<i>In vivo</i> mapping of the functional regions of the DEAD-box helicase Vasa
Bibliographic record
Abstract
The maternally expressed Drosophila melanogaster DEAD-box helicase Vasa (Vas) is necessary for many cellular and developmental processes, including specification of primordial germ cells (pole cells), posterior patterning of the embryo, piRNA-mediated repression of transposon-encoded mRNAs, translational activation of gurken (grk) mRNA, and completion of oogenesis itself. Vas protein accumulates in the perinuclear nuage in nurse cells soon after their specification, and then at stage 10 Vas translocates to the posterior pole plasm of the oocyte. We produced a series of transgenic constructs encoding eGFP-Vas proteins carrying mutations affecting different regions of the protein, and analyzed in vivo which Vas functions each could support. We identified novel domains in the N- and C-terminal regions of the protein that are essential for localization, transposon repression, posterior patterning, and pole cell specification. One such functional region, the most C-terminal seven amino acids, is specific to Vas orthologues and is thus critical to distinguishing Vas from other closely related DEAD-box helicases. Surprisingly, we also found that many eGFP-Vas proteins carrying mutations that would be expected to abrogate DEAD-box helicase function localized to the nuage and posterior pole, and retained the capacity to support oogenesis, although they did not function in embryonic patterning, pole cell specification, grk activation, or transposon repression. We conclude from these experiments that Vas, a multifunctional protein, uses different domains and different molecular associations to carry out its various cellular and developmental roles.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".