Elise Lepage

Pierre Mustin

Marion Szadkowski

Judith Hirsch

Benoît Moury

Loup Rimbaud

Itinerary of a fluorescently labelled virus in a resistant plant

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Plant resistance to viruses is a highly effective and low-input approach to control epidemics in agricultural crops. Although the genetic determinism of many sources of resistance has been well characterized, their phenotypic expression at the plant scale is still poorly known. Yet, the extent of epidemic limitation and the evolutionary outcome of resistance deployment depend on which step(s) of the viral infectious cycle is/are targeted and impeded by plant resistance: i) infection of a healthy plant, ii) viral accumulation in the infected leaf, iii) systemic plant colonisation, and iv) transmission to new plants.

Using the pathosystem pepper-potato virus Y (PVY, Potyvirus), we developed an experimental approach to quantify the effect of host resistance on the two first steps. For this, we used a modified virus that expresses a Green Fluorescent Protein (GFP) and automated image analyses to: i) estimate the probability of infection by a single viruliferous aphid, and ii) monitor the dynamics of viral accumulation in inoculated leaves. Indeed, viral load, traditionally measured by destructive serological or molecular methods, can be approximated by the proportion of the leaf surface emitting fluorescence, which can be evaluated in a non-destructive way using an appropriate camera device.

Experiments on seven different accessions of pepper (Capsicum annuum) are currently ongoing. Early results indicate contrasted resistance profiles: accessions associated with the smallest probability of infection are not necessarily those that best mitigate subsequent viral accumulation.

Oral presentation Theme 3: Résistance & silencing / Plant defense and RNA silencing Student: no Itinerary of a fluorescently labelled virus in a resistant plant

	Elise Lepage 1 , Pierre Mustin 2 , Marion Szadkowski 1 , Judith Hirsch 1 , Benoît Moury 1 , Loup
	Rimbaud 1
	1 INRAE -Pathologie Végétale, elise.lepage@inrae.fr, 84140, Montfavet, France.
	marion.szadkowski@inrae.fr
	judith.hirsch@inrae.fr
	benoit.moury@inrae.fr
	loup.rimbaud@inrae.fr
	2 Université de Strasbourg, INRAE, UMR-A 1131 Santé de la Vigne et Qualité du Vin, pierre.mustin@inrae.fr,
	F-68000 Colmar, France.


Loup Rimbaud

Julien Papaïx

Jean-François Rey

Jean-Loup Gaussen

Marta Zafarroni

Modelling plant resistance deployment: the R package landsepi

The R package landespi provides a general modelling framework to help compare plant resistance deployment strategies and understand the impact of epidemiological, evolutionary and genetic factors for a wide range of pathosystems. In landsepi, the landscape is a dynamic mosaic of fields cultivated with croptypes. Each croptype is composed of either a pure cultivar or a mixture; and each cultivar may carry one or several resistance genes. Each resistance gene targets one or several pathogenicity traits, with complete or partial efficiency, and may be expressed from the beginning of the season or later (e.g. APR gene). The pathogen may adapt to these genes (restoring its pathogenicity), possibly associated with a fitness cost.

PUBLICATIONS ACKNOWLEDGEMENTS

The model is based on a spatial geometry for describing the heterogeneous landscape and allocating different cultivars, a dispersal kernel for the dissemination of the pathogen, and a stochastic SEIR ('Susceptible-Exposed-Infectious-Removed') structure with a discrete time step for the description of the host-pathogen interaction. Cropping seasons are split by host harvests which impose potential bottlenecks to the pathogen. The model accounts for pathogen evolution (via mutation, sexual reproduction, selection and drift) and provides epidemiological, evolutionary and economic outputs to assess the performance of the simulated strategies.

The package also includes a shiny interface for pedagogical purposes.

  time step, randomness seed) Evolutionary: Resistance durability ability to limit pathogen evolution and delay resistance breakdown (Pathotype and genotype frequencies, Time to resistance breakdown) Epidemiological: Disease control ability to reduce disease impact (AUDPC, GLA) Economic: Cost efficiency ability to overcompensate epidemic losses and management costs (Yield, Product, Operational cost, Margin) Spatial unit: The spatial unit is a polygon. An agricultural field (i.e. a piece of land cultivated by the same croptype) may be composed of a single or several polygons. Individual: A host 'individual' is an infection unit and may correspond to a given amount of plant tissue (where a local infection may develop, e.g. fungal lesion) or a whole plant (e.g. systemic viral infection). In the first case, plant growth increases the amount of available plant tissue (hence the number of individuals) during the cropping season.Strategies to improve plant resistance management rely on careful selection of resistance sources and their combination at various spatio-temporal scales.

  Adapted from Rimbaud L., Fabre F., Papaïx J., Moury B., Lannou C., Barrett L. and Thrall P. (2021). Models of plant resistance deployment. Annual Review of Phytopathology 59(1: 30 seconds (for a 30-year simulation with 3 cultivars and 2 major resistance genes)