Genome-wide association and genomic prediction of resistance to viral nervous necrosis in European sea bass (Dicentrarchus labrax) using RAD sequencing

Identification of candidate SNPs and genes associated with resistance to nervous necrosis virus in leopard coral grouper (Plectropomus leopardus) using GWAS

The leopard coral grouper (Plectropomus leopardus), which has become increasingly popular in consumption due to its bright body color and great nutritional, holds a high economic and breeding potential. However, in recent years, the P.leopardus aquaculture industry has been impeded by the nervous necrosis virus (NNV) outbreak, leading to widespread mortality among fry and juvenile grouper. However, the genetic basis of resistance to NNV in P. leopardus remains to be investigated. In the present study, we conducted a genome-wide association analysis (GWAS) on 100 resistant and 100 susceptible samples to discover variants and potential genes linked with NNV resistance. For this study, 157,926 high-quality single nucleotide polymorphisms (SNPs) based on whole genome resequencing were discovered, and eighteen SNPs loci linked to disease resistance were discovered. We annotated six relevant candidate genes, including sik2, herc2, pip5k1c, npr1, mybpc3, and arhgap9, which showed important roles in lipid metabolism, oxidative stress, and neuronal survival. In the brain tissues of resistant and susceptible groups, candidate genes against NNV infection showed significant differential expression. The results indicate that regulating neuronal survival or pathways involved in lipid metabolism may result in increased resistance to NNV. Understanding the molecular mechanisms that lead to NNV resistance will be beneficial for the growth of the P. leopardus breeding sector. Additionally, the identified SNPs could be employed as biomarkers of disease resistance in P. leopardus, which will facilitate the selective breeding of grouper.

Whole-genome sequencing identifies interferon-induced protein IFI6/IFI27-like as a strong candidate gene for VNN resistance in European sea bass

BACKGROUND

Viral nervous necrosis (VNN) is a major disease that affects European sea bass, and understanding the biological mechanisms that underlie VNN resistance is important for the welfare of farmed fish and sustainability of production systems. The aim of this study was to identify genomic regions and genes that are associated with VNN resistance in sea bass.

RESULTS

We generated a dataset of 838,451 single nucleotide polymorphisms (SNPs) identified from whole-genome sequencing (WGS) in the parental generation of two commercial populations (A: 2371 individuals and B: 3428 individuals) of European sea bass with phenotypic records for binary survival in a VNN challenge. For each population, three cohorts were submitted to a red-spotted grouper nervous necrosis virus (RGNNV) challenge by immersion and genotyped on a 57K SNP chip. After imputation of WGS SNPs from their parents, quantitative trait loci (QTL) were mapped using a Bayesian sparse linear mixed model (BSLMM). We found several QTL regions that were specific to one of the populations on different linkage groups (LG), and one 127-kb QTL region on LG12 that was shared by both populations and included the genes ZDHHC14, which encodes a palmitoyltransferase, and IFI6/IFI27-like, which encodes an interferon-alpha induced protein. The most significant SNP in this QTL region was only 1.9 kb downstream of the coding sequence of the IFI6/IFI27-like gene. An unrelated population of four large families was used to validate the effect of the QTL. Survival rates of susceptible genotypes were 40.6% and 45.4% in populations A and B, respectively, while that of the resistant genotype was 66.2% in population B and 78% in population A.

CONCLUSIONS

We have identified a genomic region that carries a major QTL for resistance to VNN and includes the ZDHHC14 and IFI6/IFI27-like genes. The potential involvement of the interferon pathway, a well-known anti-viral defense mechanism in several organisms (chicken, human, or fish), in survival to VNN infection is of particular interest. Our results can lead to major improvements for sea bass breeding programs through marker-assisted genomic selection to obtain more resistant fish.

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.

Genome-wide association study revealed suggestive QTLs for production and reproduction traits in Indian Murrah buffalo

The present study was aimed to identify the genome-wide SNPs associated with production and reproduction traits in 96 Indian Murrah buffalo genotyped based on ddRAD approach using Genome-Wide Association Study (GWAS) along with phenotypes of contemporary animals using mixed linear model for production and reproduction traits. A total of 27,735 SNPs identified using ddRAD approach in 96 Indian Murrah buffaloes were used for GWAS. A total of 28 SNPs were found to be associated with production and reproductive traits. Among these, 14 SNPs were present in the intronic region of AK5, BACH2, DIRC2, ECPAS, MPZL1, MYO16, QRFPR, RASGRF1, SLC9A4, TANC1, and TRIM67 genes and one SNP in long non-coding region of LOC102414911. Out of these 28 SNPs, 9 SNPs were found to have pleiotropic effect over milk production traits and were present in chromosome number BBU 1, 2, 4, 6, 9, 10, 12, 19, and 20. SNPs in the intronic region of AK5, TRIM67 genes were found to be associated with milk production traits. Eleven and five SNPs in the intergenic region were associated with milk production and reproduction traits respectively. The above genomic information may be used for selection of Murrah animals for genetic improvement.

Applying genetic technologies to combat infectious diseases in aquaculture

Disease and parasitism cause major welfare, environmental and economic concerns for global aquaculture. In this review, we examine the status and potential of technologies that exploit genetic variation in host resistance to tackle this problem. We argue that there is an urgent need to improve understanding of the genetic mechanisms involved, leading to the development of tools that can be applied to boost host resistance and reduce the disease burden. We draw on two pressing global disease problems as case studies-sea lice infestations in salmonids and white spot syndrome in shrimp. We review how the latest genetic technologies can be capitalised upon to determine the mechanisms underlying inter- and intra-species variation in pathogen/parasite resistance, and how the derived knowledge could be applied to boost disease resistance using selective breeding, gene editing and/or with targeted feed treatments and vaccines. Gene editing brings novel opportunities, but also implementation and dissemination challenges, and necessitates new protocols to integrate the technology into aquaculture breeding programmes. There is also an ongoing need to minimise risks of disease agents evolving to overcome genetic improvements to host resistance, and insights from epidemiological and evolutionary models of pathogen infestation in wild and cultured host populations are explored. Ethical issues around the different approaches for achieving genetic resistance are discussed. Application of genetic technologies and approaches has potential to improve fundamental knowledge of mechanisms affecting genetic resistance and provide effective pathways for implementation that could lead to more resistant aquaculture stocks, transforming global aquaculture.

Integrative analysis of GWAS and transcriptome reveals p53 signaling pathway mediates resistance to visceral white-nodules disease in large yellow croaker

Visceral white-nodules disease (VWND), caused by Pseudomonas plecoglossicida, is one of the primary causes of morbidity and mortality in large yellow croaker aquaculture. Host disease resistance is a heritable trait that involves complex regulatory processes. However, the regulatory mechanism of bacterial resistance in large yellow croaker is still unclear. This study attempted to systematically evaluate the major genetic loci and transcriptional regulatory mechanisms associated with the resistance to VWND in large yellow croaker by crossover method studies. A large population of large yellow croaker was challenged with P. plecoglossicida, with survival time recorded and samples were taken for genotyping. Meanwhile, spleen samples that were used for RNA-seq to compare their transcriptomic profiles before and after infection were taken from resistant populations (RS) and susceptible control populations (CS) bred using the genomic selection (GS) technique. Genome-wide association analyses using 46 K imputed SNP genotypes highlighted that resistance is a polygenic trait. The integrative analysis results show the co-localization of the cd82a gene between disease resistance-related genetic loci and comparative transcriptional analysis. And functional enrichment analysis showed differential enrichment of the p53 signaling pathway in RS and CS groups, suggesting that there may be cd82a-mediated p53 signaling pathway activation for VWND resistance. This large-scale study provides further evidence for the heritability and transcriptional regulatory mechanisms of host inheritance of VWND resistance.

Insight into selective breeding for robustness based on field survival records: New genetic evaluation of survival traits in pacific white shrimp (Penaeus vannamei) breeding line

Survival can be considered a relatively ‘old’ trait in animal breeding, yet commonly neglected in aquaculture breeding because of the simple binary records and generally low heritability estimates. Developing routine genetic evaluation systems for survival traits however, will be important for breeding robust strains based on valuable field survival data. In the current study, linear multivariate animal model (LMA) was used for the genetic analysis of survival records from 2-year classes (BL2019 and BL2020) of pacific white shrimp (Penaeus vannamei) breeding lines with data collection of 52, 248 individuals from 481 fullsib families. During grow-out test period, 10 days intervals of survival data were considered as separate traits. Two survival definitions, binary survivability (S) and continuous survival in days (SL), were used for the genetic analysis of survival records to investigate; 1) whether adding more survival time information could improve estimation of genetic parameters; 2) the trajectory of survival heritability across time, and 3) patterns of genetic correlations of survival traits across time. Levels of heritability estimates for both S and SL were low (0.005–0.076), while heritability for survival day number was found to be similar with that of binary records at each observation time and were highly genetically correlated (r_g > 0.8). Heritability estimates of body weight (BW) for BL2019 and BL2020 were 0.486 and 0.373, respectively. Trajectories of survival heritability showed a gradual increase across the grow-out test period but slowed or reached a plateau during the later grow-out test period. Genetic correlations among survival traits in the grow-out tests were moderate to high, and the closer the times were between estimates, the higher were their genetic correlations. In contrast, genetic correlations between both survival traits and body weight were low but positive. Here we provide the first report on the trajectory of heritability estimates for survival traits across grow-out stage in aquaculture. Results will be useful for developing robust improved pacific white shrimp culture strains in selective breeding programs based on field survival data.

Genome-Wide Population Structure and Selection Signatures of Yunling Goat Based on RAD-seq

Simple Summary

Goats are important domestic animals that provide meat, milk, fur, and other products for humans. The demand for these products has increased in recent years. Disease resistance among goat breeds is different, but the genetic basis of the differences in resistance to diseases is still unclear and needs to be further studied. In this study, many genes and pathways related to immunity and diseases were identified to be under positive selection between Yunling and Nubian goats using RAD-seq technology. This study on the selection signatures of Yunling goats provides the scientific basis and technical support for the breeding of domestic goats for disease resistance, which has important social and economic significance.

Abstract

Animal diseases impose a huge burden on the countries where diseases are endemic. Conventional control strategies of vaccines and veterinary drugs are to control diseases from a pharmaceutical perspective. Another alternative approach is using pre-existing genetic disease resistance or tolerance. We know that the Yunling goat is an excellent local breed from Yunnan, southwestern China, which has characteristics of strong disease resistance and remarkable adaptability. However, genetic information about the selection signatures of Yunling goats is limited. We reasoned that the genes underlying the observed difference in disease resistance might be identified by investigating selection signatures between two different goat breeds. Herein, we selected the Nubian goat as the reference group to perform the population structure and selection signature analysis by using RAD-seq technology. The results showed that two goat breeds were divided into two clusters, but there also existed gene flow. We used Fst (F-statistics) and π (pi/θπ) methods to carry out selection signature analysis. Eight selected regions and 91 candidate genes were identified, in which some genes such as DOK2, TIMM17A, MAVS, and DOCK8 related to disease and immunity and some genes such as SPEFI, CDC25B, and MIR103 were associated with reproduction. Four GO (Gene Ontology) terms (GO:0010591, GO:001601, GO:0038023, and GO:0017166) were associated with cell migration, signal transduction, and immune responses. The KEGG (Kyoto Encyclopedia of Genes and Genomes) signaling pathways were mainly associated with immune responses, inflammatory responses, and stress reactions. This study preliminarily revealed the genetic basis of strong disease resistance and adaptability of Yunling goats. It provides a theoretical basis for the subsequent genetic breeding of disease resistance of goats.

Genetic Basis for Resistance Against Viral Nervous Necrosis: GWAS and Potential of Genomic Prediction Explored in Farmed European Sea Bass (Dicentrarchus labrax)

Viral nervous necrosis (VNN) is an infectious disease caused by the red-spotted grouper nervous necrosis virus (RGNNV) in European sea bass and is considered a serious concern for the aquaculture industry with fry and juveniles being highly susceptible. To understand the genetic basis for resistance against VNN, a survival phenotype through the challenge test against the RGNNV was recorded in populations from multiple year classes (YC2016 and YC2017). A total of 4,851 individuals from 181 families were tested, and a subset (n∼1,535) belonging to 122 families was genotyped using a ∼57K Affymetrix Axiom array. The survival against the RGNNV showed low to moderate heritability with observed scale estimates of 0.18 and 0.25 obtained using pedigree vs. genomic information, respectively. The genome-wide association analysis showed a strong signal of quantitative trait loci (QTL) at LG12 which explained ∼33% of the genetic variance. The QTL region contained multiple genes (ITPK1, PLK4, HSPA4L, REEP1, CHMP2, MRPL35, and SCUBE) with HSPA4L and/or REEP1 genes being highly relevant with a likely effect on host response in managing disease-associated symptoms. The results on the accuracy of predicting breeding values presented 20–43% advantage in accuracy using genomic over pedigree-based information which varied across model types and applied validation schemes.

Integrated Management Strategies for Viral Nervous Necrosis (VNN) Disease Control in Marine Fish Farming in the Mediterranean

Viral nervous necrosis (VNN) is the most important viral disease affecting farmed fish in the Mediterranean. VNN can affect multiple fish species in all production phases (broodstock, hatchery, nursery and ongrowing) and sizes, but it is especially severe in larvae and juvenile stages, where can it cause up to 100% mortalities. European sea bass has been and is still the most affected species, and VNN in gilthead sea bream has become an emerging problem in recent years affecting larvae and juveniles and associated to the presence of new nervous necrosis virus (NNV) reassortants. The relevance of this disease as one of the main biological hazards for Mediterranean finfish farming has been particularly addressed in two recent H2020 projects: PerformFISH and MedAID. The presence of the virus in the environment and in the farming systems poses a serious menace for the development of the Mediterranean finfish aquaculture. Several risks associated to the VNN development in farms have been identified in the different phases of the farming system. The main risks concerning VNN affecting gilthead seabream and European seabass have been identified as restocking from wild fish in broodstock facilities, the origin of eggs and juveniles, quality water supply and live food in hatcheries and nurseries, and infected juveniles and location of farms in endemic areas for on-growing sites. Due to the potential severe impact, a holistic integrated management approach is the best strategy to control VNN in marine fish farms. This approach should include continuous surveillance and early and accurate diagnosis, essential for an early intervention when an outbreak occurs, the implementation of biosecurity and disinfection procedures in the production sites and systematic vaccination with effective vaccines. Outbreak management practices, clinical aspects, diagnostic techniques, and disinfections methods are reviewed in detail in this paper. Additionally, new strategies are becoming more relevant, such as the use of genetic resistant lines and boosting the fish immune system though nutrition.

Genomic Predictions of Phenotypes and Pseudo-Phenotypes for Viral Nervous Necrosis Resistance, Cortisol Concentration, Antibody Titer and Body Weight in European Sea Bass

Simple Summary

Selective breeding programs based on genomic data are still not a common practice in aquaculture, although genomic selection has been widely demonstrated to be advantageous when trait phenotyping is a difficult task. In this study, we investigated the accuracy of predicting the phenotype and the estimated breeding value (EBV) of three Bayesian models and a Random Forest algorithm exploiting the information of a genome-wide SNP panel for European sea bass. The genomic predictions were developed for mortality caused by viral nervous necrosis, post-stress cortisol concentration, antibody titer against nervous necrosis virus and body weight. Selective breeding based on genomic data is a possible option for improving these traits while overcoming difficulties related to individual phenotyping of the investigated traits. Our results evidenced that the EBV used as a pseudo-phenotype enhances the predictive performances of genomic models, and that EBV can be predicted with satisfactory accuracy. The genomic prediction of the EBV for mortality might also be used to classify the phenotype for the same trait.

Abstract

In European sea bass (Dicentrarchus labrax L.), the viral nervous necrosis mortality (MORT), post-stress cortisol concentration (HC), antibody titer (AT) against nervous necrosis virus and body weight (BW) show significant heritability, which makes selective breeding a possible option for their improvement. An experimental population (N = 650) generated by a commercial broodstock was phenotyped for the aforementioned traits and genotyped with a genome-wide SNP panel (16,075 markers). We compared the predictive accuracies of three Bayesian models (Bayes B, Bayes C and Bayesian Ridge Regression) and a machine-learning method (Random Forest). The prediction accuracy of the EBV for MORT was approximately 0.90, whereas the prediction accuracies of the EBV and the phenotype were 0.86 and 0.21 for HC, 0.79 and 0.26 for AT and 0.71 and 0.38 for BW. The genomic prediction of the EBV for MORT used to classify the phenotype for the same trait showed moderate classification performance. Genome-wide association studies confirmed the polygenic nature of MORT and demonstrated a complex genetic structure for HC and AT. Genomic predictions of the EBV for MORT could potentially be used to classify the phenotype of the same trait, though further investigations on a larger experimental population are needed.

Genomic Selection and Genome-Wide Association Analysis for Stress Response, Disease Resistance and Body Weight in European Seabass

Simple Summary

In the present study, the genetic architecture of the stress response, body weight, and disease resistance in European seabass were studied, providing fruitful results for further research. Initially, the above traits were recorded and genotyping on a large scale was performed in those fish. The recorded data and genotypes were combined and analyzed to find genomic areas affecting them as well as to estimate the heritability of those traits. Stress response traits and body weight were medium heritable, while genomic regions affecting them were detected. However, no genomic areas related to disease resistance were revealed. These findings improve our knowledge of the genetic structure of those traits and can be utilized in a breeding program for the genetic improvement of aquaculture broodstocks.

Abstract

The majority of the genetic studies in aquaculture breeding programs focus on commercial traits such as body weight, morphology, and resistance against diseases. However, studying stress response in European seabass may contribute to the understanding of the genetic component of stress and its future use to select broodstock whose offspring may potentially be less affected by handling. A total of 865 European seabass offspring were used to measure body weight and stress response. Moreover, a disease challenge experiment with Vibrio anguillarum was conducted in a subset (332) of the above fish to study disease resistance. Fish were genotyped with a 57k SNP array, and a Genome-Wide Association study (GWAS) was performed. Five SNPs were found to be statistically significant, three of which affect stress indicators and body weight (in a subgroup of the population), and a putative SNP affects growth performance, while no SNP associated with resistance to Vibrio was found. A moderate to high genomic heritability regarding stress indicators and body weight was estimated using the Restricted Maximum Likelihood (REML) process. Finally, the accuracy, along with the correlation between Estimated Breeding Values (EBVs) and Genomic Estimated Breeding Values (GEBVs), were calculated for all the traits.

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.

Estimates of recent and historical effective population size in turbot, seabream, seabass and carp selective breeding programmes

Background

The high fecundity of fish species allows intense selection to be practised and therefore leads to fast genetic gains. Based on this, numerous selective breeding programmes have been started in Europe in the last decades, but in general, little is known about how the base populations of breeders have been built. Such knowledge is important because base populations can be created from very few individuals, which can lead to small effective population sizes and associated reductions in genetic variability. In this study, we used genomic information that was recently made available for turbot (Scophthalmus maximus), gilthead seabream (Sparus aurata), European seabass (Dicentrarchus labrax) and common carp (Cyprinus carpio) to obtain accurate estimates of the effective size for commercial populations.

Methods

Restriction-site associated DNA sequencing data were used to estimate current and historical effective population sizes. We used a novel method that considers the linkage disequilibrium spectrum for the whole range of genetic distances between all pairs of single nucleotide polymorphisms (SNPs), and thus accounts for potential fluctuations in population size over time.

Results

Our results show that the current effective population size for these populations is small (equal to or less than 50 fish), potentially putting the sustainability of the breeding programmes at risk. We have also detected important drops in effective population size about five to nine generations ago, most likely as a result of domestication and the start of selective breeding programmes for these species in Europe.

Conclusions

Our findings highlight the need to broaden the genetic composition of the base populations from which selection programmes start, and suggest that measures designed to increase effective population size within all farmed populations analysed here should be implemented in order to manage genetic variability and ensure the sustainability of the breeding programmes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00680-9.

Genomic Selection and Genome-wide Association Study for Feed-Efficiency Traits in a Farmed Nile Tilapia (Oreochromis niloticus) Population

Nile tilapia is a key aquaculture species with one of the highest production volumes globally. Genetic improvement of feed efficiency via selective breeding is an important goal, and genomic selection may expedite this process. The aims of this study were to 1) dissect the genetic architecture of feed-efficiency traits in a Nile tilapia breeding population, 2) map the genomic regions associated with these traits and identify candidate genes, 3) evaluate the accuracy of breeding value prediction using genomic data, and 4) assess the impact of the genetic marker density on genomic prediction accuracies. Using an experimental video recording trial, feed conversion ratio (FCR), body weight gain (BWG), residual feed intake (RFI) and feed intake (FI) traits were recorded in 40 full-sibling families from the GIFT (Genetically Improved Farmed Tilapia) Nile tilapia breeding population. Fish were genotyped with a ThermoFisher Axiom 65 K Nile tilapia SNP array. Significant heritabilities, ranging from 0.12 to 0.22, were estimated for all the assessed traits using the genomic relationship matrix. A negative but favourable genetic correlation was found between BWG and the feed-efficiency related traits; -0.60 and -0.63 for FCR and RFI, respectively. While the genome-wide association analyses suggested a polygenic genetic architecture for all the measured traits, there were significant QTL identified for BWG and FI on chromosomes seven and five respectively. Candidate genes previously found to be associated with feed-efficiency traits were located in these QTL regions, including ntrk3a, ghrh and eif4e3. The accuracy of breeding value prediction using the genomic data was up to 34% higher than using pedigree records. A SNP density of approximately 5,000 SNPs was sufficient to achieve similar prediction accuracy as the full genotype data set. Our results highlight the potential of genomic selection to improve feed efficiency traits in Nile tilapia breeding programmes.

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.

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.

Development of a 38 K single nucleotide polymorphism array and application in genomic selection for resistance against Vibrio harveyi in Chinese tongue sole, Cynoglossus semilaevis

Based on 1572 re-sequenced Chinese tongue sole (Cynoglossus semilaevis), we investigated the accuracy of four genomic methods at predicting genomic estimated breeding values (GEBVs) of Vibrio harveyi resistance in C. semilaevis when SNPs varying from 500 to 500 k. All methods outperformed the pedigree-based best linear unbiased prediction when SNPs reached 50 k or more. Then, we developed an SNP array "Solechip No.1" for C. semilaevis breeding using the Affymetrix Axiom technology. This array contains 38,295 SNPs with an average of 10.5 kb inter-spacing between two adjacent SNPs. We selected 44 candidates as the parents of 23 families and genotyped them by the array. The challenge survival rates of offspring families had a correlation of 0.706 with the mid-parental GEBVs. This SNP array is a convenient and reliable tool in genotyping, which could be used for improving V. harveyi resistance in C. semilaevis coupled with the genomic selection methods.

Resistance to viral nervous necrosis in European sea bass (Dicentrarchus labrax L.): heritability and relationships with body weight, cortisol concentration, and antibody titer

Background

Susceptibility of European sea bass (Dicentrarchus labrax L.) to viral nervous necrosis (VNN) is well-known. Interest towards selective breeding as a tool to enhance genetic resistance in this species has increased sharply due to the major threat represented by VNN for farmed sea bass and limitations concerning specific therapeutical measures. A sea bass experimental population (N = 650) was challenged with nervous necrosis virus (NNV) to investigate genetic variation in VNN mortality. In addition, relationships of this trait with serum cortisol concentration after stress exposure, antibody titer against NNV antigens, and body weight at a fixed age were studied to identify potential indicator traits of VNN resistance.

Results

The estimate of heritability for VNN mortality was moderate and ranged from 0.15 (HPD95%, 95% highest posterior density interval: 0.02, 0.31) to 0.23 (HPD95%: 0.06, 0.47). Heritability estimates for cortisol concentration, antibody titer, and body weight were 0.19 (HPD95%: 0.07, 0.34), 0.36 (HPD95%: 0.16, 0.59) and 0.57 (HPD95%: 0.33, 0.84), respectively. Phenotypic relationships between traits were trivial and not statistically significant, except for the estimated correlation between antibody titer and body weight (0.24). Genetic correlations of mortality with body weight or antibody titer (− 0.39) exhibited a 0.89 probability of being negative. A negligible genetic correlation between mortality and cortisol concentration was detected. Antibody titer was estimated to be positively correlated with body weight (0.49).

Conclusions

Antibody titer against NNV offers the opportunity to use indirect selection to enhance resistance, while the use of cortisol concentration as an indicator trait in breeding programs for VNN resistance is questionable. The estimate of heritability for VNN mortality indicates the feasibility of selective breeding to enhance resistance to NNV and raises attention to the development of genomic prediction tools to simplify testing procedures for selection candidates.

Genome-Wide Marker Analysis for Traits of Economic Importance in Asian Seabass Lates calcarifer

To date, it is not known whether animal breeding values in Asian seabass (Lates calcarifer) can be estimated using single nucleotide polymorphisms (SNPs) generated from new high-throughput genotyping by sequencing platforms. The principal aim of the present study was to assess the genomic prediction accuracy for growth traits, survival, cannibalism, and disease resistance against Streptococcus iniae in this species L. calcarifer. Additionally, this study attempted to identify markers associated with the five traits studied as well as to understand if the genotype data can be used to estimate genetic parameters for these complex traits. The genomic best linear unbiased prediction (gBLUP) method was used to analyze 11,084 SNPs and showed that the prediction accuracies for growth traits (weight and length) were high (0.67–0.75). By contrast, these estimates for survival were low (0.25). Multi-locus mixed model analyses identified four SNPs significantly associated with body weight (p < 5 × 10−8 or −log10 p ≥ 5). There were, however, no significant associations detected for other traits. Similarly, the SNP heritability was moderate, while the estimates for other traits were approximated to zero and not significant. Genetic correlations between body weight and standard length were close to unity. Collectively, the results obtained from this study suggest that genotyping by sequencing platforms can provide informative DNA markers to conduct genome-wide association analysis, estimation of genetic parameters, and evaluation of genomic prediction accuracy for complex traits in Asian seabass.

Genomic selection for heterobothriosis resistance concurrent with body size in the tiger pufferfish, Takifugu rubripes

Parasite resistance traits in aquaculture species often have moderate heritability, indicating the potential for genetic improvements by selective breeding. However, parasite resistance is often synonymous with an undesirable negative correlation with body size. In this study, we first tested the feasibility of genomic selection (GS) on resistance to heterobothriosis, caused by the monogenean parasite Heterobothrium okamotoi, which leads to huge economic losses in aquaculture of the tiger pufferfish Takifugu rubripes. Then, using a simulation study, we tested the possibility of simultaneous improvement of parasite resistance, assessed by parasite counts on host fish (HC), and standard length (SL). Each trait showed moderate heritability (square-root transformed HC: h2 = 0.308 ± 0.123, S.E.; SL: h2 = 0.405 ± 0.131). The predictive abilities of genomic prediction among 12 models, including genomic Best Linear Unbiased Predictor (GBLUP), Bayesian regressions, and machine learning procedures, were also moderate for both transformed HC (0.248‒0.344) and SL (0.340‒0.481). These results confirmed the feasibility of GS for this trait. Although an undesirable genetic correlation was suggested between transformed HC and SL (rg = 0.228), the simulation study suggested the desired gains index can help achieve simultaneous genetic improvements in both traits.

Development of a SNP linkage map and genome-wide association study for resistance to Aeromonas hydrophila in pacu (Piaractus mesopotamicus)

BACKGROUND

Pacu (Piaractus mesopotamicus) is one of the most important Neotropical aquaculture species from South America. Disease outbreaks caused by Aeromonas hydrophila infection have been considered significant contributors to the declining levels of pacu production. The current implementation of genomic selection for disease resistance has been adopted as a powerful strategy for improvement in fish species. This study aimed to investigate the genetic architecture of resistance to A. hydrophila in pacu via Genome-Wide Association Study (GWAS), the identification of suggestive Quantitative Trait Loci (QTLs) and putative genes associated with this trait. The genetic data were obtained from 381 juvenile individuals belonging to 14 full-sibling families. An experimental challenge was performed to gain access to the levels of genetic variation for resistance against the bacteria using the following trait definitions: binary test survival (TS) and time of death (TD).

RESULTS

The analyses of genetic parameters estimated moderate heritability (h2) for both resistance traits: 0.20 (± 0.09) for TS and 0.35 (± 0.15) for TD. A linkage map for pacu was developed to enable the GWAS, resulting in 27 linkage groups (LGs) with 17,453 mapped Single Nucleotide Polymorphisms (SNPs). The length of the LGs varied from 79.95 (LG14) to 137.01 (LG1) cM, with a total map length of 2755.60 cM. GWAS identified 22 putative QTLs associated to A. hydrophila resistance. They were distributed into 17 LGs, and were considered suggestive genomic regions explaining > 1% of the additive genetic variance (AGV) for the trait. Several candidate genes related to immune response were located close to the suggestive QTLs, such as tbk1, trim16, Il12rb2 and lyz2.

CONCLUSION

This study describes the development of the first medium density linkage map for pacu, which will be used as a framework to study relevant traits to the production of this species. In addition, the resistance to A. hydrophila was found to be moderately heritable but with a polygenic architecture suggesting that genomic selection, instead of marker assisted selection, might be useful for efficiently improving resistance to one of the most problematic diseases that affects the South American aquaculture.

Prediction of genomic breeding values based on pre-selected SNPs using ssGBLUP, WssGBLUP and BayesB for Edwardsiellosis resistance in Japanese flounder

Background

Edwardsiella tarda causes acute symptoms with ascites in Japanese flounder (Paralichthys olivaceus) and is a major problem for China’s aquaculture sector. Genomic selection (GS) has been widely adopted in breeding industries because it shortens generation intervals and results in the selection of individuals that have great breeding potential with high accuracy. Based on an artificial challenge test and re-sequenced data of 1099 flounders, the aims of this study were to estimate the genetic parameters of resistance to E. tarda in Japanese flounder and to evaluate the accuracy of single-step GBLUP (ssGBLUP), weighted ssGBLUP (WssGBLUP), and BayesB for improving resistance to E. tarda by using three subsets of pre-selected single nucleotide polymorphisms (SNPs). In addition, SNPs that are associated with this trait were identified using a single-SNP genome-wide association study (GWAS) and WssGBLUP.

Results

We estimated a heritability of 0.13 ± 0.02 for resistance to E. tarda in Japanese flounder. One million SNPs at fixed intervals were selected from 4,978,724 SNPs that passed quality controls. GWAS identified significant SNPs on chromosomes 14 and 24. WssGBLUP revealed that the putative quantitative trait loci on chromosomes 1 and 14 contained SNPs that explained more than 1% of the genetic variance. Three 50 k-SNP subsets were pre-selected based on different criteria. Compared with pedigree-based prediction (ABLUP), the three genomic methods evaluated resulted in at least 7.7% greater accuracy of predictions. The accuracy of these genomic prediction methods was almost unchanged when pre-selected trait-related SNPs were used for prediction.

Conclusions

Resistance to E. tarda in Japanese flounder has a low heritability. GWAS and WssGBLUP revealed that the genetic architecture of this trait is polygenic. Genomic prediction of breeding values performed better than ABLUP. It is feasible to implement genomic selection to increase resistance to E. tarda in Japanese flounder with 50 k SNPs. Based on the criteria used here, pre-selection of SNPs was not beneficial and other criteria for pre-selection should be considered.

Combining Multiple Approaches and Models to Dissect the Genetic Architecture of Resistance to Infections in Fish

Infectious diseases represent a major threat for the sustainable development of fish farming. Efficient vaccines are not available against all diseases, and growing antibiotics resistance limits the use of antimicrobial drugs in aquaculture. It is therefore important to understand the basis of fish natural resistance to infections to help genetic selection and to develop new approaches against infectious diseases. However, the identification of the main mechanisms determining the resistance or susceptibility of a host to a pathogenic microbe is challenging, integrating the complexity of the variation of host genetics, the variability of pathogens, and their capacity of fast evolution and adaptation. Multiple approaches have been used for this purpose: (i) genetic approaches, QTL (quantitative trait loci) mapping or GWAS (genome-wide association study) analysis, to dissect the genetic architecture of disease resistance, and (ii) transcriptomics and functional assays to link the genetic constitution of a fish to the molecular mechanisms involved in its interactions with pathogens. To date, many studies in a wide range of fish species have investigated the genetic determinism of resistance to many diseases using QTL mapping or GWAS analyses. A few of these studies pointed mainly toward adaptive mechanisms of resistance/susceptibility to infections; others pointed toward innate or intrinsic mechanisms. However, in the majority of studies, underlying mechanisms remain unknown. By comparing gene expression profiles between resistant and susceptible genetic backgrounds, transcriptomics studies have contributed to build a framework of gene pathways determining fish responsiveness to a number of pathogens. Adding functional assays to expression and genetic approaches has led to a better understanding of resistance mechanisms in some cases. The development of knock-out approaches will complement these analyses and help to validate putative candidate genes critical for resistance to infections. In this review, we highlight fish isogenic lines as a unique biological material to unravel the complexity of host response to different pathogens. In the future, combining multiple approaches will lead to a better understanding of the dynamics of interaction between the pathogen and the host immune response, and contribute to the identification of potential targets of selection for improved resistance.

Harnessing genomics to fast-track genetic improvement in aquaculture

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

Characterising the mechanisms underlying genetic resistance to amoebic gill disease in Atlantic salmon using RNA sequencing

Background

Gill health is one of the main concerns for Atlantic salmon aquaculture, and Amoebic Gill Disease (AGD), attributable to infection by the amoeba Neoparamoeba perurans, is a frequent cause of morbidity. In the absence of preventive measures, increasing genetic resistance of salmon to AGD via selective breeding can reduce the incidence of the disease and mitigate gill damage. Understanding the mechanisms leading to AGD resistance and the underlying causative genomic features can aid in this effort, while also providing critical information for the development of other control strategies. AGD resistance is considered to be moderately heritable, and several putative QTL have been identified. The aim of the current study was to improve understanding of the mechanisms underlying AGD resistance, and to identify putative causative genomic factors underlying the QTL. To achieve this, RNA was extracted from the gill and head kidney of AGD resistant and susceptible animals following a challenge with N. perurans, and sequenced.

Results

Comparison between resistant and susceptible animals primarily highlighted differences mainly in the local immune response in the gill, involving red blood cell genes and genes related to immune function and cell adhesion. Differentially expressed immune genes pointed to a contrast in Th2 and Th17 responses, which is consistent with the increased heritability observed after successive challenges with the amoeba. Five QTL-region candidate genes showed differential expression, including a gene connected to interferon responses (GVINP1), a gene involved in systemic inflammation (MAP4K4), and a positive regulator of apoptosis (TRIM39). Analyses of allele-specific expression highlighted a gene in the QTL region on chromosome 17, cellular repressor of E1A-stimulated genes 1 (CREG1), showing allelic differential expression suggestive of a cis-acting regulatory variant.

Conclusions

In summary, this study provides new insights into the mechanisms of resistance to AGD in Atlantic salmon, and highlights candidate genes for further functional studies that can further elucidate the genomic mechanisms leading to resistance and contribute to enhancing salmon health via improved genomic selection.

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.

Quantitative Trait Loci (QTL) Mapping

Quantitative trait loci (QTL) are genetic regions that influence phenotypic variation of a complex trait, often through genetic interactions with each other and the environment. These are commonly identified through a statistical genetic analysis known as QTL mapping. Here, I present a step-by-step, practical approach to QTL mapping along with a sample data file. I focus on methods commonly used and discoveries that have been made in fishes, and utilize a multiple QTL mapping (MQM) approach in the free software package R/qtl.

Optimizing Genomic Prediction of Host Resistance to Koi Herpesvirus Disease in Carp

Genomic selection (GS) is increasingly applied in breeding programs of major aquaculture species, enabling improved prediction accuracy and genetic gain compared to pedigree-based approaches. Koi Herpesvirus disease (KHVD) is notifiable by the World Organization for Animal Health and the European Union, causing major economic losses to carp production. GS has potential to breed carp with improved resistance to KHVD, thereby contributing to disease control. In the current study, Restriction-site Associated DNA sequencing (RAD-seq) was applied on a population of 1,425 common carp juveniles which had been challenged with Koi herpes virus, followed by sampling of survivors and mortalities. GS was tested on a wide range of scenarios by varying both SNP densities and the genetic relationships between training and validation sets. The accuracy of correctly identifying KHVD resistant animals using GS was between 8 and 18% higher than pedigree best linear unbiased predictor (pBLUP) depending on the tested scenario. Furthermore, minor decreases in prediction accuracy were observed with decreased SNP density. However, the genetic relationship between the training and validation sets was a key factor in the efficacy of genomic prediction of KHVD resistance in carp, with substantially lower prediction accuracy when the relationships between the training and validation sets did not contain close relatives.

The European sea bass: a key marine fish model in the wild and in aquaculture

The European sea bass (Dicentrarchus labrax L.) is a marine fish of key economic and cultural importance in Europe. It is now more an aquaculture than a fisheries species (>96% of the production in 2016), although modern rearing techniques date back only from the late 1980s. It also has high interest for evolutionary studies, as it is composed of two semispecies (Atlantic and Mediterranean lineages) that have come into secondary contact following the last glaciation. Based on quantitative genetics studies of most traits of interest over the past 10–15 years, selective breeding programs are now applied to this species, which is at the beginning of its domestication process. The availability of a good quality reference genome has accelerated the development of new genomic resources, including SNP arrays that will enable genomic selection to improve genetic gain. There is a need to improve feed efficiency, both for economic and environmental reasons, but this will require novel phenotyping approaches. Further developments will likely focus on the understanding of genotype‐by‐environment interactions, which will be important both for efficient breeding of farmed stocks and for improving knowledge of the evolution of natural populations. At the interface between both, the domestication process must be better understood to improve production and also to fully evaluate the possible impact of aquaculture escapees on wild populations. The latter is an important question for all large‐scale aquaculture productions.

Parentage assignment with genotyping-by-sequencing data

In this paper, we evaluate using genotype-by-sequencing (GBS) data to perform parentage assignment in lieu of traditional array data. The use of GBS data raises two issues: First, for low-coverage (e.g., <2×) GBS data, it may not be possible to call the genotype at many loci, a critical first step for detecting opposing homozygous markers. Second, the amount of sequencing coverage may vary across individuals, making it challenging to directly compare the likelihood scores between putative parents. To address these issues, we extend the probabilistic framework of Huisman (Molecular Ecology Resources, 2017, 17, 1009) and evaluate putative parents by comparing their (potentially noisy) genotypes to a series of proposal distributions. These distributions describe the expected genotype probabilities for the relatives of an individual. We assign putative parents as a parent if they are classified as a parent (as opposed to e.g., an unrelated individual), and if the assignment score passes a threshold. We evaluated this method on simulated data and found that (a) high-coverage (>2×) GBS data performs similarly to array data and requires only a small number of markers to correctly assign parents and (b) low-coverage GBS data (as low as 0.1×) can also be used, provided that it is obtained across a large number of markers. When analysing the low-coverage GBS data, we also found a high number of false positives if the true parent is not contained within the list of candidate parents, but that this false positive rate can be greatly reduced by hand tuning the assignment threshold. We provide this parentage assignment method as a standalone program called AlphaAssign.

Developing Successful Breeding Programs for New Zealand Aquaculture: A Perspective on Progress and Future Genomic Opportunities

Over the past 40 years New Zealand (NZ) aquaculture has grown into a significant primary industry. Tonnage is small on a global scale, but the industry has built an international reputation for the supply of high quality seafood to many overseas markets. Since the early 1990s the industry has recognized the potential gains from selective breeding and the challenge has been to develop programs that can overcome biological obstacles (such as larval rearing and mortality) and operate cost-effectively on a relatively small scale while still providing significant gains in multiple traits of economic value. This paper provides an overview of the current status, and a perspective on genomic technology implementation, for the family based genetic improvement programs established for the two main species farmed in NZ: Chinook (king) salmon (Oncorhynchus tshawytscha) and Greenshell^TM mussel (Perna canaliculus). These programs have provided significant benefit to the industry in which we are now developing genomic resources based on genotyping-by-sequencing to complement the breeding programs, enable evaluation of the genetic diversity and identify the potential benefits of genomic selection. This represents an opportunity to increase genetic gain and more effectively utilize the potential for within family selection.

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.

Disentangling Genetic Variation for Resistance and Endurance to Scuticociliatosis in Turbot Using Pedigree and Genomic Information

Selective breeding for improving host responses to infectious pathogens is a promising option for disease control. In fact, disease resilience, the ability of a host to survive or cope with infectious challenge, has become a highly desirable breeding goal. However, resilience is a complex trait composed of two different host defence mechanisms, namely resistance (the ability of a host to avoid becoming infected or diseased) and endurance (the ability of an infected host to survive the infection). While both could be targeted for genetic improvement, it is currently unknown how they contribute to survival, as reliable estimates of genetic parameters for both traits obtained simultaneously are scarce. A difficulty lies in obtaining endurance phenotypes for genetic analyses. In this study, we present the results from an innovative challenge test carried out in turbot whose design allowed disentangling the genetic basis of resistance and endurance to Philasterides dicentrarchi, a parasite causing scuticociliatosis that leads to substantial economic losses in the aquaculture industry. A noticeable characteristic of the parasite is that it causes visual signs that can be used for disentangling resistance and endurance. Our results showed the existence of genetic variation for both traits (heritability = 0.26 and 0.12 for resistance and endurance, respectively) and for the composite trait resilience (heritability = 0.15). The genetic correlation between resistance and resilience was very high (0.90) indicating that both are at a large extent the same trait, but no significant genetic correlation was found between resistance and endurance. A total of 18,125 SNPs obtained from 2b-RAD sequencing enabled genome-wide association analyses for detecting QTLs controlling the three traits. A candidate QTL region on linkage group 19 that explains 33% of the additive genetic variance was identified for resilience. The region contains relevant genes related to immune response and defence mechanisms. Although no significant associations were found for resistance, the pattern of association was the same as for resilience. For endurance, one significant association was found on linkage group 2. The accuracy of genomic breeding values was also explored for resilience, showing that it increased by 12% when compared with the accuracy of pedigree-based breeding values. To our knowledge, this is the first study in turbot disentangling the genetic basis of resistance and endurance to scuticociliatosis.

Mapping and Sequencing of a Significant Quantitative Trait Locus Affecting Resistance to Koi Herpesvirus in Common Carp

Cyprinids are the most highly produced group of fishes globally, with common carp being one of the most valuable species of the group. Koi herpesvirus (KHV) infections can result in high levels of mortality, causing major economic losses, and is listed as a notifiable disease by the World Organization for Animal Health. Selective breeding for host resistance has the potential to reduce morbidity and losses due to KHV. Therefore, improving knowledge about host resistance and methods of incorporating genomic data into breeding for resistance may contribute to a decrease in economic losses in carp farming. In the current study, a population of 1,425 carp juveniles, originating from a factorial cross between 40 sires and 20 dams was challenged with KHV. Mortalities and survivors were recorded and sampled for genotyping by sequencing using Restriction Site-Associated DNA sequencing (RADseq). Genome-wide association analyses were performed to investigate the genetic architecture of resistance to KHV. A genome-wide significant QTL affecting resistance to KHV was identified on linkage group 44, explaining approximately 7% of the additive genetic variance. Pooled whole genome resequencing of a subset of resistant (n = 60) and susceptible animals (n = 60) was performed to characterize QTL regions, including identification of putative candidate genes and functional annotation of associated polymorphisms. The TRIM25 gene was identified as a promising positional and functional candidate within the QTL region of LG 44, and a putative premature stop mutation in this gene was discovered.