Sex Chromosomes and Sex Phenotype Contribute to Biased DNA Methylation in Mouse Liver
Bibliographic record
Abstract
Sex biases in the genome-wide distribution of DNA methylation and gene expression levels are some of the manifestations of sexual dimorphism in mammals. To advance our understanding of the mechanisms that contribute to sex biases in DNA methylation and gene expression, we conducted whole genome bisulfite sequencing (WGBS) as well as RNA-seq on liver samples from mice with different combinations of sex phenotype and sex-chromosome complement. We compared groups of animals with different sex phenotypes, but the same genetic sexes, and vice versa, same sex phenotypes, but different sex-chromosome complements. We also compared sex-biased DNA methylation in mouse and human livers. Our data show that sex phenotype, X-chromosome dosage, and the presence of Y chromosome shape the differences in DNA methylation between males and females. We also demonstrate that sex bias in autosomal methylation is associated with sex bias in gene expression, whereas X-chromosome dosage-dependent methylation differences are not, as expected for a dosage-compensation mechanism. Furthermore, we find partial conservation between the repertoires of mouse and human genes that are associated with sex-biased methylation, an indication that gene function is likely to be an important factor in this phenomenon.
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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".