The Arabidopsis effector-triggered immunity landscape is conserved in oilseed crops
Bibliographic record
Abstract
The bacterial phytopathogen Pseudomonas syringae causes disease on a wide array of plants, including the model plant Arabidopsis thaliana and its agronomically important relatives in the Brassicaceae family. To cause disease, P. syringae delivers effector proteins into plant cells through a type III secretion system. In response, plant nucleotide-binding leucine-rich repeat proteins recognize specific effectors and mount effector-triggered immunity (ETI). While ETI is pervasive across A. thaliana, with at least 19 families of P. syringae effectors recognized in this model species, the ETI landscapes of crop species have yet to be systematically studied. Here, we investigated the conservation of the A. thaliana ETI landscape in two closely related oilseed crops, Brassica napus (canola) and Camelina sativa (false flax). We show that the level of immune conservation is inversely related to the degree of evolutionary divergence from A. thaliana, with the more closely related C. sativa losing ETI responses to only one of the 19 P. syringae effectors tested, while the more distantly related B. napus loses ETI responses to four effectors. In contrast to the qualitative conservation of immune response, the quantitative rank order is not as well-maintained across the three species and diverges increasingly with evolutionary distance from A. thaliana. Overall, our results indicate that the A. thaliana ETI profile is qualitatively conserved in oilseed crops, but quantitatively distinct.
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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) | 0.000 | 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".