Characterization of a New Upstream GnRH Receptor Promoter in Human Ovarian Granulosa-Luteal Cells
Bibliographic record
Abstract
GnRH has been implicated as an important local autocrine and paracrine factor in regulating ovarian function. However, to date, the transcriptional regulation of GnRH receptor (GnRHR) gene in human ovary remains poorly understood. Here we report the characterization of a new upstream promoter for the GnRHR gene in human granulosa-luteal cells. Using progressive deletion analysis, a region between nucleotide -1300 and -1018 (relative to the translation start site) was shown to exhibit the highest promoter activities in two immortalized human granulosa-luteal cell lines, SVOG-4o and SVOG-4m. Two putative CCAAT/enhancer binding protein (C/EBP) motifs and one GATA motif were identified within this region. Mutational studies showed that these three motifs cooperated synergistically to regulate GnRHR gene transcription in the granulosa cells but not in other cell types including human ovarian carcinoma OVCAR-3, human embryonic kidney-293 (HEK-293) and mouse pituitary gonadotrope-derived alphaT3-1 cells. Surprisingly, by competitive EMSAs, we found that an Oct-1 consensus sequence was able to inhibit protein complex formation with the distal C/EBP motif, suggesting a possible cross-talk between the Oct-1 transcription factor and this C/EBP motif. Taken together, our results strongly indicate a role of the C/EBP and GATA motifs in regulating GnRHR gene transcription in human granulosa-luteal cells and further suggest that tissue-specific expression of human GnRHR gene is mediated by differential promoter usage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 teacher head, 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".