A Short Promoter Region Containing Conserved Regulatory Motifs Is Required for Steroidogenic Acute Regulatory Protein (Star) Gene Expression in the Mouse Testis
Bibliographic record
Abstract
In the testis, Leydig cells produce steroid hormones that are needed to masculinize typical genetic males during fetal development and to initiate and maintain spermatogenesis at puberty and adulthood, respectively. Steroidogenesis is initiated by the transfer of cholesterol from the outer to the inner mitochondrial membrane through the action of steroidogenic acute regulatory protein (STAR). Given its importance for the steroidogenic process, the regulation of STAR gene expression has been the subject of numerous studies. These studies have involved the characterization of key promoter sequences through the identification of relevant transcription factors and the nucleotide motifs (regulatory elements) that they bind. This work has traditionally relied on in vitro studies carried out in cell cultures along with reconstructed promoter sequences. While this approach has been useful for developing models of how a gene might be transcriptionally regulated, one must ultimately validate that these modes of regulation occur in an endogenous context. We have used CRISPR/Cas9 genome editing to modify a short region of the mouse Star promoter (containing a subset of regulatory elements, including conserved CRE, C/EBP, AP1, and GATA motifs) that has been proposed to be critical for Star transcription. Analysis of the resultant mutant mice showed that this short promoter region is indeed required for maximal STAR mRNA and protein levels in the testis. Analysis also showed that both basal and hormone-activated testosterone production in mature mice was unaffected despite significant changes in Star expression. Our results therefore provide the first in vivo validation of regulatory sequences required for Star gene expression.
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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 | 0.001 |
| 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".