CNOT6 regulates a novel pattern of mRNA deadenylation during oocyte meiotic maturation
Bibliographic record
Abstract
In many cell types, the length of the poly(A) tail of an mRNA is closely linked to its fate - a long tail is associated with active translation, a short tail with silencing and degradation. During mammalian oocyte development, two contrasting patterns of polyadenylation have been identified. Some mRNAs carry a long poly(A) tail during the growth stage and are actively translated, then become deadenylated and down-regulated during the subsequent stage, termed meiotic maturation. Other mRNAs carry a short tail poly(A) tail and are translationally repressed during growth, and their poly(A) tail lengthens and they become translationally activated during maturation. As well, a program of elimination of this 'maternal' mRNA is initiated during oocyte maturation. Here we describe a third pattern of polyadenylation: mRNAs are deadenylated in growing oocytes, become polyadenylated during early maturation and then deadenylated during late maturation. We show that the deadenylase, CNOT6, is present in cortical foci of oocytes and regulates deadenylation of these mRNAs, and that PUF-binding elements (PBEs) regulate deadenylation in mature oocytes. Unexpectedly, maintaining a long poly(A) tail neither enhances translation nor inhibits degradation of these mRNAs. Our findings implicate multiple machineries, more complex than previously thought, in regulating mRNA activity in oocytes.
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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 | 0.000 | 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) | 0.001 | 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".