Genetic variation in the Y chromosome and sex-biased DNA methylation in somatic cells in the mouse
Bibliographic record
Abstract
Several lines of evidence suggest that the presence of the Y chromosome influences DNA methylation of autosomal loci. To better understand the impact of the Y chromosome on autosomal DNA methylation patterns and its contribution to sex bias in methylation, we identified Y chromosome dependent differentially methylated regions (yDMRs) using whole-genome bisulfite sequencing methylation data from livers of mice with different combinations of sex-chromosome complement and gonadal sex. Nearly 90% of the autosomal yDMRs mapped to transposable elements (TEs) and most of them had lower methylation in XY compared to XX or XO mice. Follow-up analyses of four reporter autosomal yDMRs showed that Y-dependent methylation levels were consistent across most somatic tissues but varied in strains with different origins of the Y chromosome, suggesting that genetic variation in the Y chromosome influenced methylation levels of autosomal regions. Mice lacking the q-arm of the Y chromosome (B6.NPYq-2) as well as mice with a loss-of-function mutation in Kdm5d showed no differences in methylation levels compared to wild type mice. In conclusion, the Y-linked modifier of TE methylation is likely to reside on the short arm of Y chromosome and further studies are required to identify this gene.
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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 | 0.001 | 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".