The OsMAPK6–OsWRKY72 module positively regulates rice leaf angle through brassinosteroid signals
Bibliographic record
Abstract
Leaf angle is a major agronomic trait that determines plant architecture, which directly affects rice planting density, photosynthetic efficiency, and yield. The plant phytohormones brassinosteroids (BRs) and the MAPK signaling cascade are known to play crucial roles in regulating leaf angle, but the underlying molecular mechanisms are not fully understood. Here, we report a rice WRKY family transcription factor gene, OsWRKY72, which positively regulates leaf angle by affecting lamina joint development and BR signaling. Phenotypic analysis showed that oswrky72 mutants have smaller leaf angles and exhibit insensitivity to exogenous BRs, whereas OsWRKY72 overexpression lines show enlarged leaf angles and are hypersensitive to exogenous BRs. Histological sections revealed that the change in leaf inclination is due to asymmetric cell proliferation and growth at the lamina joint. Further investigation showed that OsWRKY72 binds directly to the promoter region of BR receptor kinase (OsBRI1), a key gene in the BR signaling pathway, and activates its expression to positively regulate rice BR signaling. In addition, we discovered that OsWRKY72 interacts with and is phosphorylated by OsMAPK6, and this phosphorylation event can enhance OsWRKY72 activity in promoting OsBRI1 expression. Genetic evidence confirmed that OsMAPK6, OsWRKY72, and OsBRI1 function in a common pathway to regulate leaf angle. Collectively, our findings clarify the critical role of the OsWRKY72 transcription factor in regulating rice leaf angle. These results provide valuable insights into the molecular regulatory networks that govern plant architecture in rice.
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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 | 0.000 |
| 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".