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PathoGenoPredict

Financiado

Cerrado

Landscape genomic prediction of plant pathogen interactions

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... ver más

29/02/2024

MPG

175K€

Presupuesto del proyecto: 175K€

Líder del proyecto

MAXPLANCKGESELLSCHAFT ZUR FORDERUNG DER WISSE... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2024-02-29

MSCA-IF-2020: Individual Fellowships

I+D

Cerrada hace 4 años

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

1 Participantes

MPG

174.81K€ | Lider

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Duración del proyecto: 34 meses Fecha Inicio: 2021-04-16
Fecha Fin: 2024-02-29

Líder del proyecto

MAXPLANCKGESELLSCHAFT ZUR FORDERUNG DER WISSE... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 175K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto 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.

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