Vasa promotes <i>Drosophila</i> germline stem cell differentiation by activating <i>mei-P26</i> translation by directly interacting with a (U)-rich motif in its 3′ UTR
Bibliographic record
Abstract
Vasa (Vas) is a DEAD-box RNA-binding protein required in Drosophila at several steps of oogenesis and for primordial germ cell (PGC) specification. Vas associates with eukaryotic initiation factor 5B (eIF5B), and this interaction has been implicated in translational activation of gurken mRNA in the oocyte. Vas is expressed in all ovarian germline cells, and aspects of the vas-null phenotype suggest a function in regulating the balance between germline stem cells (GSCs) and their fate-restricted descendants. We used a biochemical approach to recover Vas-associated mRNAs and obtained mei-P26, whose product represses microRNA activity and promotes GSC differentiation. We found that vas and mei-P26 mutants interact, and that mei-P26 translation is substantially reduced in vas mutant cells. In vitro, Vas protein bound specifically to a (U)-rich motif in the mei-P26 3' untranslated region (UTR), and Vas-dependent regulation of GFP-mei-P26 transgenes in vivo was dependent on the same (U)-rich 3' UTR domain. The ability of Vas to activate mei-P26 expression in vivo was abrogated by a mutation that greatly reduces its interaction with eIF5B. Taken together, our data support the conclusion that Vas promotes germ cell differentiation by directly activating mei-P26 translation in early-stage committed cells.
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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) | 0.001 | 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".