OsSAE1 orchestrates the antagonistical regulation of gibberellin and abscisic acid signaling to control rice seed germination
Bibliographic record
Abstract
The plant life cycle and the promise of crop yield start with successful seed germination, which requires an optimal balance between the phytohormones abscisic acid (ABA) and gibberellin (GA). Here, we report that the APETALA 2-type transcription factor SALT AND ABA RESPONSE ERF 1 (OsSAE1) antagonistically modulates ABA and GA signaling to control seed germination in rice (Oryza sativa L.). We show that knocking out OsSAE1 delays seed germination, concomitant with the accumulation of SLENDER RICE1 (OsSLR1), a GA signaling repressor DELLA protein; importantly, GA application rescued the seed germination defect of ossae1 mutants. OsSAE1 directly activates transcription of the GA biosynthesis gene OsKS1 and represses that of the GA metabolism gene OsGA2ox3, resulting in higher GA levels. Moreover, OsSLR1 physically interacts with ABA-INSENSITIVE 5 (OsABI5), a key ABA signaling component, enhancing the transcriptional activation capacity of OsABI5 toward its target genes to regulate seed germination. The temporal expression pattern of OsSAE1 supports its role in orchestrating GA and ABA signaling to modulate seed germination and seed dormancy. Different OsSAE1 haplotypes differentially affected OsSAE1 transcript levels and seed germination rates, illustrating the potential of the elite OsSAE1 haplotype for genetic improvement of seed germination. Overall, our study reveals that OsSAE1 controls rice seed germination by regulating the balance between ABA and GA, providing a pivotal selection target for breeding rice cultivars suitable for direct seeding.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".