Genomic Selection for Growth Traits in Pacific Oyster (Crassostrea gigas): Potential of Low-Density Marker Panels for Breeding Value Prediction

No trade-off between growth and OsHV-1 tolerance in Pacific oysters (Crassostrea gigas) farmed on the West Coast, USA

An important pathogen of concern for Pacific oyster growers in the USA is ostreid herpesvirus 1 (OsHV-1). Currently, oyster stocks exist that are tolerant to OsHV-1; however, it is uncertain if a trade-off exists between their tolerance to OsHV-1 and their growth in different environments. To investigate any potential trade-offs, Pacific oyster families with varying levels of OsHV-1 tolerance were grown in a bay where OsHV-1 is endemic (Tomales Bay, CA) and in a bay where OsHV-1 is absent (Willapa Bay, WA). In Tomales Bay, we found that oysters from OsHV-1 tolerant families grew faster than oysters from OsHV-1 susceptible families, while in Willapa Bay, no statistically significant difference in growth was found between oyster families with different levels of OsHV-1 tolerance observed in Tomales Bay. These findings indicate that Pacific oysters bred to be tolerant to OsHV-1 would not be expected to have a longer time-to-market regardless of the presence of OsHV-1 in the growing environment.

Effects of common full-sib families on accuracy of genomic prediction for tagging weight in striped catfish Pangasianodon hypophthalmus

Common full-sib families (c ² ) make up a substantial proportion of total phenotypic variation in traits of commercial importance in aquaculture species and omission or inclusion of the c ² resulted in possible changes in genetic parameter estimates and re-ranking of estimated breeding values. However, the impacts of common full-sib families on accuracy of genomic prediction for commercial traits of economic importance are not well known in many species, including aquatic animals. This research explored the impacts of common full-sib families on accuracy of genomic prediction for tagging weight in a population of striped catfish comprising 11,918 fish traced back to the base population (four generations), in which 560 individuals had genotype records of 14,154 SNPs. Our single step genomic best linear unbiased prediction (ssGLBUP) showed that the accuracy of genomic prediction for tagging weight was reduced by 96.5%-130.3% when the common full-sib families were included in statistical models. The reduction in the prediction accuracy was to a smaller extent in multivariate analysis than in univariate models. Imputation of missing genotypes somewhat reduced the upward biases in the prediction accuracy for tagging weight. It is therefore suggested that genomic evaluation models for traits recorded during the early phase of growth development should account for the common full-sib families to minimise possible biases in the accuracy of genomic prediction and hence, selection response.

Comparative Methylome Analysis Reveals Epigenetic Signatures Associated with Growth and Shell Color in the Pacific Oyster, Crassostrea gigas

Fast growth is one of the most important breeding goals for all economic species such as the Pacific oyster (Crassostrea gigas), an aquaculture mollusk with top global production. Although the genetic basis and molecular mechanisms of growth-related traits have been widely investigated in the oyster, the role of DNA methylation involved in growth regulation remains largely unexplored. In this study, we performed a comparative DNA methylome analysis of two selectively bred C. gigas strains with contrasted phenotypes in growth and shell color based on whole-genome bisulfite sequencing (WGBS). Genome-wide profiling of DNA methylation at the single-base resolution revealed that DNA methylations were widely spread across the genome with obvious hotspots, coinciding with the distribution of genes and repetitive elements. Higher methylation levels were observed within genic regions compared with intergenic and promoter regions. Comparative analysis of DNA methylation allowed the identification of 339,604 differentially methylated CpG sites (DMCs) clustering in 27,600 differentially methylated regions (DMRs). Functional annotation analysis identified 11,033 genes from DMRs which were enriched in biological processes including cytoskeleton system, cell cycle, signal transduction, and protein biosynthesis. Integrative analysis of methylome and transcriptome profiles revealed a positive correlation between gene expression and DNA methylation within gene-body regions. Protein-protein interaction (PPI) analysis of differentially expressed and methylated genes allowed for the identification of integrin beta-6 (homolog of human ITGB3) as a hub modulator of the PI3K/Akt signaling pathway that was involved in various growth-related processes. This work provided insights into epigenetic regulation of growth in oysters and will be valuable resources for studying DNA methylation in invertebrates.

Two parallel chromosome‐level reference genomes to support restoration and aquaculture of European flat oyster Ostrea edulis

This volume of Evolutionary Applications sees the publication of two genomes for the European native flat oyster Ostrea edulis, a species of significant evolutionary, ecological and commercial value. Each is a highly contiguous chromosome‐level assembly from individuals of different genetic backgrounds, which have been benchmarked against one another. This situation has resulted from the serendipitous discovery that two independent research groups were both deep into the process of building, annotating and investigating separately produced assemblies. Due to constraints with funder requirements and the need to recognize early career researchers for their work, alongside the technical challenge of integrating assemblies from two very different genomes, there was limited capacity to merge the sequences into one publication at the stage of discovery. This issue is likely to become very common over the next few years until the technologies for working with multiple genomes at once, for example, graph genomes, become commonplace in nonmodel species. Consequently, both of our teams have decided to collaborate rather than compete, recognizing the benefit to copublishing two separate genome resources for the research community, each with distinct scientific investigations, and working collaboratively to benchmark the assemblies.

Genome-Wide Association and Genomic Prediction of Growth Traits in the European Flat Oyster (Ostrea edulis)

The European flat oyster (Ostrea edulis) is a bivalve mollusc that was once widely distributed across Europe and represented an important food resource for humans for centuries. Populations of O. edulis experienced a severe decline across their biogeographic range mainly due to overexploitation and disease outbreaks. To restore the economic and ecological benefits of European flat oyster populations, extensive protection and restoration efforts are in place within Europe. In line with the increasing interest in supporting restoration and oyster farming through the breeding of stocks with enhanced performance, the present study aimed to evaluate the potential of genomic selection for improving growth traits in a European flat oyster population obtained from successive mass-spawning events. Four growth-related traits were evaluated: total weight (TW), shell height (SH), shell width (SW) and shell length (SL). The heritability of the growth traits was in the low-moderate range, with estimates of 0.45, 0.37, 0.22, and 0.32 for TW, SH, SW and SL, respectively. A genome-wide association analysis revealed a largely polygenic architecture for the four growth traits, with two distinct QTLs detected on chromosome 4. To investigate whether genomic selection can be implemented in flat oyster breeding at a reduced cost, the utility of low-density SNP panels was assessed. Genomic prediction accuracies using the full density panel were high (> 0.83 for all traits). The evaluation of the effect of reducing the number of markers used to predict genomic breeding values revealed that similar selection accuracies could be achieved for all traits with 2K SNPs as for a full panel containing 4,577 SNPs. Only slight reductions in accuracies were observed at the lowest SNP density tested (i.e., 100 SNPs), likely due to a high relatedness between individuals being included in the training and validation sets during cross-validation. Overall, our results suggest that the genetic improvement of growth traits in oysters is feasible. Nevertheless, and although low-density SNP panels appear as a promising strategy for applying GS at a reduced cost, additional populations with different degrees of genetic relatedness should be assessed to derive estimates of prediction accuracies to be expected in practical breeding programmes.

Whole genome resequencing reveals signatures of rapid selection in a virus affected commercial fishery

Infectious diseases are recognized as one of the greatest global threats to biodiversity and ecosystem functioning. Consequently, there is a growing urgency to understand the speed at which adaptive phenotypes can evolve and spread in natural populations to inform future management. Here we provide evidence of rapid genomic changes in wild Australian blacklip abalone (Haliotis rubra) following a major population crash associated with an infectious disease. Genome scans on H. rubra were performed using pooled whole genome resequencing data from commercial fishing stocks varying in historical exposure to haliotid herpesvirus‐1 (HaHV‐1). Approximately 25,000 single nucleotide polymorphism loci associated with virus exposure were identified, many of which mapped to genes known to contribute to HaHV‐1 immunity in the New Zealand pāua (Haliotis iris) and herpesvirus response pathways in haliotids and other animal systems. These findings indicate genetic changes across a single generation in H. rubra fishing stocks decimated by HaHV‐1, with stock recovery potentially determined by rapid evolutionary changes leading to virus resistance. This is a novel example of apparently rapid adaptation in natural populations of a nonmodel marine organism, highlighting the pace at which selection can potentially act to counter disease in wildlife communities.

Genome-wide analysis of acute low salinity tolerance in the eastern oyster Crassostrea virginica and potential of genomic selection for trait improvement

As the global demand for seafood increases, research into the genetic basis of traits that can increase aquaculture production is critical. The eastern oyster (Crassostrea virginica) is an important aquaculture species along the Atlantic and Gulf Coasts of the United States, but increases in heavy rainfall events expose oysters to acute low salinity conditions, which negatively impact production. Low salinity survival is known to be a moderately heritable trait, but the genetic architecture underlying this trait is still poorly understood. In this study, we used ddRAD sequencing to generate genome-wide single-nucleotide polymorphism (SNP) data for four F₂ families to investigate the genomic regions associated with survival in extreme low salinity (<3). SNP data were also used to assess the feasibility of genomic selection (GS) for improving this trait. Quantitative trait locus (QTL) mapping and combined linkage disequilibrium analysis revealed significant QTL on eastern oyster chromosomes 1 and 7 underlying both survival and day to death in a 36-day experimental challenge. Significant QTL were located in genes related to DNA/RNA function and repair, ion binding and membrane transport, and general response to stress. GS was investigated using Bayesian linear regression models and prediction accuracies ranged from 0.48 to 0.57. Genomic prediction accuracies were largest using the BayesB prior and prediction accuracies did not substantially decrease when SNPs located within the QTL region on Chr1 were removed, suggesting that this trait is controlled by many genes of small effect. Our results suggest that GS will likely be a viable option for improvement of survival in extreme low salinity.

Genomic Selection in Aquaculture Species

To date, genomic prediction has been conducted in about 20 aquaculture species, with a preference for intra-family genomic selection (GS). For every trait under GS, the increase in accuracy obtained by genomic estimated breeding values instead of classical pedigree-based estimation of breeding values is very important in aquaculture species ranging from 15% to 89% for growth traits, and from 0% to 567% for disease resistance. Although the implementation of GS in aquaculture is of little additional investment in breeding programs already implementing sib testing on pedigree, the deployment of GS remains sparse, but could be boosted by adaptation of cost-effective imputation from low-density panels. Moreover, GS could help to anticipate the effect of climate change by improving sustainability-related traits such as production yield (e.g., carcass or fillet yields), feed efficiency or disease resistance, and by improving resistance to environmental variation (tolerance to temperature or salinity variation). This chapter synthesized the literature in applications of GS in finfish, crustaceans and molluscs aquaculture in the present and future breeding programs.

Inheritance of Yield Components and Morphological Traits in Avocado cv. Hass From "Criollo" "Elite Trees" via Half-Sib Seedling Rootstocks

Grafting induces precocity and maintains clonal integrity in fruit tree crops. However, the complex rootstock × scion interaction often precludes understanding how the tree phenotype is shaped, limiting the potential to select optimum rootstocks. Therefore, it is necessary to assess (1) how seedling progenies inherit trait variation from elite 'plus trees', and (2) whether such family superiority may be transferred after grafting to the clonal scion. To bridge this gap, we quantified additive genetic parameters (i.e., narrow sense heritability-h ², and genetic-estimated breeding values-GEBVs) across landraces, "criollo", "plus trees" of the super-food fruit tree crop avocado (Persea americana Mill.), and their open-pollinated (OP) half-sib seedling families. Specifically, we used a genomic best linear unbiased prediction (G-BLUP) model to merge phenotypic characterization of 17 morpho-agronomic traits with genetic screening of 13 highly polymorphic SSR markers in a diverse panel of 104 avocado "criollo" "plus trees." Estimated additive genetic parameters were validated at a 5-year-old common garden trial (i.e., provenance test), in which 22 OP half-sib seedlings from 82 elite "plus trees" served as rootstocks for the cv. Hass clone. Heritability (h ²) scores in the "criollo" "plus trees" ranged from 0.28 to 0.51. The highest h ² values were observed for ribbed petiole and adaxial veins with 0.47 (CI 95%0.2-0.8) and 0.51 (CI 0.2-0.8), respectively. The h ² scores for the agronomic traits ranged from 0.34 (CI 0.2-0.6) to 0.39 (CI 0.2-0.6) for seed weight, fruit weight, and total volume, respectively. When inspecting yield variation across 5-year-old grafted avocado cv. Hass trees with elite OP half-sib seedling rootstocks, the traits total number of fruits and fruits' weight, respectively, exhibited h ² scores of 0.36 (± 0.23) and 0.11 (± 0.09). Our results indicate that elite "criollo" "plus trees" may serve as promissory donors of seedling rootstocks for avocado cv. Hass orchards due to the inheritance of their outstanding trait values. This reinforces the feasibility to leverage natural variation from "plus trees" via OP half-sib seedling rootstock families. By jointly estimating half-sib family effects and rootstock-mediated heritability, this study promises boosting seedling rootstock breeding programs, while better discerning the consequences of grafting in fruit tree crops.

Rootstock-Mediated Genetic Variance in Cadmium Uptake by Juvenile Cacao (Theobroma cacao L.) Genotypes, and Its Effect on Growth and Physiology

Grafting typically offers a shortcut to breed tree orchards throughout a multidimensional space of traits. Despite an overwhelming spectrum of rootstock-mediated effects on scion traits observed across several species, the exact nature and mechanisms underlying the rootstock-mediated effects on scion traits in cacao (Theobroma cacao L.) plants often remain overlooked. Therefore, we aimed to explicitly quantify rootstock-mediated genetic contributions in recombinant juvenile cacao plants across target traits, specifically cadmium (Cd) uptake, and its correlation with growth and physiological traits. Content of chloroplast pigments, fluorescence of chlorophyll a, leaf gas exchange, nutrient uptake, and plant biomass were examined across ungrafted saplings and target rootstock × scion combinations in soils with contrasting levels of Cd. This panel considered a total of 320 progenies from open-pollinated half-sib families and reciprocal full-sib progenies (derived from controlled crosses between the reference genotypes IMC67 and PA121). Both family types were used as rootstocks in grafts with two commercial clones (ICS95 and CCN51) commonly grown in Colombia. A pedigree-based best linear unbiased prediction (A-BLUP) mixed model was implemented to quantify rootstock-mediated narrow-sense heritability (h 2) for target traits. A Cd effect measured on rootstocks before grafting was observed in plant biomass, nutrient uptake, and content of chloroplast pigments. After grafting, damage to the Photosystem II (PSII) was also evident in some rootstock × scion combinations. Differences in the specific combining ability for Cd uptake were mostly detected in ungrafted rootstocks, or 2 months after grafting with the clonal CCN51 scion. Moderate rootstock effects (h 2> 0.1) were detected before grafting for five growth traits, four nutrient uptake properties, and chlorophylls and carotenoids content (h 2 = 0.19, 95% CI 0.05-0.61, r = 0.7). Such rootstock effects faded (h 2< 0.1) when rootstock genotypes were examined in soils without Cd, or 4 months after grafting. These results suggest a pervasive genetic conflict between the rootstock and the scion genotypes, involving the triple rootstock × scion × soil interaction when it refers to Cd and nutrient uptake, early growth, and photosynthetic process in juvenile cacao plants. Overall, deepening on these findings will harness early breeding schemes of cacao rootstock genotypes compatible with commercial clonal scions and adapted to soils enriched with toxic levels of Cd.

Tomato genomic prediction for good performance under high-temperature and identification of loci involved in thermotolerance response

Many studies showed that few degrees above tomato optimum growth temperature threshold can lead to serious loss in production. Therefore, the development of innovative strategies to obtain tomato cultivars with improved yield under high temperature conditions is a main goal both for basic genetic studies and breeding activities. In this paper, a F4 segregating population was phenotypically evaluated for quantitative and qualitative traits under heat stress conditions. Moreover, a genotyping by sequencing (GBS) approach has been employed for building up genomic selection (GS) models both for yield and soluble solid content (SCC). Several parameters, including training population size, composition and marker quality were tested to predict genotype performance under heat stress conditions. A good prediction accuracy for the two analyzed traits (0.729 for yield production and 0.715 for SCC) was obtained. The predicted models improved the genetic gain of selection in the next breeding cycles, suggesting that GS approach is a promising strategy to accelerate breeding for heat tolerance in tomato. Finally, the annotation of SNPs located in gene body regions combined with QTL analysis allowed the identification of five candidates putatively involved in high temperatures response, and the building up of a GS model based on calibrated panel of SNP markers.

Impact of genotypic errors with equal and unequal family contribution on accuracy of genomic prediction in aquaculture using simulation

Genotypic errors, conflict between recorded genotype and the true genotype, can lead to false or biased population genetic parameters. Here, the effect of genotypic errors on accuracy of genomic predictions and genomic relationship matrix are investigated using a simulation study based on population and genomic structure comparable to black tiger prawn, Penaeus monodon. Fifty full-sib families across five generations with phenotypic and genotypic information on 53 K SNPs were simulated. Ten replicates of different scenarios with three heritability estimates, equal and unequal family contributions were generated. Within each scenario, four SNP densities and three genotypic error rates in each SNP density were implemented. Results showed that family contribution did not have a substantial impact on accuracy of predictions across different datasets. In the absence of genotypic errors, 3 K SNP density was found to be efficient in estimating the accuracy, whilst increasing the SNP density from 3 to 20 K resulted in a marginal increase in accuracy of genomic predictions using the current population and genomic parameters. In addition, results showed that the presence of even 10% errors in a 10 and 20 K SNP panel might not have a severe impact on accuracy of predictions. However, below 10 K marker density, even a 5% error can result in lower accuracy of predictions.

Genomic Prediction for Whole Weight, Body Shape, Meat Yield, and Color Traits in the Portuguese Oyster Crassostrea angulata

Genetic improvement for quality traits, especially color and meat yield, has been limited in aquaculture because the assessment of these traits requires that the animals be slaughtered first. Genotyping technologies do, however, provide an opportunity to improve the selection efficiency for these traits. The main purpose of this study is to assess the potential for using genomic information to improve meat yield (soft tissue weight and condition index), body shape (cup and fan ratios), color (shell and mantle), and whole weight traits at harvest in the Portuguese oyster, Crassostrea angulata. The study consisted of 647 oysters: 188 oysters from 57 full-sib families from the first generation and 459 oysters from 33 full-sib families from the second generation. The number per family ranged from two to eight oysters for the first and 12–15 oysters for the second generation. After quality control, a set of 13,048 markers were analyzed to estimate the genetic parameters (heritability and genetic correlation) and predictive accuracy of the genomic selection for these traits. The multi-locus mixed model analysis indicated high estimates of heritability for meat yield traits: 0.43 for soft tissue weight and 0.77 for condition index. The estimated genomic heritabilities were 0.45 for whole weight, 0.24 for cup ratio, and 0.33 for fan ratio and ranged from 0.14 to 0.54 for color traits. The genetic correlations among whole weight, meat yield, and body shape traits were favorably positive, suggesting that the selection for whole weight would have beneficial effects on meat yield and body shape traits. Of paramount importance is the fact that the genomic prediction showed moderate to high accuracy for the traits studied (0.38–0.92). Therefore, there are good prospects to improve whole weight, meat yield, body shape, and color traits using genomic information. A multi-trait selection program using the genomic information can boost the genetic gain and minimize inbreeding in the long-term for this population.

Impact of Marker Pruning Strategies Based on Different Measurements of Marker Distance on Genomic Prediction in Dairy Cattle

Simple Summary

The usefulness of genomic prediction (GP) has been widely proofed by breeding analysis in livestock, plants and aquatic populations. It is well known that ‘marker density’ is a critical factor that affects the accuracy of GP, however, how to properly measure ‘marker density’ in GP is yet to be determined. With population-level whole-genome sequence data or high-density single nucleotide polymorphism (SNP) data available, this question seems to be answered more convincingly. In this study, we investigated and discussed the impact of four ‘marker density’ measures that reflect genetic or physical distances between SNPs on the accuracy of GP in a Germany Holstein dairy cattle population. Our results showed that the degree of variation of physical distance between adjacent SNPs had significant effects on the accuracy of GP, while the genetic distance between SNPs had no relationship with the accuracy of GP. Therefore, for studies based on high-density SNP data, the default strategy of pruning SNPs based on genetic distance is detrimental to heritability estimation and genomic prediction. The results extended the communities knowledge of ‘marker density’ and provided useful suggestions for the application and research on genome prediction.

Abstract

With the availability of high-density single-nucleotide polymorphism (SNP) data and the development of genotype imputation methods, high-density panel-based genomic prediction (GP) has become possible in livestock breeding. It is generally considered that the genomic estimated breeding value (GEBV) accuracy increases with the marker density, while studies have shown that the GEBV accuracy does not increase or even decrease when high-density panels were used. Therefore, in addition to the SNP number, other measurements of ‘marker density’ seem to have impacts on the GEBV accuracy, and exploring the relationship between the GEBV accuracy and the measurements of ‘marker density’ based on high-density SNP or whole-genome sequence data is important for the field of GP. In this study, we constructed different SNP panels with certain SNP numbers (e.g., 1 k) by using the physical distance (PhyD), genetic distance (GenD) and random distance (RanD) between SNPs respectively based on the high-density SNP data of a Germany Holstein dairy cattle population. Therefore, there are three different panels at a certain SNP number level. These panels were used to construct GP models to predict fat percentage, milk yield and somatic cell score. Meanwhile, the mean (d¯) and variance (σd2) of the physical distance between SNPs and the mean (r2¯) and variance (σr22) of the genetic distance between SNPs in each panel were used as marker density-related measurements and their influence on the GEBV accuracy was investigated. At the same SNP number level, the d¯ of all panels is basically the same, but the σd2, r2¯ and σr22 are different. Therefore, we only investigated the effects of σd2, r2¯ and σr22 on the GEBV accuracy. The results showed that at a certain SNP number level, the GEBV accuracy was negatively correlated with σd2, but not with r2¯ and σr22. Compared with GenD and RanD, the σd2 of panels constructed by PhyD is smaller. The low and moderate-density panels (< 50 k) constructed by RanD or GenD have large σd2, which is not conducive to genomic prediction. The GEBV accuracy of the low and moderate-density panels constructed by PhyD is 3.8~34.8% higher than that of the low and moderate-density panels constructed by RanD and GenD. Panels with 20–30 k SNPs constructed by PhyD can achieve the same or slightly higher GEBV accuracy than that of high-density SNP panels for all three traits. In summary, the smaller the variation degree of physical distance between adjacent SNPs, the higher the GEBV accuracy. The low and moderate-density panels construct by physical distance are beneficial to genomic prediction, while pruning high-density SNP data based on genetic distance is detrimental to genomic prediction. The results provide suggestions for the development of SNP panels and the research of genome prediction based on whole-genome sequence data.

Sensitivity of Staphylococcus aureus cultures of different biological origin to commercial bacteriophages and phages of Staphylococcus aureus var. bovis

Background and Aim:

Mastitis, an inflammation of the mammary gland, is an ongoing problem in dairy herds. In this study, we determined the sensitivity of Staphylococcus aureus cultures of different biological origins to commercial bacteriophages and phages of S. aureus var. bovis which were isolated on dairy farms, to create a drug for the treatment of mastitis in cows.

Materials and Methods:

We used cultures of S. aureus isolated from different habitats, and other types of staphylococci isolated on dairy farms. As antibacterial agents, the commercially available bacteriophages staphylococcal bacteriophage and Intestifag and field strains of phages Phage SAvB07, Phage SAvB08, Phage SAvB12, and Phage SAvB14 were used. Evaluation of their lytic properties was performed using the drip method.

Results:

The drug Intestifag lysed cultures isolated from human habitats and archival strains of S. aureus No.209-P and S. aureus (ATCC 25923) in 91.8%–100% of cases. Staphylococcal bacteriophage killed 3.6 times fewer cultures of S. aureus isolated from humans than Intestifag and did not affect the growth of archival strains. Neither drug lysed cultures isolated from cows or cultures isolated from dairy products sold in agri-food markets. Phage SAvB14 lysed 92.7±8.3% of S. aureus isolated from the mammary glands of cows and 69.2±6.4% of cultures isolated from dairy products sold in agri-food markets. Phage SAvB12, Phage SAvB08, and Phage SAvB07 lysed 1.2-1.7 times fewer cultures isolated from the mammary glands of cows and 6-18 times fewer cultures isolated from dairy products, compared with Phage SAvB14. Phages of S. aureus var. bovis can infect staphylococcal species such as Staphylococcus epidermidis, Staphylococcus haemolyticus, Staphylococcus saprophyticus, and Staphylococcus xylosus. The widest range of hosts was found for Phage SAvB14, which indicates its polyvalence.

Conclusion:

The biological origin of staphylococcal strains must be considered when developing effective phage therapy. Phage SAvB14 appears to be a good candidate for the development of a drug for the treatment of mastitis in cows.

Potential of genomic technologies to improve disease resistance in molluscan aquaculture

Molluscan aquaculture is a major contributor to global seafood production, but is hampered by infectious disease outbreaks that can cause serious economic losses. Selective breeding has been widely used to improve disease resistance in major agricultural and aquaculture species, and has clear potential in molluscs, albeit its commercial application remains at a formative stage. Advances in genomic technologies, especially the development of cost-efficient genomic selection, have the potential to accelerate genetic improvement. However, tailored approaches are required owing to the distinctive reproductive and life cycle characteristics of molluscan species. Transgenesis and genome editing, in particular CRISPR/Cas systems, have been successfully trialled in molluscs and may further understanding and improvement of genetic resistance to disease through targeted changes to the host genome. Whole-organism genome editing is achievable on a much greater scale compared to other farmed species, making genome-wide CRISPR screening approaches plausible. This review discusses the current state and future potential of selective breeding, genomic tools and genome editing approaches to understand and improve host resistance to infectious disease in molluscs. This article is part of the Theo Murphy meeting issue 'Molluscan genomics: broad insights and future directions for a neglected phylum'.

Genetic Dissection of a Precocious Phenotype in Male Tiger Pufferfish (Takifugu rubripes) using Genotyping by Random Amplicon Sequencing, Direct (GRAS-Di)

The novel non-targeted PCR-based genotyping system, namely Genotyping by Random Amplicon Sequencing, Direct (GRAS-Di), is characterized by the simplicity in library construction and robustness against DNA degradation and is expected to facilitate advancements in genetics, in both basic and applied sciences. In this study, we tested the utility of GRAS-Di for genetic analysis in a cultured population of the tiger pufferfish Takifugu rubripes. The genetic analyses included family structure analysis, genetic map construction, and quantitative trait locus (QTL) analysis for the male precocious phenotype using a population consisting of four full-sib families derived from a genetically precocious line. An average of 4.7 million raw reads were obtained from 198 fish. Trimmed reads were mapped onto a Fugu reference genome for genotyping, and 21,938 putative single-nucleotide polymorphisms (SNPs) were obtained. These 22 K SNPs accurately resolved the sibship and parent-offspring pairs. A fine-scale linkage map (total size: 1,949 cM; average interval: 1.75 cM) was constructed from 1,423 effective SNPs, for which the allele inheritance patterns were known. QTL analysis detected a significant locus for testes weight on Chr_14 and three suggestive loci on Chr_1, Chr_8, and Chr_19. The significant QTL was shared by body length and body weight. The effect of each QTL was small (phenotypic variation explained, PVE: 3.1-5.9%), suggesting that the precociousness seen in the cultured pufferfish is polygenic. Taken together, these results indicate that GRAS-Di is a practical genotyping tool for aquaculture species and applicable for molecular breeding programs, such as marker-assisted selection and genomic selection.

A chromosome-level genome assembly for the Pacific oyster Crassostrea gigas

Background

The Pacific oyster (Crassostrea gigas) is a bivalve mollusc with vital roles in coastal ecosystems and aquaculture globally. While extensive genomic tools are available for C. gigas, highly contiguous reference genomes are required to support both fundamental and applied research. Herein we report the creation and annotation of a chromosome-level assembly for C. gigas.

Findings

High-coverage long- and short-read sequence data generated on Pacific Biosciences and Illumina platforms were used to generate an initial assembly, which was then scaffolded into 10 pseudo-chromosomes using both Hi-C sequencing and a high-density linkage map. The assembly has a scaffold N50 of 58.4 Mb and a contig N50 of 1.8 Mb, representing a step advance on the previously published C. gigas assembly. Annotation based on Pacific Biosciences Iso-Seq and Illumina RNA-Seq resulted in identification of ∼30,000 putative protein-coding genes. Annotation of putative repeat elements highlighted an enrichment of Helitron rolling-circle transposable elements, suggesting their potential role in shaping the evolution of the C. gigas genome.

Conclusions

This new chromosome-level assembly will be an enabling resource for genetics and genomics studies to support fundamental insight into bivalve biology, as well as for selective breeding of C. gigas in aquaculture.

First genomic prediction and genome‐wide association for complex growth‐related traits in Rock Bream (Oplegnathus fasciatus)

Rock Bream (Oplegnathus fasciatus) is an important aquaculture species for offshore cage aquaculture and fish stocking of marine ranching in East Asia. Genomic selection has the potential to expedite genetic gain for the key target traits of a breeding program, but has not yet been evaluated in Oplegnathus. The purposes of the present study were to explore the performance of genomic selection to improve breeding value accuracy through real data analyses using six statistical models and to carry out genome‐wide association studies (GWAS) to dissect the genetic architecture of economically vital growth‐related traits (body weight, total length, and body depth) in the O. fasciatus population. After quality control, genotypes for 16,162 SNPs were acquired for 455 fish. Heritability was estimated to be moderate for the three traits (0.38 for BW, 0.33 for TL, and 0.24 for BD), and results of GWAS indicated that the underlying genetic architecture was polygenic. Six statistic models (GBLUP, BayesA, BayesB, BayesC, Bayesian Ridge‐Regression, and Bayesian LASSO) showed similar performance for the predictability of genomic estimated breeding value (GEBV). The low SNP density (around 1 K selected SNP based on GWAS) is sufficient for accurate prediction on the breeding value for the three growth‐related traits in the current studied population, which will provide a good compromise between genotyping costs and predictability in such standard breeding populations advanced. These consequences illustrate that the employment of genomic selection in O. fasciatus breeding could provide advantages for the selection of breeding candidates to facilitate complex economic growth traits.

Prediction Accuracies of Genomic Selection for Nine Commercially Important Traits in the Portuguese Oyster (Crassostrea angulata) Using DArT-Seq Technology

Genomic selection has been widely used in terrestrial animals but has had limited application in aquaculture due to relatively high genotyping costs. Genomic information has an important role in improving the prediction accuracy of breeding values, especially for traits that are difficult or expensive to measure. The purposes of this study were to (i) further evaluate the use of genomic information to improve prediction accuracies of breeding values from, (ii) compare different prediction methods (BayesA, BayesCπ and GBLUP) on prediction accuracies in our field data, and (iii) investigate the effects of different SNP marker densities on prediction accuracies of traits in the Portuguese oyster (Crassostrea angulata). The traits studied are all of economic importance and included morphometric traits (shell length, shell width, shell depth, shell weight), edibility traits (tenderness, taste, moisture content), and disease traits (Polydora sp. and Marteilioides chungmuensis). A total of 18,849 single nucleotide polymorphisms were obtained from genotyping by sequencing and used to estimate genetic parameters (heritability and genetic correlation) and the prediction accuracy of genomic selection for these traits. Multi-locus mixed model analysis indicated high estimates of heritability for edibility traits; 0.44 for moisture content, 0.59 for taste, and 0.72 for tenderness. The morphometric traits, shell length, shell width, shell depth and shell weight had estimated genomic heritabilities ranging from 0.28 to 0.55. The genomic heritabilities were relatively low for the disease related traits: Polydora sp. prevalence (0.11) and M. chungmuensis (0.10). Genomic correlations between whole weight and other morphometric traits were from moderate to high and positive (0.58–0.90). However, unfavourably positive genomic correlations were observed between whole weight and the disease traits (0.35–0.37). The genomic best linear unbiased prediction method (GBLUP) showed slightly higher accuracy for the traits studied (0.240–0.794) compared with both BayesA and BayesCπ methods but these differences were not significant. In addition, there is a large potential for using low-density SNP markers for genomic selection in this population at a number of 3000 SNPs. Therefore, there is the prospect to improve morphometric, edibility and disease related traits using genomic information in this species.

Genetic variability in Ruditapes decussatus clam combined with Perkinsus infection level to support founder population selection for a breeding program

Clam farmers worldwide face several challenges, including irregular seed supply and high mortalities due to pathogenic organisms such as Perkinsus olseni. In Europe, there is a high unmet consumer demand for native clam species such as Ruditapes decussatus. The high market value of R. decussatus makes the culture of this species potentially more attractive than that culture of the alien species Ruditapes philippinarum. Thus, there is a market opportunity in breeding and producing R. decussatus at an industrial scale. A selective breeding program to improve R. decussatus performance will be carried out in Portugal; and the first critical step to develop such a breeding program is the establishment of a founder population. In this study, intra- and interpopulation genetic diversity was assessed using 13 microsatellite markers in eight natural beds located in Portugal, Spain and Italy. Also, allele and genotypic frequencies of each microsatellite locus were assessed discriminating between clams infected and non-infected by P. olseni. All locations showed similar values for several genetic diversity parameters. Analyses of population differentiation (F_ST, Bayesian clustering and AMOVAs) revealed five genetically differentiated regions: Rías Altas and Rías Baixas (NW Spain), North/Central Coast of Portugal, Gulf of Cadiz and Adriatic Sea. Significant differences in the allelic and genotypic frequency distribution between infected clams and non-infected ones at four microsatellite loci are reported suggesting that resistance to the disease could have a genetic basis. Moreover, a positive or negative relationship between the frequency of certain alleles and the parasite infection was inferred. Further studies should confirm the potential use of those alleles as genetic markers for P. olseni infection. Integrating results of genetic diversity within and between populations and Perkinsus infection levels, a founder population for a R. decussatus breeding program is proposed, composed by individuals from Barallobre (Rías Altas), Pontevedra or Cangas (Rías Baixas), Óbidos (North/Central Coast of Portugal), Algarve (Gulf of Cadiz) and Venice (Adriatic Sea).

Development and Validation of an Open Access SNP Array for Nile Tilapia (Oreochromis niloticus)

Tilapia are among the most important farmed fish species worldwide, and are fundamental for the food security of many developing countries. Several genetically improved Nile tilapia (Oreochromis niloticus) strains exist, such as the iconic Genetically Improved Farmed Tilapia (GIFT), and breeding programs typically follow classical pedigree-based selection. The use of genome-wide single-nucleotide polymorphism (SNP) data can enable an understanding of the genetic architecture of economically important traits and the acceleration of genetic gain via genomic selection. Due to the global importance and diversity of Nile tilapia, an open access SNP array would be beneficial for aquaculture research and production. In the current study, a ∼65K SNP array was designed based on SNPs discovered from whole-genome sequence data from a GIFT breeding nucleus population and the overlap with SNP datasets from wild fish populations and several other farmed Nile tilapia strains. The SNP array was applied to clearly distinguish between different tilapia populations across Asia and Africa, with at least ∼30,000 SNPs segregating in each of the diverse population samples tested. It is anticipated that this SNP array will be an enabling tool for population genetics and tilapia breeding research, facilitating consistency and comparison of results across studies.

Contribution of Viral Genomic Diversity to Oyster Susceptibility in the Pacific Oyster Mortality Syndrome

Juvenile Pacific oysters (Crassostrea gigas) are subjected to recurrent episodes of mass mortalities that constitute a threat for the oyster industry. This mortality syndrome named “Pacific Oyster Mortality Syndrome” (POMS) is a polymicrobial disease whose pathogenesis is initiated by a primary infection by a variant of an Ostreid herpes virus named OsHV-1 μVar. The characterization of the OsHV-1 genome during different disease outbreaks occurring in different geographic areas has revealed the existence of a genomic diversity for OsHV-1 μVar. However, the biological significance of this diversity is still poorly understood. To go further in understanding the consequences of OsHV-1 diversity on POMS, we challenged five biparental families of oysters to two different infectious environments on the French coasts (Atlantic and Mediterranean). We observed that the susceptibility to POMS can be different among families within the same environment but also for the same family between the two environments. Viral diversity analysis revealed that Atlantic and Mediterranean POMS are caused by two distinct viral populations. Moreover, we observed that different oyster families are infected by distinct viral populations within a same infectious environment. Altogether these results suggest that the co-evolutionary processes at play between OsHV-1 μVar and oyster populations have selected a viral diversity that could facilitate the infection process and the transmission in oyster populations. These new data must be taken into account in the development of novel selective breeding programs better adapted to the oyster culture environment.

Relative genomic impacts of translocation history, hatchery practices, and farm selection in Pacific oyster Crassostrea gigas throughout the Northern Hemisphere

Pacific oyster Crassostrea gigas, endemic to coastal Asia, has been translocated globally throughout the past century, resulting in self-sustaining introduced populations (naturalized). Oyster aquaculture industries in many parts of the world depend on commercially available seed (hatchery-farmed) or naturalized/wild oysters to move onto a farm (naturalized-farmed). It is therefore important to understand genetic variation among populations and farm types. Here, we genotype naturalized/wild populations from France, Japan, China, and most extensively in coastal British Columbia, Canada. We also genotype cultured populations from throughout the Northern Hemisphere to compare with naturalized populations. In total, 16,942 markers were identified using double-digest RAD-sequencing in 182 naturalized, 112 hatchery-farmed, and 72 naturalized-farmed oysters (n = 366). Consistent with previous studies, very low genetic differentiation was observed around Vancouver Island (mean F _ST = 0.0019) and low differentiation between countries in the Japan-Canada-France historical translocation lineage (France-Canada F _ST = 0.0024; Japan-Canada F _ST = 0.0060). Chinese populations were more differentiated (China-Japan F _ST = 0.0241). Hatchery-propagated populations had higher interindividual relatedness suggesting family structure. Within-population inbreeding was not detected on farms, but nucleotide diversity and polymorphism rate were lower in one farm population. Moving oysters from nature onto farms did not result in strong within-generation selection. Private alleles at substantial frequency were identified in several hatchery populations grown in BC, suggesting nonlocal origins. Tests of selection identified outlier loci consistent with selective differences associated with domestication, in some cases consistently identified in multiple farms. Top outlier candidates were nearby genes involved in calcium signaling and calmodulin activity. Implications of potential introgression from hatchery-farmed oysters depend on whether naturalized populations are valued as a locally adapted resource or as an introduced, invasive species. Given the value of the industry in BC and the challenges the industry faces (e.g., climate change, crop losses, biotic stressors), this remains an important question.

Harnessing genomics to fast-track genetic improvement in aquaculture

Aquaculture is the fastest-growing farmed food sector and will soon become the primary source of fish and shellfish for human diets. In contrast to crop and livestock production, aquaculture production is derived from numerous, exceptionally diverse species that are typically in the early stages of domestication. Genetic improvement of production traits via well-designed, managed breeding programmes has great potential to help meet the rising seafood demand driven by human population growth. Supported by continuous advances in sequencing and bioinformatics, genomics is increasingly being applied across the broad range of aquaculture species and at all stages of the domestication process to optimize selective breeding. In the future, combining genomic selection with biotechnological innovations, such as genome editing and surrogate broodstock technologies, may further expedite genetic improvement in aquaculture.

Identification of SNPs involved in Zn and Cu accumulation in the Pacific oyster (Crassostrea gigas) by genome-wide association analysis

Oysters accumulate high concentrations of zinc (Zn) and copper (Cu), which can be transferred to human due to sea food consumption. Breeding new oyster varieties with low Zn and Cu accumulations is one important way to improve food safety. However, the genetic basis for metal accumulation in mollusks is not well understood. To address this issue, oysters collected in the field were used for genome-wide association study (GWAS) and then the identified genes were used for mRNA expressions analysis in laboratory. First, GWAS were conducted for Zn and Cu accumulation in 288 wild Pacific oysters (Crassostrea gigas) farmed in the same ocean environment. The oysters did not show obvious population structure or kinship but exhibited 8.43- and 10.0- fold changes of Zn and Cu contents respectively. GWAS have identified 11 and 12 single nucleotide polymorphisms (SNPs) associated with Zn and Cu, respectively, as well as 16 genes, which were Zn-containing proteins or participated in caveolae-dependent endocytosis. Second, the mRNA expressions of these 16 genes were observed under Zn and Cu exposure. After 9 days of Zn exposure, Zn contents increased 3.1-fold, while the mRNA expression of cell number regulator 3 increased 1.65-fold. Under 9 days of Cu exposure, Cu contents increased 1.97-fold, while the mRNA expression of caveolin-1 decreased 0.61-fold. These provide the evidence for their roles in regulating physiological levels of these two metals. The findings advance our understanding of the genetic basis of Zn and Cu accumulation in mollusks, which can be useful for breeding new, less toxic varieties of oysters.

Potential of genomic selection for improvement of resistance to ostreid herpesvirus in Pacific oyster (Crassostrea gigas)

In genomic selection (GS), genome-wide SNP markers are used to generate genomic estimated breeding values for selection candidates. The application of GS in shellfish looks promising and has the potential to help in dealing with one of the main issues currently affecting Pacific oyster production worldwide, which is the 'summer mortality syndrome'. This causes periodic mass mortality in farms worldwide and has mainly been attributed to a specific variant of the ostreid herpesvirus (OsHV-1). In the current study, we evaluated the potential of genomic selection for host resistance to OsHV-1 in Pacific oysters, and compared it with pedigree-based approaches. An OsHV-1 disease challenge was performed using an immersion-based virus exposure treatment for oysters for 7 days. A total of 768 samples were genotyped using the medium-density SNP array for oysters. A GWAS was performed for the survival trait using a GBLUP approach in blupf90 software. Heritability ranged from 0.25 ± 0.05 to 0.37 ± 0.05 (mean ± SE) based on pedigree and genomic information respectively. Genomic prediction was more accurate than pedigree prediction, and SNP density reduction had little impact on prediction accuracy until marker densities dropped below approximately 500 SNPs. This demonstrates the potential for GS in Pacific oyster breeding programmes, and importantly, demonstrates that a low number of SNPs might suffice to obtain accurate genomic estimated breeding values, thus potentially making the implementation of GS more cost effective.

Genomic Prediction Using Low Density Marker Panels in Aquaculture: Performance Across Species, Traits, and Genotyping Platforms

Genomic selection increases the rate of genetic gain in breeding programs, which results in significant cumulative improvements in commercially important traits such as disease resistance. Genomic selection currently relies on collecting genome-wide genotype data accross a large number of individuals, which requires substantial economic investment. However, global aquaculture production predominantly occurs in small and medium sized enterprises for whom this technology can be prohibitively expensive. For genomic selection to benefit these aquaculture sectors, more cost-efficient genotyping is necessary. In this study the utility of low and medium density SNP panels (ranging from 100 to 9,000 SNPs) to accurately predict breeding values was tested and compared in four aquaculture datasets with different characteristics (species, genome size, genotyping platform, family number and size, total population size, and target trait). The traits show heritabilities between 0.19–0.49, and genomic prediction accuracies using the full density panel of 0.55–0.87. A consistent pattern of genomic prediction accuracy was observed across species with little or no accuracy reduction until SNP density was reduced below 1,000 SNPs (prediction accuracies of 0.44–0.75). Below this SNP density, heritability estimates and genomic prediction accuracies tended to be lower and more variable (93% of maximum accuracy achieved with 1,000 SNPs, 89% with 500 SNPs, and 70% with 100 SNPs). A notable drop in accuracy was observed between 200 SNP panels (0.44–0.75) and 100 SNP panels (0.39–0.66). Now that a multitude of studies have highlighted the benefits of genomic over pedigree-based prediction of breeding values in aquaculture species, the results of the current study highlight that these benefits can be achieved at lower SNP densities and at lower cost, raising the possibility of a broader application of genetic improvement in smaller and more fragmented aquaculture settings.

Genomic prediction for disease resistance to Hepatopancreatic parvovirus and growth, carcass and quality traits in Banana shrimp Fenneropenaeus merguiensis

Conventional genetic improvement of disease resistance in aquatic animal species involves challenge tests or using qPCR to quantify viral load that is costly, time-consuming and causing biosecurity concerns. Recent developments in high throughput next generation genome sequencing platforms such as genotyping by sequencing (GBS) have opened new possibilities for improving disease traits based on DNA information. The principal aim of this study was thus to examine potential application of genomic selection to improve resistance to hepatopancreatic parvovirus (HPV) in banana shrimp Fenneropenaeus merguiensis. Specifically, we used a total of 9472 single nucleotide polymorphisms (SNPs) developed de novo from GBS platforms to assess accuracy of genomic prediction for HPV resistance and growth, carcass and quality-related traits in this white shrimp species. Our multi-locus mixed model analysis showed moderate heritabilities for HPV resistance (h² = 0.46) and other traits studied (0.10 to 0.55). Genetic correlations of HPV titre with growth and carcass traits, estimated using SNPs markers, were negative (i.e., favourable), suggesting that selection for improved growth and carcass traits may have increased HPV resistance (i.e., reduced HPV titre). More importantly, our gBLUP model demonstrated that the accuracy of gBLUP prediction was moderate for HPV disease resistance (0.46). The genomic prediction accuracy was somewhat greater for growth and carcass related traits especially for body weight (0.76) and meat or tail weight (0.77). On the other hand, the prediction accuracy was from 0.25 to 0.41 for quality traits (raw and cooked colour and flesh streaks). Collectively, it is concluded that there are prospects to apply genomic selection in the genetic improvement for increased disease resistance, carcass and quality-related traits in this population of banana shrimp F. merguiensis.

Assessment of genetic diversity and population structure in cultured Australian Pacific oysters

The recent development of Pacific oyster (Crassostrea gigas) SNP genotyping arrays has allowed detailed characterisation of genetic diversity and population structure within and between oyster populations. It also raises the potential of harnessing genomic selection for genetic improvement in oyster breeding programmes. The aim of this study was to characterise a breeding population of Australian oysters through genotyping and analysis of 18 027 SNPs, followed by comparison with genotypes of oyster sampled from Europe and Asia. This revealed that the Australian populations had similar population diversity (H_E ) to oysters from New Zealand, the British Isles, France and Japan. Population divergence was assessed using PCA of genetic distance and revealed that Australian oysters were distinct from all other populations tested. Australian Pacific oysters originate from planned introductions sourced from three Japanese populations. Approximately 95% of these introductions were from geographically, and potentially genetically, distinct populations from the Nagasaki oysters assessed in this study. Finally, in preparation for the application of genomic selection in oyster breeding programmes, the strength of LD was evaluated and subsets of loci were tested for their ability to accurately infer relationships. Weak LD was observed on average; however, SNP subsets were shown to accurately reconstitute a genomic relationship matrix constructed using all loci. This suggests that low-density SNP panels may have utility in the Australian population tested, and the findings represent an important first step towards the design and implementation of genomic approaches for applied breeding in Pacific oysters.

Genome-Wide Association Study and Cost-Efficient Genomic Predictions for Growth and Fillet Yield in Nile Tilapia (Oreochromis niloticus)

Fillet yield (FY) and harvest weight (HW) are economically important traits in Nile tilapia production. Genetic improvement of these traits, especially for FY, are lacking, due to the absence of efficient methods to measure the traits without sacrificing fish and the use of information from relatives to selection. However, genomic information could be used by genomic selection to improve traits that are difficult to measure directly in selection candidates, as in the case of FY. The objectives of this study were: (i) to perform genome-wide association studies (GWAS) to dissect the genetic architecture of FY and HW, (ii) to evaluate the accuracy of genotype imputation and (iii) to assess the accuracy of genomic selection using true and imputed low-density (LD) single nucleotide polymorphism (SNP) panels to determine a cost-effective strategy for practical implementation of genomic information in tilapia breeding programs. The data set consisted of 5,866 phenotyped animals and 1,238 genotyped animals (108 parents and 1,130 offspring) using a 50K SNP panel. The GWAS were performed using all genotyped and phenotyped animals. The genotyped imputation was performed from LD panels (LD0.5K, LD1K and LD3K) to high-density panel (HD), using information from parents and 20% of offspring in the reference set and the remaining 80% in the validation set. In addition, we tested the accuracy of genomic selection using true and imputed genotypes comparing the accuracy obtained from pedigree-based best linear unbiased prediction (PBLUP) and genomic predictions. The results from GWAS supports evidence of the polygenic nature of FY and HW. The accuracy of imputation ranged from 0.90 to 0.98 for LD0.5K and LD3K, respectively. The accuracy of genomic prediction outperformed the estimated breeding value from PBLUP. The use of imputation for genomic selection resulted in an increased relative accuracy independent of the trait and LD panel analyzed. The present results suggest that genotype imputation could be a cost-effective strategy for genomic selection in Nile tilapia breeding programs.

Genome-wide association analysis of nutrient traits in the oyster Crassostrea gigas: genetic effect and interaction network

Background

Oyster is rich in glycogen and free amino acids and is called “the milk of sea”. To understand the main genetic effects of these traits and the genetic networks underlying their correlation, we have conducted the whole genome resequencing with 427 oysters collected from the world-wide scale.

Results

After association analysis, 168 clustered significant single nucleotide polymorphism (SNP) loci were identified for glycogen content and 17 SNPs were verified with 288 oyster individuals in another wide populations. These were the most important candidate loci for oyster breeding. Among 24 genes in the 100-kb regions of the leading SNP loci, cytochrome P450 17A1 (CYP17A1) contained a non-synonymous SNP and displayed higher expressions in high glycogen content individuals. This might enhance the gluconeogenesis process by the transcriptionally regulating the expression of phosphoenolpyruvate carboxykinase (PEPCK) and glucose 6-phosphatase (G6Pase). Also, for amino acids content, 417 clustered significant SNPs were identified. After genetic network analysis, three node SNP regions were identified to be associated with glycogen, protein, and Asp content, which might explain their significant correlation.

Conclusion

Overall, this study provides insights into the genetic correlation among complex traits, which will facilitate future oyster functional studies and breeding through molecular design.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5971-z) contains supplementary material, which is available to authorized users.

Comparative Transcriptome Analysis Reveals Molecular Basis Underlying Fast Growth of the Selectively Bred Pacific Oyster, Crassostrea gigas

Fast growth is one of the most desired traits for all food animals, which affects the profitability of animal production. The Pacific oyster, Crassostrea gigas, is an important aquaculture shellfish around the world with the largest annual production. Growth of the Pacific oyster has been greatly improved by artificial selection breeding, but molecular mechanisms underlying growth remains poorly understood, which limited the molecular integrative breeding of fast growth with other superior traits. In this study, comparative transcriptome analyses between the fast-growing selectively bred Pacific oyster and unselected wild Pacific oysters were conducted by RNA-Seq. A total of 1,303 protein-coding genes differentially expressed between fast-growing oysters and wild controls were identified, of which 888 genes were expressed at higher levels in the fast-growing oysters. Functional analysis of the differentially expressed genes (DEGs) indicated that genes involved in microtubule motor activity and biosynthesis of nucleotides and proteins are potentially important for growth in the oyster. Positive selection analysis of genes at the transcriptome level showed that a significant number of ribosomal protein genes had undergone positive selection during the artificial selection breeding process. These results also indicated the importance of protein biosynthesis and metabolism for the growth of oysters. The alternative splicing (AS) of genes was also compared between the two groups of oysters. A total of 3,230 differential alternative splicing events (DAS) were identified, involved in 1,818 genes. These DAS genes were associated with specific functional pathways related to growth, such as “long-term potentiation,” “salivary secretion,” and “phosphatidylinositol signaling system.” The findings of this study will be valuable resources for future investigation to unravel molecular mechanisms underlying growth regulation in the oyster and other marine invertebrates and to provide solid support for breeding application to integrate fast growth with other superior traits in the Pacific oyster.

Comparative physiology and aquaculture: Toward Omics-enabled improvement of aquatic animal health and sustainable production

Omics-technologies have revolutionized biomedical research over the past two decades, and are now poised to play a transformative role in aquaculture. This article serves as an introduction to a Virtual Special Issue of Comparative Biochemistry and Physiology - Part D: Genomics and Proteomics (CBPD), with the objective to showcase the state-of-the-science for Omics in aquaculture. In this editorial, we describe the role that Omics can play in aquaculture, and provide a synopsis for each of the Special Issue articles that use these technologies to improve aquaculture practices. Current genomic resources available for some aquaculture species are also described. The number of datasets is impressive for species such as Atlantic salmon and rainbow trout, totaling in the thousands (NCBI Gene Expression Omnibus and Sequence Read Archive). We present a conceptual framework that describes how Omics can be leveraged to understand complex responses of aquatic animals in culture for relevant physiological outcomes, such as fecundity, growth, and immunity. Lastly, knowledge gaps and new directions are identified to address current obstacles in aquaculture. Articles in this Special Issue on aquaculture in CBPD highlight the diversity and scope of Omics in aquaculture. As the technology becomes more cost-effective, it is anticipated that genomics, transcriptomics, proteomics, metabolomics and lipidomics will play increasingly important roles in stock diagnostics (e.g. genetics, health, performance). The timing is right, as global concerns are reaching critical levels over food availability/security and water restrictions for humankind.

Genome-Wide Association Study Reveals Candidate Genes for Growth Relevant Traits in Pigs

Improvement of the growth rate is a challenge in the pig industry, the Average Daily Gain (ADG) and Days (AGE) to 100 kg are directly related to growth performance. We performed genome-wide association study (GWAS) and genetic parameters estimation for ADG and AGE using the genomic and phonemic from four breed (Duroc, Yorkshire, Landrace, and Pietrain) populations. All analyses were performed by a multi-loci GWAS model, FarmCPU. The GWAS results of all four breeds indicate that five genome-wide significant SNPs were associated with ADG, and the nearby genomic regions explained 4.08% of the genetic variance and 1.90% of the phenotypic variance, respectively. For AGE, six genome-wide significant SNPs were detected, and the nearby genomic regions explained 8.09% of the genetic variance and 3.52% of phenotypic variance, respectively. In total, nine candidate genes were identified to be associated with growth and metabolism. Among them, TRIB3 was reported to associate with pig growth, GRP, TTR, CNR1, GLP1R, BRD2, HCRTR2, SEC11C, and ssc-mir-122 were reported to associate with growth traits in human and mouse. The newly detected candidate genes will advance the understanding of growth related traits and the identification of the novel variants will suggest a potential use in pig genomic breeding programs.

Association and Functional Analyses Revealed That PPP1R3B Plays an Important Role in the Regulation of Glycogen Content in the Pacific Oyster Crassostrea gigas

The Pacific oyster (Crassostrea gigas) is one of the most important aquaculture species worldwide. Glycogen contributes greatly to the special taste and creamy white color of oysters. Previous genome-wide association studies (GWAS) identified several single nucleotide polymorphism (SNP) sites that were strongly related to glycogen content. Genes within 100 kb upstream and downstream of the associated SNPs were screened. One gene annotated as protein phosphatase 1 regulatory subunit 3B (PPP1R3B), which can promote glycogen synthesis together with protein phosphatase 1 catalytic subunit (PPP1C) in mammals, was selected as a candidate gene in this study. First, full-length CgPPP1R3B was cloned and its function was characterized. The gene expression profiles of CgPPP1R3B in different tissues and seasons showed a close relationship to glycogen content. RNA interference (RNAi) experiments of this gene in vivo showed that decreased CgPPP1R3B levels resulted in lower glycogen contents in the experimental group than in the control group. Co-immunoprecipitation (Co-IP) and yeast two-hybrid (Y2H) assays indicated that CgPPP1R3B can interact with CgPPP1C, glycogen synthase (CgGS) and glycogen phosphorylase (CgGP), thus participating in glycogen metabolism. Co-sedimentation analysis in vitro demonstrated that the CgPPP1R3B protein can bind to glycogen molecules directly, and these results indicated the conserved function of the CgPPP1R3B protein compared to that of mammals. In addition, thirteen SNPs were precisely mapped in this gene. Ten of the thirteen SNPs were confirmed to be significantly (p < 0.05) related to glycogen content in an independent wild population (n = 288). The CgPPP1R3B levels in oysters with high glycogen content were significantly higher than those of oysters with low glycogen content, and gene expression levels were significantly associated with various genotypes of four associated SNPs (p < 0.05). The data indicated that the associated SNPs may control glycogen content by regulating CgPPP1R3B expression. These results suggest that CgPPP1R3B is an important gene for glycogen metabolic regulation and that the associated SNPs of this gene are potential markers for oyster molecular breeding for increased glycogen content.