RNA surveillance by uridylation-dependent RNA decay in<i>Schizosaccharomyces pombe</i>
Bibliographic record
Abstract
Uridylation-dependent RNA decay is a widespread eukaryotic pathway modulating RNA homeostasis. Terminal uridylyltransferases (Tutases) add untemplated uridyl residues to RNA 3'-ends, marking them for degradation by the U-specific exonuclease Dis3L2. In Schizosaccharomyces pombe, Cid1 uridylates a variety of RNAs. In this study, we investigate the prevalence and impact of uridylation-dependent RNA decay in S. pombe by transcriptionally profiling cid1 and dis3L2 deletion strains. We found that the exonuclease Dis3L2 represents a bottleneck in uridylation-dependent mRNA decay, whereas Cid1 plays a redundant role that can be complemented by other Tutases. Deletion of dis3L2 elicits a cellular stress response, upregulating transcription of genes involved in protein folding and degradation. Misfolded proteins accumulate in both deletion strains, yet only trigger a strong stress response in dis3L2 deficient cells. While a deletion of cid1 increases sensitivity to protein misfolding stress, a dis3L2 deletion showed no increased sensitivity or was even protective. We furthermore show that uridylyl- and adenylyltransferases cooperate to generate a 5'-NxAUUAAAA-3' RNA motif on dak2 mRNA. Our studies elucidate the role of uridylation-dependent RNA decay as part of a global mRNA surveillance, and we found that perturbation of this pathway leads to the accumulation of misfolded proteins and elicits cellular stress responses.
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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".