Faculty Opinions recommendation of Translation readthrough mitigation.
Bibliographic record
Abstract
A fraction of ribosomes engaged in translation will fail to terminate when reaching a stop codon, yielding nascent proteins inappropriately extended on their C-termini.Although such extended proteins can interfere with normal cellular processes, known mechanisms of translational surveillance are insufficient to protect cells from potential dominant consequences.Through a combination of transgenics and CRISPR/Cas9 gene editing in C. elegans, we demonstrate a consistent ability of cells to block accumulation of C-terminal extended proteins that result from failure to terminate at stop codons.3'UTR-encoded sequences were sufficient to lower protein levels.Measurements of mRNA levels and translation suggested a co-or post-translational mechanism of action for these sequences in C. elegans.Similar mechanisms evidently operate in human cells, where we observed a comparable tendency for translated human 3'UTR sequences to reduce mature protein expression in tissue culture assays, including 3' sequences from the hypomorphic "Constant Spring" hemoglobin stop codon variant.We suggest 3'UTRs may encode peptide sequences that destabilize the attached protein, providing mitigation of unwelcome and varied translation errors.Failure of translation termination to occur at a stop codon can lead to ribosomes translating into a 3'UTR.In some cases translation may proceed through the 3'UTR and into the poly(A) tail, triggering a process termed "nonstop" decay and destabilizing both the mRNA and nascent protein (reviewed in 1 ).However, for a majority of 3'UTRs a stop codon is encountered prior to the poly(A) tail 2,3 .Readthrough events that encounter a subsequent termination codon are outside the scope of known translational surveillance pathways including nonstop 1 .Depending on the 3'UTR and the frame in which the ribosome enters, the late stop codon can be several, tens, or even hundreds of codons into a 3'UTR, producing variant proteins with potentially problematic C-terminal appendages.This issue is
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.155 | 0.151 |
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".