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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.

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

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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