Fecal Microbiome Analysis Distinguishes Bacterial Taxa Biomarkers Associated with Red Fillet Color in Rainbow Trout.

The characteristic reddish-pink fillet color of rainbow trout is an important marketing trait. The gastrointestinal microbiome is vital for host health, immunity, and nutrient balance. Host genetics play a crucial role in determining the gut microbiome, and the host-microbiome interaction impacts the host's phenotypic expression. We hypothesized that fecal microbiota could be used to predict fillet color in rainbow trout. Fish were fed Astaxanthin-supplemented feed for six months, after which 16s rDNA sequencing was used to investigate the fecal microbiome composition in rainbow trout families with reddish-pink fillet coloration (red fillet group, average saturation index = 26.50 ± 2.86) compared to families with pale white fillet color (white fillet group, average saturation index = 21.21 ± 3.53). The linear discriminant analysis effect size (LEFse) tool was used to identify bacterial biomarkers associated with fillet color. The alpha diversity measure shows no difference in the red and white fillet groups. Beta diversity principal component analysis showed clustering of the samples along the white versus red fillet group. The red fillet group has enrichment (LDA score > 1.5) of taxa Leuconostoc lactis, Corynebacterium variabile, Jeotgalicoccus halotolerans, and Leucobacter chromiireducens. In contrast, the white fillet group has an enriched presence of mycoplasma, Lachnoclostridium, and Oceanobacillus indicireducens. The enriched bacterial taxa in the red fillet group have probiotic functions and can generate carotenoid pigments. Bacteria taxa enriched in the white fillet group are either commensal, parasitic, or capable of reducing indigo dye. The study identified specific bacterial biomarkers differentially abundant in fish families of divergent fillet color that could be used in genetic selection to improve feed carotenoid retention and reddish-pink fillet color. This work extends our understanding of carotenoid metabolism in rainbow trout through the interaction between gut microbiota and fillet color.

RNA-Seq analysis of the pyloric caecum, liver, and muscle reveals molecular mechanisms regulating fillet color in rainbow trout.

BACKGROUND: The characteristic pink-reddish color in the salmonids fillet is an important, appealing quality trait for consumers and producers. The color results from diet supplementation with carotenoids, which accounts for up to 20-30% of the feed cost. Pigment retention in the muscle is a highly variable phenotype. In this study, we aimed to understand the molecular basis for the variation in fillet color when rainbow trout (Oncorhynchus mykiss) fish families were fed an Astaxanthin-supplemented diet. We used RNA-Seq to study the transcriptome profile in the pyloric caecum, liver, and muscle from fish families with pink-reddish fillet coloration (red) versus those with lighter pale coloration (white). RESULTS: More DEGs were identified in the muscle (5,148) and liver (3,180) than in the pyloric caecum (272). Genes involved in lipid/carotenoid metabolism and transport, ribosomal activities, mitochondrial functions, and stress homeostasis were uniquely enriched in the muscle and liver. For instance, the two beta carotene genes (BCO1 and BCO2) were significantly under-represented in the muscle of the red fillet group favoring more carotenoid retention. Enriched genes in the pyloric caecum were involved in intestinal absorption and transport of carotenoids and lipids. In addition, the analysis revealed the modulation of several genes with immune functions in the pyloric caecum, liver, and muscle. CONCLUSION: The results from this study deepen our understanding of carotenoid dynamics in rainbow trout and can guide us on strategies to improve Astaxanthin retention in the rainbow trout fillet.

Genomic selection models substantially improve the accuracy of genetic merit predictions for fillet yield and body weight in rainbow trout using a multi-trait model and multi-generation progeny testing.

BACKGROUND: In aquaculture, the proportion of edible meat (FY = fillet yield) is of major economic importance, and breeding animals of superior genetic merit for this trait can improve efficiency and profitability. Achieving genetic gains for fillet yield is possible using a pedigree-based best linear unbiased prediction (PBLUP) model with direct and indirect selection. To investigate the feasibility of using genomic selection (GS) to improve FY and body weight (BW) in rainbow trout, the prediction accuracy of GS models was compared to that of PBLUP. In addition, a genome-wide association study (GWAS) was conducted to identify quantitative trait loci (QTL) for the traits. All analyses were performed using a two-trait model with FY and BW, and variance components, heritability, and genetic correlations were estimated without genomic information. The data used included 14,165 fish in the pedigree, of which 2742 and 12,890 had FY and BW phenotypic records, respectively, and 2484 had genotypes from the 57K single nucleotide polymorphism (SNP) array. RESULTS: The heritabilities were moderate, at 0.41 and 0.33 for FY and BW, respectively. Both traits were lowly but positively correlated (genetic correlation; r = 0.24), which suggests potential favourable correlated genetic gains. GS models increased prediction accuracy compared to PBLUP by up to 50% for FY and 44% for BW. Evaluations were found to be biased when validation was performed on future performances but not when it was performed on future genomic estimated breeding values. CONCLUSIONS: The low but positive genetic correlation between fillet yield and body weight indicates that some improvement in fillet yield may be achieved through indirect selection for body weight. Genomic information increases the prediction accuracy of breeding values and is an important tool to accelerate genetic progress for fillet yield and growth in the current rainbow trout population. No significant QTL were found for either trait, indicating that both traits are polygenic, and that marker-assisted selection will not be helpful to improve these traits in this population.

Weighted Single-Step GWAS Identifies Genes Influencing Fillet Color in Rainbow Trout.

The visual appearance of the fish fillet is a significant determinant of consumers' purchase decisions. Depending on the rainbow trout diet, a uniform bright white or reddish/pink fillet color is desirable. Factors affecting fillet color are complex, ranging from the ability of live fish to accumulate carotenoids in the muscle to preharvest environmental conditions, early postmortem muscle metabolism, and storage conditions. Identifying genetic markers of fillet color is a desirable goal but a challenging task for the aquaculture industry. This study used weighted, single-step GWAS to explore the genetic basis of fillet color variation in rainbow trout. We identified several SNP windows explaining up to 3.5%, 2.5%, and 1.6% of the additive genetic variance for fillet redness, yellowness, and whiteness, respectively. SNPs are located within genes implicated in carotenoid metabolism (ß,ß-carotene 15,15'-dioxygenase, retinol dehydrogenase) and myoglobin homeostasis (ATP synthase subunit ß, mitochondrial (ATP5F1B)). These genes are involved in processes that influence muscle pigmentation and postmortem flesh coloration. Other identified genes are involved in the maintenance of muscle structural integrity (kelch protein 41b (klh41b), collagen α-1(XXVIII) chain (COL28A1), and cathepsin K (CTSK)) and protection against lipid oxidation (peroxiredoxin, superoxide dismutase 2 (SOD2), sestrin-1, Ubiquitin carboxyl-terminal hydrolase-10 (USP10)). A-to-G single-nucleotide polymorphism in ß,ß-carotene 15,15'-dioxygenase, and USP10 result in isoleucine-to-valine and proline-to-leucine non-synonymous amino acid substitutions, respectively. Our observation confirms that fillet color is a complex trait regulated by many genes involved in carotenoid metabolism, myoglobin homeostasis, protection against lipid oxidation, and maintenance of muscle structural integrity. The significant SNPs identified in this study could be prioritized via genomic selection in breeding programs to improve fillet color in rainbow trout.

Genomic predictions for fillet yield and firmness in rainbow trout using reduced-density SNP panels.

BACKGROUND: One of the most important goals for the rainbow trout aquaculture industry is to improve fillet yield and fillet quality. Previously, we showed that a 50 K transcribed-SNP chip can be used to detect quantitative trait loci (QTL) associated with fillet yield and fillet firmness. In this study, data from 1568 fish genotyped for the 50 K transcribed-SNP chip and ~ 774 fish phenotyped for fillet yield and fillet firmness were used in a single-step genomic BLUP (ssGBLUP) model to compute the genomic estimated breeding values (GEBV). In addition, pedigree-based best linear unbiased prediction (PBLUP) was used to calculate traditional, family-based estimated breeding values (EBV). RESULTS: The genomic predictions outperformed the traditional EBV by 35% for fillet yield and 42% for fillet firmness. The predictive ability for fillet yield and fillet firmness was 0.19-0.20 with PBLUP, and 0.27 with ssGBLUP. Additionally, reducing SNP panel densities indicated that using 500-800 SNPs in genomic predictions still provides predictive abilities higher than PBLUP. CONCLUSION: These results suggest that genomic evaluation is a feasible strategy to identify and select fish with superior genetic merit within rainbow trout families, even with low-density SNP panels.

Distinct microbial assemblages associated with genetic selection for high- and low- muscle yield in rainbow trout.

BACKGROUND: Fish gut microbial assemblages play a crucial role in the growth rate, metabolism, and immunity of the host. We hypothesized that the gut microbiota of rainbow trout was correlated with breeding program based genetic selection for muscle yield. To test this hypothesis, fecal samples from 19 fish representing an F2 high-muscle genetic line (ARS-FY-H) and 20 fish representing an F1 low-muscle yield genetic line (ARS-FY-L) were chosen for microbiota profiling using the 16S rRNA gene. Significant differences in microbial assemblages between these two genetic lines might represent the effect of host genetic selection in structuring the gut microbiota of the host. RESULTS: Tukey's transformed inverse Simpson indices indicated that high muscle yield genetic line (ARS-FY-H) samples have higher microbial diversity compared to those of the low muscle yield genetic line (ARS-FY-L) (LMM, χ2(1) =14.11, p < 0.05). The fecal samples showed statistically distinct structure in microbial assemblages between the genetic lines (F1,36 = 4.7, p < 0.05, R2 = 11.9%). Functional profiling of bacterial operational taxonomic units predicted characteristic functional capabilities of the microbial communities in the high (ARS-FY-H) and low (ARS-FY-L) muscle yield genetic line samples. CONCLUSION: The significant differences of the microbial assemblages between high (ARS-FY-H) and low (ARS-FY-L) muscle yield genetic lines indicate a possible effect of genetic selection on the microbial diversity of the host. The functional composition of taxa demonstrates a correlation between bacteria and improving the muscle accretion in the host, probably, by producing various metabolites and enzymes that might aid in digestion. Further research is required to elucidate the mechanisms involved in shaping the microbial community through host genetic selection.

Genome-wide scan for common variants associated with intramuscular fat and moisture content in rainbow trout.

BACKGROUND: Genetic improvement of fillet quality attributes is a priority of the aquaculture industry. Muscle composition impacts quality attributes such as flavor, appearance, texture, and juiciness. Fat and moisture make up about ~ 80% of the tissue weight. The genetic architecture underlying the fat and moisture content of the muscle is still to be fully explored in fish. A 50 K gene transcribed SNP chip was used for genotyping 789 fish with available phenotypic data for fat and moisture content. Genotyped fish were obtained from two consecutive generations produced in the National Center for Cool and Cold Water Aquaculture (NCCCWA) growth-selective breeding program. Estimates of SNP effects from weighted single-step GBLUP (WssGBLUP) were used to perform genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with the studied traits. RESULTS: Using genomic sliding windows of 50 adjacent SNPs, 137 and 178 SNPs were identified as associated with fat and moisture content, respectively. Chromosomes 19 and 29 harbored the highest number of SNPs explaining at least 2% of the genetic variation in fat and moisture content. A total of 61 common SNPs on chromosomes 19 and 29 affected the aforementioned traits; this association suggests common mechanisms underlying intramuscular fat and moisture content. Additionally, based on single-marker GWA analyses, 8 and 24 SNPs were identified in association with fat and moisture content, respectively. CONCLUSION: SNP-harboring genes were primarily involved in lipid metabolism, cytoskeleton remodeling, and protein turnover. This work provides putative SNP markers that could be prioritized and used for genomic selection in breeding programs.

Genome-wide identification of loci associated with growth in rainbow trout.

BACKGROUND: Growth is a major economic production trait in aquaculture. Improvements in growth performance will reduce time and cost for fish to reach market size. However, genes underlying growth have not been fully explored in rainbow trout. RESULTS: A previously developed 50 K gene-transcribed SNP chip, containing ~ 21 K SNPs showing allelic imbalances potentially associated with important aquaculture production traits including body weight, muscle yield, was used for genotyping a total of 789 fish with available phenotypic data for bodyweight gain. Genotyped fish were obtained from two consecutive generations produced in the NCCCWA growth-selection breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform a genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with bodyweight gain. Using genomic sliding windows of 50 adjacent SNPs, 247 SNPs associated with bodyweight gain were identified. SNP-harboring genes were involved in cell growth, cell proliferation, cell cycle, lipid metabolism, proteolytic activities, chromatin modification, and developmental processes. Chromosome 14 harbored the highest number of SNPs (n = 50). An SNP window explaining the highest additive genetic variance for bodyweight gain (~ 6.4%) included a nonsynonymous SNP in a gene encoding inositol polyphosphate 5-phosphatase OCRL-1. Additionally, based on a single-marker GWA analysis, 33 SNPs were identified in association with bodyweight gain. The highest SNP explaining variation in bodyweight gain was identified in a gene coding for thrombospondin-1 (THBS1) (R2 = 0.09). CONCLUSION: The majority of SNP-harboring genes, including OCRL-1 and THBS1, were involved in developmental processes. Our results suggest that development-related genes are important determinants for growth and could be prioritized and used for genomic selection in breeding programs.

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.

Genome-Wide Association Study Identifies Genomic Loci Affecting Filet Firmness and Protein Content in Rainbow Trout.

Filet quality traits determine consumer satisfaction and affect profitability of the aquaculture industry. Soft flesh is a criterion for fish filet downgrades, resulting in loss of value. Filet firmness is influenced by many factors, including rate of protein turnover. A 50K transcribed gene SNP chip was used to genotype 789 rainbow trout, from two consecutive generations, produced in the USDA/NCCCWA selective breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform genome-wide association (GWA) analyses to identify quantitative trait loci affecting filet firmness and protein content. Applying genomic sliding windows of 50 adjacent SNPs, 212 and 225 SNPs were associated with genetic variation in filet shear force and protein content, respectively. Four common SNPs in the ryanodine receptor 3 gene (RYR3) affected the aforementioned filet traits; this association suggests common mechanisms underlying filet shear force and protein content. Genes harboring SNPs were mostly involved in calcium homeostasis, proteolytic activities, transcriptional regulation, chromatin remodeling, and apoptotic processes. RYR3 harbored the highest number of SNPs (n = 32) affecting genetic variation in shear force (2.29%) and protein content (4.97%). Additionally, based on single-marker analysis, a SNP in RYR3 ranked at the top of all SNPs associated with variation in shear force. Our data suggest a role for RYR3 in muscle firmness that may be considered for genomic- and marker-assisted selection in breeding programs of rainbow trout.

Aquaculture genomics, genetics and breeding in the United States: current status, challenges, and priorities for future research.

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.

Differences in growth, fillet quality, and fatty acid metabolism-related gene expression between juvenile male and female rainbow trout.

Sexual maturation occurs at the expense of stored energy and nutrients, including lipids; however, little is known regarding sex effects on nutrient regulatory mechanisms in rainbow trout prior to maturity. Thirty-two, 14-month-old, male and female rainbow trout were sampled for growth, carcass yield, fillet composition, and gene expression of liver, white muscle, and visceral adipose tissue. Growth parameters, including gonadosomatic index, were not affected by sex. Females had higher percent separable muscle yield, but there were no sex effects on fillet proximate composition. Fillet shear force indicated females produce firmer fillets than males. Male livers had greater expression of three cofactors within the mTOR signaling pathway that act to inhibit TORC1 assembly; mo25, rictor, and pras40. Male liver also exhibited increased expression of ß-oxidation genes cpt1b and ehhadh. These findings are indicative of increased mitochondrial ß-oxidation in male liver. Females exhibited increased expression of the mTOR cofactor raptor in white muscle and had higher expression levels of several genes within the fatty acid synthesis pathway, including gpat, srebp1, scd1, and cd36. Female muscle also had increased expression of ß-oxidation genes cpt1d and cpt2. Increased expression of both fatty acid synthesis and ß-oxidation genes suggests female muscle may have greater fatty acid turnover. Differences between sexes were primarily associated with variation of gene expression within the mTOR signaling pathway. Overall, data suggest there is differential regulation of gene expression in male and female rainbow trout tissues prior to the onset of sexual maturity that may lead to nutrient repartitioning during maturation.