RDR1 and SGS3, Components of RNA-Mediated Gene Silencing, Are Required for the Regulation of Cuticular Wax Biosynthesis in Developing Inflorescence Stems of Arabidopsis
Bibliographic record
Abstract
The cuticle is a protective layer that coats the primary aerial surfaces of land plants and mediates plant interactions with the environment. It is synthesized by epidermal cells and is composed of a cutin polyester matrix that is embedded and covered with cuticular waxes. Recently, we have discovered a novel regulatory mechanism of cuticular wax biosynthesis that involves the ECERIFERUM7 (CER7) ribonuclease, a core subunit of the exosome. We hypothesized that at the onset of wax production, the CER7 ribonuclease degrades an mRNA specifying a repressor of CER3, a wax biosynthetic gene whose protein product is required for wax formation via the decarbonylation pathway. In the absence of this repressor, CER3 is expressed, leading to wax production. To identify the putative repressor of CER3 and to unravel the mechanism of CER7-mediated regulation of wax production, we performed a screen for suppressors of the cer7 mutant. Our screen resulted in the isolation of components of the RNA-silencing machinery, RNA-DEPENDENT RNA POLYMERASE1 and SUPPRESSOR OF GENE SILENCING3, implicating RNA silencing in the control of cuticular wax deposition during inflorescence stem development in Arabidopsis (Arabidopsis thaliana).
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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".