Development of a Medium Density Combined-Species SNP Array for Pacific and European Oysters (Crassostrea gigas and Ostrea edulis)

A multiplexed plant-animal SNP array for selective breeding and species conservation applications

Reliable and high-throughput genotyping platforms are of immense importance for identifying and dissecting genomic regions controlling important phenotypes, supporting selection processes in breeding programs, and managing wild populations and germplasm collections. Amongst available genotyping tools, single nucleotide polymorphism arrays have been shown to be comparatively easy to use and generate highly accurate genotypic data. Single-species arrays are the most commonly used type so far; however, some multi-species arrays have been developed for closely related species that share single nucleotide polymorphism markers, exploiting inter-species cross-amplification. In this study, the suitability of a multiplexed plant-animal single nucleotide polymorphism array, including both closely and distantly related species, was explored. The performance of the single nucleotide polymorphism array across species for diverse applications, ranging from intra-species diversity assessments to parentage analysis, was assessed. Moreover, the value of genotyping pooled DNA of distantly related species on the single nucleotide polymorphism array as a technique to further reduce costs was evaluated. Single nucleotide polymorphism performance was generally high, and species-specific single nucleotide polymorphisms proved suitable for diverse applications. The multi-species single nucleotide polymorphism array approach reported here could be transferred to other species to achieve cost savings resulting from the increased throughput when several projects use the same array, and the pooling technique adds another highly promising advancement to additionally decrease genotyping costs by half.

Potential of low-density genotype imputation for cost-efficient genomic selection for resistance to Flavobacterium columnare in rainbow trout (Oncorhynchus mykiss)

BACKGROUND

Flavobacterium columnare is the pathogen agent of columnaris disease, a major emerging disease that affects rainbow trout aquaculture. Selective breeding using genomic selection has potential to achieve cumulative improvement of the host resistance. However, genomic selection is expensive partly because of the cost of genotyping large numbers of animals using high-density single nucleotide polymorphism (SNP) arrays. The objective of this study was to assess the efficiency of genomic selection for resistance to F. columnare using in silico low-density (LD) panels combined with imputation. After a natural outbreak of columnaris disease, 2874 challenged fish and 469 fish from the parental generation (n = 81 parents) were genotyped with 27,907 SNPs. The efficiency of genomic prediction using LD panels was assessed for 10 panels of different densities, which were created in silico using two sampling methods, random and equally spaced. All LD panels were also imputed to the full 28K HD panel using the parental generation as the reference population, and genomic predictions were re-evaluated. The potential of prioritizing SNPs that are associated with resistance to F. columnare was also tested for the six lower-density panels.

RESULTS

The accuracies of both imputation and genomic predictions were similar with random and equally-spaced sampling of SNPs. Using LD panels of at least 3000 SNPs or lower-density panels (as low as 300 SNPs) combined with imputation resulted in accuracies that were comparable to those of the 28K HD panel and were 11% higher than the pedigree-based predictions.

CONCLUSIONS

Compared to using the commercial HD panel, LD panels combined with imputation may provide a more affordable approach to genomic prediction of breeding values, which supports a more widespread adoption of genomic selection in aquaculture breeding programmes.

Evaluation of low-density SNP panels and imputation for cost-effective genomic selection in four aquaculture species

Genomic selection can accelerate genetic progress in aquaculture breeding programmes, particularly for traits measured on siblings of selection candidates. However, it is not widely implemented in most aquaculture species, and remains expensive due to high genotyping costs. Genotype imputation is a promising strategy that can reduce genotyping costs and facilitate the broader uptake of genomic selection in aquaculture breeding programmes. Genotype imputation can predict ungenotyped SNPs in populations genotyped at a low-density (LD), using a reference population genotyped at a high-density (HD). In this study, we used datasets of four aquaculture species (Atlantic salmon, turbot, common carp and Pacific oyster), phenotyped for different traits, to investigate the efficacy of genotype imputation for cost-effective genomic selection. The four datasets had been genotyped at HD, and eight LD panels (300-6,000 SNPs) were generated in silico. SNPs were selected to be: i) evenly distributed according to physical position ii) selected to minimise the linkage disequilibrium between adjacent SNPs or iii) randomly selected. Imputation was performed with three different software packages (AlphaImpute2, FImpute v.3 and findhap v.4). The results revealed that FImpute v.3 was faster and achieved higher imputation accuracies. Imputation accuracy increased with increasing panel density for both SNP selection methods, reaching correlations greater than 0.95 in the three fish species and 0.80 in Pacific oyster. In terms of genomic prediction accuracy, the LD and the imputed panels performed similarly, reaching values very close to the HD panels, except in the pacific oyster dataset, where the LD panel performed better than the imputed panel. In the fish species, when LD panels were used for genomic prediction without imputation, selection of markers based on either physical or genetic distance (instead of randomly) resulted in a high prediction accuracy, whereas imputation achieved near maximal prediction accuracy independently of the LD panel, showing higher reliability. Our results suggests that, in fish species, well-selected LD panels may achieve near maximal genomic selection prediction accuracy, and that the addition of imputation will result in maximal accuracy independently of the LD panel. These strategies represent effective and affordable methods to incorporate genomic selection into most aquaculture settings.

SNP discovery and genetic structure in blue mussel species using low coverage sequencing and a medium density 60 K SNP-array

Blue mussels from the genus Mytilus are an abundant component of the benthic community, found in the high latitude habitats. These foundation species are relevant to the aquaculture industry, with over 2 million tonnes produced globally each year. Mussels withstand a wide range of environmental conditions and species from the Mytilus edulis complex readily hybridize in regions where their distributions overlap. Significant effort has been made to investigate the consequences of environmental stress on mussel physiology, reproductive isolation, and local adaptation. Yet our understanding on the genomic mechanisms underlying such processes remains limited. In this study, we developed a multi species medium-density 60 K SNP-array including four species of the Mytilus genus. SNPs included in the platform were called from 138 mussels from 23 globally distributed mussel populations, sequenced using a whole-genome low coverage approach. The array contains polymorphic SNPs which capture the genetic diversity present in mussel populations thriving across a gradient of environmental conditions (~59 K SNPs) and a set of published and validated SNPs informative for species identification and for diagnosis of transmissible cancer (610 SNPs). The array will allow the consistent genotyping of individuals, facilitating the investigation of ecological and evolutionary processes in these taxa. The applications of this array extend to shellfish aquaculture, contributing to the optimization of this industry via genomic selection of blue mussels, parentage assignment, inbreeding assessment and traceability. Further applications such as genome wide association studies (GWAS) for key production traits and those related to environmental resilience are especially relevant to safeguard aquaculture production under climate change.

Chromosome-level genome assembly of the European flat oyster (Ostrea edulis) provides insights into its evolution and adaptation

The European flat oyster (Ostrea edulis) is an endangered and economically important marine bivalve species that plays a critical role in the coastal ecosystem. Here, we report a high-quality chromosome-level genome assembly of O. edulis, generated using PacBio HiFi-CCS long reads and annotated with Nanopore full-length transcriptome. The O. edulis genome covers 946.06 Mb (scaffold N50 94.82 Mb) containing 34,495 protein-coding genes and a high proportion of repeat sequences (58.49 %). The reconstructed demographic histories show that O. edulis population might be shaped by breeding habit (embryo brooding) and historical climatic change. Comparative genomic analysis indicates that transposable elements may drive lineage-specific evolution in oysters. Notably, the O. edulis genome has a Hox gene cluster rearrangement that has never been reported in bivalves, making this species valuable for evolutionary studies of molluscan diversification. Moreover, genome expansion of O. edulis is probably central to its adaptation to filter-feeding and sessile lifestyles, as well as embryo brooding and pathogen resistance, in coastal ecosystems. This chromosome-level genome assembly provides new insights into the genome feature of oysters, and presents an important resource for genetic research, evolutionary studies, and biological conservation of O. edulis.

Development and Evaluation of High-Density SNP Arrays for the Eastern Oyster Crassostrea virginica

The eastern oyster Crassostrea virginica is a major aquaculture species for the USA. The sustainable development of eastern oyster aquaculture depends upon the continued improvement of cultured stocks through advanced breeding technologies. The Eastern Oyster Breeding Consortium (EOBC) was formed to advance the genetics and breeding of the eastern oyster. To facilitate efficient genotyping needed for genomic studies and selection, the consortium developed two single-nucleotide polymorphism (SNP) arrays for the eastern oyster: one screening array with 566K SNPs and one breeders' array with 66K SNPs. The 566K screening array was developed based on whole-genome resequencing data from 292 oysters from Atlantic and Gulf of Mexico populations; it contains 566,262 SNPs including 47K from protein-coding genes with a marker conversion rate of 48.34%. The 66K array was developed using best-performing SNPs from the screening array, which contained 65,893 oyster SNPs including 22,984 genic markers with a calling rate of 99.34%, a concordance rate of 99.81%, and a much-improved marker conversion rate of 92.04%. Null alleles attributable to large indels were found in 13.1% of the SNPs, suggesting that copy number variation is pervasive. Both arrays provided easy identification and separation of selected stocks from wild progenitor populations. The arrays contain 31 mitochondrial SNPs that allowed unambiguous identification of Gulf mitochondrial genotypes in some Atlantic populations. The arrays also contain 756 probes from 13 oyster and human pathogens for possible detection. Our results show that marker conversion rate is low in high polymorphism species and that the two-step process of array development can greatly improve array performance. The two arrays will advance genomic research and accelerate genetic improvement of the eastern oyster by delineating genetic architecture of production traits and enabling genomic selection. The arrays also may be used to monitor pedigree and inbreeding, identify selected stocks and their introgression into wild populations, and assess the success of oyster restoration.

Pooled resequencing of larvae and adults reveals genomic variations associated with Ostreid herpesvirus 1 resistance in the Pacific oyster Crassostrea gigas

The Ostreid herpesvirus 1 (OsHV-1) is a lethal pathogen of the Pacific oyster (Crassostrea gigas), an important aquaculture species. To understand the genetic architecture of the defense against the pathogen, we studied genomic variations associated with herpesvirus-caused mortalities by pooled whole-genome resequencing of before and after-mortality larval samples as well as dead and surviving adults from a viral challenge. Analysis of the resequencing data identified 5,271 SNPs and 1,883 genomic regions covering 3,111 genes in larvae, and 18,692 SNPs and 28,314 regions covering 4,863 genes in adults that were significantly associated with herpesvirus-caused mortalities. Only 1,653 of the implicated genes were shared by larvae and adults, suggesting that the antiviral response or resistance in larvae and adults involves different sets of genes or differentiated members of expanded gene families. Combined analyses with previous transcriptomic data from challenge experiments revealed that transcription of many mortality-associated genes was also significantly upregulated by herpesvirus infection confirming their importance in antiviral response. Key immune response genes especially those encoding antiviral receptors such as TLRs and RLRs displayed strong association between variation in regulatory region and herpesvirus-caused mortality, suggesting they may confer resistance through transcriptional modulation. These results point to previously undescribed genetic mechanisms for disease resistance at different developmental stages and provide candidate polymorphisms and genes that are valuable for understanding antiviral immune responses and breeding for herpesvirus resistance.

A single genomic region involving a putative chromosome rearrangement in flat oyster ( Ostrea edulis ) is associated with differential host resilience to the parasite Bonamia ostreae

European flat oyster (Ostrea edulis) is an ecologically and economically important marine bivalve, that has been severely affected by the intracellular parasite Bonamia ostreae. In this study, a flat oyster SNP array (~14,000 SNPs) was used to validate previously reported outlier loci for divergent selection associated with B. ostreae exposure in the Northeast Atlantic Area. A total of 134 wild and hatchery individuals from the North Sea, collected in naïve (NV) and long‐term affected (LTA) areas, were analysed. Genetic diversity and differentiation were related to the sampling origin (wild vs. hatchery) when using neutral markers, and to bonamiosis status (NV vs. LTA) when using outlier loci for divergent selection. Two genetic clusters appeared intermingled in all sampling locations when using outlier loci, and their frequency was associated with their bonamiosis status. When both clusters were compared, outlier data sets showed high genetic divergence (F_ST > 0.25) unlike neutral loci (F_ST not ≠ 0). Moreover, the cluster associated with LTA samples showed much higher genetic diversity and significant heterozygote excess with outlier loci, but not with neutral data. Most outliers mapped on chromosome 8 (OE‐C8) of the flat oyster genome, supporting a main genomic region underlying resilience to bonamiosis. Furthermore, differentially expressed genes previously reported between NV and LTA strains showed higher mapping density on OE‐C8. A range of relevant immune functions were specifically enriched among genes annotated on OE‐C8, providing hypotheses for resilience mechanisms to an intracellular parasite. The results suggest that marker‐assisted selection could be applied to breed resilient strains of O. edulis to bonamiosis, if lower parasite load and/or higher viability of the LTA genetic cluster following B. ostreae infection is demonstrated.

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.

Genomic survey of edible cockle ( Cerastoderma edule ) in the Northeast Atlantic: a baseline for sustainable management of its wild resources

Knowledge on correlations between environmental factors and genome divergence between populations of marine species is crucial for sustainable management of fisheries and wild populations. The edible cockle (Cerastoderma edule) is a marine bivalve distributed along the Northeast Atlantic coast of Europe and is an important resource from both commercial and ecological perspectives. We performed a population genomics screening using 2b‐RAD genotyping on 9309 SNPs localized in the cockle's genome on a sample of 536 specimens pertaining to 14 beds in the Northeast Atlantic Ocean to analyse the genetic structure with regard to environmental variables. Larval dispersal modelling considering species behaviour and interannual/interseasonal variation in ocean conditions was carried out as an essential background to which compare genetic information. Cockle populations in the Northeast Atlantic displayed low but significant geographical differentiation between populations (F_ST = 0.0240; p < 0.001), albeit not across generations. We identified 742 and 36 outlier SNPs related to divergent and balancing selection in all the geographical scenarios inspected, and sea temperature and salinity were the main environmental correlates suggested. Highly significant linkage disequilibrium was detected at specific genomic regions against the very low values observed across the whole genome. Two main genetic groups were identified, northwards and southwards of French Brittany. Larval dispersal modelling suggested a barrier for larval dispersal linked to the Ushant front that could explain these two genetic clusters. Further genetic subdivision was observed using outlier loci and considering larval advection. The northern group was divided into the Irish/Celtic Seas and the English Channel/North Sea, while the southern group was divided into three subgroups. This information represents the baseline for the management of cockles, designing conservation strategies, founding broodstock for depleted beds and producing suitable seed for aquaculture production.

Design and performance of a bovine 200 k SNP chip developed for endangered German Black Pied cattle (DSN)

BACKGROUND

German Black Pied cattle (DSN) are an endangered dual-purpose breed which was largely replaced by Holstein cattle due to their lower milk yield. DSN cattle are kept as a genetic reserve with a current herd size of around 2500 animals. The ability to track sequence variants specific to DSN could help to support the conservation of DSN's genetic diversity and to provide avenues for genetic improvement.

RESULTS

Whole-genome sequencing data of 304 DSN cattle were used to design a customized DSN200k SNP chip harboring 182,154 variants (173,569 SNPs and 8585 indels) based on ten selection categories. We included variants of interest to DSN such as DSN unique variants and variants from previous association studies in DSN, but also variants of general interest such as variants with predicted consequences of high, moderate, or low impact on the transcripts and SNPs from the Illumina BovineSNP50 BeadChip. Further, the selection of variants based on haplotype blocks ensured that the whole-genome was uniformly covered with an average variant distance of 14.4 kb on autosomes. Using 300 DSN and 162 animals from other cattle breeds including Holstein, endangered local cattle populations, and also a Bos indicus breed, performance of the SNP chip was evaluated. Altogether, 171,978 (94.31%) of the variants were successfully called in at least one of the analyzed breeds. In DSN, the number of successfully called variants was 166,563 (91.44%) while 156,684 (86.02%) were segregating at a minor allele frequency > 1%. The concordance rate between technical replicates was 99.83 ± 0.19%.

CONCLUSION

The DSN200k SNP chip was proved useful for DSN and other Bos taurus as well as one Bos indicus breed. It is suitable for genetic diversity management and marker-assisted selection of DSN animals. Moreover, variants that were segregating in other breeds can be used for the design of breed-specific customized SNP chips. This will be of great value in the application of conservation programs for endangered local populations in the future.

A 2b-RAD parentage analysis pipeline for complex and mixed DNA samples

Next-generation sequencing technology has revolutionized genotyping in many fields of study, yet parentage analysis often still relies on microsatellite markers that are costly to generate and are currently available only for a limited number of species. 2b-RAD sequencing (2b-RAD) is a DNA sequencing technique developed for ecological population genomics that utilizes type IIB restriction enzymes to generate consistent, uniform fragments across samples. This technology is inexpensive, effective with low DNA inputs, and robust to DNA degradation. Here, we developed a probabilistic genotyping-by-sequencing genetic testing pipeline for parentage analysis by using 2b-RAD for inferring familial relationships from mixed DNA samples and populations. Our approach to partial paternity assignment utilizes a novel weighted outlier paternity index (WOPI) adapted for next-generation sequencing data and an identity-by-state (IBS) matrix-based clustering method for pedigree reconstruction. The combination of these two parentage assignment methods overcomes two major obstacles faced by other genetic testing methods: 1) It allows detection of parentage when closely related or inbred individuals are in the alleged parent population (e.g., in laboratory strains); and 2) it resolves mixed DNA samples. We successfully demonstrate this novel approach by correctly inferring paternity for samples pooled from multiple offspring (i.e., entire clutches) in a highly inbred population of an East African cichlid fish. The unique advantages of 2b-RAD in combination with our bioinformatics pipeline enable straightforward and cost-effective parentage analysis in any species regardless of genomic resources available.

Ancestral Physical Stress and Later Immune Gene Family Expansions Shaped Bivalve Mollusc Evolution

Bivalve molluscs comprise 20,000 species occupying a wide diversity of marine habitats. As filter feeders and detritivores they act as ecosystem engineers clarifying water, creating reefs, and protecting coastlines. The global decline of natural oyster reefs has led to increased restoration efforts in recent years. Bivalves also play an important role in global food security contributing to >20% of worldwide aquaculture production. Despite this importance, relatively little is known about bivalve evolutionary adaptation strategies. Difficulties previously associated with highly heterozygous and repetitive regions of bivalve genomes have been overcome by long-read sequencing, enabling the generation of accurate bivalve assemblies. With these resources we have analyzed the genomes of 32 species representing each molluscan class, including 15 bivalve species, to identify gene families that have undergone expansion during bivalve evolution. Gene family expansions across bivalve genomes occur at the point of evolutionary pressures. We uncovered two key factors that shape bivalve evolutionary history: expansion of bivalvia into environmental niches with high stress followed by later exposure to specific pathogenic pressures. The conserved expansion of protein recycling gene families we found across bivalvia is mirrored by adaptations to a sedentary lifestyle seen in plants. These results reflect the ability of bivalves to tolerate high levels of environmental stress and constant exposure to pathogens as filter feeders. The increasing availability of accurate genome assemblies will provide greater resolution to these analyses allowing further points of evolutionary pressure to become clear in other understudied taxa and potentially different populations of a single species.

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'.

Construction of a chromosome-level genome and variation map for the Pacific oyster Crassostrea gigas

The Pacific oyster (Crassostrea gigas) is a widely distributed marine bivalve of great ecological and economic importance. In this study, we provide a high-quality chromosome-level genome assembled using Pacific Bioscience long reads and Hi-C-based and linkage-map-based scaffolding technologies and a high-resolution variation map constructed using large-scale resequencing analysis. The 586.8 Mb genome consists of 10 pseudochromosome sequences ranging from 38.6 to 78.9 Mb, containing 301 contigs with an N50 size of 3.1 Mb. A total of 30,078 protein-coding genes were predicted, of which 22,757 (75.7%) were high-reliability annotations supported by a homologous match to a curated protein in the SWISS-PROT database or transcript expression. Although a medium level of repeat components (57.2%) was detected, the genomic content of the segmental duplications reached 26.2%, which is the highest among the reported genomes. By whole genome resequencing analysis of 495 Pacific oysters, a comprehensive variation map was built, comprised of 4.78 million single nucleotide polymorphisms, 0.60 million short insertions and deletions, and 49,333 copy number variation regions. The structural variations can lead to an average interindividual genomic divergence of 0.21, indicating their crucial role in shaping the Pacific oyster genome diversity. The large amount of mosaic distributed repeat elements, small variations, and copy number variations indicate that the Pacific oyster is a diploid organism with an extremely high genomic complexity at the intra- and interindividual level. The genome and variation maps can improve our understanding of oyster genome diversity and enrich the resources for oyster molecular evolution, comparative genomics, and genetic research.

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.

The Pacific Oyster Mortality Syndrome, a Polymicrobial and Multifactorial Disease: State of Knowledge and Future Directions

The Pacific oyster (Crassostreae gigas) has been introduced from Asia to numerous countries around the world during the 20th century. C. gigas is the main oyster species farmed worldwide and represents more than 98% of oyster production. The severity of disease outbreaks that affect C. gigas, which primarily impact juvenile oysters, has increased dramatically since 2008. The most prevalent disease, Pacific oyster mortality syndrome (POMS), has become panzootic and represents a threat to the oyster industry. Recently, major steps towards understanding POMS have been achieved through integrative molecular approaches. These studies demonstrated that infection by Ostreid herpesvirus type 1 µVar (OsHV-1 µvar) is the first critical step in the infectious process and leads to an immunocompromised state by altering hemocyte physiology. This is followed by dysbiosis of the microbiota, which leads to a secondary colonization by opportunistic bacterial pathogens, which in turn results in oyster death. Host and environmental factors (e.g. oyster genetics and age, temperature, food availability, and microbiota) have been shown to influence POMS permissiveness. However, we still do not understand the mechanisms by which these different factors control disease expression. The present review discusses current knowledge of this polymicrobial and multifactorial disease process and explores the research avenues that must be investigated to fully elucidate the complexity of POMS. These discoveries will help in decision-making and will facilitate the development of tools and applied innovations for the sustainable and integrated management of oyster aquaculture.

Development and Evaluation of a High-Throughput Single-Nucleotide Polymorphism Array for Large Yellow Croaker (Larimichthys crocea)

High-density single-nucleotide polymorphism (SNP) genotyping array is an essential tool for genetic analyses of animals and plants. Large yellow croaker (Larimichthys crocea) is one of the most commercially important marine fish species in China. Although plenty of SNPs have been identified in large yellow croaker, no high-throughput genotyping array is available. In this study, a high-throughput SNP array named NingXin-I with 600K SNPs was developed and evaluated. A set of 82 large yellow croakers were collected from different locations of China and re-sequenced. A total of 9.34M SNPs were identified by mapping sequence reads to the large yellow croaker reference genome. About 1.98M candidate SNPs were selected for further analyses by using criteria such as SNP quality score and conversion performance in the final array. Finally, 579.5K SNPs evenly distributed across the large yellow croaker genome with an average spacing of 1.19 kb were proceeded to array production. The performance of NingXin-I array was evaluated in 96 large yellow croaker individuals from five populations, and 83.38% SNPs on the array were polymorphic sites. A further test of the NingXin-I array in five closely related species in Sciaenidae identified 26.68–56.23% polymorphic SNP rate across species. A phylogenetic tree inferred by using the genotype data generated by NingXin-I confirmed the phylogenetic distance of the species in Sciaenidae. The performance of NingXin-I in large yellow croaker and the other species in Sciaenidae suggested high accuracy and broad application. The NingXin-I array should be valuable for quantitative genetic studies, such as genome-wide association studies (GWASs), high-density linkage map construction, haplotype analysis, and genome-based selection.

Favorable Conditions for Genomic Evaluation to Outperform Classical Pedigree Evaluation Highlighted by a Proof-of-Concept Study in Poplar

Forest trees like poplar are particular in many ways compared to other domesticated species. They have long juvenile phases, ongoing crop-wild gene flow, extensive outcrossing, and slow growth. All these particularities tend to make the conduction of breeding programs and evaluation stages costly both in time and resources. Perennials like trees are therefore good candidates for the implementation of genomic selection (GS) which is a good way to accelerate the breeding process, by unchaining selection from phenotypic evaluation without affecting precision. In this study, we tried to compare GS to pedigree-based traditional evaluation, and evaluated under which conditions genomic evaluation outperforms classical pedigree evaluation. Several conditions were evaluated as the constitution of the training population by cross-validation, the implementation of multi-trait, single trait, additive and non-additive models with different estimation methods (G-BLUP or weighted G-BLUP). Finally, the impact of the marker densification was tested through four marker density sets. The population under study corresponds to a pedigree of 24 parents and 1,011 offspring, structured into 35 full-sib families. Four evaluation batches were planted in the same location and seven traits were evaluated on 1 and 2 years old trees. The quality of prediction was reported by the accuracy, the Spearman rank correlation and prediction bias and tested with a cross-validation and an independent individual test set. Our results show that genomic evaluation performance could be comparable to the already well-optimized pedigree-based evaluation under certain conditions. Genomic evaluation appeared to be advantageous when using an independent test set and a set of less precise phenotypes. Genome-based methods showed advantages over pedigree counterparts when ranking candidates at the within-family levels, for most of the families. Our study also showed that looking at ranking criteria as Spearman rank correlation can reveal benefits to genomic selection hidden by biased predictions.

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.

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.

Divergent northern and southern populations and demographic history of the pearl oyster in the western Pacific revealed with genomic SNPs

In the open ocean without terrain boundaries, marine invertebrates with pelagic larvae can migrate long distances using ocean currents, suggesting reduced genetic diversification. Contrary to this assumption, however, genetic differentiation is often observed in marine invertebrates. In the present study, we sought to explain how population structure is established in the western Pacific Ocean, where the strong Kuroshio Current maintains high levels of gene flow from south to north, presumably promoting genetic homogeneity. We determined the population structure of the pearl oyster, Pinctada fucata, in the Indo-Pacific Ocean using genome-wide genotyping data from multiple sampling localities. Cluster analysis showed that the western Pacific population is distinct from that of the Indian Ocean, and that it is divided into northern (Japanese mainland) and southern (Nansei Islands, China, and Cambodia) populations. Genetic differentiation of P. fucata can be explained by geographic barriers in the Indian Ocean and a local lagoon, and by environmental gradients of sea surface temperature (SST) and oxygen concentration in the western Pacific. A genome scan showed evidence of adaptive evolution in genomic loci, possibly associated with changes in environmental factors, including SST and oxygen concentration. Furthermore, Bayesian simulation demonstrated that the past population expansion and division are congruent with ocean warming after the last glacial period. It is highly likely that the environmental gradient forms a genetic barrier that diversifies P. fucata populations in the western Pacific. This hypothesis helps to explain genetic differentiation and possible speciation of marine invertebrates.

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.

Differential basal expression of immune genes confers Crassostrea gigas resistance to Pacific oyster mortality syndrome

Background

As a major threat to the oyster industry, Pacific Oyster Mortality Syndrome (POMS) is a polymicrobial disease affecting the main oyster species farmed across the world. POMS affects oyster juveniles and became panzootic this last decade, but POMS resistance in some oyster genotypes has emerged. While we know some genetic loci associated with resistance, the underlying mechanisms remained uncharacterized. So, we developed a comparative transcriptomic approach using basal gene expression profiles between different oyster biparental families with contrasted phenotypes when confronted to POMS (resistant or susceptible).

Results

We showed that POMS resistant oysters show differential expression of genes involved in stress responses, protein modifications, maintenance of DNA integrity and repair, and immune and antiviral pathways. We found similarities and clear differences among different molecular pathways in the different resistant families. These results suggest that the resistance process is polygenic and partially varies according to the oyster genotype.

Conclusions

We found differences in basal expression levels of genes related to TLR-NFκB, JAK-STAT and STING-RLR pathways. These differences could explain the best antiviral response, as well as the robustness of resistant oysters when confronted to POMS. As some of these genes represent valuable candidates for selective breeding, we propose future studies should further examine their function.

Potential for Genetic Improvement of Resistance to Perkinsus olseni in the Manila Clam, Ruditapes philippinarum, Using DNA Parentage Assignment and Mass Spawning

The Manila clam Ruditapes philippinarum, a major cultured shellfish species, is threatened by infection with the microparasite Perkinsus olseni, whose prevalence increases with high water temperatures. Under the current trend of climate change, the already severe effects of this parasitic infection might rapidly increase the frequency of mass mortality events. Treating infectious diseases in bivalves is notoriously problematic, therefore selective breeding for resistance represents a key strategy for mitigating the negative impact of pathogens. A crucial step in initiating selective breeding is the estimation of genetic parameters for traits of interest, which relies on the ability to record parentage and accurate phenotypes in a large number of individuals. Here, to estimate the heritability of resistance against P. olseni, a field experiment mirroring conditions in industrial clam production was set up, a genomic tool was developed for parentage assignment, and parasite load was determined through quantitative PCR. A mixed-family cohort of potentially 1,479 clam families was produced in a hatchery by mass spawning of 53 dams and 57 sires. The progenies were seeded in a commercial clam production area in the Venice lagoon, Italy, where high prevalence of P. olseni had previously been reported. Growth and parasite load were monitored every month and, after 1 year, more than 1,000 individuals were collected for DNA samples and phenotype recording. A pooled sequencing approach was carried out using DNA samples from the hatchery broodstock and from a Venice lagoon clam population, providing candidate markers used to develop a 245-SNP panel. Parentage assignment for 246 F1 individuals showed sire and dam representation were high (75 and 85%, respectively), indicating a very limited risk of inbreeding. Moderate heritability (0.23 ± 0.11-0.35 ± 0.13) was estimated for growth traits (shell length, shell weight, total weight), while parasite load showed high heritability, estimated at 0.51 ± 0.20. No significant genetic correlations were found between growth-associated traits and parasite load. Overall, the preliminary results provided by this study show high potential for selecting clams resistant to parasite load. Breeding for resistance may help limit the negative effects of climate change on clam production, as the prevalence of the parasite is predicted to increase under a future scenario of higher temperatures. Finally, the limited genetic correlation between resistance and growth suggests that breeding programs could incorporate dual selection without negative interactions.

Demonstration of the Use of Environmental DNA for the Non-Invasive Genotyping of a Bivalve Mollusk, the European Flat Oyster (Ostrea edulis)

Accurate SNP (single nucleotide polymorphism) genotype information is critical for a wide range of selective breeding applications in aquaculture, including parentage assignment, marker-assisted, and genomic selection. However, the sampling of tissue for genetic analysis can be invasive for juvenile animals or taxa where sampling tissue is difficult or may cause mortality (e.g. bivalve mollusks). Here, we demonstrate a novel, non-invasive technique for sampling DNA based on the collection of environmental DNA using European Flat Oysters (Ostrea edulis) as an example. The live animals are placed in individual containers until sufficient genetic material is released into the seawater which is then recovered by filtration. We compared the results of tissue and eDNA derived SNP genotype calls using a PCR based genotyping platform. We found that 100% accurate genotype calls from eDNA are possible, but depend on appropriate filtration and the dilution of the sample throughout the workflow. We also developed an additional low-cost DNA extraction technique which provided >99% correct SNP genotype calls in comparison to tissue. It was concluded that eDNA sampling can be used in hatchery and selective breeding programs applicable to any aquatic organism for which direct tissue sampling may result in animal welfare concerns or mortality.

Signatures of selection for bonamiosis resistance in European flat oyster (Ostrea edulis): New genomic tools for breeding programs and management of natural resources

The European flat oyster (Ostrea edulis) is a highly appreciated mollusk with an important aquaculture production throughout the 20th century, in addition to playing an important role on coastal ecosystems. Overexploitation of natural beds, habitat degradation, introduction of non-native species, and epidemic outbreaks have severely affected this important resource, particularly, the protozoan parasite Bonamia ostreae, which is the main concern affecting its production and conservation. In order to identify genomic regions and markers potentially associated with bonamiosis resistance, six oyster beds distributed throughout the European Atlantic coast were sampled. Three of them have been exposed to this parasite since the early 1980s and showed some degree of innate resistance (long-term affected group, LTA), while the other three were free of B. ostreae at least until sampling date (naïve group, NV). A total of 14,065 SNPs were analyzed, including 37 markers from candidate genes and 14,028 from a medium-density SNP array. Gene diversity was similar between LTA and NV groups suggesting no genetic erosion due to long-term exposure to the parasite, and three population clusters were detected using the whole dataset. Tests for divergent selection between NV and LTA groups detected the presence of a very consistent set of 22 markers, located within a putative single genomic region, which suggests the presence of a major quantitative trait locus associated with B. ostreae resistance. Moreover, 324 outlier loci associated with factors other than bonamiosis were identified allowing fully discrimination of all the oyster beds. A practical tool which included the 84 highest discriminative markers for tracing O. edulis populations was developed and tested with empirical data. Results reported herein could assist the production of stocks with improved resistance to bonamiosis and facilitate the management of oyster beds for recovery production and ecosystem services provided by this species.

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.

A-to-I editing of Malacoherpesviridae RNAs supports the antiviral role of ADAR1 in mollusks

Background

Adenosine deaminase enzymes of the ADAR family are conserved in metazoans. They convert adenine into inosine in dsRNAs and thus alter both structural properties and the coding potential of their substrates. Acting on exogenous dsRNAs, ADAR1 exerts a pro- or anti-viral role in vertebrates and Drosophila.

Results

We traced 4 ADAR homologs in 14 lophotrochozoan genomes and we classified them into ADAD, ADAR1 or ADAR2, based on phylogenetic and structural analyses of the enzymatic domain. Using RNA-seq and quantitative real time PCR we demonstrated the upregulation of one ADAR1 homolog in the bivalve Crassostrea gigas and in the gastropod Haliotis diversicolor supertexta during Ostreid herpesvirus-1 or Haliotid herpesvirus-1 infection. Accordingly, we demonstrated an extensive ADAR-mediated editing of viral RNAs. Single nucleotide variation (SNV) profiles obtained by pairing RNA- and DNA-seq data from the viral infected individuals resulted to be mostly compatible with ADAR-mediated A-to-I editing (up to 97%). SNVs occurred at low frequency in genomic hotspots, denoted by the overlapping of viral genes encoded on opposite DNA strands. The SNV sites and their upstream neighbor nucleotide indicated the targeting of selected adenosines. The analysis of viral sequences suggested that, under the pressure of the ADAR editing, the two Malacoherpesviridae genomes have evolved to reduce the number of deamination targets.

Conclusions

We report, for the first time, evidence of an extensive editing of Malacoherpesviridae RNAs attributable to host ADAR1 enzymes. The analysis of base neighbor preferences, structural features and expression profiles of molluscan ADAR1 supports the conservation of the enzyme function among metazoans and further suggested that ADAR1 exerts an antiviral role in mollusks.

Electronic supplementary material

The online version of this article (10.1186/s12862-019-1472-6) contains supplementary material, which is available to authorized users.

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.

Design and characterization of an 87k SNP genotyping array for Arctic charr (Salvelinus alpinus)

We have generated a high-density, high-throughput genotyping array for characterizing genome-wide variation in Arctic charr (Salvelinus alpinus). Novel single nucleotide polymorphisms (SNPs) were identified in charr from the Fraser, Nauyuk and Tree River aquaculture strains, which originated from northern Canada and fish from Iceland using high coverage sequencing, reduced representation sequencing and RNA-seq datasets. The array was designed to capture genome-wide variation from a diverse suite of Arctic charr populations. Cross validation of SNPs from various sources and comparison with previously published Arctic charr SNP data provided a set of candidate SNPs that generalize across populations. Further candidate SNPs were identified based on minor allele frequency, association with RNA transcripts, even spacing across intergenic regions and association with the sex determining (sdY) gene. The performance of the 86,503 SNP array was assessed by genotyping Fraser, Nauyuk and Tree River strain individuals, as well as wild Icelandic Arctic charr. Overall, 63,060 of the SNPs were polymorphic within at least one group and 36.8% were unique to one of the four groups, suggesting that the array design allows for characterization of both within and across population genetic diversity. The concordance between sdY markers and known phenotypic sex indicated that the array can accurately determine the sex of individuals based on genotype alone. The Salp87k genotyping array provides researchers and breeders the opportunity to analyze genetic variation in Arctic charr at a more detailed level than previously possible.

Seascape genomics of eastern oyster (Crassostrea virginica) along the Atlantic coast of Canada

Interactions between environmental factors and complex life-history characteristics of marine organisms produce the genetic diversity and structure observed within species. Our main goal was to test for genetic differentiation among eastern oyster populations from the coastal region of Canadian Maritimes against expected genetic homogeneity caused by historical events, taking into account spatial and environmental (temperature, salinity, turbidity) variation. This was achieved by genotyping 486 individuals originating from 13 locations using RADSeq. A total of 11,321 filtered SNPs were used in a combination of population genomics and environmental association analyses. We revealed significant neutral genetic differentiation (mean F ST = 0.009) between sampling locations, and the occurrence of six major genetic clusters within the studied system. Redundancy analyses (RDAs) revealed that spatial and environmental variables explained 3.1% and 4.9% of the neutral genetic variation and 38.6% and 12.2% of the putatively adaptive genetic variation, respectively. These results indicate that these environmental factors play a role in the distribution of both neutral and putatively adaptive genetic diversity in the system. Moreover, polygenic selection was suggested by genotype-environment association analysis and significant correlations between additive polygenic scores and temperature and salinity. We discuss our results in the context of their conservation and management implications for the eastern oyster.

Detailed insights into pan-European population structure and inbreeding in wild and hatchery Pacific oysters (Crassostrea gigas) revealed by genome-wide SNP data

Cultivated bivalves are important not only because of their economic value, but also due to their impacts on natural ecosystems. The Pacific oyster (Crassostrea gigas) is the world's most heavily cultivated shellfish species and has been introduced to all continents except Antarctica for aquaculture. We therefore used a medium-density single nucleotide polymorphism (SNP) array to investigate the genetic structure of this species in Europe, where it was introduced during the 1960s and has since become a prolific invader of coastal ecosystems across the continent. We analyzed 21,499 polymorphic SNPs in 232 individuals from 23 localities spanning a latitudinal cline from Portugal to Norway and including the source populations of Japan and Canada. We confirmed the results of previous studies by finding clear support for a southern and a northern group, with the former being indistinguishable from the source populations indicating the absence of a pronounced founder effect. We furthermore conducted a large-scale comparison of oysters sampled from the wild and from hatcheries to reveal substantial genetic differences including significantly higher levels of inbreeding in some but not all of the sampled hatchery cohorts. These findings were confirmed by a smaller but representative SNP dataset generated using restriction site-associated DNA sequencing. We therefore conclude that genomic approaches can generate increasingly detailed insights into the genetics of wild and hatchery produced Pacific oysters.

The future of parentage analysis: From microsatellites to SNPs and beyond

Parentage analysis is a cornerstone of molecular ecology that has delivered fundamental insights into behaviour, ecology and evolution. Microsatellite markers have long been the king of parentage, their hypervariable nature conferring sufficient power to correctly assign offspring to parents. However, microsatellite markers have seen a sharp decline in use with the rise of next-generation sequencing technologies, especially in the study of population genetics and local adaptation. The time is ripe to review the current state of parentage analysis and see how it stands to be affected by the emergence of next-generation sequencing approaches. We find that single nucleotide polymorphisms (SNPs), the typical next-generation sequencing marker, remain underutilized in parentage analysis but are gaining momentum, with 58 SNP-based parentage analyses published thus far. Many of these papers, particularly the earlier ones, compare the power of SNPs and microsatellites in a parentage context. In virtually every case, SNPs are at least as powerful as microsatellite markers. As few as 100-500 SNPs are sufficient to resolve parentage completely in most situations. We also provide an overview of the analytical programs that are commonly used and compatible with SNP data. As the next-generation parentage enterprise grows, a reliance on likelihood and Bayesian approaches, as opposed to strict exclusion, will become increasingly important. We discuss some of the caveats surrounding the use of next-generation sequencing data for parentage analysis and conclude that the future is bright for this important realm of molecular ecology.

Genomic Selection in Aquaculture: Application, Limitations and Opportunities With Special Reference to Marine Shrimp and Pearl Oysters

Within aquaculture industries, selection based on genomic information (genomic selection) has the profound potential to change genetic improvement programs and production systems. Genomic selection exploits the use of realized genomic relationships among individuals and information from genome-wide markers in close linkage disequilibrium with genes of biological and economic importance. We discuss the technical advances, practical requirements, and commercial applications that have made genomic selection feasible in a range of aquaculture industries, with a particular focus on molluscs (pearl oysters, Pinctada maxima) and marine shrimp (Litopenaeus vannamei and Penaeus monodon). The use of low-cost genome sequencing has enabled cost-effective genotyping on a large scale and is of particular value for species without a reference genome or access to commercial genotyping arrays. We highlight the pitfalls and offer the solutions to the genotyping by sequencing approach and the building of appropriate genetic resources to undertake genomic selection from first-hand experience. We describe the potential to capture large-scale commercial phenotypes based on image analysis and artificial intelligence through machine learning, as inputs for calculation of genomic breeding values. The application of genomic selection over traditional aquatic breeding programs offers significant advantages through being able to accurately predict complex polygenic traits including disease resistance; increasing rates of genetic gain; minimizing inbreeding; and negating potential limiting effects of genotype by environment interactions. Further practical advantages of genomic selection through the use of large-scale communal mating and rearing systems are highlighted, as well as presenting rate-limiting steps that impact on attaining maximum benefits from adopting genomic selection. Genomic selection is now at the tipping point where commercial applications can be readily adopted and offer significant short- and long-term solutions to sustainable and profitable aquaculture industries.

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

Pacific oysters are a key aquaculture species globally, and genetic improvement via selective breeding is a major target. Genomic selection has the potential to expedite genetic gain for key target traits of a breeding program, but has not yet been evaluated in oyster. The recent development of SNP arrays for Pacific oyster (Crassostrea gigas) raises the opportunity to test genomic selection strategies for polygenic traits. In this study, a population of 820 oysters (comprising 23 full-sibling families) were genotyped using a medium density SNP array (23 K informative SNPs), and the genetic architecture of growth-related traits [shell height (SH), shell length (SL), and wet weight (WW)] was evaluated. Heritability was estimated to be moderate for the three traits (0.26 ± 0.06 for SH, 0.23 ± 0.06 for SL and 0.35 ± 0.05 for WW), and results of a GWAS indicated that the underlying genetic architecture was polygenic. Genomic prediction approaches were used to estimate breeding values for growth, and compared to pedigree based approaches. The accuracy of the genomic prediction models (GBLUP) outperformed the traditional pedigree approach (PBLUP) by ∼25% for SL and WW, and ∼30% for SH. Further, reduction in SNP marker density had little impact on prediction accuracy, even when density was reduced to a few hundred SNPs. These results suggest that the use of genomic selection in oyster breeding could offer benefits for the selection of breeding candidates to improve complex economic traits at relatively modest cost.

Genomic Tools and Selective Breeding in Molluscs

The production of most farmed molluscs, including mussels, oysters, scallops, abalone, and clams, is heavily dependent on natural seed from the plankton. Closing the lifecycle of species in hatcheries can secure independence from wild stocks and enables long-term genetic improvement of broodstock through selective breeding. Genomic techniques have the potential to revolutionize hatchery-based selective breeding by improving our understanding of the characteristics of mollusc genetics that can pose a challenge for intensive aquaculture and by providing a new suite of tools for genetic improvement. Here we review characteristics of the life history and genetics of molluscs including high fecundity, self-fertilization, high genetic diversity, genetic load, high incidence of deleterious mutations and segregation distortion, and critically assess their impact on the design and effectiveness of selective breeding strategies. A survey of the results of current breeding programs in the literature show that selective breeding with inbreeding control is likely the best strategy for genetic improvement of most molluscs, and on average growth rate can be improved by 10% per generation and disease resistance by 15% per generation across the major farmed species by implementing individual or family-based selection. Rapid advances in sequencing technology have resulted in a wealth of genomic resources for key species with the potential to greatly improve hatchery-based selective breeding of molluscs. In this review, we catalog the range of genomic resources currently available for molluscs of aquaculture interest and discuss the bottlenecks, including lack of high-quality reference genomes and the relatively high cost of genotyping, as well as opportunities for applying genomics-based selection.

A New Single Nucleotide Polymorphism Database for Rainbow Trout Generated Through Whole Genome Resequencing

Single-nucleotide polymorphisms (SNPs) are highly abundant markers, which are broadly distributed in animal genomes. For rainbow trout (Oncorhynchus mykiss), SNP discovery has been previously done through sequencing of restriction-site associated DNA (RAD) libraries, reduced representation libraries (RRL) and RNA sequencing. Recently we have performed high coverage whole genome resequencing with 61 unrelated samples, representing a wide range of rainbow trout and steelhead populations, with 49 new samples added to 12 aquaculture samples from AquaGen (Norway) that we previously used for SNP discovery. Of the 49 new samples, 11 were double-haploid lines from Washington State University (WSU) and 38 represented wild and hatchery populations from a wide range of geographic distribution and with divergent migratory phenotypes. We then mapped the sequences to the new rainbow trout reference genome assembly (GCA_002163495.1) which is based on the Swanson YY doubled haploid line. Variant calling was conducted with FreeBayes and SAMtools mpileup, followed by filtering of SNPs based on quality score, sequence complexity, read depth on the locus, and number of genotyped samples. Results from the two variant calling programs were compared and genotypes of the double haploid samples were used for detecting and filtering putative paralogous sequence variants (PSVs) and multi-sequence variants (MSVs). Overall, 30,302,087 SNPs were identified on the rainbow trout genome 29 chromosomes and 1,139,018 on unplaced scaffolds, with 4,042,723 SNPs having high minor allele frequency (MAF > 0.25). The average SNP density on the chromosomes was one SNP per 64 bp, or 15.6 SNPs per 1 kb. Results from the phylogenetic analysis that we conducted indicate that the SNP markers contain enough population-specific polymorphisms for recovering population relationships despite the small sample size used. Intra-Population polymorphism assessment revealed high level of polymorphism and heterozygosity within each population. We also provide functional annotation based on the genome position of each SNP and evaluate the use of clonal lines for filtering of PSVs and MSVs. These SNPs form a new database, which provides an important resource for a new high density SNP array design and for other SNP genotyping platforms used for genetic and genomics studies of this iconic salmonid fish species.

A Genome-Wide Association Study for Host Resistance to Ostreid Herpesvirus in Pacific Oysters (Crassostrea gigas)

Ostreid herpesvirus (OsHV) can cause mass mortality events in Pacific oyster aquaculture. While various factors impact on the severity of outbreaks, it is clear that genetic resistance of the host is an important determinant of mortality levels. This raises the possibility of selective breeding strategies to improve the genetic resistance of farmed oyster stocks, thereby contributing to disease control. Traditional selective breeding can be augmented by use of genetic markers, either via marker-assisted or genomic selection. The aim of the current study was to investigate the genetic architecture of resistance to OsHV in Pacific oyster, to identify genomic regions containing putative resistance genes, and to inform the use of genomics to enhance efforts to breed for resistance. To achieve this, a population of ∼1,000 juvenile oysters were experimentally challenged with a virulent form of OsHV, with samples taken from mortalities and survivors for genotyping and qPCR measurement of viral load. The samples were genotyped using a recently-developed SNP array, and the genotype data were used to reconstruct the pedigree. Using these pedigree and genotype data, the first high density linkage map was constructed for Pacific oyster, containing 20,353 SNPs mapped to the ten pairs of chromosomes. Genetic parameters for resistance to OsHV were estimated, indicating a significant but low heritability for the binary trait of survival and also for viral load measures (h2 0.12 – 0.25). A genome-wide association study highlighted a region of linkage group 6 containing a significant QTL affecting host resistance. These results are an important step toward identification of genes underlying resistance to OsHV in oyster, and a step toward applying genomic data to enhance selective breeding for disease resistance in oyster aquaculture.