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Zawartość zarchiwizowana w dniu 2024-06-18

Identification of Sclerotinia sclerotiorum Effector Proteins mediating virulence on Arabidopsis thaliana ecotypes

Cel

Sclerotinia sclerotiorum is a necrotrophic fungus notorious for its broad host range, including notably oilseed rape, sunflower, lettuce, carrot, onion and potato. In most cases there is no variety with significant resistance or tolerance known to date. Small secreted proteins and low molecular weight metabolites have been reported in several necrotrophic fungi as critical for virulence. However, the role of these effector proteins in S. sclerotiorum virulence is largely unknown, and the molecular mechanisms by which S. sclerotiorum promotes host susceptibility remain poorly understood. We recently discovered that susceptibility to S. sclerotiorum is highly variable among A. thaliana accessions and our preliminary analyses on S. sclerotiorum genome sequence identified promising effector candidates. The objective of this proposal is to validate the function of S. sclerotiorum effector candidates in altering plant cells to promote susceptibility. We will (i) document the diversity of S. sclerotiorum effector protein candidates; (ii) identify effector candidates that promote susceptibility to S. sclerotiorum and (iii) identify effector candidates required for S. sclerotiorum virulence. This project will have a significant impact on our understanding of plant-microbe interactions by providing insights into key molecular processes regulating susceptibility to a necrotrophic pathogen. Besides, it will open new perspectives toward the development of tolerant crop varieties.

Dziedzina nauki (EuroSciVoc)

Program(-y)

Temat(-y)

Zaproszenie do składania wniosków

FP7-PEOPLE-2012-CIG
Zobacz inne projekty w ramach tego zaproszenia

System finansowania

MC-CIG - Support for training and career development of researcher (CIG)

Koordynator

INSTITUT NATIONAL DE RECHERCHE POUR L'AGRICULTURE, L'ALIMENTATION ET L'ENVIRONNEMENT
Wkład UE
€ 100 000,00
Koszt całkowity
Brak danych