Simultaneous induction of jasmonic acid and disease-responsive genes signifies tolerance of American elm to Dutch elm disease
Bibliographic record
Abstract
Dutch elm disease (DED), caused by three fungal species in the genus Ophiostoma, is the most devastating disease of both native European and North American elm trees. Although many tolerant cultivars have been identified and released, the tolerance mechanisms are not well understood and true resistance has not yet been achieved. Here we show that the expression of disease-responsive genes in reactions leading to tolerance or susceptibility is significantly differentiated within the first 144 hours post-inoculation (hpi). Analysis of the levels of endogenous plant defense molecules such as jasmonic acid (JA) and salicylic acid (SA) in tolerant and susceptible American elm saplings suggested SA and methyl-jasmonate as potential defense response elicitors, which was further confirmed by field observations. However, the tolerant phenotype can be best characterized by a concurrent induction of JA and disease-responsive genes at 96 hpi. Molecular investigations indicated that the expression of fungal genes (i.e. cerato ulmin) was also modulated by endogenous SA and JA and this response was unique among aggressive and non-aggressive fungal strains. The present study not only provides better understanding of tolerance mechanisms to DED, but also represents a first, verified template for examining simultaneous transcriptomic changes during American elm-fungus interactions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".