Titel: Effect of genetic drift and selection on plant resistance durability to viruses.
Plants can be fully protected from their pathogens when they carry major resistance genes, but the efficiency of these genes is limited by the emergence and spread of adapted, resistance-breaking pathogen variants. This thesis studies how evolutionary forces imposed by the plants on pathogen populations may increase the durability of major resistance genes. Using plant viruses as a biological model, this thesis investigates the effect of genetic drift and selection, from the within-host to the host population level. Firstly, a stochastic epidemiological SI model at the field level showed that genetic drift could be particularly beneficial for crop yield when the fitness cost associated with virus adaptation to resistance was intermediate in susceptible plants. Then, the design and validation of a mechanistic-statistical model based on deterministic Lotka-Volterra equations and stochastic Dirichlet-multinomial processes allowed to disentangle the effects of genetic drift from those of selection on temporal data of within-host competition between virus variants. The intensities of genetic drift and selection acting on virus populations were shown to be controlled genetically by the hosts. Finally, a correlation analysis between these estimations of genetic drift and selection intensities and an experimental estimation of the durability of a major resistance gene showed that strong genetic drift during the early stages of plant infection led to an increase in resistance durability. These results open new perspectives for more durable management of plant resistance, by breeding plant varieties inducing strong genetic drift on pathogen populations
Jury members:
Fernando GARCIA ARENAL, Universidad Politécnica de Madrid
Frédéric HOSPITAL, INRA
Elisabeta VERGU, INRA
Christian LANNOU, INRA
Gaël THEBAUD, INRA
Alain VIARI, Inria
Jean Luc GOUZE, Inria
Frédéric FABRE, INRA
Keywords: genetic drift, selection, resistance durability, experimental evolution, epidemiology.
