ArticlePathogens (Basel, Switzerland)2021
Predicting Lifestyle from Positive Selection Data and Genome Properties in Oomycetes.
Article in Pathogens (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Polyploidy and plant resilience to environmental stresses: Molecular mechanisms and future applications.Plant communications · 2026Review
- In silico prediction method for plant Nucleotide-binding leucine-rich repeat- and pathogen effector interactions.The Plant journal : for cell and molecular biology · 2025Article
- The massive 340 megabase genome of Anisogramma anomala, a biotrophic ascomycete that causes eastern filbert blight of hazelnut.BMC genomics · 2024Article
- Ten decadal advances in fungal biology leading towards human well-being.Fungal diversity · 2022Review
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Authors and funding
2 authors.
Funding
Abstract
As evidenced in parasitism, host and niche shifts are a source of genomic and phenotypic diversification. Exemplary is a reduction in the core metabolism as parasites adapt to a particular host, while the accessory genome often maintains a high degree of diversification. However, selective pressures acting on the genome of organisms that have undergone recent lifestyle or host changes have not been fully investigated. Here, we developed a comparative genomics approach to study underlying adaptive trends in oomycetes, a eukaryotic phylum with a wide and diverse range of economically important plant and animal parasitic lifestyles. Our analysis reveals converging evolution on biological processes for oomycetes that have similar lifestyles. Moreover, we find that certain functions, in particular carbohydrate metabolism, transport, and signaling, are important for host and environmental adaptation in oomycetes. Given the high correlation between lifestyle and genome properties in our oomycete dataset, together with the known convergent evolution of fungal and oomycete genomes, we developed a model that predicts plant pathogenic lifestyles with high accuracy based on functional annotations. These insights into how selective pressures correlate with lifestyle may be crucial to better understand host/lifestyle shifts and their impact on the genome.
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Registered trials
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