Proteasomal Activity Is Required to Initiate and to Sustain Translational Activation of Messenger RNA Encoding the Stem-Loop-Binding Protein During Meiotic Maturation in Mice1
Bibliographic record
Abstract
Developmentally regulated translation plays a key role in controlling gene expression during oogenesis. In particular, numerous mRNA species are translationally repressed in growing oocytes and become translationally activated during meiotic maturation. While many studies have focused on a U-rich sequence, termed the cytoplasmic polyadenylation element (CPE), located in the 3'-untranslated region (UTR) and the CPE-binding protein (CPEB) 1, multiple mechanisms likely contribute to translational control in oocytes. The stem-loop-binding protein (SLBP) is expressed in growing oocytes, where it is required for the accumulation of nonpolyadenylated histone mRNAs, and then accumulates substantially during meiotic maturation. We report that, in immature oocytes, Slbp mRNA carries a short poly(A) tail, and is weakly translated, and that a CPE-like sequence in the 3'-UTR is required to maintain this low activity. During maturation, Slbp mRNA becomes polyadenylated and translationally activated. Unexpectedly, proteasomal activity is required both to initiate and to sustain translational activation. This proteasomal activity is not required for the polyadenylation of Slbp mRNA during early maturation; however, it is required for a subsequent deadenylation of the mRNA that occurs during late maturation. Moreover, although CPEB1 is degraded during maturation, inhibiting its degradation by blocking mitogen-activated protein kinase 1/3 activity does not prevent the accumulation of SLBP, indicating that CPEB1 is not the protein whose degradation is required for translational activation of Slbp mRNA. These results identify a new role for proteasomal activity in initiating and sustaining translational activation during meiotic maturation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".