Overexpression of <i>Brassica napus MPK4</i> Enhances Resistance to <i>Sclerotinia sclerotiorum</i> in Oilseed Rape
Bibliographic record
Abstract
Sclerotinia sclerotiorum causes a highly destructive disease in oilseed rape (Brassica napus) resulting in significant economic losses. Studies on the Arabidopsis thaliana MPK4 loss-of-function mutant have implicated that AtMPK4 is involved in plant defense regulation, and its effect on disease resistance varies in different plant-pathogen interactions. In this study, we isolated a B. napus mitogen-activated protein kinase, BnMPK4, and found that BnMPK4 along with PDF1.2 are inducible in resistant line Zhongshuang9 but both are consistently suppressed in susceptible line 84039 after inoculation with S. sclerotiorum. Transgenic oilseed rape overexpressing BnMPK4 markedly enhances resistance to S. sclerotiorum and Botrytis cinerea. Further experiments showed that transgenic plants inhibited growth of S. sclerotiorum and constitutively activated PDF1.2 but decreased H2O2 production and constitutively suppressed PR-1 expression. Treatment of roots of the transgenic plants with H2O2 solution resulted in enhanced susceptibility to the two pathogens. Our results support the idea that MPK4 positively regulates jasmonic acid-mediated defense response, which might play an important role in resistance to S. sclerotiorum in oilseed rape.
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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".