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PATH2EVOL SIGNED

Unravelling pathogen evolution breaking down crop resistance in agricultural ecosystems

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 PATH2EVOL project word cloud

Explore the words cloud of the PATH2EVOL project. It provides you a very rough idea of what is the project "PATH2EVOL" about.

fungi    virulence    genes    functional    genome    elusive    deployment    phenotypic    mapping    breakdown    ecosystem    responding    levels    basis    frameworks    avenue    virulent    fungal    blotch    populations    gained    pandemic    me    architecture    yield    replicated    strategies    collections    filamentous    repeatedly    security    resistant    adaptive    crop    reverse    flow    wheat    causing    speed    plots    conducive    thought    analyze    model    guide    hosts    agricultural    severe    evolution    associate    gene    link    lost    predictions    pathogen    locations    varieties    resistance    traits    threaten    causal    environment    tritici    zymoseptoria    holistic    genomes    loci    mechanisms    epidemics    stb    largely    pathogenic    ecology    genomic    prevent    rapid    septoria    substantially    overcome    statistical    host    emergence    genetic    favor    full    data    losses    isolated    sustainable    settings    previously    diverse    association    combination    food    deploying    pathogens    ecosystems    unbiased    disease    evolutionary   

Project "PATH2EVOL" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITE DE NEUCHATEL 

Organization address
address: FAUBOURG DE L'HOPITAL 41
city: NEUCHATEL
postcode: 2000
website: www.unine.ch

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Switzerland [CH]
 Total cost 175˙419 €
 EC max contribution 175˙419 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2017
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2018
 Duration (year-month-day) from 2018-07-01   to  2020-06-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITE DE NEUCHATEL CH (NEUCHATEL) coordinator 175˙419.00

Map

 Project objective

'Fungal crop pathogens cause severe yield losses and threaten food security. To prevent epidemics, deploying resistant varieties is currently the major avenue. However, agricultural ecosystems are highly conducive to the emergence of virulent pathogens and host resistance is rapidly overcome. The evolutionary mechanisms how virulence is gained on previously resistant hosts remains largely elusive. Identifying the genetic basis of adaptive evolution of pathogenic fungi in agricultural fields will be crucial to design future sustainable disease control strategies. The proposed project will analyze the process of pathogen adaptation to overcome crop resistance in agricultural ecosystem. The genomic architecture (i.e. 'two-speed genome') of filamentous pathogens is thought to favor the rapid evolution of virulence genes and the rapid breakdown of host resistance. However, the causal link between pathogen adaptation in the field and rapidly evolving loci has not been established. I propose to use “reverse ecology”, an unbiased and holistic approach to associate genomic loci with adaptation to the host and environment using the fungal pathogen Zymoseptoria tritici as a model. Z. tritici is a pandemic pathogen causing the severe Septoria Tritici Blotch (STB) on wheat. Populations are highly diverse with high levels of gene flow and wheat resistance was repeatedly lost in field settings. To identify loci responding to selection driven by host resistance, I will analyze full genomes of large pathogen collections isolated from replicated field plots using a robust statistical frameworks. This will allow me to test for an association of selection responses and genomic locations. I will also identify the phenotypic traits under selection with a combination of association mapping data and functional predictions. My research will substantially increase our understanding of pathogen adaptation and guide future resistance deployment strategies in agricultural ecosystem.'

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The information about "PATH2EVOL" are provided by the European Opendata Portal: CORDIS opendata.

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