The effect of human GATA4 gene mutations on the activity of target gonadal promoters
Bibliographic record
Abstract
GATA transcription factors are crucial regulators of cell-specific gene expression in many tissues including the gonads. Although clinical cases of reproductive dysfunction have yet to be formally linked to GATA gene mutations, they have begun to be reported in other systems. Heterozygous GATA4 mutations have been associated with cases of congenital heart defects. Little is known, however, about the effect of these mutations on gonadal gene transcription. Since individuals carrying these mutations do not appear to suffer from gross reproductive defects, we hypothesized that this might be due to the differential transcriptional properties of the mutant proteins on heart versus gonadal target genes. Five mutations (S52F, E215D, G295S, V266M, and E359X) were recreated in the rat GATA4 protein. Several parameters were used to analyze the transcriptional properties of the mutants: activation of known gonadal target promoters (Star, Cyp19a1, and Inha), DNA binding, and interaction with GATA4 transcriptional partners. Three mutations (S52F, G295S, and E359X) reduced GATA4 transcriptional activity on the different gonadal promoters. With the exception of the G295S mutant, which showed a significant loss of DNA-binding affinity, the decrease in activity of the other GATA4 mutants was not associated with a change in DNA binding. All GATA4 mutants retained their ability to interact and cooperate with their major gonadal partners (NR5A1 and NR5A2) thereby compensating in part for the loss in intrinsic GATA4 transcriptional activity. Thus, unlike the heart, where the GATA4 mutations have deleterious effects, our data suggest that they would have a lesser impact on gonadal gene transcription and function.
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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 | 0.000 |
| 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".