GATA4 knockdown in MA-10 Leydig cells identifies multiple target genes in the steroidogenic pathway
Bibliographic record
Abstract
GATA4 is an essential transcription factor required for the initiation of genital ridge formation, for normal testicular and ovarian differentiation at the time of sex determination, and for male and female fertility in adulthood. In spite of its crucial roles, the genes and/or gene networks that are ultimately regulated by GATA4 in gonadal tissues remain to be fully understood. This is particularly true for the steroidogenic lineages such as Leydig cells of the testis where many in vitro (promoter) studies have provided good circumstantial evidence that GATA4 is a key regulator of Leydig cell gene expression and steroidogenesis, but formal proof is still lacking. We therefore performed a microarray screening analysis of MA-10 Leydig cells in which Gata4 expression was knocked down using an siRNA strategy. Analysis identified several GATA4-regulated pathways including cholesterol synthesis, cholesterol transport, and especially steroidogenesis. A decrease in GATA4 protein was associated with decreased expression of steroidogenic genes previously suspected to be GATA4 targets such as Cyp11a1 and Star. Gata4 knockdown also led to an important decrease in other novel steroidogenic targets including Srd5a1, Gsta3, Hsd3b1, and Hsd3b6, as well as genes known to participate in cholesterol metabolism such as Scarb1, Ldlr, Soat1, Scap, and Cyp51. Consistent with the decreased expression of these genes, a reduction in GATA4 protein compromised the ability of MA-10 cells to produce steroids both basally and under hormone stimulation. These data therefore provide strong evidence that GATA4 is an essential transcription factor that sits atop of the Leydig cell steroidogenic program.
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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".