RNA sequencing of Brassica napus reveals cellular redox control of Sclerotinia infection
Bibliographic record
Abstract
Brassica napus is one of the world's most valuable oilseeds and is under constant pressure by the necrotrophic fungal pathogen, Sclerotinia sclerotiorum, the causal agent of white stem rot. Despite our growing understanding of host pathogen interactions at the molecular level, we have yet to fully understand the biological processes and underlying gene regulatory networks responsible for determining disease outcomes. Using global RNA sequencing, we profiled gene activity at the first point of infection on the leaf surface 24 hours after pathogen exposure in susceptible (B. napus cv. Westar) and tolerant (B. napus cv. Zhongyou 821) plants. We identified a family of ethylene response factors that may contribute to host tolerance to S. sclerotiorum by activating genes associated with fungal recognition, subcellular organization, and redox homeostasis. Physiological investigation of redox homeostasis was further studied by quantifying cellular levels of the glutathione and ascorbate redox pathway and the cycling enzymes associated with host tolerance to S. sclerotiorum. Functional characterization of an Arabidopsis redox mutant challenged with the fungus provides compelling evidence into the role of the ascorbate-glutathione redox hub in the maintenance and enhancement of plant tolerance against fungal pathogens.
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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 | 0.001 | 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".