Opendata, web and dolomites

PATH2EVOL SIGNED

Unravelling pathogen evolution breaking down crop resistance in agricultural ecosystems

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 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.

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

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.'

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "PATH2EVOL" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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

More projects from the same programme (H2020-EU.1.3.2.)

CREDit (2020)

Chronological REference Datasets and Sites (CREDit) towards improved accuracy and precision in luminescence-based chronologies

Read More  

NSTree (2020)

Understanding substrate delivery for cell wall biosynthesis in plants

Read More  

MemoryAggregates (2020)

Mechanism of Whi3 Aggregation and its Age-dependent Malfunction

Read More