Sugarcane microRNA shy-miR164 regulates sugar metabolism through direct cleavage of the transcription factor <i>ScNAC</i> mRNA
Bibliographic record
Abstract
High sugar content is the primary objective in sugarcane (Saccharum spp. hybrids) breeding. Plant microRNA 164 (miR164) plays pivotal roles in plant development and stress responses through the post-transcriptional regulation of its target genes. NAC transcription factors play a crucial role in various plant physiological processes. However, their role in sugar metabolism remains uncharacterized. Our previous work revealed the potential role of the shy-miR164 and a sugarcane NAC transcription factor (ScNAC) in sugar metabolism based on multiomics analysis. In this study, shy-miR164 and ScNAC exhibited an inverse regulatory relationship in sugarcane. Subsequent RLM-RACE and dual-luciferase assays confirmed that shy-miR164 regulates ScNAC expression through direct cleavage of its mRNA. Knockdown of miR164 using short tandem target mimic technology significantly enhanced sugar content in tomato (Solanum lycopersicum L.) fruits, whereas the opposite effect was observed in miR164-overexpressing plants, indicating its involvement in sugar metabolism. Furthermore, heterologous expression of ScNAC in tomato also enhanced fruit sugar content. Taken together, these findings reveal a previously unexplored role of shy-miR164 in sugar metabolism through the direct cleavage of its target gene ScNAC. This work advances our understanding of the mechanisms underlying sugar metabolism and provides candidate targets for improved sugar production in sugarcane through biotechnology.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".