10.5061/DRYAD.G108557
Leclerc, Melen
French National Institute for Agricultural Research
Clément, Julie
French National Centre for Scientific Research
Andrivon, Didier
French National Institute for Agricultural Research
Hamelin, Frédéric
French National Institute for Agricultural Research
Data from: Assessing the effects of quantitative host resistance on the
life-history traits of sporulating parasites with growing lesions
Dryad
dataset
2019
epidemiological modelling
potato late blight
aggressiveness
sporulation dynamics
Phytophthora infestans
lesion model
2019-09-23T00:00:00Z
2019-09-23T00:00:00Z
en
43771 bytes
2
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Assessing life-history traits of parasites on resistant hosts is crucial
in evolutionary ecology. In the particular case of sporulating pathogens
with growing lesions, phenotyping is difficult because one needs to
disentangle properly pathogen spread from sporulation. By considering
Phytophthora infestans on potato, we use mathematical modelling to tackle
this issue and refine the assessment pathogen response to quantitative
host resistance. We elaborate a parsimonious leaf-scale model by
convolving a lesion growth model and a sporulation function, after a
latency period. This model is fitted to data obtained on two isolates
inoculated on three cultivars with contrasted resistance level. Our
results confirm a significant host-pathogen interaction on the various
estimated traits, and a reduction of both pathogen spread and spore
production, induced by host resistance. Most interestingly, we highlight
that quantitative resistance also changes the sporulation function, whose
mode is significantly time-lagged.This alteration of the infectious period
distribution on resistant hosts may have strong impacts on the dynamics of
parasite populations, and should be considered when assessing the
durability of disease control tactics based on plant resistance
management. This inter-disciplinary work also supports the relevance of
mechanistic models for analysing phenotypic data of plant-pathogen
interactions.
Phenotypic dataPhenotypic data used for the study. Columns names are
similar to the notations used in the manuscript (See Table
1).data.csvR_code_lesion_modelR script for fitting lesion growth and
sporulation models to destructive phenotypic data.