Chromosome-wide DNA methylation analysis predicts human tissue-specific X inactivation
Bibliographic record
Abstract
X-chromosome inactivation (XCI) results in the differential marking of the active and inactive X with epigenetic modifications including DNA methylation. Consistent with the previous studies showing that CpG island-containing promoters of genes subject to XCI are approximately 50% methylated in females and unmethylated in males while genes which escape XCI are unmethylated in both sexes; our chromosome-wide (Methylated DNA ImmunoPrecipitation) and promoter-targeted methylation analyses (Illumina Infinium HumanMethylation27 array) showed the largest methylation difference (D = 0.12, p < 2.2 E-16) between male and female blood at X-linked CpG islands promoters. We used the methylation differences between males and females to predict XCI statuses in blood and found that 81% had the same XCI status as previously determined using expression data. Most genes (83%) showed the same XCI status across tissues (blood, fetal: muscle, kidney and nerual); however, the methylation of a subset of genes predicted different XCI statuses in different tissues. Using previously published expression data the effect of transcription on gene-body methylation was investigated and while X-linked introns of highly expressed genes were more methylated than the introns of lowly expressed genes, exonic methylation did not differ based on expression level. We conclude that the XCI status predicted using methylation of X-linked promoters with CpG islands was usually the same as determined by expression analysis and that 12% of X-linked genes examined show tissue-specific XCI whereby a gene has a different XCI status in at least one of the four tissues examined.
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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 | 0.001 |
| 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".