The OsMYB30 Transcription Factor Suppresses Cold Tolerance by Interacting with a JAZ Protein and Suppressing <i>β</i>-Amylase Expression
Bibliographic record
Abstract
Cold stress is one of the major limiting factors for rice (Oryza sativa) productivity. Several MYB transcriptional factors have been reported as important regulators in the cold stress response, but the molecular mechanisms are largely unknown. In this study, we characterized a cold-responsive R2R3-type MYB gene, OsMYB30, for its regulatory function in cold tolerance in rice. Functional analysis revealed that overexpression of OsMYB30 in rice resulted in increased cold sensitivity, while the osmyb30 knockout mutant showed increased cold tolerance. Microarray and quantitative real-time polymerase chain reaction analyses revealed that a few β-amylase (BMY) genes were down-regulated by OsMYB30. The BMY activity and maltose content, which were decreased and increased in the OsMYB30 overexpression and osmyb30 knockout mutant, respectively, were correlated with the expression patterns of the BMY genes. OsMYB30 was shown to bind to the promoters of the BMY genes. These results suggested that OsMYB30 exhibited a regulatory effect on the breakdown of starch through the regulation of the BMY genes. In addition, application of maltose had a protective effect for cell membranes under cold stress conditions. Furthermore, we identified an OsMYB30-interacting protein, OsJAZ9, that had a significant effect in suppressing the transcriptional activation of OsMYB30 and in the repression of BMY genes mediated by OsMYB30. These results together suggested that OsMYB30 might be a novel regulator of cold tolerance through the negative regulation of the BMY genes by interacting with OsJAZ9 to fine-tune the starch breakdown and the content of maltose, which might contribute to the cold tolerance as a compatible solute.
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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) | 0.001 | 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".