RT Journal Article
SR Electronic
T1 An epi-evolutionary model to predict spore-producing pathogens adaptation to quantitative resistance in heterogeneous environments
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 423467
DO 10.1101/423467
A1 Frédéric Fabre
A1 Jean-Baptiste Burie
A1 Arnaud Ducrot
A1 Sébastien Lion
A1 Quentin Richard
A1 Ramsès Djidjou-Demasse
YR 2021
UL http://biorxiv.org/content/early/2021/09/21/423467.abstract
AB We model the evolutionary epidemiology of spore-producing plant pathogens in heterogeneous environments sown with several cultivars carrying quantitative resistances. The model explicitly tracks the infection-age structure and genetic composition of the pathogen population. Each strain is characterized by pathogenicity traits describing its infection efficiency and a time-varying sporulation curve taking into account lesion ageing. We first derive a general expression of the basic reproduction number ℛ0 for fungal pathogens in heterogeneous environments. We show that evolutionary attractors of the model coincide with local maxima of ℛ0 only if the infection efficiency is the same on all host types. We then study how three basic resistance characteristics (pathogenicity trait targeted, resistance effectiveness, and adaptation cost) in interaction with the deployment strategy (proportion of fields sown with a resistant cultivar) (i) lead to pathogen diversification at equilibrium and (ii) shape the transient dynamics from evolutionary and epidemiological perspectives. We show that quantitative resistance impacting only the sporulation curve will always lead to a monomorphic population, while dimorphism (i.e. pathogen diversification) can occur with resistance altering infection efficiency, notably with high adaptation cost and proportion of R cultivar. Accordingly, the choice of quantitative resistance genes operated by plant breeders is a driver of pathogen diversification. From an evolutionary perspective, the emergence time of the evolutionary attractor best adapted to the R cultivar tends to be shorter when the resistance impacts infection efficiency than when it impacts sporulation. In contrast, from an epidemiological perspective, the epidemiological control is always higher when the resistance impacts infection efficiency. This highlights the difficulty of defining deployment strategies of quantitative resistance maximising at the same time epidemiological and evolutionary outcomes.Competing Interest StatementThe authors have declared no competing interest.