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

Cost-effective genomic prediction of critical economic traits in sturgeons through low-coverage sequencing

Low-coverage whole-genome sequencing (LCS) offers a cost-effective alternative for sturgeon breeding, especially given the lack of SNP chips and the high costs associated with whole-genome sequencing. In this study, the efficiency of LCS for genotype imputation and genomic prediction was assessed in 643 sequenced Russian sturgeons (∼13.68×). The results showed that using BaseVar+STITCH at a sequencing depth of 2× with a sample size larger than 300 resulted in the highest genotyping accuracy. In addition, when the sequencing depth reached 0.5× and SNP density was reduced to 50 K through linkage disequilibrium pruning, the prediction accuracy was comparable to that of whole sequencing depth. Furthermore, an incremental feature selection method has the potential to improve prediction accuracy. This study suggests that the combination of LCS and imputation can be a cost-effective strategy, contributing to the genetic improvement of economic traits and promoting genetic gains in aquaculture species.

A high-density linkage map and sex-determination loci in Pacific white shrimp (Litopenaeus vannamei)

BACKGROUND

Expansion of genomic resources for the Pacific white shrimp (Litopenaeus vannamei), such as the construction of dense genetic linkage maps, is crucial for the application of genomic tools in order to improve economically relevant traits. Sexual dimorphism exists in Pacific white shrimp, and the mapping of the sex-determination region in this species may help in future reproductive applications. We have constructed male, female, and sex-averaged high-density genetic maps using a 50 K single-nucleotide polymorphism (SNP) array, followed by a genome-wide association study (GWAS) to identify genomic regions associated with sex in white shrimp.

RESULTS

The genetic map yielded 15,256 SNPs assigned to 44 linkage groups (LG). The lengths of the male, female, and sex-averaged maps were 5,741.36, 5,461.20 and 5,525.26 cM, respectively. LG18 was found to be the largest for both sexes, whereas LG44 was the shortest for males and LG31 for females. A sex-determining region was found in LG31 with 21 statistically significant SNPs. The most important SNP was previously identified as a sex-linked marker and was able to identify 99% of the males and 88% of the females. Although other significant markers had a lower ability to determine sex, putative genes were intercepted or close to them. The oplophorus-luciferin 2-monooxygenase, serine/arginine repetitive matrix protein and spermine oxidase genes were identified as candidates with possible participation in important processes of sexual differentiation in shrimp.

CONCLUSIONS

Our results provide novel genomic resources for shrimp, including a high-density linkage map and new insights into the sex-determining region in L. vannamei, which may be usefulfor future genetics and reproduction applications.

Consequences of domestication in eastern oyster: Insights from whole genomic analyses

Selective breeding for production traits has yielded relatively rapid successes with high-fecundity aquaculture species. Discovering the genetic changes associated with selection is an important goal for understanding adaptation and can also facilitate better predictions about the likely fitness of selected strains if they escape aquaculture farms. Here, we hypothesize domestication as a genetic change induced by inadvertent selection in culture. Our premise is that standardized culture protocols generate parallel domestication effects across independent strains. Using eastern oyster as a model and a newly developed 600K SNP array, this study tested for parallel domestication effects in multiple independent selection lines compared with their progenitor wild populations. A single contrast was made between pooled selected strains (1-17 generations in culture) and all wild progenitor samples combined. Population structure analysis indicated rank order levels of differentiation as [wild - wild] < [wild - cultured] < [cultured - cultured]. A genome scan for parallel adaptation to the captive environment applied two methodologically distinct outlier tests to the wild versus selected strain contrast and identified a total of 1174 candidate SNPs. Contrasting wild versus selected strains revealed the early evolutionary consequences of domestication in terms of genomic differentiation, standing genetic diversity, effective population size, relatedness, runs of homozygosity profiles, and genome-wide linkage disequilibrium patterns. Random Forest was used to identify 37 outlier SNPs that had the greatest discriminatory power between bulked wild and selected oysters. The outlier SNPs were in genes enriched for cytoskeletal functions, hinting at possible traits under inadvertent selection during larval culture or pediveliger setting at high density. This study documents rapid genomic changes stemming from hatchery-based cultivation of eastern oysters, identifies candidate loci responding to domestication in parallel among independent aquaculture strains, and provides potentially useful genomic resources for monitoring interbreeding between farm and wild oysters.

Identification of pigmentation genes in skin, muscle and tail of a Thai-flag variety of Siamese fighting fish Betta splendens

Pigmentation genes expressed in skin, body muscle and tail of Thai-flag compared with Blue, White and Red varieties of Siamese fighting fish Betta splendens were identified. In total, 22,919 new unigenes were found. Pearson correlation and PCA analysis revealed that expression profiles of genes in muscle, skin and tail across solid color variety were similar. In contrast, those in skin and red tail part of Thai-flag were closely related but they showed different expression profiles with the white tail part. Moreover, 21,347-64,965 SNPs were identified in exonic regions of identified genes. In total, 28,899 genes were differentially expressed between paired comparisons of libraries where 13,907 genes (48.12 %) were upregulated and 14,992 genes (51.88 %) were downregulated. DEGs between paired libraries were 106-5775 genes relative to the compared libraries (56-2982 and 50-2782 for upregulated and downregulated DEGs). Interestingly, 432 pigmentation genes of B. splendens were found. Of these, 297 DEGs showed differential expression between varieties. Many DEGs in melanogenesis (Bsmcr1r, Bsmcr5r, and Bsslc2a15b), tyrosine metabolism (Bstyr, Bstyrp1b and Bsdct), stripe repressor (BsAsip1 and BsAsip2b), pteridine (Bsgch2) and carotenoid (BsBco2) biosynthesis were downregulated in the Thai-flag compared with solid color varieties. Expression of Bsbco1l, Bsfrem2b, Bskcnj13, Bszic2a and Bspah in skin, muscle and tail of Thai-flag, Blue, Red and White varieties was analyzed by qRT-PCR and revealed differential expression between fish varieties and showed anatomical tissue-preferred expression patterns in the same fish variety. The information could be applied to assist genetic-based development of new B. splendens varieties in the future.

Characterization of microsatellite markers in the coding regions of the Penaeus vannamei genome

In this study, an extensive analysis of microsatellite markers (Single Tandem Repeats-STRs) in Penaeus vannamei was conducted at an advanced level. The markers were thoroughly examined, characterized, and specific markers located within coding regions were identified. Out of a total of 306 STRs, 117 were classified as perfect markers based on their single repeat motif. Among these perfect markers, 62 were found to be associated with predicted coding genes (mRNA), which were involved in various functions such as binding, catalytic activity, ATP-dependent activity, transcription, structural and molecular regulation. To validate the accuracy of the findings, a sample of nine markers was subjected to in vitro testing, which confirmed the presence of polymorphisms within the population. These results suggest the existence of different protein isoforms within the population, indicating the potential of these markers for application in both population and phenotype-genotype association studies. This innovative approach opens up new possibilities for investigating the impact of genomic plasticity in populations of P. vannamei.

MassArray Genotyping as a Selection Tool for Extending the Shelf-Life of Fresh Gilthead Sea Bream and European Seabass

In modern aquaculture, genomics-driven breeding programs have emerged as powerful tools for optimizing fish quality. This study focused on two emblematic Mediterranean fish species, the European seabass (Dicentrarchus labrax) and the gilthead sea bream (Sparus aurata), with a primary aim of exploring the genetic basis of white muscle/fillet degradation in fresh fish following harvest. We identified 57 and 44 missense SNPs in gilthead sea bream and European seabass, respectively, located within genes encoding for endogenous proteases responsible for fillet quality. These SNPs were cherry-picked based on their strategic location within the catalytic/regulatory domains of endogenous proteases that are expressed in the white muscle. Using MassArray technology, we successfully associated differentiated enzymatic activity of those endogenous proteases post-harvest as a phenotypic trait with genetic polymorphism of six SNPs in gilthead sea bream and nine in European seabass. These findings can be valuable attributes in selective breeding programs toward the extension of freshness and shelf life of these species. The integration of MassArray technology into breeding programs offers a cost-effective strategy for harnessing the potential of these genetic variants to enhance the overall quality of the final product. Recognizing that fresh fish perishability is a challenge, extending shelf-life is pivotal in reducing losses and production costs.

Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data

BACKGROUND

Microhaplotypes have the potential to be more cost-effective than SNPs for applications that require genetic panels of highly variable loci. However, development of microhaplotype panels is hindered by a lack of methods for estimating microhaplotype allele frequency from low-coverage whole genome sequencing or pooled sequencing (pool-seq) data.

RESULTS

We developed new methods for estimating microhaplotype allele frequency from low-coverage whole genome sequence and pool-seq data. We validated these methods using datasets from three non-model organisms. These methods allowed estimation of allele frequency and expected heterozygosity at depths routinely achieved from pooled sequencing.

CONCLUSIONS

These new methods will allow microhaplotype panels to be designed using low-coverage WGS and pool-seq data to discover and evaluate candidate loci. The python script implementing the two methods and documentation are available at https://www.github.com/delomast/mhFromLowDepSeq .

An Integrated Multi-Omics and Artificial Intelligence Framework for Advance Plant Phenotyping in Horticulture

This review discusses the transformative potential of integrating multi-omics data and artificial intelligence (AI) in advancing horticultural research, specifically plant phenotyping. The traditional methods of plant phenotyping, while valuable, are limited in their ability to capture the complexity of plant biology. The advent of (meta-)genomics, (meta-)transcriptomics, proteomics, and metabolomics has provided an opportunity for a more comprehensive analysis. AI and machine learning (ML) techniques can effectively handle the complexity and volume of multi-omics data, providing meaningful interpretations and predictions. Reflecting the multidisciplinary nature of this area of research, in this review, readers will find a collection of state-of-the-art solutions that are key to the integration of multi-omics data and AI for phenotyping experiments in horticulture, including experimental design considerations with several technical and non-technical challenges, which are discussed along with potential solutions. The future prospects of this integration include precision horticulture, predictive breeding, improved disease and stress response management, sustainable crop management, and exploration of plant biodiversity. The integration of multi-omics and AI holds immense promise for revolutionizing horticultural research and applications, heralding a new era in plant phenotyping.

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.

Viral nervous necrosis resistance in gilthead sea bream (Sparus aurata) at the larval stage: heritability and accuracy of genomic prediction with different training and testing settings

BACKGROUND

The gilthead sea bream (Sparus aurata) has long been considered resistant to viral nervous necrosis (VNN), until recently, when significant mortalities caused by a reassortant nervous necrosis virus (NNV) strain were reported. Selective breeding to enhance resistance against NNV might be a preventive action. In this study, 972 sea bream larvae were subjected to a NNV challenge test and the symptomatology was recorded. All the experimental fish and their parents were genotyped using a genome-wide single nucleotide polymorphism (SNP) array consisting of over 26,000 markers.

RESULTS

Estimates of pedigree-based and genomic heritabilities of VNN symptomatology were consistent with each other (0.21, highest posterior density interval at 95% (HPD95%): 0.1-0.4; 0.19, HPD95%: 0.1-0.3, respectively). The genome-wide association study suggested one genomic region, i.e., in linkage group (LG) 23 that might be involved in sea bream VNN resistance, although it was far from the genome-wide significance threshold. The accuracies (r) of the predicted estimated breeding values (EBV) provided by three Bayesian genomic regression models (Bayes B, Bayes C, and Ridge Regression) were consistent and on average were equal to 0.90 when assessed in a set of cross-validation (CV) procedures. When genomic relationships between training and testing sets were minimized, accuracy decreased greatly (r = 0.53 for a validation based on genomic clustering, r = 0.12 for a validation based on a leave-one-family-out approach focused on the parents of the challenged fish). Classification of the phenotype using the genomic predictions of the phenotype or using the genomic predictions of the pedigree-based, all data included, EBV as classifiers was moderately accurate (area under the ROC curve 0.60 and 0.66, respectively).

CONCLUSIONS

The estimate of the heritability for VNN symptomatology indicates that it is feasible to implement selective breeding programs for increased resistance to VNN of sea bream larvae/juveniles. Exploiting genomic information offers the opportunity of developing prediction tools for VNN resistance, and genomic models can be trained on EBV using all data or phenotypes, with minimal differences in classification performance of the trait phenotype. In a long-term view, the weakening of the genomic ties between animals in the training and test sets leads to decreased genomic prediction accuracies, thus periodical update of the reference population with new data is mandatory.

Immune diversity in lophotrochozoans, with a focus on recognition and effector systems

Lophotrochozoa is one of the most species-rich but immunologically poorly explored phyla. Although lack of acquired response in a narrow sense, lophotrochozoans possess various genetic mechanisms that enhance the diversity and specificity of innate immune system. Here, we review the recent advances of comparative immunology studies in lophotrochozoans with focus on immune recognition and effector systems. Haemocytes and coelomocytes are general important yet understudied player. Comparative genomics studies suggest expansion and functional divergence of lophotrochozoan immune reorganization systems is not as "homogeneous and simple" as we thought including the large-scale expansion and molecular divergence of pattern recognition receptors (PRRs) (TLRs, RLRs, lectins, etc.) and signaling adapters (MyD88s etc.), significant domain recombination of immune receptors (RLR, NLRs, lectins, etc.), extensive somatic recombination of fibrinogenrelated proteins (FREPs) in snails. Furthermore, there are repeatedly identified molecular mechanisms that generate immune effector diversity, including high polymorphism of antimicrobial peptides and proteins (AMPs), reactive oxygen and nitrogen species (RONS) and cytokines. Finally, we argue that the next generation omics tools and the recently emerged genome editing technicism will revolutionize our understanding of innate immune system in a comparative immunology perspective.

Animal board invited review: Widespread adoption of genetic technologies is key to sustainable expansion of global aquaculture

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The extent of application of genetic technologies to aquaculture production varies widely by species and geography.

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Achieving a more universal application of seed derived from scientifically based breeding programmes is an important goal in order to meet increasing global demands for seafood production.

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This article reviews the status of genetic technologies across the world’s top 10 highly produced species.

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Opportunities and barriers to achieving broad-scale uptake of genetic technologies in global aquaculture are discussed.

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A future outlook for potential disruptive genetic technologies and how they might affect global aquaculture production is given.

Aquaculture production comprises a diverse range of species, geographies, and farming systems. The application of genetics and breeding technologies towards improved production is highly variable, ranging from the use of wild-sourced seed through to advanced family breeding programmes augmented by genomic techniques. This technical variation exists across some of the most highly produced species globally, with several of the top ten global species by volume generally lacking well-managed breeding programmes. Given the well-documented incremental and cumulative benefits of genetic improvement on production, this is a major missed opportunity. This short review focusses on (i) the status of application of selective breeding in the world’s most produced aquaculture species, (ii) the range of genetic technologies available and the opportunities they present, and (iii) a future outlook towards realising the potential contribution of genetic technologies to aquaculture sustainability and global food security.

What Can Genetics Do for the Control of Infectious Diseases in Aquaculture?

Simple Summary

Infectious diseases place an economic burden on aquaculture and a limitation to its growth. This state-of-the-art review describes the application of genetics and genomics as novel tools to control infectious disease in aquaculture.

Abstract

Infectious diseases place an economic burden on aquaculture and a limitation to its growth. An innovative approach to mitigate their impact on production is breeding for disease resistance: selection for domestication, family-based selection, marker-assisted selection, and more recently, genomic selection. Advances in genetics and genomics approaches to the control of infectious diseases are key to increasing aquaculture efficiency, profitability, and sustainability and to reducing its environmental footprint. Interaction and co-evolution between a host and pathogen can, however, turn breeding to boost infectious disease resistance into a potential driver of pathogenic change. Parallel molecular characterization of the pathogen and its virulence and antimicrobial resistance genes is therefore essential to understand pathogen evolution over time in response to host immunity, and to apply appropriate mitigation strategies.

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.

Development of a high-throughput SNP array for sea cucumber (Apostichopus japonicus) and its application in genomic selection with MCP regularized deep neural networks

High-throughput single nucleotide polymorphism (SNP) genotyping assays are powerful tools for genetic studies and genomic breeding applications for many species. Though large numbers of SNPs have been identified in sea cucumber (Apostichopus japonicus), but, as yet, no high-throughput genotyping platform is available for this species. In this study, we designed and developed a high-throughput 24 K SNP genotyping array named HaishenSNP24K for A. japonicus, based on the multi-objective-local optimization (MOLO) algorithm and HD-Marker genotyping method. The SNP array exhibited a relatively high genotyping call rate (> 96%), genotyping accuracy (>95%) and exhibited highly polymorphic in sea cucumber populations. In addition, we also assessed its application in genomic selection (GS). Deep neural networks (DNN) that can capture the complicated interactions of genes have been proposed as a promising tool in GS for SNP-based genomic prediction of complex traits in animal breeding. To overcome the problem of over-fitting when using the HaishenSNP24K array as high-dimensional DNN input, we developed minmax concave penalty (MCP) regularization for sparse deep neural networks (DNN-MCP) that finds an optimal sparse structure of a DNN by minimizing the square error subject to the non-convex penalty MCP on the parameters (weights and biases). Compared to two linear models, namely RR-GBLUP and Bayes B, and the nonlinear model DNN, DNN-MCP has greatly improved the genomic prediction ability for three quantitative traits (e.g., wet weight, dry weight and survival time) in the sea cucumber population. To the best of our knowledge, this is the first work to develop a high-throughput SNP array for A. japonicus and a new model DNN-MCP for genomic prediction of complex traits in GS. The present results provide evidence that supports the HaishenSNP24K array with DNN-MCP will be valuable for genetic studies and molecular breeding in A. japonicus.

Genomic Prediction Strategies for Dry-Down-Related Traits in Maize

For efficient mechanical harvesting, low grain moisture content at harvest time is essential. Dry-down rate (DR), which refers to the reduction in grain moisture content after the plants enter physiological maturity, is one of the main factors affecting the amount of moisture in the kernels. Dry-down rate is estimated using kernel moisture content at physiological maturity and at harvest time; however, measuring kernel water content at physiological maturity, which is sometimes referred as kernel water content at black layer formation (BWC), is time-consuming and resource-demanding. Therefore, inferring BWC from other correlated and easier to measure traits could improve the efficiency of breeding efforts for dry-down-related traits. In this study, multi-trait genomic prediction models were used to estimate genetic correlations between BWC and water content at harvest time (HWC) and flowering time (FT). The results show there is moderate-to-high genetic correlation between the traits (0.24-0.66), which supports the use of multi-trait genomic prediction models. To investigate genomic prediction strategies, several cross-validation scenarios representing possible implementations of genomic prediction were evaluated. The results indicate that, in most scenarios, the use of multi-trait genomic prediction models substantially increases prediction accuracy. Furthermore, the inclusion of historical records for correlated traits can improve prediction accuracy, even when the target trait is not measured on all the plots in the training set.

ATP synthase subunit e is a shrimp growth-associated breeding marker

Penaeus vannamei is one of the most popular aquaculture species in the world. This species is featured with its fast-growing and delicious taste, which drives people develop various strains. During this process identification of trait-associated markers could effectively increase breeding efficiency. Driven by this, we tried to screen fast-growing key regulators via a FACS-based high throughput method, in which 2-NBDG was applied as a fluorescent indicator for direct glucose uptake measurement. Totally six candidate genes were screened out followed by in vitro validation in 293T cells. After that, the correlation between these genes and shrimp growing was further verified in a hybrid lineage. The expression level of two genes including ATP synthase subunit e and inhibitor of apoptosis protein showed some correlation with shrimp growth speed. Furthermore, we tested these two candidate markers in various lineages and confirmed that ATP synthase subunit e could be a shrimp growth-associated breeding marker.

A High-Quality Genome Assembly of Striped Catfish (Pangasianodon hypophthalmus) Based on Highly Accurate Long-Read HiFi Sequencing Data

The HiFi sequencing technology yields highly accurate long-read data with accuracies greater than 99.9% that can be used to improve results for complex applications such as genome assembly. Our study presents a high-quality chromosome-scale genome assembly of striped catfish (Pangasianodon hypophthalmus), a commercially important species cultured mainly in Vietnam, integrating HiFi reads and Hi-C data. A 788.4 Mb genome containing 381 scaffolds with an N50 length of 21.8 Mb has been obtained from HiFi reads. These scaffolds have been further ordered and clustered into 30 chromosome groups, ranging from 1.4 to 57.6 Mb, based on Hi-C data. The present updated assembly has a contig N50 of 14.7 Mb, representing a 245-fold and 4.2-fold improvement over the previous Illumina and Illumina-Nanopore-Hi-C based version, respectively. In addition, the proportion of repeat elements and BUSCO genes identified in our genome is remarkably higher than in the two previously released striped catfish genomes. These results highlight the power of using HiFi reads to assemble the highly repetitive regions and to improve the quality of genome assembly. The updated, high-quality genome assembled in this work will provide a valuable genomic resource for future population genetics, conservation biology and selective breeding studies of striped catfish.

Genome-wide association study of VHSV-resistance trait in Paralichthys olivaceus

In flounder aquaculture, selective breeding plays a vital role in the development of disease-resistant traits and animals with high growth rates. Moreover, superior animals are required to achieve high profits. Unlike growth-related traits, disease-resistant experiments need to be conducted in a controlled environment, as the improper measurement of traits often leads to low genetic correlation and incorrect estimation of breeding values. In this study, viral hemorrhagic septicemia virus (VHSV) resistance was studied using a genome-wide association study (GWAS), and the genetic parameters were estimated. Genotyping was performed using a high-quality 70 K single nucleotide polymorphism (SNP) Affymetrix® Axiom® myDesign™ Genotyping Array of olive flounder. A heritability of ∼0.18 for resistance to VHSV was estimated using genomic information of the fish. According to the GWAS, significant SNPs were detected in chromosomes 21, 24, and contig AGQT02032065.1. Three SNPs showed significance at the genome-wide level (p < 1 × 10^-6), while others showed significance above the suggestive cutoff (p < 1 × 10^-4). The 3% phenotypic variation was explained by the highest significant SNP, named AX-419319631. Of the important genes for disease resistance, SNPs were associated with plcg1, epha4, clstn2, pik3cb, hes6, meis3, prx6, cep164, siae, and kirrel3b. Most of the genes associated with these SNPs have been previously reported with respect to viral entry, propagation, and immune mechanisms. Therefore, our study provides helpful information regarding VHSV resistance in olive flounder, which can be used for breeding applications.

Genome assembly of the Australian black tiger shrimp (Penaeus monodon) reveals a novel fragmented IHHNV EVE sequence

Shrimp are a valuable aquaculture species globally; however, disease remains a major hindrance to shrimp aquaculture sustainability and growth. Mechanisms mediated by endogenous viral elements have been proposed as a means by which shrimp that encounter a new virus start to accommodate rather than succumb to infection over time. However, evidence on the nature of such endogenous viral elements and how they mediate viral accommodation is limited. More extensive genomic data on Penaeid shrimp from different geographical locations should assist in exposing the diversity of endogenous viral elements. In this context, reported here is a PacBio Sequel-based draft genome assembly of an Australian black tiger shrimp (Penaeus monodon) inbred for 1 generation. The 1.89 Gbp draft genome is comprised of 31,922 scaffolds (N50: 496,398 bp) covering 85.9% of the projected genome size. The genome repeat content (61.8% with 30% representing simple sequence repeats) is almost the highest identified for any species. The functional annotation identified 35,517 gene models, of which 25,809 were protein-coding and 17,158 were annotated using interproscan. Scaffold scanning for specific endogenous viral elements identified an element comprised of a 9,045-bp stretch of repeated, inverted, and jumbled genome fragments of infectious hypodermal and hematopoietic necrosis virus bounded by a repeated 591/590 bp host sequence. As only near complete linear ∼4 kb infectious hypodermal and hematopoietic necrosis virus genomes have been found integrated in the genome of P. monodon previously, its discovery has implications regarding the validity of PCR tests designed to specifically detect such linear endogenous viral element types. The existence of joined inverted infectious hypodermal and hematopoietic necrosis virus genome fragments also provides a means by which hairpin double-stranded RNA could be expressed and processed by the shrimp RNA interference machinery.

Simulation of sugar kelp (Saccharina latissima) breeding guided by practices to accelerate genetic gains

Though Saccharina japonica cultivation has been established for many decades in East Asian countries, the domestication process of sugar kelp (Saccharina latissima) in the Northeast United States is still at its infancy. In this study, by using data from our breeding experience, we will demonstrate how obstacles for accelerated genetic gain can be assessed using simulation approaches that inform resource allocation decisions. Thus far, we have used 140 wild sporophytes that were sampled in 2018 from the northern Gulf of Maine to southern New England. From these sporophytes, we sampled gametophytes and made and evaluated over 600 progeny sporophytes from crosses among the gametophytes in 2019 and 2020. The biphasic life cycle of kelp gives a great advantage in selective breeding as we can potentially select both on the sporophytes and gametophytes. However, several obstacles exist, such as the amount of time it takes to complete a breeding cycle, the number of gametophytes that can be maintained in the laboratory, and whether positive selection can be conducted on farm-tested sporophytes. Using the Gulf of Maine population characteristics for heritability and effective population size, we simulated a founder population of 1,000 individuals and evaluated the impact of overcoming these obstacles on rate of genetic gain. Our results showed that key factors to improve current genetic gain rely mainly on our ability to induce reproduction of the best farm-tested sporophytes, and to accelerate the clonal vegetative growth of released gametophytes so that enough gametophyte biomass is ready for making crosses by the next growing season. Overcoming these challenges could improve rates of genetic gain more than 2-fold. Future research should focus on conditions favorable for inducing spring reproduction, and on increasing the amount of gametophyte tissue available in time to make fall crosses in the same year.

Construction of Genetic Linkage Maps From a Hybrid Family of Large Yellow Croaker (Larimichthys crocea)

Consensus and sex-specific genetic linkage maps for large yellow croaker (Larimichthys crocea) were constructed using samples from an F₁ family produced by crossing a Daiqu female and a Mindong male. A total of 20,147 single nucleotide polymorphisms (SNPs) by restriction site associated DNA sequencing were assigned to 24 linkage groups (LGs). The total length of the consensus map was 1757.4 centimorgan (cM) with an average marker interval of 0.09 cM. The total length of female and male linkage map was 1533.1 cM and 1279.2 cM, respectively. The average female-to-male map length ratio was 1.2 ± 0.23. Collapsed markers in the genetic maps were re-ordered according to their relative positions in the ASM435267v1 genome assembly to produce integrated genetic linkage maps with 9885 SNPs distributed across the 24 LGs. The recombination pattern of most LGs showed sigmoidal patterns of recombination, with higher recombination in the middle and suppressed recombination at both ends, which corresponds with the presence of sub-telocentric and acrocentric chromosomes in the species. The average recombination rate in the integrated female and male maps was respectively 3.55 cM/Mb and 3.05 cM/Mb. In most LGs, higher recombination rates were found in the integrated female map, compared to the male map, except in LG12, LG16, LG21, LG22, and LG24. Recombination rate profiles within each LG differed between the male and the female, with distinct regions indicating potential recombination hotspots. Separate quantitative trait loci (QTL) and association analyses for growth related traits in 6 months fish were performed, however, no significant QTL was detected. The study indicates that there may be genetic differences between the two strains, which may have implications for the application of DNA-information in the further breeding schemes.

Genetic approaches for increasing fitness in endangered species

The global rate of wildlife extinctions is accelerating, and the persistence of many species requires conservation breeding programs. A central paradigm of these programs is to preserve the genetic diversity of the founder populations. However, this may preserve original characteristics that make them vulnerable to extinction. We introduce targeted genetic intervention (TGI) as an alternative approach that promotes traits that enable species to persist in the face of threats by changing the incidence of alleles that impact on fitness. The TGI toolkit includes methods with established efficacy in model organisms and agriculture but are largely untried for conservation, such as synthetic biology and artificial selection. We explore TGI approaches as a species-restoration tool for intractable threats including infectious disease and climate change.

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.

Genomic prediction for testes weight of the tiger pufferfish, Takifugu rubripes, using medium to low density SNPs

Aquaculture production is expected to increase with the help of genomic selection (GS). The possibility of performing GS using only a small number of SNPs has been examined in order to reduce genotyping costs; however, the practicality of this approach is still unclear. Here, we tested whether the effects of reducing the number of SNPs impaired the prediction accuracy of GS for standard length, body weight, and testes weight in the tiger pufferfish (Takifugu rubripes). High values for predictive ability (0.563-0.606) were obtained with 4000 SNPs for all traits under a genomic best linear unbiased predictor (GBLUP) model. These values were still within an acceptable range with 1200 SNPs (0.554-0.588). However, predictive abilities and prediction accuracies deteriorated using less than 1200 SNPs largely due to the reduced power in accurately estimating the genetic relationship among individuals; family structure could still be resolved with as few as 400 SNPs. This suggests that the SNPs informative for estimation of genetic relatedness among individuals differ from those for inference of family structure, and that non-random SNP selection based on the effects on family structure (e.g., site-F_ST, principal components, or random forest) is unlikely to increase the prediction accuracy for these traits.

Commercial implementation of genomic selection in Tasmanian Atlantic salmon: Scheme evolution and validation

Genomic information was included for the first time in the prediction of breeding values for Atlantic salmon within the Australian Salmon Enterprises of Tasmania Pty Ltd selective breeding program in 2016. The process to realize genomic selection in the breeding program begun in 2014 with the scheme finalized and fully implemented for the first time in 2018. The high potential of within family selection to accelerate genetic gain, something not possible using the traditional pedigree‐based approach, provided the impetus for implementation. Efficient and effective genotyping platforms are essential for genomic selection. Genotype data from high density arrays revealed extensive persistence of linkage disequilibrium in the Tasmania Atlantic salmon population, resulting in high accuracies of both imputation and genomic breeding values when using imputed data. Consequently, a low‐density novel genotype‐by‐sequence assay was designed and incorporated into the scheme. Through the use of a static high‐ and dynamic low‐density genotyping platforms, an optimized genotyping scheme was devised and implemented such that all individuals in every year class are genotyped efficiently while maximizing the genetic gains and minimizing costs. The increase in the rates of genetic gain attributed to the implementation of genomic selection is significant across both the breeding programs primary and secondary traits. Substantial improvement in the ability to select parents prior to progeny testing is observed across multiple years. The resultant economic impacts for the industry are considerable based on the increases in genetic gain for traits achieved within the breeding program and the use of genomic selection for commercial production.

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.

Chromosome-level genome assembly of the blue crab, Callinectes sapidus

The blue crab, Callinectes sapidus (Rathbun, 1896) is an economically, culturally, and ecologically important species found across the temperate and tropical North and South American Atlantic coast. A reference genome will enable research for this high-value species. Initial assembly combined 200× coverage Illumina paired-end reads, a 60× 8 kb mate-paired library, and 50× PacBio data using the MaSuRCA assembler resulting in a 985 Mb assembly with a scaffold N50 of 153 kb. Dovetail Chicago and HiC sequencing with the 3d DNA assembler and Juicebox assembly tools were then used for chromosome scaffolding. The 50 largest scaffolds span 810 Mb are 1.5-37 Mb long and have a repeat content of 36%. The 190 Mb unplaced sequence is in 3921 sequences over 10 kb with a repeat content of 68%. The final assembly N50 is 18.9 Mb for scaffolds and 9317 bases for contigs. Of arthropod BUSCO, ∼88% (888/1013) were complete and single copies. Using 309 million RNAseq read pairs from 12 different tissues and developmental stages, 25,249 protein-coding genes were predicted. Between C. sapidus and Portunus trituberculatus genomes, 41 of 50 large scaffolds had high nucleotide identity and protein-coding synteny, but 9 scaffolds in both assemblies were not clear matches. The protein-coding genes included 9423 one-to-one putative orthologs, of which 7165 were syntenic between the two crab species. Overall, the two crab genome assemblies show strong similarities at the nucleotide, protein, and chromosome level and verify the blue crab genome as an excellent reference for this important seafood species.

A major quantitative trait locus affecting resistance to Tilapia lake virus in farmed Nile tilapia (Oreochromis niloticus)

Enhancing host resistance to infectious disease has received increasing attention in recent years as a major goal of farm animal breeding programs. Combining field data with genomic tools can provide opportunities to understand the genetic architecture of disease resistance, leading to new opportunities for disease control. In the current study, a genome-wide association study was performed to assess resistance to the Tilapia lake virus (TiLV), one of the biggest threats affecting Nile tilapia (Oreochromis niloticus); a key aquaculture species globally. A pond outbreak of TiLV in a pedigreed population of the GIFT strain was observed, with 950 fish classified as either survivor or mortality, and genotyped using a 65 K SNP array. A significant QTL of large effect was identified on chromosome Oni22. The average mortality rate of tilapia homozygous for the resistance allele at the most significant SNP (P value = 4.51E-10) was 11%, compared to 43% for tilapia homozygous for the susceptibility allele. Several candidate genes related to host response to viral infection were identified within this QTL, including lgals17, vps52, and trim29. These results provide a rare example of a major QTL affecting a trait of major importance to a farmed animal. Genetic markers from the QTL region have potential in marker-assisted selection to improve host resistance, providing a genetic solution to an infectious disease where few other control or mitigation options currently exist.

Optimization of Genomic Selection to Improve Disease Resistance in Two Marine Fishes, the European Sea Bass (Dicentrarchus labrax) and the Gilthead Sea Bream (Sparus aurata)

Disease outbreaks are a major threat to the aquaculture industry, and can be controlled by selective breeding. With the development of high-throughput genotyping technologies, genomic selection may become accessible even in minor species. Training population size and marker density are among the main drivers of the prediction accuracy, which both have a high impact on the cost of genomic selection. In this study, we assessed the impact of training population size as well as marker density on the prediction accuracy of disease resistance traits in European sea bass (Dicentrarchus labrax) and gilthead sea bream (Sparus aurata). We performed a challenge to nervous necrosis virus (NNV) in two sea bass cohorts, a challenge to Vibrio harveyi in one sea bass cohort and a challenge to Photobacterium damselae subsp. piscicida in one sea bream cohort. Challenged individuals were genotyped on 57K-60K SNP chips. Markers were sampled to design virtual SNP chips of 1K, 3K, 6K, and 10K markers. Similarly, challenged individuals were randomly sampled to vary training population size from 50 to 800 individuals. The accuracy of genomic-based (GBLUP model) and pedigree-based estimated breeding values (EBV) (PBLUP model) was computed for each training population size using Monte-Carlo cross-validation. Genomic-based breeding values were also computed using the virtual chips to study the effect of marker density. For resistance to Viral Nervous Necrosis (VNN), as one major QTL was detected, the opportunity of marker-assisted selection was investigated by adding a QTL effect in both genomic and pedigree prediction models. As training population size increased, accuracy increased to reach values in range of 0.51-0.65 for full density chips. The accuracy could still increase with more individuals in the training population as the accuracy plateau was not reached. When using only the 6K density chip, accuracy reached at least 90% of that obtained with the full density chip. Adding the QTL effect increased the accuracy of the PBLUP model to values higher than the GBLUP model without the QTL effect. This work sets a framework for the practical implementation of genomic selection to improve the resistance to major diseases in European sea bass and gilthead sea bream.

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.

A chromosome-level assembly of the black tiger shrimp (Penaeus monodon) genome facilitates the identification of growth-associated genes

To salvage marine ecosystems from fishery overexploitation, sustainable and efficient aquaculture must be emphasized. The knowledge obtained from available genome sequence of marine organisms has accelerated marine aquaculture in many cases. The black tiger shrimp (Penaeus monodon) is one of the most prominent cultured penaeid shrimps (Crustacean) with an average annual global production of half a million tons in the last decade. However, its currently available genome assemblies lack the contiguity and completeness required for accurate genome annotation due to the highly repetitive nature of the genome and technical difficulty in extracting high-quality, high-molecular weight DNA. Here, we report the first chromosome-level whole-genome assembly of P. monodon. The combination of long-read Pacific Biosciences (PacBio) and long-range Chicago and Hi-C technologies enabled a successful assembly of this first high-quality genome sequence. The final assembly covered 2.39 Gb (92.3% of the estimated genome size) and contained 44 pseudomolecules, corresponding to the haploid chromosome number. Repetitive elements occupied a substantial portion of the assembly (62.5%), the highest of the figures reported among crustacean species. The availability of this high-quality genome assembly enabled the identification of genes associated with rapid growth in the black tiger shrimp through the comparison of hepatopancreas transcriptome of slow-growing and fast-growing shrimps. The results highlighted several growth-associated genes. Our high-quality genome assembly provides an invaluable resource for genetic improvement and breeding penaeid shrimp in aquaculture. The availability of P. monodon genome enables analyses of ecological impact, environment adaptation and evolution, as well as the role of the genome to protect the ecological resources by promoting sustainable shrimp farming.

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'.

Exploring genetic resistance to infectious salmon anaemia virus in Atlantic salmon by genome-wide association and RNA sequencing

Background

Infectious Salmonid Anaemia Virus (ISAV) causes a notifiable disease that poses a large threat for Atlantic salmon (Salmo salar) aquaculture worldwide. There is no fully effective treatment or vaccine, and therefore selective breeding to increase resistance to ISAV is a promising avenue for disease prevention. Genomic selection and potentially genome editing can be applied to enhance host resistance, and these approaches benefit from improved knowledge of the genetic and functional basis of the target trait. The aim of this study was to characterise the genetic architecture of resistance to ISAV in a commercial Atlantic salmon population and study its underlying functional genomic basis using RNA Sequencing.

Results

A total of 2833 Atlantic salmon parr belonging to 194 families were exposed to ISAV in a cohabitation challenge in which cumulative mortality reached 63% over 55 days. A total of 1353 animals were genotyped using a 55 K SNP array, and the estimate of heritability for the trait of binary survival was 0.13–0.33 (pedigree-genomic). A genome-wide association analysis confirmed that resistance to ISAV was a polygenic trait, albeit a genomic region in chromosome Ssa13 was significantly associated with resistance and explained 3% of the genetic variance. RNA sequencing of the heart of 16 infected (7 and 14 days post infection) and 8 control fish highlighted 4927 and 2437 differentially expressed genes at 7 and 14 days post infection respectively. The complement and coagulation pathway was down-regulated in infected fish, while several metabolic pathways were up-regulated. The interferon pathway showed little evidence of up-regulation at 7 days post infection but was mildly activated at 14 days, suggesting a potential crosstalk between host and virus. Comparison of the transcriptomic response of fish with high and low breeding values for resistance highlighted TRIM25 as being up-regulated in resistant fish.

Conclusions

ISAV resistance shows moderate heritability with a polygenic architecture, but a significant QTL was detected on chromosome 13. A mild up-regulation of the interferon pathway characterises the response to the virus in heart samples from this population of Atlantic salmon, and candidate genes showing differential expression between samples with high and low breeding values for resistance were identified.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07671-6.

Development and testing of a combined species SNP array for the European seabass (Dicentrarchus labrax) and gilthead seabream (Sparus aurata)

SNP arrays are powerful tools for high-resolution studies of the genetic basis of complex traits, facilitating both selective breeding and population genomic research. The European seabass (Dicentrarchus labrax) and the gilthead seabream (Sparus aurata) are the two most important fish species for Mediterranean aquaculture. While selective breeding programmes increasingly underpin stock supply for this industry, genomic selection is not yet widespread. Genomic selection has major potential to expedite genetic gain, particularly for traits practically impossible to measure on selection candidates, such as disease resistance and fillet characteristics. The aim of our study was to design a combined-species 60 K SNP array for European seabass and gilthead seabream, and to test its performance on farmed and wild populations from numerous locations throughout the species range. To achieve this, high coverage Illumina whole-genome sequencing of pooled samples was performed for 24 populations of European seabass and 27 populations of gilthead seabream. This resulted in a database of ~20 million SNPs per species, which were then filtered to identify high-quality variants and create the final set for the development of the ‘MedFish’ SNP array. The array was then tested by genotyping a subset of the discovery populations, highlighting a high conversion rate to functioning polymorphic assays on the array (92% in seabass; 89% in seabream) and repeatability (99.4–99.7%). The platform interrogates ~30 K markers in each species, includes features such as SNPs previously shown to be associated with performance traits, and is enriched for SNPs predicted to have high functional effects on proteins. The array was demonstrated to be effective at detecting population structure across a wide range of fish populations from diverse geographical origins, and to examine the extent of haplotype sharing among Mediterranean farmed fish populations. In conclusion, the new MedFish array enables efficient and accurate high-throughput genotyping for genome-wide distributed SNPs for each fish species, and will facilitate stock management, population genomics approaches, and acceleration of selective breeding through genomic selection.

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Α 60 K SNP array (MedFish) was designed for European seabass and gilthead seabream from wild and domesticated populations.

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The array exhibited a high conversion rate (92% in seabass; 89% in seabream) and repeatability (99.4 and 99.7%).

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The MedFish array is expected to facilitate stock management and acceleration of selective breeding via genomic selection.

Surrogate broodstock to enhance biotechnology research and applications in aquaculture

Aquaculture is playing an increasingly important role in meeting global demands for seafood, particularly in low and middle income countries. Genetic improvement of aquaculture species has major untapped potential to help achieve this, with selective breeding and genome editing offering exciting avenues to expedite this process. However, limitations to these breeding and editing approaches include long generation intervals of many fish species, alongside both technical and regulatory barriers to the application of genome editing in commercial production. Surrogate broodstock technology facilitates the production of donor-derived gametes in surrogate parents, and comprises transplantation of germ cells of donors into sterilised recipients. There are many successful examples of intra- and inter-species germ cell transfer and production of viable offspring in finfish, and this leads to new opportunities to address the aforementioned limitations. Firstly, surrogate broodstock technology raises the opportunity to improve genome editing via the use of cultured germ cells, to reduce mosaicism and potentially enable in vivo CRISPR screens in the progeny of surrogate parents. Secondly, the technology has pertinent applications in preservation of aquatic genetic resources, and in facilitating breeding of high-value species which are otherwise difficult to rear in captivity. Thirdly, it holds potential to drastically reduce the effective generation interval in aquaculture breeding programmes, expediting the rate of genetic gain. Finally, it provides new opportunities for dissemination of tailored, potentially genome edited, production animals of high genetic merit for farming. This review focuses on the state-of-the-art of surrogate broodstock technology, and discusses the next steps for its applications in research and production. The integration and synergy of genomics, genome editing, and reproductive technologies have exceptional potential to expedite genetic gain in aquaculture species in the coming decades.

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Genetic improvement in aquaculture species has a major role in global food security. Advances in biotechnology provide new opportunities to support aquaculture breeding.

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Advances in biotechnology provide new opportunities to support aquaculture breeding.

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Donor-derived gametes can be produced from surrogate broodstock of several aquaculture species.

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Surrogate broodstock technology provides new opportunities for application of genome editing.

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Surrogate broodstock can accelerate genetic gain, and improve dissemination of elite germplasm.

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.

Investigating mechanisms underlying genetic resistance to Salmon Rickettsial Syndrome in Atlantic salmon using RNA sequencing

Background

Salmon Rickettsial Syndrome (SRS), caused by Piscirickettsia salmonis, is one of the primary causes of morbidity and mortality in Atlantic salmon aquaculture, particularly in Chile. Host resistance is a heritable trait, and functional genomic studies have highlighted genes and pathways important in the response of salmon to the bacteria. However, the functional mechanisms underpinning genetic resistance are not yet well understood. In the current study, a large population of salmon pre-smolts were challenged with P. salmonis, with mortality levels recorded and samples taken for genotyping. In parallel, head kidney and liver samples were taken from animals of the same population with high and low genomic breeding values for resistance, and used for RNA-Sequencing to compare their transcriptome profile both pre and post infection.

Results

A significant and moderate heritability (h² = 0.43) was shown for the trait of binary survival. Genome-wide association analyses using 38 K imputed SNP genotypes across 2265 animals highlighted that resistance is a polygenic trait. Several thousand genes were identified as differentially expressed between controls and infected samples, and enriched pathways related to the host immune response were highlighted. In addition, several networks with significant correlation with SRS resistance breeding values were identified, suggesting their involvement in mediating genetic resistance. These included apoptosis, cytoskeletal organisation, and the inflammasome.

Conclusions

While resistance to SRS is a polygenic trait, this study has highlighted several relevant networks and genes that are likely to play a role in mediating genetic resistance. These genes may be future targets for functional studies, including genome editing, to further elucidate their role underpinning genetic variation in host resistance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07443-2.

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 Variation, GWAS and Accuracy of Prediction for Host Resistance to Sparicotyle chrysophrii in Farmed Gilthead Sea Bream (Sparus aurata)

Gilthead sea bream (Sparus aurata) belongs to a group of teleost which has high importance in Mediterranean aquaculture industry. However, industrial production is increasingly compromised by an elevated outbreak of diseases in sea cages, especially a disease caused by monogeneans parasite Sparicotyle chrysophrii. This parasite mainly colonizes gill tissues of host and causes considerable economical losses with mortality and reduction in growth. The aim of current study was to explore the genetics of host resistance against S. chrysophrii and investigate the potential for genomic selection to possibly accelerate genetic progress. To achieve the desired goals, a test population derived from the breeding nucleus of Andromeda Group was produced. This experimental population was established by crossing of parents mated in partial factorial crosses of ∼8 × 8 using 58 sires and 62 dams. The progeny obtained from this mating design was challenged with S. chrysophrii using a controllable cohabitation infection model. At the end of the challenge, fish were recorded for parasite count, and all the recorded fish were tissue sampled for genotyping by sequencing using 2b-RAD methodology. The initial (before challenge test) and the final body weight (after challenge test) of the fish were also recorded. The results obtained through the analysis of phenotypic records (n = 615) and the genotypic data (n = 841, 724 offspring and 117 parents) revealed that the resistance against this parasite is lowly heritable (h² = 0.147 with pedigree and 0.137 with genomic information). We observed moderately favorable genetic correlation (R_g = −0.549 to −0.807) between production traits (i.e., body weight and specific growth rate) and parasite count, which signals a possibility of indirect selection. A locus at linkage group 17 was identified that surpassed chromosome-wide Bonferroni threshold which explained 22.68% of the total genetic variance, and might be playing role in producing genetic variation. The accuracy of prediction was improved by 8% with genomic information compared to pedigree.

Development of EST-Molecular Markers from RNA Sequencing for Genetic Management and Identification of Growth Traits in Potato Grouper (Epinephelus tukula)

Simple Summary

The potato grouper is a novel aquaculture species in Taiwan. Due to the lack of genetic information concerning this species, we have developed molecular markers based on transcriptome sequencing and further characterized their association with gene diversity and growth traits of this species. Ultimately, these markers could be utilized as accurate and efficient tools for genetic management and marker-assisted selection of potato grouper with distinct growth traits.

Abstract

The accuracy and efficiency of marker-assisted selection (MAS) has been proven for economically critical aquaculture species. The potato grouper (Epinephelus tukula), a novel cultured grouper species in Taiwan, shows large potential in aquaculture because of its fast growth rate among other groupers. Because of the lack of genetic information for the potato grouper, the first transcriptome and expressed sequence tag (EST)-derived simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers were developed. Initially, the transcriptome was obtained from seven cDNA libraries by using the Illumina platform. De novo transcriptome of the potato grouper yielded 51.34 Gb and 111,490 unigenes. The EST-derived SSR and SNP markers were applied in genetic management, in parentage analysis, and to discover the functional markers of economic traits. The F₁ juveniles were identified as siblings from one pair of parents (80 broodstocks). Fast- and slow-growth individuals were analyzed using functional molecular markers and through their association with growth performance. The results revealed that two SNPs were correlated with growth traits. The transcriptome database obtained in this study and its derived SSR and SNP markers may be applied not only for MAS but also to maintain functional gene diversity in the novel cultured grouper.

An ultra-high density SNP-based linkage map for enhancing the pikeperch (Sander lucioperca) genome assembly to chromosome-scale

Pikeperch (Sander lucioperca) is a fish species with growing economic significance in the aquaculture industry. However, successful positioning of pikeperch in large-scale aquaculture requires advances in our understanding of its genome organization. In this study, an ultra-high density linkage map for pikeperch comprising 24 linkage groups and 1,023,625 single nucleotide polymorphisms markers was constructed after genotyping whole-genome sequencing data from 11 broodstock and 363 progeny, belonging to 6 full-sib families. The sex-specific linkage maps spanned a total of 2985.16 cM in females and 2540.47 cM in males with an average inter-marker distance of 0.0030 and 0.0026 cM, respectively. The sex-averaged map spanned a total of 2725.53 cM with an average inter-marker distance of 0.0028 cM. Furthermore, the sex-averaged map was used for improving the contiguity and accuracy of the current pikeperch genome assembly. Based on 723,360 markers, 706 contigs were anchored and oriented into 24 pseudomolecules, covering a total of 896.48 Mb and accounting for 99.47% of the assembled genome size. The overall contiguity of the assembly improved with a scaffold N50 length of 41.06 Mb. Finally, an updated annotation of protein-coding genes and repetitive elements of the enhanced genome assembly is provided at NCBI.

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.

Single nucleotide polymorphism associated with disease resistance in Penaeus vannamei

Despite the considerable number of genetic markers published for Penaeus vannamei, the classification of these markers and their standardization in specific databases is still insufficient. As a consequence, access to these markers is difficult, hampering their application in genetic association studies. In this study, all previously described single nucleotide polymorphisms (SNPs) related to resistance for P. vannamei were revised, and 512 SNPs were identified and classified in detail. We observed that most of the SNPs occurred in the proteins including Toll like receptors 1 and 3, hemocyanin large and small subunits, and anti-lipopolysaccharide factors 1 and 2, allowing to propose to use them as targets in association studies involving resistance in P. vannamei. Additionally, the potential effects of the most frequent non-synonymous coding SNPs in the secondary structure of the main target proteins were evaluated using an in silico approach. These data can serve as the starting point for the development of new genetic and computational tools as well as for the design of new association studies that involve resistance in P. vannamei.

A SNP of the hemocyanin gene (LvHc) is a marker for high growth and ammonia-tolerance in Pacific white shrimp Litopenaeus vannamei

Expression levels of hemocyanin (LvHc), activating transcription factor 4 (LvAtf4), glutathione S-transferase (LvGst), caspase 2 (LvCasp2) and anti-lipopolysaccharide factor (LvAlf) were examined in the hepatopancreas of Pacific white shrimp Litopenaeus vannamei juveniles exposed to a lethal concentration of ammonia-N (32.15 mg/l). The expression levels of all transcripts except LvAlf were significantly greater (P < 0.05) in tolerant shrimp (Lv-AT; N = 30) that survived up to 72 h post treatment (hpt) than in susceptible shrimp (Lv-AS24 and Lv-AS72; N = 45 and 15), that died within 24 h or between 24 and 72 hpt, respectively. Subsequently, effects of non-lethal concentrations of ammonia-N (control, 10 and 20 mg/l) on the expression of LvHc in juvenile shrimp were examined. Compared to the control, expression levels of LvHc transcripts in hemocytes and the hepatopancreas of tested shrimp changed after exposure to ammonia-N. One SNP (C > T₅₄₅) was found in the LvHc₃₂₂ gene segment. Real-time PCR amplification of specific alleles (real-time PASA) was developed for detection of C > T₅₄₅ genotypes. Juveniles in the lethal exposure test that carried a C/T₅₄₅ genotype showed a greater average body weight and total length (8.46 ± 0.36 g and 10.05 ± 0.16 cm) than those with a C/C₅₄₅ genotype (7.48 ± 0.31 g and 9.60 ± 0.13 cm) (P < 0.05). Similar results were found in the second generation (G2) of a growth-improved stock (3 and 4 families of BIOTEC-G2-L1 and BIOTEC-G2-L2) and in commercially farmed shrimp (2 groups). Accordingly, expression levels and SNP of LvHc can serve as markers for selection high growth performance in ammonia-tolerant L. vannamei.

Twelve quick steps for genome assembly and annotation in the classroom

Eukaryotic genome sequencing and de novo assembly, once the exclusive domain of well-funded international consortia, have become increasingly affordable, thus fitting the budgets of individual research groups. Third-generation long-read DNA sequencing technologies are increasingly used, providing extensive genomic toolkits that were once reserved for a few select model organisms. Generating high-quality genome assemblies and annotations for many aquatic species still presents significant challenges due to their large genome sizes, complexity, and high chromosome numbers. Indeed, selecting the most appropriate sequencing and software platforms and annotation pipelines for a new genome project can be daunting because tools often only work in limited contexts. In genomics, generating a high-quality genome assembly/annotation has become an indispensable tool for better understanding the biology of any species. Herein, we state 12 steps to help researchers get started in genome projects by presenting guidelines that are broadly applicable (to any species), sustainable over time, and cover all aspects of genome assembly and annotation projects from start to finish. We review some commonly used approaches, including practical methods to extract high-quality DNA and choices for the best sequencing platforms and library preparations. In addition, we discuss the range of potential bioinformatics pipelines, including structural and functional annotations (e.g., transposable elements and repetitive sequences). This paper also includes information on how to build a wide community for a genome project, the importance of data management, and how to make the data and results Findable, Accessible, Interoperable, and Reusable (FAIR) by submitting them to a public repository and sharing them with the research community.