Distinct roles of androgen receptor, estrogen receptor alpha, and BCL6 in the establishment of sex-biased DNA methylation in mouse liver
Bibliographic record
Abstract
Sexual dimorphism in gene regulation, including DNA methylation, is the main driver of sexual dimorphism in phenotypes. However, the questions of how and when sex shapes DNA methylation remain unresolved. Recently, using mice with different combinations of genetic and phenotypic sex, we identified sex-associated differentially methylated regions (sDMRs) that depended on the sex phenotype. Focusing on a panel of validated sex-phenotype dependent male- and female-biased sDMRs, we tested the developmental dynamics of sex bias in liver methylation and the impacts of mutations in the androgen receptor, estrogen receptor alpha, or the transcriptional repressor Bcl6 gene. True hermaphrodites that carry both unilateral ovaries and contralateral testes were also tested. Our data show that sex bias in methylation either coincides with or follows sex bias in the expression of sDMR-proximal genes, suggesting that sex bias in gene expression may be required for demethylation at certain sDMRs. Global ablation of AR, ESR1, or a liver-specific loss of BCL6, all alter sDMR methylation, whereas presence of both an ovary and a testis delays the establishment of male-type methylation levels in hermaphrodites. Moreover, the Bcl6-LKO shows dissociation between expression and methylation, suggesting a distinct role of BCL6 in demethylation of intragenic sDMRs.
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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 | 0.001 | 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".