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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.

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

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

Leaflet | Map data © OpenStreetMap contributors, CC-BY-SA, Imagery © Mapbox

 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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