Implications of conflicting associations of the prion protein (PrP) gene with scrapie susceptibility and fitness on the persistence of scrapie

Expanding possibilities for intervention against small ruminant lentiviruses through genetic marker-assisted selective breeding

Small ruminant lentiviruses include members that infect sheep (ovine lentivirus [OvLV]; also known as ovine progressive pneumonia virus/maedi-visna virus) and goats (caprine arthritis encephalitis virus [CAEV]). Breed differences in seroprevalence and proviral concentration of OvLV had suggested a strong genetic component in susceptibility to infection by OvLV in sheep. A genetic marker test for susceptibility to OvLV has been developed recently based on the TMEM154 gene with validation data from over 2,800 sheep representing nine cohorts. While no single genotype has been shown to have complete resistance to OvLV, consistent association in thousands of sheep from multiple breeds and management conditions highlight a new strategy for intervention by selective breeding. This genetic marker-assisted selection (MAS) has the potential to be a useful addition to existing viral control measures. Further, the discovery of multiple additional genomic regions associated with susceptibility to or control of OvLV suggests that additional genetic marker tests may be developed to extend the reach of MAS in the future. This review will cover the strengths and limitations of existing data from host genetics as an intervention and outline additional questions for future genetic research in sheep, goats, small ruminant lentiviruses, and their host-pathogen interactions.

Immune response from a resource allocation perspective

The immune system is a life history trait that can be expected to trade off against other life history traits. Whether or not a trait is considered to be a life history trait has consequences for the expectation on how it responds to natural selection and evolution; in addition, it may have consequences for the outcome of artificial selection when it is included in the breeding objective. The immune system involved in pathogen resistance comprises multiple mechanisms that define a host's defensive capacity. Immune resistance involves employing mechanisms that either prevent pathogens from invading or eliminate the pathogens when they do invade. On the other hand, tolerance involves limiting the damage that is caused by the infection. Both tolerance and resistance traits require (re)allocation of resources and carry physiological costs. Examples of trade-offs between immune function and growth, reproduction and stress response are provided in this review, in addition to consequences of selection for increased production on immune function and vice versa. Reaction norms are used to deal with questions of immune resistance vs. tolerance to pathogens that relate host health to infection intensity. In essence, selection for immune tolerance in livestock is a particular case of selection for animal robustness. Since breeding goals that include robustness traits are required in the implementation of more sustainable agricultural production systems, it is of interest to investigate whether immune tolerance is a robustness trait that is positively correlated with overall animal robustness. Considerably more research is needed to estimate the shapes of the cost functions of different immune strategies, and investigate trade-offs and cross-over benefits of selection for disease resistance and/or disease tolerance in livestock production.

Implications of host genetic variation on the risk and prevalence of infectious diseases transmitted through the environment

Previous studies have shown that host genetic heterogeneity in the response to infectious challenge can affect the emergence risk and the severity of diseases transmitted through direct contact between individuals. However, there is substantial uncertainty about the degree and direction of influence owing to different definitions of genetic variation, most of which are not in line with the current understanding of the genetic architecture of disease traits. Also, the relevance of previous results for diseases transmitted through environmental sources is unclear. In this article a compartmental genetic–epidemiological model was developed to quantify the impact of host genetic diversity on epidemiological characteristics of diseases transmitted through a contaminated environment. The model was parameterized for footrot in sheep. Genetic variation was defined through continuous distributions with varying shape and degree of dispersion for different disease traits. The model predicts a strong impact of genetic heterogeneity on the disease risk and its progression and severity, as well as on observable host phenotypes, when dispersion in key epidemiological parameters is high. The impact of host variation depends on the disease trait for which variation occurs and on environmental conditions affecting pathogen survival. In particular, compared to homogeneous populations with the same average susceptibility, disease risk and severity are substantially higher in populations containing a large proportion of highly susceptible individuals, and the differences are strongest when environmental contamination is low. The implications of our results for the recording and analysis of disease data and for predicting response to selection are discussed.

The role of mathematical modelling in understanding the epidemiology and control of sheep transmissible spongiform encephalopathies: a review

To deal with the incompleteness of observations and disentangle the complexities of transmission much use has been made of mathematical modelling when investigating the epidemiology of sheep transmissible spongiform encephalopathies (TSE) and, in particular, scrapie. Importantly, these modelling approaches allow the incidence of clinical disease to be related to the underlying prevalence of infection, thereby overcoming one of the major difficulties when studying these diseases. Models have been used to investigate the epidemiology of scrapie within individual flocks and at a regional level; to assess the efficacy of different control strategies, especially selective breeding programmes based on prion protein (PrP) genotype; to interpret the results of scrapie surveillance; and to inform the design of surveillance programmes. Furthermore, mathematical modelling has played an important role when assessing the risk to human health posed by the possible presence of bovine spongiform encephalopathy in sheep. Here, we review the various approaches that have been taken when developing and analysing mathematical models for the epidemiology and control of sheep TSE and assess their impact on our understanding of these diseases. We also identify areas that require further work, discuss future challenges and identify data gaps.