by the IHN virus (IHNV), which can cause substantial mortality and economic losses in rainbow trout aquaculture and fisheries enhancement hatchery programs. In a previous study on a commercial rainbow trout breeding line that has undergone selection, we found that genetic resistance to IHNV is controlled by the oligogenic inheritance of several moderate and many small effect quantitative trait loci (QTL). Here we used genome wide association analyses in two different commercial aquaculture lines that were naïve to previous exposure to IHNV to determine whether QTL were shared across lines, and to investigate whether there were major effect loci that were still segregating in the naïve lines. A total of 1,859 and 1,768 offspring from two commercial aquaculture strains were phenotyped for resistance to IHNV and genotyped with the rainbow trout Axiom 57K SNP array. Moderate heritability values (0.15-0.25) were estimated. Two statistical methods were used for genome wide association analyses in the two populations. No major QTL were detected despite the naïve status of the two lines. Further, our analyses confirmed an oligogenic architecture for genetic resistance to IHNV in rainbow trout. Overall, 17 QTL with notable effect (≥1.9% of the additive genetic variance) were detected in at least one of the two rainbow trout lines with at least one of the two statistical methods. Five of those QTL were mapped to overlapping or adjacent chromosomal regions in both lines, suggesting that some loci may be shared across commercial lines. Although some of the loci detected in this GWAS merit further investigation to better understand the biological basis of IHNV disease resistance across populations, the overall genetic architecture of IHNV resistance in the two rainbow trout lines suggests that genomic selection may be a more effective strategy for genetic improvement in this trait.

Comparisons among rainbow trout, Oncorhynchus mykiss, populations of maternal transcript profile associated with egg viability.

BACKGROUND: Transcription is arrested in the late stage oocyte and therefore the maternal transcriptome stored in the oocyte provides nearly all the mRNA required for oocyte maturation, fertilization, and early cleavage of the embryo. The transcriptome of the unfertilized egg, therefore, has potential to provide markers for predictors of egg quality and diagnosing problems with embryo production encountered by fish hatcheries. Although levels of specific transcripts have been shown to associate with measures of egg quality, these differentially expressed genes (DEGs) have not been consistent among studies. The present study compares differences in select transcripts among unfertilized rainbow trout eggs of different quality based on eyeing rate, among 2 year classes of the same line (A1, A2) and a population from a different hatchery (B). The study compared 65 transcripts previously reported to be differentially expressed with egg quality in rainbow trout. RESULTS: There were 32 transcripts identified as DEGs among the three groups by regression analysis. Group A1 had the most DEGs, 26; A2 had 15, 14 of which were shared with A1; and B had 12, 7 of which overlapped with A1 or A2. Six transcripts were found in all three groups, dcaf11, impa2, mrpl39_like, senp7, tfip11 and uchl1. CONCLUSIONS: Our results confirmed maternal transcripts found to be differentially expressed between low- and high-quality eggs in one population of rainbow trout can often be found to overlap with DEGs in other populations. The transcripts differentially expressed with egg quality remain consistent among year classes of the same line. Greater similarity in dysregulated transcripts within year classes of the same line than among lines suggests patterns of transcriptome dysregulation may provide insight into causes of decreased viability within a hatchery population. Although many DEGs were identified, for each of the genes there is considerable variability in transcript abundance among eggs of similar quality and low correlations between transcript abundance and eyeing rate, making it highly improbable to predict the quality of a single batch of eggs based on transcript abundance of just a few genes.

Assessing Accuracy of Genomic Predictions for Resistance to Infectious Hematopoietic Necrosis Virus With Progeny Testing of Selection Candidates in a Commercial Rainbow Trout Breeding Population.

Infectious hematopoietic necrosis (IHN) is an economically important disease of salmonid fish caused by the IHN virus (IHNV). Under industrial aquaculture settings, IHNV can cause substantial mortality and losses. Actually, there is no confirmed and cost-effective method for IHNV control. Clear Springs Foods, Inc. has been performing family-based selective breeding to increase genetic resistance to IHNV in their rainbow trout breeding program. In an earlier study, we used siblings cross-validation to estimate the accuracy of genomic prediction (GP) for IHNV resistance in this breeding population. In the present report, we used empirical progeny testing data to evaluate whether genomic selection (GS) can improve the accuracy of breeding value predictions over traditional pedigree-based best linear unbiased predictions (PBLUP). We found that the GP accuracy with single-step GBLUP (ssGBLUP) outperformed PBLUP by 15% (from 0.33 to 0.38). Furthermore, we found that ssGBLUP had higher GP accuracy than weighted ssGBLUP (wssGBLUP) and single-step Bayesian multiple regression (ssBMR) models with BayesB and BayesC priors which supports our previous findings that the underlying liability of genetic resistance against IHNV in this breeding population might be polygenic. Our results show that GS can be more effective than either the traditional pedigree-based PBLUP model or the marker-assisted selection approach for improving genetic resistance against IHNV in this commercial rainbow trout population.

Genome-wide association analysis and accuracy of genome-enabled breeding value predictions for resistance to infectious hematopoietic necrosis virus in a commercial rainbow trout breeding population.

BACKGROUND: Infectious hematopoietic necrosis (IHN) is a disease of salmonid fish that is caused by the IHN virus (IHNV). Under intensive aquaculture conditions, IHNV can cause significant mortality and economic losses. Currently, there is no proven and cost-effective method for IHNV control. Clear Springs Foods, Inc. has been applying selective breeding to improve genetic resistance to IHNV in their rainbow trout breeding program. The goals of this study were to elucidate the genetic architecture of IHNV resistance in this commercial population by performing genome-wide association studies (GWAS) with multiple regression single-step methods and to assess if genomic selection can improve the accuracy of genetic merit predictions over conventional pedigree-based best linear unbiased prediction (PBLUP) using cross-validation analysis. RESULTS: Ten moderate-effect quantitative trait loci (QTL) associated with resistance to IHNV that jointly explained up to 42% of the additive genetic variance were detected in our GWAS. Only three of the 10 QTL were detected by both single-step Bayesian multiple regression (ssBMR) and weighted single-step GBLUP (wssGBLUP) methods. The accuracy of breeding value predictions with wssGBLUP (0.33-0.39) was substantially better than with PBLUP (0.13-0.24). CONCLUSIONS: Our comprehensive genome-wide scan for QTL revealed that genetic resistance to IHNV is controlled by the oligogenic inheritance of up to 10 moderate-effect QTL and many small-effect loci in this commercial rainbow trout breeding population. Taken together, our results suggest that whole genome-enabled selection models will be more effective than the conventional pedigree-based method for breeding value estimation or the marker-assisted selection approach for improving the genetic resistance of rainbow trout to IHNV in this population.

Whole-genome mapping of quantitative trait loci and accuracy of genomic predictions for resistance to columnaris disease in two rainbow trout breeding populations.

BACKGROUND: Columnaris disease (CD) is an emerging problem for the rainbow trout aquaculture industry in the US. The objectives of this study were to: (1) identify common genomic regions that explain a large proportion of the additive genetic variance for resistance to CD in two rainbow trout (Oncorhynchus mykiss) populations; and (2) estimate the gains in prediction accuracy when genomic information is used to evaluate the genetic potential of survival to columnaris infection in each population. METHODS: Two aquaculture populations were investigated: the National Center for Cool and Cold Water Aquaculture (NCCCWA) odd-year line and the Troutlodge, Inc., May odd-year (TLUM) nucleus breeding population. Fish that survived to 21 days post-immersion challenge were recorded as resistant. Single nucleotide polymorphism (SNP) genotypes were available for 1185 and 1137 fish from NCCCWA and TLUM, respectively. SNP effects and variances were estimated using the weighted single-step genomic best linear unbiased prediction (BLUP) for genome-wide association. Genomic regions that explained more than 1% of the additive genetic variance were considered to be associated with resistance to CD. Predictive ability was calculated in a fivefold cross-validation scheme and using a linear regression method. RESULTS: Validation on adjusted phenotypes provided a prediction accuracy close to zero, due to the binary nature of the trait. Using breeding values computed from the complete data as benchmark improved prediction accuracy of genomic models by about 40% compared to the pedigree-based BLUP. Fourteen windows located on six chromosomes were associated with resistance to CD in the NCCCWA population, of which two windows on chromosome Omy 17 jointly explained more than 10% of the additive genetic variance. Twenty-six windows located on 13 chromosomes were associated with resistance to CD in the TLUM population. Only four associated genomic regions overlapped with quantitative trait loci (QTL) between both populations. CONCLUSIONS: Our results suggest that genome-wide selection for resistance to CD in rainbow trout has greater potential than selection for a few target genomic regions that were found to be associated to resistance to CD due to the polygenic architecture of this trait, and because the QTL associated with resistance to CD are not sufficiently informative for selection decisions across populations.

Variance and covariance estimates for resistance to bacterial cold water disease and columnaris disease in two rainbow trout breeding populations1.

Family-based selective breeding can be an effective strategy for controlling diseases in aquaculture. This study aimed to estimate (co)variance components for resistance to bacterial cold water disease (BCWD) and columnaris disease (CD) in two unrelated rainbow trout nucleus breeding populations: the USDA, ARS, National Center for Cool and Cold Water Aquaculture odd-year line (ARS-Fp-R), which has been subjected to five generations of selection for improved resistance to BCWD, and the Troutlodge, Inc., May-spawning odd-year line (TLUM), which has been selected for improved growth performance but not for disease resistance. A total of 46,805 and 27,821 pedigree records were available from both populations, respectively. Between 44 and 138 families per generation and population were evaluated under controlled BCWD and CD challenges, providing 32,311 and 17,861 phenotypic records for BCWD resistance, and 13,603 and 9,413 for CD resistance, in the ARS-Fp-R and TLUM populations, respectively. A two-trait animal threshold model assuming an underlying normal distribution for the binary survival phenotypes was used to estimate (co)variance components separately for each population. Resistance to BCWD (h2 = 0.27 ± 0.04 and 0.43 ± 0.08) and CD (h2 = 0.23 ± 0.07 and 0.34 ± 0.09) was moderately heritable in the ARS-Fp-R and TLUM populations, respectively. The genetic correlation between the resistance to BCWD and CD was favorably positive in the ARS-Fp-R (0.40 ± 0.17) and TLUM (0.39 ± 0.18) populations. These findings suggest that both disease resistance traits can be improved simultaneously even if genetic selection pressure is applied to only one of the two traits.

Retrospective Evaluation of Marker-Assisted Selection for Resistance to Bacterial Cold Water Disease in Three Generations of a Commercial Rainbow Trout Breeding Population.

Bacterial cold water disease (BCWD), caused by Flavobacterium psychrophilum, is an endemic and problematic disease in rainbow trout (Oncorhynchus mykiss) aquaculture. Previously, we have identified SNPs (single nucleotide polymorphisms) associated with BCWD resistance in rainbow trout. The objectives of this study were (1) to validate the SNPs associated with BCWD resistance in a commercial breeding population; and (2) to evaluate retrospectively the accuracy of MAS (marker-assisted selection) for BCWD resistance in this commercial breeding program. Three consecutive generations of the Troutlodge May breeding population were evaluated for BCWD resistance. Based on our previous studies, a panel of 96 SNPs was selected and used to genotype the parents and ten offspring from each of the 138 full-sib families of the 2015 generation, and 37 SNPs associated with BCWD resistance were validated. Thirty-six of the validated SNPs were clustered on chromosomes Omy3, Omy8 and Omy25. Thus, at least three QTL (quantitative trait loci) for BCWD resistance were validated in the 2015 generation. Three SNPs from each QTL region were used for haplotype association analysis. Three haplotypes, Omy3TGG, Omy8GCG and Omy25CGG, were found to be associated with BCWD resistance in the 2015 generation. Retrospective analyses were then performed to evaluate the accuracy of MAS for BCWD resistance using these three favorable haplotypes. The accuracy of MAS was estimated with the Pearson correlation coefficient between the total number of favorable haplotypes in the two parents and the family BCWD survival rates. The Omy8 and Omy25 haplotypes were positively correlated with the family BCWD survival rates across all three generations. The accuracies of MAS using these two haplotypes together were consistently around 0.5, which was equal or greater than the accuracy of the conventional family-based selection in the same generation. In conclusion, we have demonstrated that MAS for BCWD resistance is feasible in this commercial rainbow trout breeding population.

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.

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 (r2  ≥ 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.

Similar Genetic Architecture with Shared and Unique Quantitative Trait Loci for Bacterial Cold Water Disease Resistance in Two Rainbow Trout Breeding Populations.

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect quantitative trait loci (QTL) for BCWD resistance in rainbow trout (Oncorhynchus mykiss). However, the recent availability of a 57 K SNP array and a reference genome assembly have enabled us to conduct genome-wide association studies (GWAS) that overcome several experimental limitations from our previous work. In the current study, we conducted GWAS for BCWD resistance in two rainbow trout breeding populations using two genotyping platforms, the 57 K Affymetrix SNP array and restriction-associated DNA (RAD) sequencing. Overall, we identified 14 moderate-large effect QTL that explained up to 60.8% of the genetic variance in one of the two populations and 27.7% in the other. Four of these QTL were found in both populations explaining a substantial proportion of the variance, although major differences were also detected between the two populations. Our results confirm that BCWD resistance is controlled by the oligogenic inheritance of few moderate-large effect loci and a large-unknown number of loci each having a small effect on BCWD resistance. We detected differences in QTL number and genome location between two GWAS models (weighted single-step GBLUP and Bayes B), which highlights the utility of using different models to uncover QTL. The RAD-SNPs detected a greater number of QTL than the 57 K SNP array in one population, suggesting that the RAD-SNPs may uncover polymorphisms that are more unique and informative for the specific population in which they were discovered.

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.

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]. 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. 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.

Genome-Wide Association Study for Identifying Loci that Affect Fillet Yield, Carcass, and Body Weight Traits in Rainbow Trout (Oncorhynchus mykiss).

Fillet yield (FY, %) is an economically-important trait in rainbow trout aquaculture that affects production efficiency. Despite that, FY has received little attention in breeding programs because it is difficult to measure on a large number of fish and cannot be directly measured on breeding candidates. The recent development of a high-density SNP array for rainbow trout has provided the needed tool for studying the underlying genetic architecture of this trait. A genome-wide association study (GWAS) was conducted for FY, body weight at 10 (BW10) and 13 (BW13) months post-hatching, head-off carcass weight (CAR), and fillet weight (FW) in a pedigreed rainbow trout population selectively bred for improved growth performance. The GWAS analysis was performed using the weighted single-step GBLUP method (wssGWAS). Phenotypic records of 1447 fish (1.5 kg at harvest) from 299 full-sib families in three successive generations, of which 875 fish from 196 full-sib families were genotyped, were used in the GWAS analysis. A total of 38,107 polymorphic SNPs were analyzed in a univariate model with hatch year and harvest group as fixed effects, harvest weight as a continuous covariate, and animal and common environment as random effects. A new linkage map was developed to create windows of 20 adjacent SNPs for use in the GWAS. The two windows with largest effect for FY and FW were located on chromosome Omy9 and explained only 1.0-1.5% of genetic variance, thus suggesting a polygenic architecture affected by multiple loci with small effects in this population. One window on Omy5 explained 1.4 and 1.0% of the genetic variance for BW10 and BW13, respectively. Three windows located on Omy27, Omy17, and Omy9 (same window detected for FY) explained 1.7, 1.7, and 1.0%, respectively, of genetic variance for CAR. Among the detected 100 SNPs, 55% were located directly in genes (intron and exons). Nucleotide sequences of intragenic SNPs were blasted to the Mus musculus genome to create a putative gene network. The network suggests that differences in the ability to maintain a proliferative and renewable population of myogenic precursor cells may affect variation in growth and fillet yield in rainbow trout.

Evaluation of Genome-Enabled Selection for Bacterial Cold Water Disease Resistance Using Progeny Performance Data in Rainbow Trout: Insights on Genotyping Methods and Genomic Prediction Models.

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.

Identification of single nucleotide polymorphism markers associated with bacterial cold water disease resistance and spleen size in rainbow trout.

Bacterial cold water disease (BCWD) is one of the frequent causes of elevated mortality in salmonid aquaculture. Previously, we identified and validated microsatellites on chromosome Omy19 associated with QTL (quantitative trait loci) for BCWD resistance and spleen size in rainbow trout. Recently, SNPs (single nucleotide polymorphism) have become the markers of choice for genetic analyses in rainbow trout as they are highly abundant, cost-effective and are amenable for high throughput genotyping. The objective of this study was to identify SNP markers associated with BCWD resistance and spleen size using both genome-wide association studies (GWAS) and linkage-based QTL mapping approaches. A total of 298 offspring from the two half-sib families used in our previous study to validate the significant BCWD QTL on chromosome Omy19 were genotyped with RAD-seq (restriction-site-associated DNA sequencing), and 7,849 informative SNPs were identified. Based on GWAS, 18 SNPs associated with BCWD resistance and 20 SNPs associated with spleen size were identified. Linkage-based QTL mapping revealed three significant QTL for BCWD resistance. In addition to the previously validated dam-derived QTL on chromosome Omy19, two significant BCWD QTL derived from the sires were identified on chromosomes Omy8 and Omy25, respectively. A sire-derived significant QTL for spleen size on chromosome Omy2 was detected. The SNP markers reported in this study will facilitate fine mapping to identify positional candidate genes for BCWD resistance in rainbow trout.

Detection and Validation of QTL Affecting Bacterial Cold Water Disease Resistance in Rainbow Trout Using Restriction-Site Associated DNA Sequencing.

Bacterial cold water disease (BCWD) causes significant economic loss in salmonid aquaculture. Using microsatellite markers in a genome scan, we previously detected significant and suggestive QTL affecting phenotypic variation in survival following challenge with Flavobacterium psychrophilum, the causative agent of BCWD in rainbow trout. In this study, we performed selective genotyping of SNPs from restriction-site associated DNA (RAD) sequence data from two pedigreed families (2009070 and 2009196) to validate the major QTL from the previous work and to detect new QTL. The use of RAD SNPs in the genome scans increased the number of mapped markers from ~300 to ~5,000 per family. The significant QTL detected in the microsatellites scan on chromosome Omy8 in family 2009070 was validated explaining up to 58% of the phenotypic variance in that family, and in addition, a second QTL was also detected on Omy8. Two novel QTL on Omy11 and 14 were also detected, and the previously suggestive QTL on Omy1, 7 and 25 were also validated in family 2009070. In family 2009196, the microsatellite significant QTL on Omy6 and 12 were validated and a new QTL on Omy8 was detected, but none of the previously detected suggestive QTL were validated. The two Omy8 QTL from family 2009070 and the Omy12 QTL from family 2009196 were found to be co-localized with handling and confinement stress response QTL that our group has previously identified in a separate pedigreed family. With the currently available data we cannot determine if the co-localized QTL are the result of genes with pleiotropic effects or a mere physical proximity on the same chromosome segment. The genetic markers linked to BCWD resistance QTL were used to query the scaffolds of the rainbow trout reference genome assembly and the QTL-positive scaffold sequences were found to include 100 positional candidate genes. Several of the candidate genes located on or near the two Omy8 QTL detected in family 2009070 suggest potential linkages between stress response and the regulation of immune response in rainbow trout.

Identification of single-nucleotide polymorphism markers associated with cortisol response to crowding in rainbow trout.

Understanding stress responses is essential for improving animal welfare and increasing agriculture production efficiency. Previously, we reported microsatellite markers associated with quantitative trait loci (QTL) affecting plasma cortisol response to crowding in rainbow trout. In this study, our main objectives were to identify single-nucleotide polymorphism (SNP) markers associated with cortisol response to crowding in rainbow trout using both GWAS (genome-wide association studies) and QTL mapping methods and to employ rapidly expanding genomic resources for rainbow trout toward the identification of candidate genes affecting this trait. A three-generation F2 mapping family (2008052) was genotyped using RAD-seq (restriction-site-associated DNA sequencing) to identify 4874 informative SNPs. GWAS identified 26 SNPs associated with cortisol response to crowding whereas QTL mapping revealed two significant QTL on chromosomes Omy8 and Omy12, respectively. Positional candidate genes were identified using marker sequences to search the draft genome assembly of rainbow trout. One of the genes in the QTL interval on Omy12 is a putative serine/threonine protein kinase gene that was differentially expressed in the liver in response to handling and confinement stress in our previous study. A homologue of this gene was differentially expressed in zebrafish embryos exposed to diclofenac, a nonsteroidal anti-inflammatory drug (NSAID) and an environmental toxicant. NSAIDs have been shown to affect the cortisol response in rainbow trout; therefore, this gene is a good candidate based on its physical position and expression. However, the reference genome resources currently available for rainbow trout require continued improvement as demonstrated by the unmapped SNPs and the putative assembly errors detected in this study.

A resource of single-nucleotide polymorphisms for rainbow trout generated by restriction-site associated DNA sequencing of doubled haploids.

Salmonid genomes are considered to be in a pseudo-tetraploid state as a result of a genome duplication event that occurred between 25 and 100 Ma. This situation complicates single-nucleotide polymorphism (SNP) discovery in rainbow trout as many putative SNPs are actually paralogous sequence variants (PSVs) and not simple allelic variants. To differentiate PSVs from simple allelic variants, we used 19 homozygous doubled haploid (DH) lines that represent a wide geographical range of rainbow trout populations. In the first phase of the study, we analysed SbfI restriction-site associated DNA (RAD) sequence data from all the 19 lines and selected 11 lines for an extended SNP discovery. In the second phase, we conducted the extended SNP discovery using PstI RAD sequence data from the selected 11 lines. The complete data set is composed of 145,168 high-quality putative SNPs that were genotyped in at least nine of the 11 lines, of which 71,446 (49%) had minor allele frequencies (MAF) of at least 18% (i.e. at least two of the 11 lines). Approximately 14% of the RAD SNPs in this data set are from expressed or coding rainbow trout sequences. Our comparison of the current data set with previous SNP discovery data sets revealed that 99% of our SNPs are novel. In the support files for this resource, we provide annotation to the positions of the SNPs in the working draft of the rainbow trout reference genome, provide the genotypes of each sample in the discovery panel and identify SNPs that are likely to be in coding sequences.

Detection of QTL in rainbow trout affecting survival when challenged with Flavobacterium psychrophilum.

Bacterial cold water disease (BCWD) causes significant economic loss in salmonid aquaculture. We previously detected genetic variation in survival following challenge with Flavobacterium psychrophilum (Fp), the causative agent of BCWD in rainbow trout (Oncorhynchus mykiss). A family-based selection program to improve resistance was initiated in 2005 at the USDA National Center for Cool and Cold Water Aquaculture. Select crosses were made in 2007 and 2009 to evaluate family-based disease survival using Fp injection challenges. From each putative F2/BC1 family generated in 2009, 200-260 fish were challenged in 4-7 replicates per family. Whole genome QTL scans of three F2/BC1 families were conducted with about 270 informative microsatellite loci per family spaced at an average interval size of 6 cM throughout the rainbow trout genome. Markers on chromosomes containing QTL were further evaluated in three additional F2/BC1 families. The additional F2/BC1 families were sire or dam half-sibs (HS) of the initially genome scanned families. Overall, we identified nine major QTL on seven chromosomes that were significant or highly significant with moderate to large effects of at least 13 % of the total phenotypic variance. The largest effect QTL for BCWD resistance explaining up to 40 % of the phenotypic variance was detected on chromosome OMY8 in family 2009070 and in the combined dam HS family 2009069-070. The nine major QTL identified in this study are candidates for fine mapping to identify new markers that are tightly linked to disease resistance loci for using in marker assisted selection strategies.

Assessment of genetic correlation between bacterial cold water disease resistance and spleen index in a domesticated population of rainbow trout: identification of QTL on chromosome Omy19.

Selective breeding of animals for increased disease resistance is an effective strategy to reduce mortality in aquaculture. However, implementation of selective breeding programs is limited by an incomplete understanding of host resistance traits. We previously reported results of a rainbow trout selection program that demonstrated increased survival following challenge with Flavobacterium psychrophilum, the causative agent of bacterial cold water disease (BCWD). Mechanistic study of disease resistance identified a positive phenotypic correlation between post-challenge survival and spleen somatic-index (SI). Herein, we investigated the hypothesis of a genetic correlation between the two traits influenced by colocalizing QTL. We evaluated the inheritance and calculated the genetic correlation in five year-classes of odd- and even-year breeding lines. A total of 322 pedigreed families (n = 25,369 fish) were measured for disease resistance, and 251 families (n = 5,645 fish) were evaluated for SI. Spleen index was moderately heritable in both even-year (h(2)  = 0.56±0.18) and odd-year (h(2)  = 0.60±0.15) lines. A significant genetic correlation between SI and BCWD resistance was observed in the even-year line (rg  = 0.45±0.20, P = 0.03) but not in the odd-year line (rg  = 0.16±0.12, P = 0.19). Complex segregation analyses of the even-year line provided evidence of genes with major effect on SI, and a genome scan of a single family, 2008132, detected three significant QTL on chromosomes Omy19, 16 and 5, in addition to ten suggestive QTL. A separate chromosome scan for disease resistance in family 2008132 identified a significant BCWD QTL on Omy19 that was associated with time to death and percent survival. In family 2008132, Omy19 microsatellite alleles that associated with higher disease resistance also associated with increased spleen size raising the hypothesis that closely linked QTL contribute to the correlation between these traits. To our knowledge, this is the first estimation of spleen size heritability and evidence for genetic linkage with specific disease resistance in a teleost fish.

Quantitative trait loci affecting response to crowding stress in an F(2) generation of rainbow trout produced through phenotypic selection.

Selective breeding programs for salmonids typically aim to improve traits associated with growth and disease resistance. It has been established that stressors common to production environments can adversely affect these and other traits which are important to producers and consumers. Previously, we employed phenotypic selection to create families that exhibit high or low plasma cortisol concentrations in response to crowding stress. Subsequent crosses of high × low phenotypes founded a multigenerational breeding scheme with the aim of dissecting the genetic basis for variation underlying stress response through the identification of quantitative trait loci (QTL). Multiple methods of QTL analyses differing in their assumptions of homozygosity of the causal alleles in the grandparental generation yielded similar results in the F1 generation, and the analysis of two stress response phenotype measurement indexes were highly correlated. In the current study, we conducted a genome scan with microsatellites to detect QTL in the F2 generation of two families created through phenotypic selection and having larger numbers of offspring than families screened in the previous generation. Seven suggestive and three significant QTL were detected, seven of which were not previously detected in the National Center for Cool and Cold Water Aquaculture germplasm, bringing the total number of chromosomes containing significant and suggestive stress response QTL to 4 and 15, respectively. One significant QTL which peaks at 7 cM on chromosome Omy12 spans 12 cM and explains 25 % of the phenotypic variance in family 2008052 particularly warrants further investigation. Five QTL with significant parent-of-origin effects were detected in family 2008052, including two QTL on Omy12. The 95 % confidence intervals for the remaining QTL we detected were broad, requiring validation and fine mapping with other genotyping approaches and mapping strategies. These results will facilitate identification of potential casual alleles that can be employed in strategies aimed at better understanding the genetic and physiological basis of stress responses to crowding in rainbow trout aquaculture production.

QTL affecting stress response to crowding in a rainbow trout broodstock population.

BACKGROUND: Genomic analyses have the potential to impact selective breeding programs by identifying markers that serve as proxies for traits which are expensive or difficult to measure. Also, identifying genes affecting traits of interest enhances our understanding of their underlying biochemical pathways. To this end we conducted genome scans of seven rainbow trout families from a single broodstock population to identify quantitative trait loci (QTL) having an effect on stress response to crowding as measured by plasma cortisol concentration. Our goal was to estimate the number of major genes having large effects on this trait in our broodstock population through the identification of QTL. RESULTS: A genome scan including 380 microsatellite markers representing 29 chromosomes resulted in the de novo construction of genetic maps which were in good agreement with the NCCCWA genetic map. Unique sets of QTL were detected for two traits which were defined after observing a low correlation between repeated measurements of plasma cortisol concentration in response to stress. A highly significant QTL was detected in three independent analyses on Omy16, many additional suggestive and significant QTL were also identified. With linkage-based methods of QTL analysis such as half-sib regression interval mapping and a variance component method, we determined that the significant and suggestive QTL explain about 40-43% and 13-27% of the phenotypic trait variation, respectively. CONCLUSIONS: The cortisol response to crowding stress is a complex trait controlled in a sub-sample of our broodstock population by multiple QTL on at least 8 chromosomes. These QTL are largely different from others previously identified for a similar trait, documenting that population specific genetic variants independently affect cortisol response in ways that may result in different impacts on growth. Also, mapping QTL for multiple traits associated with stress response detected trait specific QTL which indicate the significance of the first plasma cortisol measurement in defining the trait. Fine mapping these QTL can lead towards the identification of genes affecting stress response and may influence approaches to selection for this economically important stress response trait.