FSH Regulates YAP-TEAD Transcriptional Activity in Bovine Granulosa Cells to Allow the Future Dominant Follicle to Exert Its Augmented Estrogenic Capacity
Bibliographic record
Abstract
The molecular mechanisms that drive the granulosa cells’ (GC) differentiation into a more estrogenic phenotype during follicular divergence and establishment of follicle dominance have not been completely elucidated. The main Hippo signaling effector, YAP, has, however, emerged as a potential key player to explain such complex processes. Studies using rat and bovine GC demonstrate that, in conditions where the expression of the classic YAP-TEAD target gene tissue growth factor (CTGF) is augmented, CYP19A1 expression and activity and, consequently, estradiol (E2) secretion are reduced. These findings led us to hypothesize that, during ovarian follicular divergence in cattle, FSH downregulates YAP-TEAD-dependent transcriptional activity in GC to allow the future dominant follicle to exert its augmented estrogenic capacity. To address this, we performed a series of experiments employing distinct bovine models. Our in vitro and ex vivo experiments indicated that indeed FSH downregulates, in a concentration-dependent manner, mRNA levels not only for CTGF but also for the other classic YAP-TEAD transcriptional target genes ANKRD1 and CYR61 by a mechanism that involves increased YAP phosphorylation. To better elucidate the functional importance of such FSH-induced YAP activity regulation, we then cultured GC in the presence of verteporfin (VP) or peptide 17 (P17), two pharmacological inhibitors known to interfere with YAP binding to TEADs. The results showed that both VP and P17 increased CYP19A1 basal mRNA levels in a concentration-dependent manner. Most interestingly, by using GC samples obtained in vivo from dominant vs. subordinate follicles, we found that mRNA levels for CTGF, CYR61, and ANKRD1 are higher in subordinate follicles following the follicular divergence. Taken together, our novel results demonstrate that YAP transcriptional activity is regulated in bovine granulosa cells to allow the increased estrogenic capacity of the selected dominant follicle.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".