The eIF4E-Binding Protein Eap1p Functions in Vts1p-Mediated Transcript Decay
Bibliographic record
Abstract
Sequence-specific RNA binding proteins can induce the degradation of mRNAs through their ability to recruit proteins that trigger transcript destabilization. For example, Vts1p, the S. cerevisiae member of the Smaug family of RNA binding proteins, is thought to induce transcript decay by recruiting the Ccr4p-Pop2p-Not deadenylase complex to target mRNAs. The resulting deadenylation triggers transcript decapping followed by 5'-to-3' exonucleolytic decay. Here we show that the eIF4E-binding protein, Eap1p, is required for efficient degradation of Vts1p target transcripts and that this role involves the ability of Eap1p to interact with eIF4E. Eap1p does not stimulate deadenylation of Vts1p target transcripts but is instead involved in decapping. Eap1p interacts with Vts1p and mediates an indirect interaction between Vts1p and eIF4E. Taken together these data suggest a model whereby the interaction of Vts1p with Eap1p at target mRNAs stimulates decapping.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".