The endonuclease Cue2 cleaves mRNAs at stalled ribosomes during No Go Decay
Bibliographic record
Abstract
Abstract Translation of problematic sequences in mRNAs leads to ribosome collisions that trigger a sequence of quality control events including ribosome rescue, degradation of the stalled nascent polypeptide via the Ribosome-mediated Quality control Complex (RQC), and targeting of the mRNA for decay (No Go Decay or NGD). Previous studies provide strong evidence for the existence of an endonuclease involved in the process of NGD though the identity of the endonuclease and the extent to which it contributes to mRNA decay remain unknown. Using a reverse genetic screen in yeast, we identify Cue2 as the conserved endonuclease that is recruited to stalled ribosomes to promote NGD. Ribosome profiling and biochemistry provide strong evidence that Cue2 cleaves mRNA within the A site of the colliding ribosome. Finally, we show that NGD primarily proceeds via Xrn1-mediated exonucleolytic decay. Cue2-mediated endonucleolytic decay normally constitutes a secondary decay pathway, but becomes a major contributor in cells depleted of factors required for the resolution of stalled ribosome complexes (the RQT factors including Slh1). Together these results provide insights into how multiple decay processes converge to process problematic mRNAs in eukaryotic cells. One Sentence Summary Cue2 is the endonuclease that cleaves mRNA at ribosome stall sites.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".