GATA4 and GATA6 Silencing in Ovarian Granulosa Cells Affects Levels of mRNAs Involved in Steroidogenesis, Extracellular Structure Organization, IGF-I Activity, and Apoptosis
Bibliographic record
Abstract
Knockdown of the transcription factors GATA4 and GATA6 in granulosa cells (GCs) impairs folliculogenesis and induces infertility. To investigate the pathways and genes regulated by these factors, we performed microarray analyses on wild-type GCs or GCs lacking GATA4, GATA6, or GATA4/6 (G4(gcko), G6(gcko), and G4/6(gcko)) after in vivo treatment with equine chorionic gonadotropin. GATA4 deletion affected a greater number of genes than GATA6, which correlates with the subfertility observed in G4(gcko) mice and the normal reproductive function found in G6(gcko) animals. An even greater number of genes were affected by the deletion of both factors. Moreover, the expression of FSH receptor, LH receptor, inhibin α and β, versican, pregnancy-associated plasma protein A, and the regulatory unit 2b of protein kinase A, which are known to be crucial for ovarian function, was greatly affected in double GATA4 and GATA6 knockouts when compared with single GATA-deficient animals. This suggests that GATA4 and GATA6 functionally compensate for each other in the regulation of key ovarian genes. Functional enrichment revealed that ovulation, growth, intracellular signaling, extracellular structure organization, gonadotropin and growth factor actions, and steroidogenesis were significantly regulated in G4/6(gcko) mice. The results of this analysis were confirmed using quantitative polymerase chain reaction, immunohistochemical, and biological assays. Treatment of GCs with cAMP/IGF-I, to bypass FSH and IGF-I signaling defects, revealed that most of the affected genes are direct targets of GATA4/6. The diversity of pathways affected by the knockdown of GATA underscores the important role of these factors in the regulation of GC function.
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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) | 0.000 | 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".