Adaptation of gastrointestinal nematode parasites to host genotype: single locus simulation models

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.

Can breeders prevent pathogen adaptation when selecting for increased resistance to infectious diseases?

Background

Recent research shows that genetic selection has high potential to reduce the prevalence of infectious diseases in livestock. However, like all interventions that target infectious diseases, genetic selection of livestock can exert selection pressure on pathogen populations. Such selection on the pathogen may lead to escape strategies and reduce the effect of selection of livestock for disease resistance. Thus, to successfully breed livestock for lower disease prevalence, it is essential to develop strategies that prevent the invasion of pathogen mutants that escape host resistance. Here we investigate the conditions under which such “escape mutants” can replace wild-type pathogens in a closed livestock population using a mathematical model of disease transmission.

Results

Assuming a single gene that confers sufficient resistance, results show that genetic selection for resistance in livestock typically leads to an “invasion window” within which an escape mutant of the pathogen can invade. The bounds of the invasion window are determined by the frequency of resistant hosts in the population. The lower bound occurs when the escape mutant has an advantage over the wild-type pathogen in the population. The upper bound occurs when local eradication of the pathogen is expected. The invasion window is smallest when host resistance is strong and when infection with the wild-type pathogen provides cross immunity to infection with the escape mutant.

Conclusions

To minimise opportunities for pathogens to adapt, under the assumptions of our model, the aim of disease control through genetic selection should be to achieve herd-level eradication of the infection faster than the rate of emergence of escape mutants of the pathogen. Especially for microparasitic infections, this could be achieved by placing animals into herds according to their genetic resistance, such that these herds stay completely out of the invasion window. In contrast to classical breeding theory, our model suggests that multi-trait selection with gradual improvement of each trait of the breeding goal might not be the best strategy when resistance to infectious disease is part of the breeding goal. Temporally, combining genetic selection with other interventions helps to make the invasion window smaller, and thereby reduces the risk of invasion of escape mutants.

Serial passage in resistant sheep drives the infectivity and fitness of Teladorsagia circumcincta in susceptible lambs: Experimental evidence

Gastrointestinal nematodes (GIN) of small ruminants have adapted their life history strategies to thrive in diverse and fluctuating environments. Environments which alter their expression of life traits may also drive changes in the infection or transmission dynamics, particularly if transferred to a foreign setting. This study aimed to explore how repeated exposure to a resistant sheep host environment would alter the life history traits and infection dynamics of Teladorsagia circumcincta when consequently infected in susceptible lambs. Following just three generations of passage in resistant sheep, T. circumcincta significantly increased their infectivity and fitness in susceptible lambs compared to a control population. This is the first evidence to indicate the resistant host environment can drive such rapid changes in the expression of GIN life traits, with potentially undesirable epidemiological outcomes.

Derivation of the economic value of R0 for macroparasitic diseases and application to sea lice in salmon

BACKGROUND

Macroparasites, such as ticks, lice, and helminths, are a concern in livestock and aquaculture production, and can be controlled by genetic improvement of the host population. Genetic improvement should aim at reducing the rate at which parasites spread across the farmed population. This rate is determined by the basic reproduction ratio, i.e. [Formula: see text], which is the appropriate breeding goal trait. This study aims at providing a method to derive the economic value of [Formula: see text].

METHODS

Costs of a disease are the sum of production losses and expenditures on disease control. Genetic improvement of [Formula: see text] lowers the loss-expenditure frontier. Its economic effect depends on whether the management strategy is optimized or not. The economic value may be derived either from the reduction in losses with constant expenditures or from the reduction in expenditures with constant losses.

RESULTS

When [Formula: see text] ≤ 1, the economic value of a further reduction is zero because there is no risk of a major epidemic. When [Formula: see text] > 1 and management is optimized, the economic value increases with decreasing values of [Formula: see text], because both the mean number of parasites per host and frequency of treatments decrease at an increasing rate when [Formula: see text] decreases. When [Formula: see text] > 1 and management is not optimized, the economic value depends on whether genetic improvement is used for reducing expenditures or losses. For sea lice in salmon, the economic value depends on a reduction in expenditures with constant losses, and is estimated to be 0.065€/unit [Formula: see text]/kg production.

DISCUSSION

Response to selection for measures of disease prevalence cannot be predicted from quantitative genetic theory alone. Moreover, many studies fail to address the issue of whether genetic improvement results in reduced losses or expenditures. Using [Formula: see text] as the breeding goal trait, weighed by its appropriate economic value, avoids these issues.

CONCLUSION

When management is optimized, the economic value increases with decreasing values of [Formula: see text] (until the threshold of [Formula: see text], where it drops to zero). When management is not optimized, the economic value depends on whether genetic improvement is used for reduced expenditures or production losses. For sea lice in salmon, the economic value is estimated to be 0.065 €/unit [Formula: see text]/kg production.

Impact of Genetic Selection for Increased Cattle Resistance to Bovine Tuberculosis on Disease Transmission Dynamics

Bovine tuberculosis (bTB) poses a challenge to animal health and welfare worldwide. Presence of genetic variation in host resistance to Mycobacterium bovis infection makes the trait amenable to improvement with genetic selection. Genetic evaluations for resistance to infection in dairy cattle are currently available in the United Kingdom (UK), enabling genetic selection of more resistant animals. However, the extent to which genetic selection could contribute to bTB eradication is unknown. The objective of this study was to quantify the impact of genetic selection for bTB resistance on cattle-to-cattle disease transmission dynamics and prevalence by developing a stochastic genetic epidemiological model. The model was used to implement genetic selection in a simulated cattle population. The model considered various levels of selection intensity over 20 generations assuming genetic heterogeneity in host resistance to infection. Our model attempted to represent the dairy cattle population structure and current bTB control strategies in the UK, and was informed by genetic and epidemiological parameters inferred from data collected from UK bTB infected dairy herds. The risk of a bTB breakdown was modeled as the percentage of herds where initially infected cows (index cases) generated secondary cases by infecting herd-mates. The model predicted that this risk would be reduced by half after 4, 6, 9, and 15 generations for selection intensities corresponding to genetic selection of the 10, 25, 50, and 70% most resistant sires, respectively. In herds undergoing bTB breakdowns, genetic selection reduced the severity of breakdowns over generations by reducing both the percentage of secondary cases and the duration over which new secondary cases were detected. Selection of the 10, 25, 50, and 70% most resistant sires reduced the percentage of secondary cases to <1% in 4, 5, 7, and 11 generations, respectively. Similarly, the proportion of long breakdowns (breakdowns in which secondary cases were detected for more than 365 days) was reduced by half in 2, 2, 3, and 4 generations, respectively. Collectively, results suggest that genetic selection could be a viable tool that can complement existing management and surveillance methods to control and ultimately eradicate bTB.

Familiarity with and uptake of alternative methods to control sheep gastro-intestinal parasites on farms in England

A questionnaire was distributed electronically amongst sheep farmers in England; it aimed to provide a quantification of current anthelmintic practices, farmer awareness of the issue of anthelmintic resistance (AR) and the uptake, awareness and opinions surrounding conventional and alternative methods of nematode control. The majority of farmers relied on several anthelmintics and used faecal egg counts to identify worm problems. Although farmers were aware of the issue of AR amongst helminth parasites in the UK, there was a disconnection between such awareness and on farm problems and practice of nematode control. Grazing management was used by 52% of responders, while breeding for resistance and bioactive forages by 22 and 18% respectively. Farms with more than 500 ewes, and farmers who felt nematodes were a problem, had a higher probability of using selective breeding. Farmers who considered their wormer effective, had a qualification in agriculture and whose staff did not include any family members, were more likely to use bioactive forages; the opposite was the case if farmers dosed their lambs frequently. Amongst the alternatives, highest preference was for selective breeding and vaccination, if the latter was to become commercially available, with more respondents having a preference for breeding than actually using it. Several barriers to the uptake of an alternative were identified, the most influential factor being the cost to set it up and the length of time for which it would remain effective. The disconnection between awareness of AR and practice of nematode control on farm reinforces the need for emphasising the links between the causes of AR and the consequences of strategies to address its challenge.

A Novel Statistical Model to Estimate Host Genetic Effects Affecting Disease Transmission

There is increasing recognition that genetic diversity can affect the spread of diseases, potentially affecting plant and livestock disease control as well as the emergence of human disease outbreaks. Nevertheless, even though computational tools can guide the control of infectious diseases, few epidemiological models can simultaneously accommodate the inherent individual heterogeneity in multiple infectious disease traits influencing disease transmission, such as the frequently modeled propensity to become infected and infectivity, which describes the host ability to transmit the infection to susceptible individuals. Furthermore, current quantitative genetic models fail to fully capture the heritable variation in host infectivity, mainly because they cannot accommodate the nonlinear infection dynamics underlying epidemiological data. We present in this article a novel statistical model and an inference method to estimate genetic parameters associated with both host susceptibility and infectivity. Our methodology combines quantitative genetic models of social interactions with stochastic processes to model the random, nonlinear, and dynamic nature of infections and uses adaptive Bayesian computational techniques to estimate the model parameters. Results using simulated epidemic data show that our model can accurately estimate heritabilities and genetic risks not only of susceptibility but also of infectivity, therefore exploring a trait whose heritable variation is currently ignored in disease genetics and can greatly influence the spread of infectious diseases. Our proposed methodology offers potential impacts in areas such as livestock disease control through selective breeding and also in predicting and controlling the emergence of disease outbreaks in human populations.

Genetic resistance to infections in sheep

This paper considers genetic resistance to infectious disease in sheep, with appropriate comparison with goats, and explores how such variation may be used to assist in disease control. Many studies have attempted to quantify the extent to which host animals differ genetically in their resistance to infection or in the disease side-effects of infection, using either recorded animal pedigrees or information from genetic markers to quantify the genetic variation. Across all livestock species, whenever studies are sufficiently well powered, then genetic variation in disease resistance is usually seen and such evidence is presented here for three infections or diseases of importance to sheep, namely mastitis, foot rot and scrapie. A further class of diseases of importance in most small ruminant production systems, gastrointestinal nematode infections, is outside the scope of this review. Existence of genetic variation implies the opportunity, at least in principle, to select animals for increased resistance, with such selection ideally used as part of an integrated control strategy. For each of the diseases under consideration, evidence for genetic variation is presented, the role of selection as an aid to disease control is outlined and possible side effects of selection in terms of effects in performance, effects on resistance to other diseases and potential parasite/pathogen coevolution risks are considered. In all cases, the conclusion is drawn that selection should work and it should be beneficial, with the main challenge being to define cost effective selection protocols that are attractive to sheep farmers.

Selection methods for resistance to and tolerance of helminths in livestock

Helminthiases are among the most important livestock diseases worldwide, in particular for small ruminants, which are the focus of this review. Resource Allocation Theory implies that high-productivity farm animals proportionate insufficient resources for adequate coping with stressful conditions. Significant differences between breeds and within breeds are seen, as well as genotype vs. environment interactions. With improvement of genetic host resistance to infection, transmission of infection will be impacted. On the other hand, genetic improvement of resilience can lead to a reduction in clinical signs of disease, but not necessarily reduce transmission of infection to other animals. Faecal egg count (FEC) is the main measurement used to evaluate helminthiasis load, despite the fact that the protocols and analytical methods can affect the results, and the FEC data frequently shows aggregative, negative skewed distribution, and a high coefficient of variation. Mass selection where heritability is generally medium to low generally produces slow results and low economic returns. Many studies have been published linking resistance to nematodes in livestock to Quantitative Trait Loci and most studies have concentrated on chromosomes where the major histocompatibility complex region is located. Nevertheless, these complex traits have been seen to be affected by thousands of variants that each has a small effect. More recent studies have shown that genome-wide selection strategies can be useful in selecting animals for improved production and resistance traits in this case.

Signatures of selection in sheep bred for resistance or susceptibility to gastrointestinal nematodes

Background

Gastrointestinal nematodes are one of the most serious causes of disease in domestic ruminants worldwide. There is considerable variation in resistance to gastrointestinal nematodes within and between sheep breeds, which appears to be due to underlying genetic diversity. Through selection of resistant animals, rapid genetic progress has been demonstrated in both research and commercial flocks. Recent advances in genome sequencing and genomic technologies provide new opportunities to understand the ovine host response to gastrointestinal nematodes at the molecular level, and to identify polymorphisms conferring nematode resistance.

Results

Divergent lines of Romney and Perendale sheep, selectively bred for high and low faecal nematode egg count, were genotyped using the Illumina® Ovine SNP50 BeadChip. The resulting genome-wide SNP data were analysed for selective sweeps on loci associated with resistance or susceptibility to gastrointestinal nematode infection. Population differentiation using F_ST and Peddrift revealed sixteen regions, which included candidate genes involved in chitinase activity and the cytokine response. Two of the sixteen regions identified were contained within previously identified QTLs associated with nematode resistance.

Conclusions

In this study we identified fourteen novel regions associated with resistance or susceptibility to gastrointestinal nematodes. Results from this study support the hypothesis that host resistance to internal nematode parasites is likely to be controlled by a number of loci of moderate to small effects.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-637) contains supplementary material, which is available to authorized users.