56 - Awardee Talk: Genetic Improvement of Disease Resilience

Infectious disease represents one of the largest cost components to the swine industry, incurring veterinary costs, loss of pigs due to mortality, reduced performance, and reduced animal welfare. Strategies to reduce the incidence and impact of infectious disease include biosecurity, vaccination, veterinary treatment, and selection for genetic resistance. However, biosecurity protocols that keep most infectious pathogens out are not feasible at the commercial level in hog-dense regions, effective vaccines are only available and/or efficacious for some pathogens, and complete genetic resistance is also limited to only a few pathogens (e.g. F18 E.coli) or is only possible to achieve by gene editing (e.g. the PRRS-resistant pig created by editing the CD163 gene). Given these limitations, commercial pigs will continue to be exposed to and infected by pathogens for the foreseeable future. In such a scenario, the ability of an animal to clear the infection while maintaining performance is an important characteristic, which is referred to as disease resilience and is a useful target for inclusion in breeding programs. However, collection of data on disease resilience for genetic improvement requires animals to be exposed to disease, which is not possible in the nucleus herds of breeding programs that most selection is practiced in. To study the genetic basis of disease resilience and develop phenotypes, genetic tests, or indicator traits that could be used to select for disease resilience, a polymicrobial natural disease challenge model was established in grow-finish pigs at the Center de Développement du Porc du Québec, in collaboration with PigGen Canada. The purpose of this presentation is to present results on phenotypes that are relevant to disease resilience, including estimates of genetic parameters, and on potential indicator traits for disease resilience that could be collected in nucleus herds. Funding by Genome Canada, Genome Alberta, PigGen Canada, and USDA NIFA grant #2017-67007-26144.