Regulation of Maternal Transcript Destabilization During Egg Activation in Drosophila
Bibliographic record
Abstract
In animals, the transfer of developmental control from maternal RNAs and proteins to zygotically derived products occurs at the midblastula transition. This is accompanied by the destabilization of a subset of maternal transcripts. In Drosophila, maternal transcript destabilization occurs in the absence of fertilization and requires specific cis-acting instability elements. We show here that egg activation is necessary and sufficient to trigger transcript destabilization. We have identified 13 maternal-effect lethal loci that, when mutated, result in failure of maternal transcript degradation. All mutants identified are defective in one or more additional processes associated with egg activation. These include vitelline membrane reorganization, cortical microtubule depolymerization, translation of maternal mRNA, completion of meiosis, and chromosome condensation (the S-to-M transition) after meiosis. The least pleiotropic class of transcript destabilization mutants consists of three genes: pan gu, plutonium, and giant nuclei. These three genes regulate the S-to-M transition at the end of meiosis and are thought to be required for the maintenance of cyclin-dependent kinase (CDK) activity during this cell cycle transition. Consistent with a possible functional connection between this S-to-M transition and transcript destabilization, we show that in vitro-activated eggs, which exhibit aberrant postmeiotic chromosome condensation, fail to initiate transcript degradation. Several genetic tests exclude the possibility that reduction of CDK/cyclin complex activity per se is responsible for the failure to trigger transcript destabilization in these mutants. We propose that the trigger for transcript destabilization occurs coincidently with the S-to-M transition at the end of meiosis and that pan gu, plutonium, and giant nuclei regulate maternal transcript destabilization independent of their role in cell cycle regulation.
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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".