Genetic screens identify connections between ribosome recycling and nonsense mediated decay
Bibliographic record
Abstract
Abstract The decay of messenger RNA with a premature termination codon (PTC) by nonsense mediated decay (NMD) is an important regulatory pathway for eukaryotes and an essential pathway in mammals. NMD is typically triggered by the ribosome terminating at a stop codon that is aberrantly distant from the poly-A tail. Here, we use a fluorescence screen to identify factors involved in NMD in S. cerevisiae . In addition to the known NMD factors, including the entire UPF family (UPF1, UPF2 and UPF3), as well as NMD4 and EBS1 , we identify factors known to function in post-termination recycling and characterize their contribution to NMD. We then use a series of modified reporter constructs that block both elongating and scanning ribosomes downstream of stop codons and demonstrate that a deficiency in recycling of 80S ribosomes or 40S subunits stabilizes NMD substrates. These observations in S. cerevisiae expand on recently reported data in mammals indicating that the 60S recycling factor ABCE1 is important for NMD (1, 2) by showing that increased activities of both elongating and scanning ribosomes (80S or 40S) in the 3’UTR correlate with a loss of NMD. Author Summary In this work, we aim to understand the mechanism of targeting mRNAs for decay via the long-studied nonsense mediated decay (NMD) pathway. We demonstrate that efficient large and small subunit ribosome recycling are necessary components of NMD. We go on to provide evidence that either scanning or actively translating ribosomes in the 3’UTR disrupt the decay of NMD targets. Our work highlights the importance of the composition of the 3’UTR in NMD signaling and emphasizes the need for this region to indeed be untranslated for NMD to occur. Exon junction complexes (EJCs) in the 3’UTR are known to induce NMD, however, in the budding yeast system used here, the NMD targets are EJC-free. Therefore, our data support a model in which factors other than EJCs may accumulate in the 3’UTR and provide a signal for NMD.
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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 | 0.001 | 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) | 0.002 | 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".