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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.

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. Electronic supplementary material The online version of this article (10.1186/s12711-019-0484-4) contains supplementary material, which is available to authorized users.

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.

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.

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. Previously, we reported high genomic prediction accuracy of 0.72 for BCWD resistance in rainbow trout using the 57 K Axiom SNP array. Due to the high cost of phenotyping and genotyping in rainbow trout breeding programs, it is paramount to know if acceptable genomic prediction accuracy can be obtained in the subsequent generation without retraining the prediction model. In the current study, we found that the accuracy of genomic prediction without model retraining in the subsequent generation was reduced from 0.65 and 0.61 to 0.56 and 0.53 using a lower density array of 10 K SNPs and a panel of 49 QTL-linked SNPs, respectively. Although markedly lower than the genomic prediction with model retraining, the prediction accuracy without retraining was better than the pedigree-based model (PBLUP) with retraining (0.48) and substantially higher than the PBLUP model accuracy without retraining (0.22). We conclude that genomic selection provides better prediction accuracy than the traditional PBLUP model even when ‘skipping’ one generation of model retraining. The weighted single-step GBLUP (wssGBLUP) and single-step Bayesian multiple regression BayesB (ssBMR-BayesB) had higher genomic prediction accuracy than single-step GBLUP (ssGBLUP), which is consistent with the oligogenic inheritance of BCWD resistance in this population. Imputation from the 10 K array genotypes back to the 57 K array genotypes did not improve the accuracy of genomic prediction, likely due to the high linkage disequilibrium in rainbow trout aquaculture breeding populations and the oligogenic architecture of BCWD resistance.

A pedigreed rainbow trout population (~ 100 families per generation) was selected for five generations to improve growth performance to the standard ~ 500-gram US market weight and beyond (> 1 kg). Body weights (BW) were recorded each generation at 5, 8, 10, and 13 months post-hatch. Selection was applied to a two-trait index of estimated breeding values for 10-month body weight (i.e., approximate market weight) and thermal growth coefficient between 10 and 13 months, and both traits were given equal weighting in the index. Objectives of this study were to estimate direct selection responses for BW traits and thermal growth coefficient, and correlated response for condition factor traits. Heritability estimates were 0.28 ± 0.08 to 0.43 ± 0.14 for BW between 5 and 13 months post-hatch, 0.12 ± 0.03 for thermal growth coefficient, and 0.40 ± 0.04 and 0.36 ± 0.04 for condition factor at 10 and 13 months post-hatch, respectively. Genetic correlations among the four BW measures were highest between adjacent BW measures (0.54 ± 0.19 to 0.82 ± 0.05) and decreased as time between measures increased. Genetic correlation between thermal growth coefficient and 10-month BW was low (0.18 ± 0.13), and genetic correlations between condition factor and BW measured at the same age were moderate (0.39 ± 0.09 to 0.45 ± 0.08). Compared to randomly-mated control lines, selection response in the selected line averaged 10.6% (5-month BW), 9.8% (8-month BW), 12.7% (10-month BW), 11.9% (13-month BW), 2.1% (thermal growth coefficient), 3.4% (10-month condition factor), and 3.3% (13-month condition factor) per generation. The rate of inbreeding averaged 0.86% per generation in the selection line, with a cumulative inbreeding estimate of 4.5% in the last generation. The low heritability of thermal growth coefficient, and low genetic correlation with 10-month BW, resulted in only modest selection response for thermal growth coefficient. Larger heritabilities of BW measured at fixed ages, and large genetic correlations between serial BW measures, suggest that direct selection on BW will be more favorable than selection on TGC. This study demonstrates the large and sustained potential for genetic improvement of growth performance in domesticated rainbow trout with only modest accumulation of inbreeding, and provides empirical selection response estimates that have direct inference to commercial breeding programs aiming to select for growth to larger market BW. Statement of relevance Quantitative genetics data from this relatively long-term and large-scale selective breeding program have direct inference to commercial breeding programs selecting for improved growth, but for which maintenance of control lines is not practical.

International audience; AbstractBackgroundInfectious 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.ResultsTen 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).ConclusionsOur 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.

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 (h(2) = 0.27 ± 0.04 and 0.43 ± 0.08) and CD (h(2) = 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.

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.

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect QTL for BCWD resistance in rainbow trout (Oncorhynchus mykiss). However, the recent availability of a 57K SNP array and a genome physical map 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 57K 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 57K 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.

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.

Advancing the production efficiency and profitability of aquaculture is dependent upon the ability to utilize a diverse array of genetic resources. The ultimate goals of aquaculture genomics, genetics and breeding research are to enhance aquaculture production efficiency, sustainability, product quality, and profitability in support of the commercial sector and for the benefit of consumers. In order to achieve these goals, it is important to understand the genomic structure and organization of aquaculture species, and their genomic and phenomic variations, as well as the genetic basis of traits and their interrelationships. In addition, it is also important to understand the mechanisms of regulation and evolutionary conservation at the levels of genome, transcriptome, proteome, epigenome, and systems biology. With genomic information and information between the genomes and phenomes, technologies for marker/causal mutation-assisted selection, genome selection, and genome editing can be developed for applications in aquaculture. A set of genomic tools and resources must be made available including reference genome sequences and their annotations (including coding and non-coding regulatory elements), genome-wide polymorphic markers, efficient genotyping platforms, high-density and high-resolution linkage maps, and transcriptome resources including non-coding transcripts. Genomic and genetic control of important performance and production traits, such as disease resistance, feed conversion efficiency, growth rate, processing yield, behaviour, reproductive characteristics, and tolerance to environmental stressors like low dissolved oxygen, high or low water temperature and salinity, must be understood. QTL need to be identified, validated across strains, lines and populations, and their mechanisms of control understood. Causal gene(s) need to be identified. Genetic and epigenetic regulation of important aquaculture traits need to be determined, and technologies for marker-assisted selection, causal gene/mutation-assisted selection, genome selection, and genome editing using CRISPR and other technologies must be developed, demonstrated with applicability, and application to aquaculture industries.Major progress has been made in aquaculture genomics for dozens of fish and shellfish species including the development of genetic linkage maps, physical maps, microarrays, single nucleotide polymorphism (SNP) arrays, transcriptome databases and various stages of genome reference sequences. This paper provides a general review of the current status, challenges and future research needs of aquaculture genomics, genetics, and breeding, with a focus on major aquaculture species in the United States: catfish, rainbow trout, Atlantic salmon, tilapia, striped bass, oysters, and shrimp. While the overall research priorities and the practical goals are similar across various aquaculture species, the current status in each species should dictate the next priority areas within the species. This paper is an output of the USDA Workshop for Aquaculture Genomics, Genetics, and Breeding held in late March 2016 in Auburn, Alabama, with participants from all parts of the United States.

Bacterial cold water disease (BCWD) is caused by infection with Flavobacterium psychrophilum , and outbreaks cause significant economic losses in salmonid aquaculture. Previously, we identified a major QTL for BCWD resistance on rainbow trout chromosome Omy19 as well as a QTL for spleen size (SPLW = spleen weight and SPLI = spleen index) which in naive fish is a surrogate indicator of BCWD resistance. The objective of this study was to validate the BCWD resistance and spleen size QTL in a subsequent generation and investigate whether the correlation between BCWD resistance and spleen size loci on Omy19 was due to close linkage or pleiotropy. We designed four full-sib matings whose offspring were evaluated for BCWD resistance, body weight, SPLW and SPLI. A total of 800 offspring were genotyped with seven microsatellite markers from Omy19. Our analyses confirmed the presence of QTL for BCWD and spleen size on Omy19. Our findings also suggest that BCWD resistance and spleen size are not influenced by a single pleiotropic QTL on Omy19 as the QTL were separately inherited in the families studied. These data increase our understanding of the genetic basis of rainbow trout BCWD resistance.

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.

Arctic charr, Salvelinus alpinus, were obtained as eggs from two North American sources, an eastern (Fraser River, Canada) and a western (Bristol Bay, Alaska, USA) stock. Fish were pit tagged (eastern , western ) and stocked communally into three replicated 7-m3 tanks at a density of 7.6 ± 1.2 kg/m3. Each tank was supplied with 2 ppt salinity water from a recirculating biological filtration system. Fish were fed a commercial diet (48%P, 20%F) from automatic feeders. Fish were harvested approximately 24 mo after hatching at a final tank density of 56.2 ± 1.3 kg/m3. Mean daily water temperature was 10.4 C with a range of 5.9–12.6 C and mean dissolved oxygen was 12.6 mg/L with a range of 9.7 (91% of saturation) to 17.8 mg/L (149% of saturation). Individual fish were evaluated for total, carcass, and fillet weight, sex, stage of sexual maturity, fillet fat, fillet color, and gonad weight. The western stock fish grew faster and were significantly larger () (P

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.

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 1,447 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 to 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.

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.

Microarray analysis was conducted using liver samples from two families of rainbow trout that differed in their growth responses when compared between individuals fed a fishmeal or plant protein-based diet. Differential expression relating to dietary utilization between the two families found significant changes in expression of 33 expressed sequence tags (ESTs). Eight of the differentially expressed ESTs had identified mammalian homologs that had been previously researched with identified cellular interactions and functions. Utilizing pathway analysis software to analyze sequences annotated with known mammalian genes, we were able to map gene pathways and process interactions. From this information, we were able to infer that the metabolic changes associated with utilization of plant protein versus fishmeal were associated with differential regulation of genes related to cell oxidative stress, proliferation, growth and survival. Furthermore, we inferred from the changes we observed in immune response gene expression that ingestion of this plant-based diet upregulated the expression of genes involved in immunoregulatory processes.

Bacterial cold water disease (BCWD) causes significant economic loss in salmonid aquaculture. We previously detected genetic variation for BCWD resistance in our rainbow trout population, and a family-based selection program to improve resistance was initiated at the National Center for Cool and Cold Water Aquaculture (NCCCWA). This study investigated evidence of major trait loci affecting BCWD resistance using only phenotypic data (without using genetic markers) and Bayesian methods of segregation analysis (BMSA). A total of 10,603 juvenile fish from 101 full-sib families corresponding to 3 generations (2005, 2007, and 2009 hatch years) of the NCCCWA population were challenged by intraperitoneal injection with Flavobacterium psychrophilum, the bacterium that causes BCWD. The results from single- and multiple-QTL models of BMSA suggest that 6 to 10 QTL explaining 83 to 89% of phenotypic variance with either codominant or dominant disease-resistant alleles plus polygenic effects may underlie the genetic architecture of BCWD resistance. This study also highlights the importance of polygenic background effects in the genetic variation of BCWD resistance. The polygenic heritability on the observed scale of survival status (h 2 observed = 0.45) is slightly larger than that previously reported for rainbow trout BCWD resistance. These findings provide the basis for designing informative crosses for QTL mapping and carrying out genome scans for QTL affecting BCWD resistance in rainbow trout.

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

As a first step toward the genetic mapping of QTL affecting stress response variation in rainbow trout, we performed complex segregation analyses (CSA) fitting mixed inheritance models of plasma cortisol by using Bayesian methods in large full-sib families of rainbow trout. To date, no studies have been conducted to determine the mode of inheritance of stress response as measured by plasma cortisol response when using a crowding stress paradigm and CSA in rainbow trout. The main objective of this study was to determine the mode of inheritance of plasma cortisol after a crowding stress. The results from fitting mixed inheritance models with Bayesian CSA suggest that 1 or more major genes with dominant cortisol-decreasing alleles and small additive genetic effects of a large number of independent genes likely underlie the genetic variation of plasma cortisol in the rainbow trout families evaluated. Plasma cortisol is genetically determined, with heritabilities of 0.22 to 0.39. Furthermore, a major gene with an additive effect of -42 ng/mL (approximately 1.0 genetic SD) is segregating in this rainbow trout broodstock population. These findings provide a basis for designing and executing genome-wide linkage studies to identify QTL for stress response in rainbow trout broodstock and markers for selective breeding.

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.

The U.S. Department of Agriculture's National Center for Cool and Cold Water Aquaculture is conducting a breeding program for rainbow trout Oncorhynchus mykiss to develop improved germplasm for the U.S. aquaculture industry. Current selection efforts are focused on growth and disease resistance, but stress response is also a concern. Using plasma cortisol concentrations after a 3-h crowding stress as a measure of stress responsiveness, we have previously shown family variation in cortisol responsiveness and a positive phenotypic correlation between poststressor cortisol level and growth performance within our broodstock. Selection for improved growth performance may therefore increase cortisol responsiveness to stress. In the present studies, narrow-sense heritability (h 2) for cortisol responsiveness was estimated to be moderately high by means of midparent–offspring regression and nested family design analyses (h 2 ≥ 0.40 and 0.56, respectively). In addition, fish from the same families were us...

Genes within the major histocompatibility complex (MHC) are important for both innate and adaptive immune responses in mammals; however, much less is known regarding their contribution in teleost fishes. We examined the involvement of four major histocompatibility (MH) genomic regions in rainbow trout in resistance to the causative agent of bacterial coldwater disease (BCWD), Flavobacterium psychrophilum. Fish from the 2005 NCCCWA brood-year (71 full-sib families) were challenged with F. psychrophilum strain CSF 259-93. The overall mortality rate was 70%, with large variation in mortality between families. Disease resistance was quantified as post-challenge days to death. Phenotypic variation and additive genetic variation were estimated using mixed models of survival analysis. To examine association, eight microsatellite markers were isolated from MH gene-containing BAC clones and mapped onto the rainbow trout genetic linkage map. The parents and grandparents of the 2005 brood-year families were genotyped with these eight markers and another two markers tightly linked to the MH-IB region to assess the extent of linkage disequilibrium (LD) of MH genomic regions MH-IA, MH-IB, TAP1, and MH-II with survival post-challenge. MH-IB and MH-II markers were linked to BCWD survivability when data were analyzed by family. Tests for disease association at the population level substantiated the involvement of MH-IB, but not MH-II, with disease resistance. The impact of selective breeding for disease resistance on MH sequence variation is discussed in the context of aquaculture production.

Examination of microsatellite variation at several polymorphic loci is a widely accepted method for determining parentage and examining genetic diversity within rainbow trout ( Oncorhynchus mykiss ) breeding programs. Genotyping costs are considerable; therefore, we developed a single-step method of co-amplifying twelve microsatellites in two hexaplex reactions to reduce costs and improve efficiency. The protocol is explicitly described to ensure reproducible results. We applied the protocol to samples analyzed at the National Center for Cool and Coldwater Aquaculture (NCCCWA) with previously reported marker sets for a comparison of results. Each marker within the multiplex system was evaluated for duplication, null alleles, physical linkage, and probability of genotyping errors. Data from four of the 12 markers were excluded from parental analysis based on these criteria. Parental assignments were compared to those of a previous study that used five independently amplified microsatellites. Percentages of progeny assigned to parents were higher using the subset of eight markers from the multiplex system than with five markers used in the previous study (98% vs. 92%). Through multiplexing, additional markers were used to improve parental allocation while also improving efficiency by reducing the number of required PCR reactions and genotyping runs. We evaluated our methods further through estimation of F -statistics, pairwise genetic distances, and cluster analysis among brood-years at the NCCCWA facility. These measures were compared to estimates from nine independently amplified microsatellites used in a previous study. The F st results calculated between brood-years show similar values of genetic differentiation using both marker sets. Estimates of individual pairwise genetic distances were used for constructing neighbor-joining trees. Both marker sets yielded trees that show similar subpopulation structuring and agreed with results from a model-based cluster analysis and available pedigree information. These approaches for detecting population substructure and admixture portions within individuals are particularly useful for new breeding programs where the founders' relatedness is unknown.

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.

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.

Striped bass (Morone saxatilis) is economically important in the US due to its value as an aquaculture species and in supporting commercial and recreational fisheries, especially those off the Atlantic coast and in the Gulf of Mexico. Modern strategies for managing fishery populations and aquaculture broodstocks employ the use of molecular genetic markers to identify individuals, assign parentage, and characterize population genetic structure and levels of inbreeding and migration. As part of a collaborative effort to utilize molecular genetic technologies in striped bass breeding programs we generated microsatellite markers for use in population genetic studies, broodstock selection and management strategies, and the construction of a genetic map. We developed 345 new microsatellite markers for striped bass, a subset (n=71) of which was characterized by genotyping samples from two striped bass broodstock populations to evaluate marker polymorphism, percent heterozygosity, Hardy–Weinberg equilibrium (HWE), linkage disequilibrium (LD) and utility for population genetic studies.

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.

Chantier qualité GA; 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.

A typical problem in mapping quantitative trait loci (QTLs) comes from missing QTL genotype. A routine method for parameter estimation involving missing data is the mixture model maximum likelihood method. We developed an alternative QTL mapping method that describes a mixture of several distributions by a single model with a heterogeneous residual variance. The two methods produce similar results, but the heterogeneous residual variance method is computationally much faster than the mixture model approach. In addition, the new method can automatically generate sampling variances of the estimated parameters. We derive the new method in the context of QTL mapping for binary traits in a F2 population. Using the heterogeneous residual variance model, we identified a QTL on chromosome IV that controls Marek's disease susceptibility in chickens. The QTL alone explains 7.2% of the total disease variation.

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.

Fast growth is an important and highly desired trait, which affects the profitability of food animal production, with feed costs accounting for the largest proportion of production costs. Traditional phenotype-based selection is typically used to select for growth traits; however, genetic improvement is slow over generations. Single nucleotide polymorphisms (SNPs) explain 90% of the genetic differences between individuals; therefore, they are most suitable for genetic evaluation and strategies that employ molecular genetics for selective breeding. SNPs found within or near a coding sequence are of particular interest because they are more likely to alter the biological function of a protein. We aimed to use SNPs to identify markers and genes associated with genetic variation in growth. RNA-Seq whole-transcriptome analysis of pooled cDNA samples from a population of rainbow trout selected for improved growth versus unselected genetic cohorts (10 fish from 1 full-sib family each) identified SNP markers associated with growth-rate. The allelic imbalances (the ratio between the allele frequencies of the fast growing sample and that of the slow growing sample) were considered at scores >5.0 as an amplification and

Samples of 4285 individuals from a hybridSolanum phureja Juz. et Buk. —S. stenotomum Juz. (Phu-Stn) and 105 individuals ofSolanum phureja (Phu) diploid potato populations were twice inoculated with potato virus Y strain “o” (PVY∘) using the air brush technique. After discarding seedlings with PVY visual symptoms both in the greenhouse and in the field, 1508 seedlings were judged to be resistant to PVY∘ (35.2%). Only 5.7% of the Phu seedlings were PVY∘ resistant compared to 35.2% of the Phu-Stn seedlings. At harvest, a mild selection pressure for yield and tuber appearance was applied and 602 Phu-Stn clones were chosen for further evaluation. Selected clones were re-evaluated for PVY∘ resistance in the greenhouse. Clones were mechanically inoculated twice with PVY∘. Clones susceptible to PVY∘ were determined by visual observations, ELISA (Enzyme-linked immunosorbent assay) tests, grafting of tobacco PVY∘ infected shoots on potato clones, and infectivity tests usingNicotiana tabacum as a PVY∘ plant indicator. In the process, 224 clones were found to be extreme resistant to infection by PVY∘, with an overall frequency for PVY∘ extreme resistance of 5.2%. In another experiment, the first year Phu-Stn PVY∘ resistant clones (554 clones) were mechanically inoculated twice with “common” strain of potato virus X (PVX). Similarly, we discarded clones susceptible to PVX by combining visual evaluation and ELISA with PVX re-inoculation of negative clones and an infectivity test, usingGomphrena globosa as a PVX plant indicator. After this process, seven extreme resistant and eight resistant clones to infection by PVX were found; the overall frequency of PVX extreme resistance was 1.3%. Five clones were extreme resistant to both PVY∘ and PVX.

Preliminary data on the genetics of glandular trichomes and the feasibility of incorporating A and B glandular trichomes and polyphenol oxidase (PPO) activity from Solanum berthaultii Hawkes (Ber) into an advanced S. phureja Juz. et Buk.-S. stenotomum Juz. (Phu-Stn) diploid potato population are presented. A random sample of four Phu-Stn clones was intercrossed with a sample of three Ber progenies (pollen bulk per progeny) segregating for high density of A and B glandular trichomes. Nine F1 families [(Phu-Stn) × Ber] were evaluated over two experiments in the greenhouse for A and B trichome density (5 mm2 of abaxial surface) and PPO activity 45 days after planting. A completely randomized design in an experimental hierarchical classification arrangement was used to quantify the genetic variability and to estimate broad-sense heritabilities (defined on an individual basis) for the attributes under study. To characterize the inheritance of these attributes further and to estimate narrow-sense heritabilities, fifteen backcross (BC) families were evaluated in a randomized complete-block design with three replications and analyzed by half-sib family analysis. Phenotypic and genotypic correlations between these attributes were also estimated. In the F1 families, broad-sense heritabilities were 0.59 and 0.41 for density of A and B trichomes, respectively. In the BC population, narrow-sense heritabilities were 0.15 and 0.08 for A trichome density and PPO activity, respectively; expression of B trichomes was almost absent in this generation. Genotype × environment interaction was significant for density of A trichomes and highly significant for density of B trichomes in F1 families. There was some level of positive association between density of A and B trichomes and PPO activity. Additive genetic variance of these attributes was very low in this study; therefore, selection schemes based on family selection and progeny testing would be an appropriate breeding strategy for improving these traits.

Glandular trichomes from some Solanum species have suppressed infestation by insects including green peach aphid, which is a main vector of potato virus Y (PVY) and potato leaf roll virus (PLRV), both of which contribute to a serious loss in potato production. Eight Solanum phureja Juz. et Buk.-S. stenotomum Juz. (Phu-Stn), three S. berthaultii Hawkes (Ber), nine F1 [(Phu-Stn) × Ber], fifteen backcross (BC) [(Phu-Stn) × F1], and seventeen reciprocal BC (BCR) [F1 × (Phu-Stn)] families were evaluated to determine the genetic variability and heritability of A and B glandular trichome density and polyphenol oxidase (PPO) activity. Experiments were carried out in completely randomized and randomized complete-block designs in the greenhouse. Genetic analysis was done using half-sib family and parent-offspring regression analysis. Phu-Stn showed a higher density of A trichomes than Ber and F1, while the BC and BCR had densities of A trichomes similar to Phu-Stn. B trichomes were not observed in Phu-Stn. Ber showed a high B trichome density, which was transmitted to the F1. In the BC, B trichomes were almost absent, but, in the BCR, the density of B trichomes was higher than that of BC. Ber and F1 had similar or higher PPO activity than Phu-Stn. PPO activity decreased in the BC, but, in the BCR, it was high and similar to Ber and F1. Broad-sense heritability estimates for A and B trichome density and PPO activity were from medium to high (0.48 to 0.77) in Phu-Stn, Ber, and F1. Narrow-sense heritability estimates for A and B trichome density and PPO activity were very low (0.04 to 0.24) in BC and BCR. In the BC families, additive genetic variance was very low for A and B trichome density and PPO activity. Half-sib family selection based on progeny testing and combined with BCs to Phu-Stn in subsequent generations would be a suggested breeding procedure to improve these traits. Phenotypic correlations between A and B trichome densities were 0.26 (F1) and 0.44 (BCR), between A trichome density and PPO activity 0.20 (F1) and 0.31 (BCR), and between B trichome density and PPO activity 0.04 (F1) and 0.27(BCR. Positive associations found between traits might facilitate simultaneous improvement for high levels of A and B trichome density and PPO activity.

Rainbow trout infected with Yersinia ruckeri, the causative agent of enteric redmouth disease (ERM), produce a pro-inflammatory and acute-phase response attributed in part to the innate recognition of bacterial-produced flagellin. Recently, variants of Y. ruckeri have been identified that lack flagella and associated motility. These strains are classified as biotype 2 (BT2) Y. ruckeri and these are considered an emerging problem in salmonid aquaculture. Little is known about the salmonid immune response to these variants. Herein, we report temporal and quantitative changes in rainbow trout immune response parameters following a primary challenge with BT2 Y. ruckeri strain YRNC10. Fish were injection-challenged with ten-fold dilutions of viable bacteria and sampled on days 1, 3, 5 and 7 post-challenge. TNFalpha1 and IL1-beta1 transcripts were increased by day 1 post-challenge, and on days 3, 5 and 7 maximal gene transcript up-regulation occurred at a threshold of approximately 64-256CFU per mg spleen tissue. Infection induced robust SAA gene up-regulation that was significantly correlated with increased gene expression of IL-1beta1 (r=0.81, P

The objective of this research was to determine optimum plot size and number of replications to evaluate yield of sweetpotato (Ipomoea batatas Lam.) clones. The optimum plot size was estimated using the methods of maximum curvature and comparison of variances. The adequate number of replications was determined using the Hatheway method. Using the maximum curvature method, the estimated optimum plot size was 10 basic units (b.u. = six plants or 1.2 m) for La Molina and San Ramon, and 5 b.u. for Tacna, Peru. Using the comparison of variances method, the optimum plot size was 15 b.u. for all locations tested. The adequate number of replications with a plot size of 15 b.u. was four. Sweetpotato has many desirable characteristics such as high yield, wide adaptability, multifunctional usage, and a wide range of nutritional components, yet requires low production inputs. These attributes make sweetpotato an attractive crop for tropical regions. However, field experiments carried out with sweetpotatoes often have large coefficients of variation (cv). This may be due in part to inherent crop variation or to inadequate field plot techniques. Sweetpotato researchers use field trials to determine the potential of cultivars and experimental lines. In a breeding program, this procedure is a routine in which the main objective is to identify promising genotypes to be evaluated in additional trials as clonal accessions. To increase efficiency, optimum plot size and an adequate number of replications must be used. Federer (1967) defined the experimental unit as the total amount of material to which a treatment in a particular replication is applied. The optimum plot size depends on the nature of the experimental material, experiment design, number of entries, number of replications, and available resources. The variability of the experimental material constitutes a main component of the experimental error that must be minimized using adequate experimental techniques. In general, experimental error is reduced by increasing plot size (Immer and Raleigh, 1933; McClelland, 1926; McKenzie et al., 1964). Conversely, others found that the experimental error was reduced significantly when the number of replications rather than plot size was increased (Rampton and Petersen, 1962; Thomas and Abou-El Fittouh, 1968). Li (1971) in Taiwan found that the optimum plot size for the winter sermon sweetpotato crop was 6 to 12 m long and three rows wide (18 to 36 m) in Changlma, and 8 to 12 m long and three rows wide (24 to 36 m) in Hsinchu. In the fall crop, the optimum plot size was 6 to 12 m long and two rows wide (12 to 24 m) in Yunlin, and 6 to 12 m long and two to three rows wide (12 to 36 m) in Tainan. Boudreaux and Jones (1978) used 12% as an arbitrary level of acceptability for the cv, and found that a one-row plot of 15 to 20 hills 30.5 cm apart in length (4.6 to 9 m) and with nine for publication 18 May 1990. Accepted for publication 28 Aug. 1991. efully acknowledge the technical assistance of Jorge A. Espinoza in ng this research. This project was entirely supported by the International enter. The cost of publishing this paper was defrayed in part by the of page charges. Under postal regulations, this paper therefore must y marked advertisement solely to indicate this fact.

Background The use of molecular genetic technologies for broodstock management and selective breeding of aquaculture species is becoming increasingly more common with the continued development of genome tools and reagents. Several laboratories have produced genetic maps for rainbow trout to aid in the identification of loci affecting phenotypes of interest. These maps have resulted in the identification of many quantitative/qualitative trait loci affecting phenotypic variation in traits associated with albinism, disease resistance, temperature tolerance, sex determination, embryonic development rate, spawning date, condition factor and growth. Unfortunately, the elucidation of the precise allelic variation and/or genes underlying phenotypic diversity has yet to be achieved in this species having low marker densities and lacking a whole genome reference sequence. Experimental designs which integrate segregation analyses with linkage disequilibrium (LD) approaches facilitate the discovery of genes affecting important traits. To date the extent of LD has been characterized for humans and several agriculturally important livestock species but not for rainbow trout. Results We observed that the level of LD between syntenic loci decayed rapidly at distances greater than 2 cM which is similar to observations of LD in other agriculturally important species including cattle, sheep, pigs and chickens. However, in some cases significant LD was also observed up to 50 cM. Our estimate of effective population size based on genome wide estimates of LD for the NCCCWA broodstock population was 145, indicating that this population will respond well to high selection intensity. However, the range of effective population size based on individual chromosomes was 75.51 - 203.35, possibly indicating that suites of genes on each chromosome are disproportionately under selection pressures. Conclusions Our results indicate that large numbers of markers, more than are currently available for this species, will be required to enable the use of genome-wide integrated mapping approaches aimed at identifying genes of interest in rainbow trout.