A plethora of genetic studies show that genetic variation in host disease resistance is ubiquitous across host and pathogen species. However, surprisingly little is known how the genetics of individuals affects the spread and impact of infectious disease in livestock populations. This paper takes a genetic-epidemiological approach to address this question and to examine how host genetic variation could be utilized more effectively to reduce both the risk and severity of disease outbreaks. In particular, building on epidemiological theory, we demonstrate that three distinct host traits interactively control infection dynamics in populations, namely susceptibility (the probability of an individual to become infected upon contact with an average infectious individual or material), infectivity (the probability of an infected individual to infect a non-infected individual with average susceptibility), and tolerance (here defined as the probability of an infected individual to survive the infection). To date, understanding of the genetic (co)-regulation of these traits is lacking. This is because standard field and challenge test data and genetic models don’t provide genetic parameter estimates for these traits. Here we outline key concepts for data recording and design of field and challenge experiments to simultaneously estimate genetic effects for all three epidemiological host traits. Using IPN in Atlantic salmon as a case study, we then demonstrate how these estimates together with genetic-epidemiological prediction models could be used to devise genetic disease control strategies. The results suggest that moving genetic studies beyond the sole focus on ‘disease resistance’ towards a more holistic genetic-epidemiological approach provides new avenues for more effective genetic disease control and for identifying novel genes underlying disease transmission. Keywords: infectious disease, disease transmission, susceptibility, infectivity, tolerance, disease resistance
Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Biology - Disease Resistance 3, , 462, 2018
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