Beyond the genomes of <i>Fulvia fulva</i> (syn. <i>Cladosporium fulvum</i> ) and <i>Dothistroma septosporum</i> : New insights into how these fungal pathogens interact with their host plants
Bibliographic record
Abstract
Fulvia fulva and Dothistroma septosporum are closely related apoplastic pathogens with similar lifestyles but different hosts: F. fulva is a pathogen of tomato, whilst D. septosporum is a pathogen of pine trees. In 2012, the first genome sequences of these pathogens were published, with F. fulva and D. septosporum having highly fragmented and near-complete assemblies, respectively. Since then, significant advances have been made in unravelling their genome architectures. For instance, the genome of F. fulva has now been assembled into 14 chromosomes, 13 of which have synteny with the 14 chromosomes of D. septosporum, suggesting these pathogens are even more closely related than originally thought. Considerable advances have also been made in the identification and functional characterization of virulence factors (e.g., effector proteins and secondary metabolites) from these pathogens, thereby providing new insights into how they promote host colonization or activate plant defence responses. For example, it has now been established that effector proteins from both F. fulva and D. septosporum interact with cell-surface immune receptors and co-receptors to activate the plant immune system. Progress has also been made in understanding how F. fulva and D. septosporum have evolved with their host plants, whilst intensive research into pandemics of Dothistroma needle blight in the Northern Hemisphere has shed light on the origins, migration, and genetic diversity of the global D. septosporum population. In this review, we specifically summarize advances made in our understanding of the F. fulva-tomato and D. septosporum-pine pathosystems over the last 10 years.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".