Transcription factor GATA2 may potentiate follicle-stimulating hormone production in mice via induction of the BMP antagonist gremlin in gonadotrope cells
Bibliographic record
Abstract
Mammalian reproduction depends on the gonadotropins, follicle-stimulating hormone (FSH), and luteinizing hormone, which are secreted by pituitary gonadotrope cells. The zinc-finger transcription factor GATA2 was previously implicated in FSH production in male mice; however, its mechanisms of action and role in females were not determined. To directly address GATA2 function in gonadotropes, we generated and analyzed gonadotrope-specific Gata2 KO mice using the Cre-lox system. We found that while conditional KO (cKO) males exhibited ∼50% reductions in serum FSH levels and pituitary FSHβ subunit (Fshb) expression relative to controls, FSH production was apparently normal in cKO females. In addition, RNA-seq analysis of purified gonadotropes from control and cKO males revealed a profound decrease in expression of gremlin (Grem1), a bone morphogenetic protein (BMP) antagonist. We show Grem1 was expressed in gonadotropes, but not other cell lineages, in the adult male mouse pituitary. Furthermore, Gata2, Grem1, and Fshb mRNA levels were significantly higher in the pituitaries of WT males relative to females but decreased in males treated with estradiol and increased following ovariectomy in control but not cKO females. Finally, we found that recombinant gremlin stimulated Fshb expression in pituitary cultures from WT mice. Collectively, the data suggest that GATA2 promotes Grem1 expression in gonadotropes and that the gremlin protein potentiates FSH production. The mechanisms of gremlin action have not yet been established but may involve attenuation of BMP binding to activin type II receptors in gonadotropes, facilitating induction of Fshb transcription by activins or related ligands.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".