Applying genetic technologies to combat infectious diseases in aquaculture

The Genomics Revolution in Nonmodel Species: Predictions vs. Reality for Salmonids

The increasing feasibility of whole-genome sequencing has been highly anticipated, promising to transform our understanding of the biology of nonmodel species. Notably, dramatic cost reductions beginning around 2007 with the advent of high-throughput sequencing inspired publications heralding the 'genomics revolution', with predictions about its future impacts. Although such predictions served as useful guideposts, value is added when statements are evaluated with the benefit of hindsight. Here, we review 10 key predictions made early in the genomics revolution, highlighting those realised while identifying challenges limiting others. We focus on predictions concerning applied aspects of genomics and examples involving salmonid species which, due to their socioeconomic and ecological significance, have been frontrunners in applications of genomics in nonmodel species. Predicted outcomes included enhanced analytical power, deeper insights into the genetic basis of phenotype and fitness variation, disease management and breeding program advancements. Although many predictions have materialised, several expectations remain unmet due to technological, analytical and knowledge barriers. Additionally, largely unforeseen advancements, including the identification and management applicability of large-effect loci, close-kin mark-recapture, environmental DNA and gene editing have added under-anticipated value. Finally, emerging innovations in artificial intelligence and bioinformatics offer promising new directions. This retrospective evaluation of the impacts of the genomic revolution offers insights into the future of genomics for nonmodel species.

SIRE 2.0: a novel method for estimating polygenic host effects underlying infectious disease transmission, and analytical expressions for prediction accuracies

BACKGROUND

Genetic selection of individuals that are less susceptible to infection, less infectious once infected, and recover faster, offers an effective and long-lasting solution to reduce the incidence and impact of infectious diseases in farmed animals. However, computational methods for simultaneously estimating genetic parameters for host susceptibility, infectivity and recoverability from real-word data have been lacking. Our previously developed methodology and software tool SIRE 1.0 (Susceptibility, Infectivity and Recoverability Estimator) allows estimation of host genetic effects of a single nucleotide polymorphism (SNP), or other fixed effects (e.g. breed, vaccination status), for these three host traits using individual disease data typically available from field studies and challenge experiments. SIRE 1.0, however, lacks the capability to estimate genetic parameters for these traits in the likely case of underlying polygenic control.

RESULTS

This paper introduces novel Bayesian methodology and a new software tool SIRE 2.0 for estimating polygenic contributions (i.e. variance components and additive genetic effects) for host susceptibility, infectivity and recoverability from temporal epidemic data, assuming that pedigree or genomic relationships are known. Analytical expressions for prediction accuracies (PAs) for these traits are derived for simplified scenarios, revealing their dependence on genetic and phenotypic variances, and the distribution of related individuals within and between contact groups. PAs for infectivity are found to be critically dependent on the size of contact groups. Validation of the methodology with data from simulated epidemics demonstrates good agreement between numerically generated PAs and analytical predictions. Genetic correlations between infectivity and other traits substantially increase trait PAs. Incomplete data (e.g. time censored or infrequent sampling) generally yield only small reductions in PAs, except for when infection times are completely unknown, which results in a substantial reduction.

CONCLUSIONS

The method presented can estimate genetic parameters for host susceptibility, infectivity and recoverability from individual disease records. The freely available SIRE 2.0 software provides a valuable extension to SIRE 1.0 for estimating host polygenic effects underlying infectious disease transmission. This tool will open up new possibilities for analysis and quantification of genetic determinates of disease dynamics.

Transcriptomic and biometric parameters analysis in rainbow trout (Oncorhynchus mykiss) challenged with viral hemorrhagic septicemia virus (VHSV)

BACKGROUND

Viral hemorrhagic septicemia virus (VHSV) is a highly pathogenic virus that poses a significant threat to the health of diverse marine species. Among these, trout species, particularly rainbow trout (Oncorhynchus mykiss), are highly susceptible. This study evaluated the effects of VHSV infection on the biometric traits of rainbow trout and investigated the molecular mechanisms associated with the disease.

RESULTS

Biometric traits of fish were collected and documented weekly during the fourth and fifth weeks of the experiment. A statistically significant difference in body weight was observed in the fifth week, particularly between the control group and the groups injected with either physiological saline or the virus. Additionally, body length-related attributes showed significant variation across all treatment groups within the designated timeframe. RNA was extracted from spleen tissue of the group injected with high doses of physiological saline and the group injected with high doses of the virus using the TRIzol protocol. Differential gene expression analysis revealed 1,726 genes with significant differences between the two groups. Several key immune-related genes were identified, including TLR2, TLR7, TLR8, TLR22, IRF5, IRF6, IRF7, IRF8, IRF10, IL11a, IL12B, IL1b, IL7R, ILR1 II, HSP90B1, HSP47, TNF-α, TRF3, SPRY1, CASP3, FN1, GAPDH, and IgGFc-binding proteins. Network-based analysis of differentially expressed genes was conducted using the GeneMANIA module in Cytoscape, and metabolic pathways were identified through the DAVID database. The results highlighted the involvement of key pathways, including the Toll-like receptor pathway, p53 signaling pathway, PPAR signaling pathway, and the cell cycle, in the infected group. Validation tests for selected upregulated (EPCAM, APOC2 and XDD4) and downregulated (TLR7, XDH, and TSPAN36) candidate genes, were conducted using qRT-PCR. The qPCR results showed a strong and statistically significant correlation with the RNA-seq data, confirming the reliability of the findings.

CONCLUSIONS

VHSV significantly impacts the growth of rainbow trout, affecting both body length and gene expression. This study underscores the substantial economic risks posed by the virus and the absence of an effective cure, highlighting the importance of preventative measures. Additionally, potential resistance genes and pathways were identified through RNA sequencing, providing valuable insights for improving trout breeding programs.

Keratinocytes drive the epithelial hyperplasia key to sea lice resistance in coho salmon

BACKGROUND

Salmonid species have followed markedly divergent evolutionary trajectories in their interactions with sea lice. While sea lice parasitism poses significant economic, environmental, and animal welfare challenges for Atlantic salmon (Salmo salar) aquaculture, coho salmon (Oncorhynchus kisutch) exhibit near-complete resistance to sea lice, achieved through a potent epithelial hyperplasia response leading to rapid louse detachment. The molecular mechanisms underlying these divergent responses to sea lice are unknown.

RESULTS

We characterized the cellular and molecular responses of Atlantic salmon and coho salmon to sea lice using single-nuclei RNA sequencing. Juvenile fish were exposed to copepodid sea lice (Lepeophtheirus salmonis), and lice-attached pelvic fin and skin samples were collected 12 h, 24 h, 36 h, 48 h, and 60 h after exposure, along with control samples. Comparative analysis of control and treatment samples revealed an immune and wound-healing response that was common to both species, but attenuated in Atlantic salmon, potentially reflecting greater sea louse immunomodulation. Our results revealed unique but complementary roles of three layers of keratinocytes in the epithelial hyperplasia response leading to rapid sea lice rejection in coho salmon. Our results suggest that basal keratinocytes direct the expansion and mobility of intermediate and, especially, superficial keratinocytes, which eventually encapsulate the parasite.

CONCLUSIONS

Our results highlight the key role of keratinocytes in coho salmon's sea lice resistance and the diverged biological response of the two salmonid host species when interacting with this parasite. This study has identified key pathways and candidate genes that could be manipulated using various biotechnological solutions to improve Atlantic salmon sea lice resistance.

Disease resistance and infectivity of virus susceptible and resistant common carp strains

Infectious diseases challenge health and welfare of humans and animals. Unlike for humans, breeding of genetically resistant animals is a sustainable solution, also providing unique research opportunities. Chances to survive a disease are improved by disease resistance, but depend also on chances to get infected and infect others. Considerable knowledge exists on chances of susceptible and resistant animals to survive a disease, yet, almost none on their infectivity and if and how resistance and infectivity correlate. Common carp (Cyprinus carpio) is widely produced in aquaculture, suffering significantly from a disease caused by cyprinid herpes virus type 3 (CyHV-3). Here, the infectivity of disease-resistant and susceptible fish types was tested by playing roles of shedders (infecting) and cohabitants (infected) in all four type-role combinations. Resistant shedders restricted spleen viral load and survived more than susceptible ones. However, mortality of susceptible cohabitants infected by resistant shedders was lower than that of resistant cohabitants infected by susceptible shedders. Virus levels in water were lower in tanks with resistant shedders leading to lower spleen viral loads in cohabitants. Thus, we empirically demonstrated that disease resistant fish survive better and infect less, with implications to epidemiology in general and to the benefit of aquaculture production.

Genetics and Genomics of Infectious Diseases in Key Aquaculture Species

Diseases pose a significant and pressing concern for the sustainable development of the aquaculture sector, particularly as their impact continues to grow due to climatic shifts such as rising water temperatures. While various approaches, ranging from biosecurity measures to vaccines, have been devised to combat infectious diseases, their efficacy is disease and species specific and contingent upon a multitude of factors. The fields of genetics and genomics offer effective tools to control and prevent disease outbreaks in aquatic animal species. In this study, we present the key findings from our recent research, focusing on the genetic resistance to three specific diseases: White Spot Syndrome Virus (WSSV) in white shrimp, Bacterial Necrotic Pancreatitis (BNP) in striped catfish, and skin fluke (a parasitic ailment) in yellowtail kingfish. Our investigations reveal that all three species possess substantial heritable genetic components for disease-resistant traits, indicating their potential responsiveness to artificial selection in genetic improvement programs tailored to combat these diseases. Also, we observed a high genetic association between disease traits and survival rates. Through selective breeding aimed at enhancing resistance to these pathogens, we achieved substantial genetic gains, averaging 10% per generation. These selection programs also contributed positively to the overall production performance and productivity of these species. Although the effects of selection on immunological traits or immune responses were not significant in white shrimp, they yielded favorable results in striped catfish. Furthermore, our genomic analyses, including shallow genome sequencing of pedigreed populations, enriched our understanding of the genomic architecture underlying disease resistance traits. These traits are primarily governed by a polygenic nature, with numerous genes or genetic variants, each with small effects. Leveraging a range of advanced statistical methods, from mixed models to machine and deep learning, we developed prediction models that demonstrated moderate-to-high levels of accuracy in forecasting these disease-related traits. In addition to genomics, our RNA-seq experiments identified several genes that undergo upregulation in response to infection or viral loads within the populations. Preliminary microbiome data, while offering limited predictive accuracy for disease traits in one of our studied species, underscore the potential for combining such data with genome sequence information to enhance predictive power for disease traits in our populations. Lastly, this paper briefly discusses the roles of precision agriculture systems and AI algorithms and outlines the path for future research to expedite the development of disease-resistant genetic lines tailored to our target species. In conclusion, our study underscores the critical role of genetics and genomics in fortifying the aquaculture sector against the threats posed by diseases, paving the way for more sustainable and resilient aquaculture development.

Evolutionary predictions for a parasite metapopulation: Modelling salmon louse resistance to pest controls in aquaculture

Pests often evolve resistance to pest controls used in agriculture and aquaculture. The rate of pest adaptation is influenced by the type of control, the selective pressure it imposes, and the gene flow between farms. By understanding how these factors influence evolution at the metapopulation level, pest management strategies that prevent resistance from evolving can be developed. We developed a model for the metapopulation and evolutionary dynamics of the salmon louse (Lepeophtheirus salmonis), which is a major parasite affecting salmon aquaculture. Different management scenarios were simulated across a network of salmon farms covering half of Norway, and their effects on louse epidemiology and evolution were investigated. We compared louse controls that differed in how they were deployed through time (discrete vs. continuous), how they impacted the louse life cycle, and in their overall efficacy. We adjusted the strength of selection imposed by treatments, the dominance effect of the resistant allele, and the geographic location at which resistance originated. Continuously acting strategies (e.g., louse-resistant salmon) were generally more effective than discrete strategies at controlling lice, especially when they increased louse mortality during early developmental stages. However, effective strategies also risked imposing frequent and/or strong selection on lice, thus driving rapid adaptation. Resistant alleles were more likely to be lost through genetic drift when they were recessive, had a low-fitness advantage, or originated in low-farm-density areas. The north-flowing current along the Norwegian coastline dispersed resistant genes from south to north, and limited gene flow in the opposite direction. We demonstrate how evolutionary models can produce quantitative predictions over large spatial and temporal scales and for a range of pest control scenarios. Quantitative outputs can be translated into practical management decisions applied at a regional level to minimise the risk of resistance developing.

Megalocytivirus and Other Members of the Family Iridoviridae in Finfish: A Review of the Etiology, Epidemiology, Diagnosis, Prevention and Control

Aquaculture has expanded to become the fastest growing food-producing sector in the world. However, its expansion has come under threat due to an increase in diseases caused by pathogens such as iridoviruses commonly found in aquatic environments used for fish farming. Of the seven members belonging to the family Iridoviridae, the three genera causing diseases in fish comprise ranaviruses, lymphocystiviruses and megalocytiviruses. These three genera are serious impediments to the expansion of global aquaculture because of their tropism for a wide range of farmed-fish species in which they cause high mortality. As economic losses caused by these iridoviruses in aquaculture continue to rise, the urgent need for effective control strategies increases. As a consequence, these viruses have attracted a lot of research interest in recent years. The functional role of some of the genes that form the structure of iridoviruses has not been elucidated. There is a lack of information on the predisposing factors leading to iridovirus infections in fish, an absence of information on the risk factors leading to disease outbreaks, and a lack of data on the chemical and physical properties of iridoviruses needed for the implementation of biosecurity control measures. Thus, the synopsis put forth herein provides an update of knowledge gathered from studies carried out so far aimed at addressing the aforesaid informational gaps. In summary, this review provides an update on the etiology of different iridoviruses infecting finfish and epidemiological factors leading to the occurrence of disease outbreaks. In addition, the review provides an update on the cell lines developed for virus isolation and culture, the diagnostic tools used for virus detection and characterization, the current advances in vaccine development and the use of biosecurity in the control of iridoviruses in aquaculture. Overall, we envision that the information put forth in this review will contribute to developing effective control strategies against iridovirus infections in aquaculture.

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.