Two alternatively spliced variants of <i>ZmHSF12</i> regulate the balance of plant growth and heat tolerance in maize and <i>Arabidopsis</i>
Bibliographic record
Abstract
Heat shock factors (HSFs) are pivotal in regulating plant heat tolerance; however, the mechanisms HSFs employ in regulating transcription to maintain a balance of plant growth and heat tolerance are poorly understood. This study reports that two maize HSF12 knockout lines are more sensitive to heat stress. ZmHSF12 encodes two alternative spliced transcripts: ZmHSF12-1 and ZmHSF12-2; overexpression of ZmHSF12-2 enhances, whereas overexpression of ZmHSF12-1 decreases plant heat tolerance, indicating the distinct functions of these two transcripts in plant heat stress response. In addition, ZmHSF12-2 upregulates RAFFINOSE SYNTHASE (ZmRAFS) and CYTOKININ OXIDASE (ZmCKO2) gene expression, controlling raffinose and cytokinin concentration in the cell, enhancing plant heat tolerance and inhibiting plant growth. ZmHSF12-1 interacts with ZmHSF12-2 and represses the transcriptional regulation of ZmHSF12-2 on ZmCKO2 and ZmRAFS. Co-overexpression of ZmHSF12-1 and ZmHSF12-2 in Arabidopsis not only improved the heat tolerance of plants but also compensated for the growth defect phenotype of ZmHSF12-2 overexpressing Arabidopsis plants. These findings deepen our understanding of plant heat tolerance and significantly impact the scientific community. They support the potential application of co-overexpressing ZmHSF12-1 and ZmHSF12-2 to improve crop heat tolerance without causing growth retardation and yield compensation, thereby offering a promising avenue for crop improvement.
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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".