Plasma membrane receptor-like kinase leaf panicle 2 acts downstream of the DROUGHT AND SALT TOLERANCE transcription factor to regulate drought sensitivity in rice
Bibliographic record
Abstract
Drought is a recurring climatic hazard that reduces the crop yields. To avoid the negative effects of drought on crop production, extensive efforts have been devoted to investigating the complex mechanisms of gene expression and signal transduction during drought stress. Receptor-like kinases (RLKs) play important roles in perceiving extracellular stimuli and activating downstream signalling responses. The rice genome contains >1100 RLK genes, of which only two are reported to function in drought stress. A leucine-rich repeat (LRR)-RLK gene named Leaf Panicle 2 (LP2) was previously found to be strongly expressed in leaves and other photosynthetic tissues, but its function remains unclear. In the present study, it was shown that the expression of LP2 was down-regulated by drought and abscisic acid (ABA). Transgenic plants overexpressing LP2 accumulated less H₂O₂, had more open stomata in leaves, and showed hypersensitivity to drought stress. Further investigation revealed that transcription of LP2 was directly regulated by the zinc finger transcription factor DROUGHT AND SALT TOLERANCE (DST). In addition, LP2 was identified as a functional kinase localized to the plasma membrane and interacted with the drought-responsive aquaporin proteins OsPIP1; 1, OsPIP1; 3, and OsPIP2; 3. Thus, the findings provided evidence that the LRR-RLK LP2, transcriptionally regulated by the drought-related transcription factor DST, served as a negative regulator in drought response.
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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".