Knockout of <scp><i>SlNPR1</i></scp> enhances tomato plants resistance against <i>Botrytis cinerea</i> by modulating <scp>ROS</scp> homeostasis and <scp>JA</scp>/<scp>ET</scp> signaling pathways
Bibliographic record
Abstract
Tomato is one of the most popular horticultural crops, and many commercial tomato cultivars are particularly susceptible to Botrytis cinerea. Non-expressor of pathogenesis-related gene 1 (NPR1) is a critical component of the plant defense mechanisms. However, our understanding of how SlNPR1 influences disease resistance in tomato is still limited. In this study, two independent slnpr1 mutants were used to study the role of SlNPR1 in tomato resistance against B. cinerea. Compared to (WT), slnpr1 leaves exhibited enhanced resistance against B. cinerea with smaller lesion sizes, higher activities of chitinase (CHI), β-1, 3-glucanases (GLU) and phenylalanine ammonia-lyase (PAL), and significantly increased expressions of pathogenesis-related genes (PRs). The increased activities of peroxidase (POD), ascorbate peroxidase (APX) and decreased catalase (CAT) activities collectively regulated reactive oxygen species (ROS) homeostasis in slnpr1 mutants. The integrity of the cell wall in slnpr1 mutants was maintained. Moreover, the enhanced resistance was further reflected by induction of defense genes involved in jasmonic acid (JA) and ethylene (ET) signaling pathways. Taken together, these findings revealed that knocking out SlNPR1 resulted in increased activities of defense enzymes, changes in ROS homeostasis and integrity of cell walls, and activation of JA and ET pathways, which confers resistance against B. cinerea in tomato plants.
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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) | 0.001 | 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 | 0.001 |
| 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".