On Wednesday June 15, Mahlet Teka Anche successfully defended her PhD-thesis entitled “Estimating host genetic effects on susceptibility and infectivity to infectious diseases and their contribution to response to selection”. With her research Mahlet developed methodologies to investigate the genetic effects of host susceptibility and infectivity on the prevalence of an infection. Moreover, she investigated the effect of relatedness among groupmates on the utilization of among host genetic variation in susceptibility and infectivity so as to reduce the prevalence of infectious diseases.
Infectious diseases of animals are a major concern to the livestock industry, particularly due to their effect on the welfare and productivity of livestock and some also poses a threat to public health. Studies have reported that there exists among hosts genetic variation for different disease related traits. These findings suggest that breeders can implement selective breeding as a complementary method to the existing disease control strategies to genetically improve host populations in order to decrease the prevalence of infectious diseases in livestock populations.
Mahlet’s thesis focusses on the quantitative genetics of infectious diseases, with specific emphasis on genetic variation in infectivity among host individuals. In her thesis, she shows how heritable variation in the basic reproduction ration, R0, can be defined, and how this variation can be utilized in selection schemes. Results show that breeders can considerably increase responses to selection by using groups of related individuals. Next to that, she presents statistical methodology for the estimation of gene effects on host susceptibility and infectivity, which can be used to identify genes affecting disease traits. These methods are applied to a population of Scottish Blackface sheep to estimate effects of MHC-polymorphisms on disease traits. At the end of her thesis, she investigates the estimation of genetic co(variances) and breeding values for host susceptibility and infectivity from data on the final disease status of hosts exposed to epidemics. Results show that time-series data on individual disease status will be needed to accurately estimate these genetic (co)variances.
From her research can be concluded that, with advancements made in statistical methods and quantitative and molecular genetics, breeders should consider breeding for reduced R0 in their breeding goal when the aim is to reduce the prevalence and risk of an infection. Overall, this thesis is an important contribution to the theoretical integration of animal breeding and quantitative epidemiology, and to the development of empirical tools for the application thereof.
Mahlet’s thesis is a result of a collaboration between the Animal Breeding and Genomics Centre and the Quantitative Veterinary Epidemiology group of Wageningen University. The research was funded by the EU Marie-Curie project Nemathode System Health, which was coordinated by Prof. Mike Stear of Glasgow University. Mahlet was supervised by Prof. dr Mart de Jong and dr Piter Bijma.