Regulation of murine follicle-stimulating hormone β subunit transcription by newly identified enhancers
Bibliographic record
Abstract
Abstract Activin-class ligands of the transforming growth factor β family induce follicle-stimulating hormone (FSH) production by pituitary gonadotrope cells in mice via the actions of the transcription factors SMAD3, SMAD4, and FOXL2, which bind to cis -elements in the FSHβ subunit ( Fshb ) promoter. An enhancer region for murine Fshb transcription was identified in vitro . However, deletion of the region using CRISPR-Cas9 did not affect FSH synthesis or secretion in mice. Using single-nucleus ATAC-seq of whole murine pituitaries, we identified three additional open chromatin regions upstream of Fshb exclusively in gonadotropes. These regions, as well as the Fshb gene, were fully or partially closed in gonadotropes of FSH-deficient mice with genetically or pharmacologically inactivated activin type II receptors. The initially characterized enhancer region did not significantly alter basal or activin-stimulated murine Fshb promoter-reporter activity in homologous LβT2 cells. In contrast, the other three open chromatin regions enhanced basal and activin A-stimulated Fshb promoter-reporter activity in LβT2 cells, with the two most distal showing the greatest effects. These two regions were open, exhibited enrichment of the enhancer mark H3K27ac, and were bound by SMAD2/3 and FOXL2 in response to activin A in LβT2 cells. The most distal enhancer exhibited strong FOXL2 and weak SMAD4 binding in gel shift assays. SMAD4, but not FOXL2, directly bound the other distal enhancer. Mutation of defined FOXL2 and SMAD4 cis -elements diminished enhancer activity in reporter assays in LβT2 cells. Collectively, the data indicate that there may be as many as four activin-sensitive enhancers upstream of murine Fshb .
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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".