The genetic basis of rapid plant pathogen evolution
| Responsable du projet | Daniel Croll |
| Résumé |
Plants and pathogens are locked in arms races to detect invasion and
to disable host resistance, respectively. A key evolutionary step
for pathogens is to evolve effectors, which are small proteins that
specifically target and disable the plant immune system. The
effector content is a major determinant of the pathogen's host
range and evolutionary potential. The ability of hosts to detect
specific pathogen effectors is expected to lead to strong
directional selection on pathogen populations. However, for most
plant pathogenic fungi, the content in effector genes and their
evolutionary trajectory are poorly known. Plants in agricultural
ecosystems are attacked by a multitude of microbial pathogens.
Rapid evolution in pathogens poses a significant threat to food
security. What enables pathogens to overcome disease resistance of
crops and cause damage is poorly understood. In this project, we
will use the highly polymorphic pathogen of wheat Zymoseptoria
tritici as a model. The wheat genome encodes a large number of
uncharacterized resistance factors against the pathogen. The very
large population sizes of the pathogen enabled the rapid evolution
of fungicide resistance and virulence on previously resistant wheat
cultivars. However, it is largely unknown what loci in the pathogen
genome contribute to virulence on wheat. We also lack an
understanding how selection, imposed by the host’s ability to
detect the pathogen, impacts the evolutionary trajectory of
pathogen populations. The major goal of the proposed research is to
establish a comprehensive understanding of the loci in the pathogen
genome that contribute to virulence evolution. The first set of
experiments will map phenotypic traits of the pathogen to loci in
the genome using genome-wide association studies (GWAS). For this,
we will create a highly diverse mapping population from an
experimental wheat field site. We will measure the ability of
fungal strains to cause disease on a series of different wheat
cultivars in greenhouse experiments. We will also assay the mapping
population for the ability to tolerate abiotic stress factors and
quantify the secretion of secondary metabolites, which likely play
a role in ecological interactions during infection. Whole genome
sequencing will provide a highly dense set of genetic markers for
association mapping. The second set of experiments takes a “reverse
ecology” approach to identify targets of selection in pathogen
populations. For this, we will collect pathogen strains in
replicated plots of multiple wheat cultivars grown at the same
experimental wheat field site. Pathogen genotypes better adapted to
cause disease on a specific wheat cultivar are expected to
accumulate over the growing season. We will perform a large-scale
sequencing study to detect responses to selection in pathogen
populations by identifying consistent allele frequency changes over
time. Finally, we will combine knowledge gained from the first and
second part of this project. Importantly, we will be able to
disentangle loci segregating adaptive genetic variation to cause
disease from loci responding to selection pressure to colonize the
same host. In principle, pathogen loci contributing to virulence
on a specific host (identified by GWAS) should match the targets of
selection on the same host in the field experiments. However,
mismatches in the identity of loci recovered by the two approaches
will provide important insights into how ecological factors impact
the evolution of host specialization. This project will identify
key mechanisms driving rapid plant pathogen evolution. Knowledge
generated in this project will advance the functional understanding
of fungal pathogenesis and inform sustainable strategies to manage
disease in agricultural ecosystems. |
| Mots-clés |
Plant pathogens, genome-wide association studies, population genomics, Zymoseptoria tritici, fungi, selection scans |
| Type de projet | Recherche fondamentale |
| Domaine de recherche | Evolution de pathogènes dans des écosystèmes agricoles |
| Source de financement | FNS |
| Etat | En cours |
| Début de projet | 1-7-2017 |
| Fin du projet | 31-3-2020 |
| Budget alloué | 549'680 CHF |
| Contact | Daniel Croll |