Regulation of <i>Drosophila</i> Vasa <i>In Vivo</i> through Paralogous Cullin-RING E3 Ligase Specificity Receptors
Bibliographic record
Abstract
In Drosophila species, molecular asymmetries guiding embryonic development are established maternally. Vasa, a DEAD-box RNA helicase, accumulates in the posterior pole plasm, where it is required for embryonic germ cell specification. Maintenance of Vasa at the posterior pole requires the deubiquitinating enzyme Fat facets, which protects Vasa from degradation. Here, we found that Gustavus (Gus) and Fsn, two ubiquitin Cullin-RING E3 ligase specificity receptors, bind to the same motif on Vasa through their paralogous B30.2/SPRY domains. Both Gus and Fsn accumulate in the pole plasm in a Vasa-dependent manner. Posterior Vasa accumulation is precocious in Fsn mutant oocytes; Fsn overexpression reduces ovarian Vasa levels, and embryos from Fsn-overexpressing females form fewer primordial germ cells (PGCs); thus, Fsn destabilizes Vasa. In contrast, endogenous Gus may promote Vasa activity in the pole plasm, as gus females produce embryos with fewer PGCs, and posterior accumulation of Vas is delayed in gus mutant oocytes that also lack one copy of cullin-5. We propose that Fsn- and Gus-containing E3 ligase complexes contribute to establishing a fine-tuned steady state of Vasa ubiquitination that influences the kinetics of posterior Vasa deployment.
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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 | 0.001 | 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".