Faculty Opinions recommendation of CUP promotes deadenylation and inhibits decapping of mRNA targets.
Bibliographic record
Abstract
CUP is an eIF4E-binding protein (4E-BP) that represses the expression of specific maternal mRNAs prior to their posterior localization. Here, we show that CUP employs multiple mechanisms to repress the expression of target mRNAs. In addition to inducing translational repression, CUP maintains mRNA targets in a repressed state by promoting their deadenylation and protects deadenylated mRNAs from further degradation. Translational repression and deadenylation are independent of eIF4E binding and require both the middle and C-terminal regions of CUP, which collectively we termed the effector domain. This domain associates with the deadenylase complex CAF1-CCR4-NOT and decapping activators. Accordingly, in isolation, the effector domain is a potent trigger of mRNA degradation and promotes deadenylation, decapping and decay. However, in the context of the full-length CUP protein, the decapping and decay mediated by the effector domain are inhibited, and target mRNAs are maintained in a deadenylated, repressed form. Remarkably, an N-terminal regulatory domain containing a noncanonical eIF4E-binding motif is required to protect CUP-associated mRNAs from decapping and further degradation, suggesting that this domain counteracts the activity of the effector domain. Our findings indicate that the mode of action of CUP is more complex than previously thought and provide mechanistic insight into the regulation of mRNA expression by 4E-BPs. PMID: 21937713
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.219 | 0.124 |
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".