The MabZIP5–MaMYB69 module cooperates with MaERF55 to modulate banana fruit ripening via cell wall degradation
Bibliographic record
Abstract
Abstract The MYB protein family comprises numerous transcription factors with important functions in various biological processes in plants; however, their role in modulating banana fruit ripening has been rarely investigated. In this study, we identified an R2R3-type MYB gene, MaMYB69, which promotes fruit ripening by directly modulating cell wall degradation. The expression of MaMYB69, which encodes a nucleus-localized transcription activator, was induced by ethylene and upregulated during banana ripening. MaMYB69 activated the expression of MaPE, MaPL1, MaGAL, and MaPG3 by directly targeting their promoters. MaMYB69 overexpression in tomato and banana accelerated fruit ripening and stimulated cell wall-modifying gene expression. Moreover, MaMYB69 interacted with MaERF55 and strengthened its transactivation activity through downstream target genes. MabZIP5, an aroma biosynthesis regulator, acted directly upstream of MaMYB69, enhancing its transcription. MaMYB69 also formed a homodimer with itself and activated its expression. Collectively, our results show that MaMYB69 is pivotal in controlling banana ripening and softening and improve our understanding of the regulatory cascades involved in fruit ripening. MaMYB69 may serve as a potential target for improving fruit quality and extending the shelf life.
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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".