The ethylene responsive factor TaERF-2 A activates gibberellin 2-oxidase gene TaGA2ox2-3B expression to enhance seed dormancy in wheat
Bibliographic record
Abstract
The plant hormone gibberellin (GA) plays a key role in breaking seed dormancy, but the underlying regulatory mechanism is not fully understood. Here, we reported TraesCS3B02G166100 (named TaGA2ox2-3B ), encoding a GA metabolism enzyme GA2ox family member, to be differentially expressed in strong- and weak-dormancy wheat seeds during germination. We confirmed that the ERF transcription factor TaERF-2 A directly bound to the TaGA2ox2-3B promoter and enhanced its transcription. Germination tests indicated that TaERF-2 A positively regulated seed dormancy in wheat. Additionally, 12 mutations were identified within the promoter and coding regions of TaGA2ox2-3B when comparing strong- and weak-dormancy wheat varieties. Six molecular markers were developed to verify correlations between these mutations and seed dormancy. Transgenic experiments verified the potential of the TaGA2ox2-3B +2246-A allele to enhance seed dormancy. Physiological and biochemical analyses indicated that the TaERF-2 A-TaGA2ox2-3B module modulated seed dormancy by influencing GA metabolism and signaling pathways. Collectively, this study revealed the molecular mechanism of GA regulating seed dormancy, and identified genetic resources and molecular markers to breed wheat varieties with preharvest sprouting resistance.
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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".