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

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.

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.

Non-synonymous variation and protein structure of candidate genes associated with selection in farm and wild populations of turbot (Scophthalmus maximus)

Non-synonymous variation (NSV) of protein coding genes represents raw material for selection to improve adaptation to the diverse environmental scenarios in wild and livestock populations. Many aquatic species face variations in temperature, salinity and biological factors throughout their distribution range that is reflected by the presence of allelic clines or local adaptation. The turbot (Scophthalmus maximus) is a flatfish of great commercial value with a flourishing aquaculture which has promoted the development of genomic resources. In this study, we developed the first atlas of NSVs in the turbot genome by resequencing 10 individuals from Northeast Atlantic Ocean. More than 50,000 NSVs where detected in the ~ 21,500 coding genes of the turbot genome, and we selected 18 NSVs to be genotyped using a single Mass ARRAY multiplex on 13 wild populations and three turbot farms. We detected signals of divergent selection on several genes related to growth, circadian rhythms, osmoregulation and oxygen binding in the different scenarios evaluated. Furthermore, we explored the impact of NSVs identified on the 3D structure and functional relationship of the correspondent proteins. In summary, our study provides a strategy to identify NSVs in species with consistently annotated and assembled genomes to ascertain their role in adaptation.

Scuticociliatosis caused by Philasterides dicentrarchi

The ciliate Philasterides dicentrarchi has been previously identified as a new agent of scuticociliatosis in marine fish. The parasite can cause high mortalities in fish reared on farms or kept in aquariums. P. dicentrarchi is usually a free-living protozoan but can become an opportunistic histophagous parasite causing rapid lethal systemic infections in cultured fish. This review provides information about the morphology and biology of the scuticociliate P. dicentrarchi, as well as information about the pathological and immunological reactions of the host in response to the infection with the parasite. The epidemiology and the control strategies of the disease are also reviewed.

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.

Potential of genomic technologies to improve disease resistance in molluscan aquaculture

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

A genome-wide association study, supported by a new chromosome-level genome assembly, suggests sox2 as a main driver of the undifferentiatiated ZZ/ZW sex determination of turbot (Scophthalmus maximus)

BACKGROUND

Understanding sex determination (SD) across taxa is a major challenge for evolutionary biology. The new genomic tools are paving the way to identify genomic features underlying SD in fish, a group frequently showing limited sex chromosome differentiation and high SD evolutionary turnover. Turbot (Scophthalmus maximus) is a commercially important flatfish with an undifferentiated ZW/ZZ SD system and remarkable sexual dimorphism. Here we describe a new long-read turbot genome assembly used to disentangle the genetic architecture of turbot SD by combining genomics and classical genetics approaches.

RESULTS

The new turbot genome assembly consists of 145 contigs (N50 = 22.9 Mb), 27 of them representing >95% of its estimated genome size. A genome wide association study (GWAS) identified a ~ 6.8 Mb region on chromosome 12 associated with sex in 69.4% of the 36 families analyzed. The highest associated markers flanked sox2, the only gene in the region showing differential expression between sexes before gonad differentiation. A single SNP showed consistent differences between Z and W chromosomes. The analysis of a broad sample of families suggested the presence of additional genetic and/or environmental factors on turbot SD.

CONCLUSIONS

The new chromosome-level turbot genome assembly, one of the most contiguous fish assemblies to date, facilitated the identification of sox2 as a consistent candidate gene putatively driving SD in this species. This chromosome SD system barely showed any signs of differentiation, and other factors beyond the main QTL seem to control SD in a certain proportion of families.

Optimum mating designs for exploiting dominance in genomic selection schemes for aquaculture species

Background

In commercial fish, dominance effects could be exploited by predicting production abilities of the offspring that would be generated by different mating pairs and choosing those pairs that maximise the average offspring phenotype. Consequently, matings would be performed to reduce inbreeding depression. This can be achieved by applying mate selection (MS) that combines selection and mating decisions in a single step. An alternative strategy to MS would be to apply minimum coancestry mating (MCM) after selection based on estimated breeding values. The objective of this study was to evaluate, by computer simulations, the potential benefits that can be obtained by implementing MS or MCM based on genomic data for exploiting dominance effects when creating commercial fish populations that are derived from a breeding nucleus.

Methods

The selected trait was determined by a variable number of loci with additive and dominance effects. The population consisted of 50 full-sib families with 30 offspring each. Males and females with the highest estimated genomic breeding values were selected in the nucleus and paired using the MCM strategy. Both MCM and MS were used to create the commercial population.

Results

For a moderate number of SNPs, equal or even higher mean phenotypic values are obtained by selecting on genomic breeding values and then applying MCM than by using MS when the trait exhibited substantial inbreeding depression. This could be because MCM leads to high levels of heterozygosity across the whole genome, even for loci affecting the trait that are in linkage equilibrium with the SNPs. In contrast, MS specifically promotes heterozygosity for SNPs for which a dominance effect has been detected.

Conclusions

In most scenarios, for the management of aquaculture breeding programs it seems advisable to follow the MCM strategy when creating the commercial population, especially for traits with large inbreeding depression. Moreover, MCM has the appealing property of reducing inbreeding levels, with a corresponding reduction in inbreeding depression for traits beyond those included in the selection objective.

Genetic selection for growth drives differences in intestinal microbiota composition and parasite disease resistance in gilthead sea bream

BACKGROUND

The key effects of intestinal microbiota in animal health have led to an increasing interest in manipulating these bacterial populations to improve animal welfare. The aquaculture sector is no exception and in the last years, many studies have described these populations in different fish species. However, this is not an easy task, as intestinal microbiota is composed of very dynamic populations that are influenced by different factors, such as diet, environment, host age, and genetics. In the current study, we aimed to determine whether the genetic background of gilthead sea bream (Sparus aurata) influences the intestinal microbial composition, how these bacterial populations are modulated by dietary changes, and the effect of selection by growth on intestinal disease resistance. To that aim, three different groups of five families of gilthead sea bream that were selected during two generations for fast, intermediate, or slow growth (F3 generation) were kept together in the same open-flow tanks and fed a control or a well-balanced plant-based diet during 9 months. Six animals per family and dietary treatment were sacrificed and the adherent bacteria from the anterior intestinal portion were sequenced. In parallel, fish of the fast- and slow-growth groups were infected with the intestinal parasite Enteromyxum leei and the disease signs, prevalence, intensity, and parasite abundance were evaluated.

RESULTS

No differences were detected in alpha diversity indexes among families, and the core bacterial architecture was the prototypical composition of gilthead sea bream intestinal microbiota, indicating no dysbiosis in any of the groups. The plant-based diet significantly changed the microbiota in the intermediate- and slow-growth families, with a much lower effect on the fast-growth group. Interestingly, the smaller changes detected in the fast-growth families potentially accounted for more changes at the metabolic level when compared with the other families. Upon parasitic infection, the fast-growth group showed significantly lower disease signs and parasite intensity and abundance than the slow-growth animals.

CONCLUSIONS

These results show a clear genome-metagenome interaction indicating that the fast-growth families harbor a microbiota that is more flexible upon dietary changes. These animals also showed a better ability to cope with intestinal infections. Video Abstract.

Why breed disease-resilient livestock, and how?

BACKGROUND

Fighting and controlling epidemic and endemic diseases represents a considerable cost to livestock production. Much research is dedicated to breeding disease resilient livestock, but this is not yet a common objective in practical breeding programs. In this paper, we investigate how future breeding programs may benefit from recent research on disease resilience.

MAIN BODY

We define disease resilience in terms of its component traits resistance (R: the ability of a host animal to limit within-host pathogen load (PL)) and tolerance (T: the ability of an infected host to limit the damage caused by a given PL), and model the host's production performance as a reaction norm on PL, depending on R and T. Based on this, we derive equations for the economic values of resilience and its component traits. A case study on porcine respiratory and reproductive syndrome (PRRS) in pigs illustrates that the economic value of increasing production in infectious conditions through selection for R and T can be more than three times higher than by selection for production in disease-free conditions. Although this reaction norm model of resilience is helpful for quantifying its relationship to its component traits, its parameters are difficult and expensive to quantify. We consider the consequences of ignoring R and T in breeding programs that measure resilience as production in infectious conditions with unknown PL-particularly, the risk that the genetic correlation between R and T is unfavourable (antagonistic) and that a trade-off between them neutralizes the resilience improvement. We describe four approaches to avoid such antagonisms: (1) by producing sufficient PL records to estimate this correlation and check for antagonisms-if found, continue routine PL recording, and if not found, shift to cheaper proxies for PL; (2) by selection on quantitative trait loci (QTL) known to influence both R and T in favourable ways; (3) by rapidly modifying towards near-complete resistance or tolerance, (4) by re-defining resilience as the animal's capacity to resist (or recover from) the perturbation caused by an infection, measured as temporal deviations of production traits in within-host longitudinal data series.

CONCLUSIONS

All four alternatives offer promising options for genetic improvement of disease resilience, and most rely on technological and methodological developments and innovation in automated data generation.

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.

Application of Low Coverage Genotyping by Sequencing in Selectively Bred Arctic Charr (Salvelinus alpinus)

Arctic charr (Salvelinus alpinus) is a species of high economic value for the aquaculture industry, and of high ecological value due to its Holarctic distribution in both marine and freshwater environments. Novel genome sequencing approaches enable the study of population and quantitative genetic parameters even on species with limited or no prior genomic resources. Low coverage genotyping by sequencing (GBS) was applied in a selected strain of Arctic charr in Sweden originating from a landlocked freshwater population. For the needs of the current study, animals from year classes 2013 (171 animals, parental population) and 2017 (759 animals; 13 full sib families) were used as a template for identifying genome wide single nucleotide polymorphisms (SNPs). GBS libraries were constructed using the PstI and MspI restriction enzymes. Approximately 14.5K SNPs passed quality control and were used for estimating a genomic relationship matrix. Thereafter a wide range of analyses were conducted in order to gain insights regarding genetic diversity and investigate the efficiency of the genomic information for parentage assignment and breeding value estimation. Heterozygosity estimates for both year classes suggested a slight excess of heterozygotes. Furthermore, FST estimates among the families of year class 2017 ranged between 0.009 - 0.066. Principal components analysis (PCA) and discriminant analysis of principal components (DAPC) were applied aiming to identify the existence of genetic clusters among the studied population. Results obtained were in accordance with pedigree records allowing the identification of individual families. Additionally, DNA parentage verification was performed, with results in accordance with the pedigree records with the exception of a putative dam where full sib genotypes suggested a potential recording error. Breeding value estimation for juvenile growth through the usage of the estimated genomic relationship matrix clearly outperformed the pedigree equivalent in terms of prediction accuracy (0.51 opposed to 0.31). Overall, low coverage GBS has proven to be a cost-effective genotyping platform that is expected to boost the selection efficiency of the Arctic charr breeding program.

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.

Genomic Signatures After Five Generations of Intensive Selective Breeding: Runs of Homozygosity and Genetic Diversity in Representative Domestic and Wild Populations of Turbot (Scophthalmus maximus)

Massive genotyping of single nucleotide polymorphisms (SNP) has opened opportunities for analyzing the way in which selection shapes genomes. Artificial or natural selection usually leaves genomic signatures associated with selective sweeps around the responsible locus. Strong selective sweeps are most often identified either by lower genetic diversity than the genomic average and/or islands of runs of homozygosity (ROHi). Here, we conducted an analysis of selective sweeps in turbot (Scophthalmus maximus) using two SNP datasets from a Northeastern Atlantic population (36 individuals) and a domestic broodstock (46 individuals). Twenty-six families (∼ 40 offspring per family) from this broodstock and three SNP datasets applying differing filtering criteria were used to adjust ROH calling parameters. The best-fitted genomic inbreeding estimate (F_ROH) was obtained by the sum of ROH longer than 1 Mb, called using a 21,615 SNP panel, a sliding window of 37 SNPs and one heterozygous SNP per window allowed. These parameters were used to obtain the ROHi distribution in the domestic and wild populations (49 and 0 ROHi, respectively). Regions with higher and lower genetic diversity within each population were obtained using sliding windows of 37 SNPs. Furthermore, those regions were mapped in the turbot genome against previously reported genetic markers associated with QTL (Quantitative Trait Loci) and outlier loci for domestic or natural selection to identify putative selective sweeps. Out of the 319 and 278 windows surpassing the suggestive pooled heterozygosity thresholds (ZHp) in the wild and domestic population, respectively, 78 and 54 were retained under more restrictive ZHp criteria. A total of 116 suggestive windows (representing 19 genomic regions) were linked to either QTL for production traits, or outliers for divergent or balancing selection. Twenty-four of them (representing 3 genomic regions) were retained under stricter ZHp thresholds. Eleven QTL/outlier markers were exclusively found in suggestive regions of the domestic broodstock, 7 in the wild population and one in both populations; one (broodstock) and two (wild) of those were found in significant regions retained under more restrictive ZHp criteria in the broodstock and the wild population, respectively. Genome mining and functional enrichment within regions associated with selective sweeps disclosed relevant genes and pathways related to aquaculture target traits, including growth and immune-related pathways, metabolism and response to hypoxia, which showcases how this genome atlas of genetic diversity can be a valuable resource to look for candidate genes related to natural or artificial selection in turbot populations.

Genetic differences in host infectivity affect disease spread and survival in epidemics

Survival during an epidemic is partly determined by host genetics. While quantitative genetic studies typically consider survival as an indicator for disease resistance (an individual's propensity to avoid becoming infected or diseased), mortality rates of populations undergoing an epidemic are also affected by endurance (the propensity of diseased individual to survive the infection) and infectivity (i.e. the propensity of an infected individual to transmit disease). Few studies have demonstrated genetic variation in disease endurance, and no study has demonstrated genetic variation in host infectivity, despite strong evidence for considerable phenotypic variation in this trait. Here we propose an experimental design and statistical models for estimating genetic diversity in all three host traits. Using an infection model in fish we provide, for the first time, direct evidence for genetic variation in host infectivity, in addition to variation in resistance and endurance. We also demonstrate how genetic differences in these three traits contribute to survival. Our results imply that animals can evolve different disease response types affecting epidemic survival rates, with important implications for understanding and controlling epidemics.