RsMYB8-RsMYB73 module positively regulates parthenocarpic fruitsetting via elevating <i>RsGA3ox9</i> expression in seedless chestnut rose ( <i>Rosa sterilis</i> )
Bibliographic record
Abstract
Abstract Fruit growth and development are generally initiated following successful pollination and fertilization. Seedless chestnut rose (Rosa sterilis), an elite promising fruit tree for both edible and medicinal purposes due to the extremely high vitamin C and superior quality, exhibits a naturally parthenocarpic character, however the underlying mechanism has been still unclear so far. Currently, gibberellins (GAs) were justified as the key hormone for parthenocarpy induction in seedless chestnut rose by endogenous hormone analysis and exogenous plant growth regulator (PGR) application. In total, 43 members of the GA oxidase gene family (RsGAoxs) were systematically identified and characterized based on genome-wide analysis of seedless chestnut rose. On the basis of transcriptomic analysis, overexpression experiments in tomato, as well as virus-induced gene silencing (VIGS) assay in seedless chestnut rose, RsGA3ox9 was substantially justified to be involved in the parthenocarpic fruitsetting of this species. Transcription factors RsMYB3, RsMYB8, and RsMYB73 were proven to positively regulate the expression of RsGA3ox9. Further, yeast two-hybrid (Y2H) and luciferase complementation assay illuminated that RsMYB8 and RsMYB73 may interact, leading to upregulating RsGA3ox9. Thereby, RsGA3ox9 substantially regulates parthenocarpy of seedless chestnut rose, and RsMYB8-RsMYB73 complex promotes parthenocarpic fruitsetting by upregulating RsGA3ox9, which may facilitate the seedless fruit breeding in chestnut rose (Rosa roxburghii Tratt.), as well as provide novel insights for better understanding the mechanism underlying the parthenocarpic fruitsetting in fruit species.
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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) | 0.002 | 0.001 |
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".