Do fungal effector repertoires diverge between mycorrhizal types?
Background:
Like plant pathogens, mutualistic symbionts such as mycorrhizal fungi modulate immune responses in their hosts by secreting effector proteins to support colonization. However, it remains unclear what mycorrhizal effector repertoires overall look like. Mycorrhizal fungi can be discriminated into four major types: arbuscular, ericoid, ectomycorrhizal, and orchid mycorrhiza, each forming distinct mutualistic associations with specific groups of plants to facilitate nutrient and water acquisition. Whether the composition and evolutionary trajectories of mycorrhizal effector repertoires differ among the mycorrhizal types remains an open question.
Project description:
We will test whether effector repertoires differ across the four major mycorrhizal types and whether evolutionarily distant fungi within the same type show convergent effector repertoires. To do this, we will generate new genome assemblies from isolates lacking reference genomes and integrate them with a broad dataset of publicly available genomes spanning all four mycorrhizal types. We will furthermore include related representatives of pathogenic and saprotrophic fungi. Effector repertoires will be predicted, clustered into orthogroups, and analysed to determine whether fungi within the same mycorrhizal type share more effector orthogroups with each other than with other types, and whether composition differs among types.
In parallel, we will establish a CRISPR–Cas9 reverse genetics system in an ericoid mycorrhizal fungus to functionally test candidate effectors identified through comparative genomics for their roles in host colonisation and symbiosis establishment. This will also enable heterologous expression of effector genes from other mycorrhizal types to assess their effects in planta.
Together, this work will reveal how host interactions shape effector evolution, test for convergent evolution across mycorrhizal lineages, and link candidate effector genes to mycorrhiza-related phenotypes through integrated evolutionary and functional analyses.
Technologies and methods:
- Bioinformatics pipelines (R, Linux, Python):
- Comparative genomics
- Secretome and effector prediction
- Orthogroup clustering and gene family analysis
- Comparative genomics
Reverse genetics in mycorrhizal fungi & phenotyping:
- CRISPR–Cas9-mediated mutagenesis
- In planta phenotyping
- Microscopy
- CRISPR–Cas9-mediated mutagenesis
Supervisor: Leonardo Castanedo