Transcription Factors <i>Rc</i> and <i>OsVP</i>1 Coordinately Regulate Preharvest Sprouting Tolerance in Red Pericarp Rice
Bibliographic record
Abstract
Red pericarp associates with seed dormancy or preharvest sprouting (PHS) tolerance in crops. To identify this association’s molecular mechanism, a PHS mutant Osviviparous1 ( Osvp1 ) was characterized in rice and crossed with Kasalath, a red pericarp cultivar with Rc ( red coleoptiles ) genotype. Among the dehulled seeds of F 2 progenies, RcRcvp1vp1 seeds performed a lower PHS rate than rcrcvp1vp1 seeds and showed shallower pigmentation than RcRcVP1VP1 seeds. Kasalath and SL9 (an RcRcVP1VP1 substitution line with Nipponbare background) showed more ABA sensitivity than the Nipponbare ( rcrcVP1VP1 ) by the germination assay, and the transcriptional abundance of ABA signal genes OsABI2, OsSnRK2, OsVP1, ABI5, and especially OsVP1 increased in the red pericarp line SL9. Moreover, OsVP1 can directly bind Rc (bHLH) promoter by yeast one-hybrid, which activates Rc and OsLAR expression in red pericarp rice. Furthermore, a luciferase complementation imaging assay showed that OsVP1 interacts with transcriptions factors Rc and OsC1. These results indicate that OsVP1 promotes proanthocyanidin accumulation through the interaction among OsVP1, Rc, and OsC1 and then increases the plant’s ABA sensitivity and PHS 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) | 0.001 | 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".