Phytochrome B‐mediated light signalling enhances rice resistance to saline‐alkaline and sheath blight by regulating multiple downstream transcription factors
Bibliographic record
Abstract
Summary Light signalling regulates plant growth and stress resistance, whereas its mechanism in controlling saline‐alkaline tolerance (SAT) remains largely unknown. This study identified that light signalling, primarily mediated by Phytochrome B (PhyB), inhibited ammonium transporter 1 ( AMT1 ) to negatively regulate SAT. Our previous findings have shown that PhyB can impede the transcription factors indeterminate domain 10 (IDD10) and brassinazole resistant 1 (BZR1) to reduce NH 4 + uptake, thereby modulating SAT and sheath blight (ShB) resistance in rice. However, inhibition of IDD10 and BZR1 in the phyB background did not fully suppress NH 4 + uptake, suggesting that other signalling pathways regulated AMT1 downstream of PhyB. Further analysis revealed that PhyB interacted with Calcineurin B‐like protein‐interacting protein kinase 31 (CIPK31), which positively regulated AMT1 expression. CIPK31 also interacted with Teosinte Branched1/Cycloidea/PCF19 (TCP19), a key regulator of nitrogen use efficiency (NUE). However, PhyB neither degraded CIPK31 nor directly interacted with TCP19. Instead, PhyB inhibited the CIPK31‐TCP19 interaction, releasing TCP19, which repressed AMT1;2 directly and AMT1;1 and AMT1;3 indirectly, thereby inhibiting NH 4 + uptake and SAT while reducing ShB resistance. Additionally, Phytochrome Interacting Factor‐Like 15 (PIL15) interacted with TCP19. Different from TCP19, PIL15 directly activated AMT1;2 to promote SAT, suggesting a balancing mechanism for NH 4 + uptake downstream of PhyB. Furthermore, PIL15 interacted with IDD10 and BZR1 to form a transcriptional complex that collaboratively activated AMT1;2 expression. Overall, this study provides novel insights into how PhyB signalling regulates NH 4 + uptake and coordinates SAT and ShB resistance in rice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".