Modelling the displacement and coexistence of clonal lineages of Phytophthora infestans through revisiting past outbreaks

The continuous changes in the lineage proportions of populations in the clonal plant pathogen Phytophthora infestans on potato and tomato crops have been perplexing to researchers and disease managers. Sudden outbreaks of newly emergent genotypes are often associated with these rapid composition cha...

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Veröffentlicht in:Plant pathology 2024-05, Vol.73 (4), p.924-936
Hauptverfasser: Huang, Chih‐Chiang, Liew, Edward C. Y., Wan, Justin S. H.
Format: Artikel
Sprache:eng
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Zusammenfassung:The continuous changes in the lineage proportions of populations in the clonal plant pathogen Phytophthora infestans on potato and tomato crops have been perplexing to researchers and disease managers. Sudden outbreaks of newly emergent genotypes are often associated with these rapid composition changes. Modelling can predict the persistence and displacement of pathogen genotypes with differential fitness among hosts. Building upon previous models, we combined analytical and simulation methods to model the outcome of interactions between competing lineages on different hosts. Model inputs include pathogenesis parameters, and the outputs are fitness and lineage proportions within each host. Analytical solutions yielding complete displacement, partial coexistence‐displacement and complete coexistence were described. In a retrospective study, the lesion growth rate and sporulation density of P . infestans lineages on potato and tomato from pathogenicity trials were used as inputs. Output lineage frequencies were compared with historical epidemiological situations to check model accuracy. The results showed that pathogenesis traits measured from empirical trials could simulate lineage constituents on potato and tomato and estimate genotypic fitness with reasonable accuracy. The model also showed promise in predicting ongoing lineage displacements in the subsequent year or few years, even when the displaced lineage was still highly prevalent during the time of isolation. However, large uncertainties remain at temporal–spatial scales owing to complex meta‐population dynamics in some regions and adaptation to local environmental factors. This simulation model provides a new tool for forecasting pathogen compositions and can be used to identify potentially problematic genotypes based on pathogen life‐history traits.
ISSN:0032-0862
1365-3059
DOI:10.1111/ppa.13862