Functional Mapping of a Placenta-Specific Upstream Promoter for Human Gonadotropin-Releasing Hormone Receptor Gene<sup>1</sup>
Bibliographic record
Abstract
GnRH has been showed to regulate hCG expression and secretion from the placenta through a GnRH receptor (GnRHR)-mediated process. Recently, we have reported the isolation of human GnRHR full-length complementary DNA from the human placental cells including choriocarcinoma JEG-3 cells, immortalized extravillous trophoblasts, and primary cultures of trophoblasts. Despite these observations, the molecular mechanism that controls the transcription regulation of the GnRHR gene expression in the placenta remains unknown. Here we described the identification of an upstream placenta-specific promoter located between nucleotide (nt) -1737 and -1346 (relative to the translation start site) for the human GnRHR gene. Using transient transfection studies, this upstream promoter has been shown to determine the placental cell-specific expression of this gene. Primer extension studies further confirmed the utilization of this promoter in JEG-3 cells in vivo. By mutagenesis coupled to functional studies, we have identified four putative transcription factor-binding sites, namely human glucocorticoid receptor (hGR)-Oct-1 (nt -1718 to -1710), hGR-cAMP response element (CRE; nt -1649 to -1641), hGR-GATA (nt -1602 to -1597), and hGR-activating protein-1 (nt -1518 to -1511), that are essential to the expression of this gene. Mutations of these cis-acting motifs reduced the promoter activity. The CRE and GATA motifs were subsequently shown to be placenta specific, as mutations of these motifs caused a dramatic loss in promoter activities in the placental JEG-3 cells, but not in the ovarian carcinoma OVCAR-3, monkey kidney COS-1, and human embryonic kidney 293 cells. Gel mobility assays confirmed the binding of nuclear proteins Oct-1, CRE-binding protein, GATA-2, GATA-3, c-Fos, and c-Jun from JEG-3 cells to these four elements.
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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 | 0.001 |
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".