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Landscape genomic prediction of plant-pathogen interactions

Project description

Predicting the impacts of climate change on plant-pathogen interactions

Numerous studies of molecular plant-pathogen interactions have probed the precise combinations of host and pathogen genes that lead to susceptibility or resistance. Although valuable, laboratory trials cannot directly predict when and where a disease will develop (pathogenesis) in natural or agricultural plant populations, as environmental factors also play a role. The EU-funded PathoGenoPredict project will create a framework that enables scientists to predict plant pathogenesis and account for spatiotemporal variation in both host and pathogen genetics over the landscape and through time. The research fellow will investigate the genetic interaction of Hyaloperonospora arabidopsidis, a model fungus-like organism known as an oomycete, and the model plant Arabidopsis thaliana across the landscape, producing maps both for today's climate and predicted future climate change.

Objective

Plants and their pathogens are locked in an ongoing coevolutionary battle, with outcomes affecting food and environmental security. Pathogenesis can occur when a host's resistance and pathogen's virulence genotypes are compatible with infection, while incompatible genotypes lead to resistance. A myriad of studies of molecular plant-pathogen interactions have probed the precise combinations of host (R) and pathogen (Avr) genes that lead to susceptibility or resistance. While laboratory trials are valuable, they cannot directly predict when and where pathogenesis will occur in natural or agricultural plant populations, as environmental factors also play a role. In this fellowship, I will build predictions of plant pathogenesis that account for spatiotemporal variation in both host and pathogen genetics over the landscape and through time.
I will investigate the model system of Hyaloperonospora arabidopsidis (Hpa; an oomycete) and Arabidopsis thaliana (Ath; a plant). Existing work in this system has identified the molecular mechanisms underlying multiple disease resistance phenotypes. I propose to extend this work by evaluating the genetic interaction of Hpa and Ath across the landscape. Specifically, I aim to
1) Determine the spatial distribution of genetic diversity across the landscape in both Ath and Hpa, investigating both neutral genome-wide patterns and R/Avr gene loci.
2) Model genetic variation in R/Avr genes across the landscape, producing maps both for today’s climate, and under predicted future climate change.
3) Predict how genetics interacts with a variable environment, including a changing climate, to produce disease, including future changes in the coevolutionary balance between plant and pathogen due to climate-induced range shifts.
These aims facilitate the projection of molecular plant-pathogen interactions onto the landscape, and provide a framework to examine the molecular mechanisms underlying ecological interaction of plants and their pathogens.

Coordinator

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Net EU contribution
€ 174 806,40
Address
Hofgartenstrasse 8
80539 Munchen
Germany

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Region
Bayern Oberbayern München, Kreisfreie Stadt
Activity type
Research Organisations
Links
Other funding
€ 0,00