DRN and TRAMP degrade specific and overlapping aberrant mRNAs formed at various stages of mRNP biogenesis in<i>Saccharomyces cerevisiae</i>
Bibliographic record
Abstract
In Saccharomyces cerevisiae, nuclear exosome along with TRAMP and DRN selectively eliminates diverse aberrant messages. These decay apparatuses appear to operate as independent mechanisms in the nucleus. Here, using genetic and molecular approach we systematically investigate the functional relationship between exosome, TRAMP and DRN mechanisms by examining their relative contributions in the degradation of diverse classes of aberrant nuclear mRNAs generated at various phases of mRNP biogenesis. Our findings suggest that nuclear exosome in association with the TRAMP complex exclusively degrades the transcription assembly-defective mRNPs and splice-defective intron-containing pre-mRNAs, whereas nuclear exosome along with DRN solely degrades the export-defective messages. The degradation of aberrant read-through transcripts with 3′-extensions, in contrast, requires the activity of TRAMP and DRN together along with nuclear exosome function. Thus, the profile of substrate specificity of these nuclear decay machines reflects dependency of the nuclear exosome for either TRAMP or DRN function to degrade distinct nuclear mRNAs. We propose that DRN apparatus may act as a novel ancillary factor required for the nuclear exosome function to degrade specific classes of aberrant messages.
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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) | 0.000 | 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".