A novel approach identifies new differentially methylated regions (DMRs) associated with imprinted genes
Bibliographic record
Abstract
Imprinted genes are critical for normal human growth and neurodevelopment. They are characterized by differentially methylated regions (DMRs) of DNA that confer parent of origin-specific transcription. We developed a new strategy to identify imprinted gene-associated DMRs. Using genome-wide methylation profiling of sodium bisulfite modified DNA from normal human tissues of biparental origin, candidate DMRs were identified by selecting CpGs with methylation levels consistent with putative allelic differential methylation. In parallel, the methylation profiles of tissues of uniparental origin, i.e., paternally-derived androgenetic complete hydatidiform moles (AnCHMs), and maternally-derived mature cystic ovarian teratoma (MCT), were examined and then used to identify CpGs with parent of origin-specific DNA methylation. With this approach, we found known DMRs associated with imprinted genomic regions as well as new DMRs for known imprinted genes, NAP1L5 and ZNF597, and novel candidate imprinted genes. The paternally methylated DMR for one candidate, AXL, a receptor tyrosine kinase, was also validated in experiments with mouse embryos that demonstrated Axl was expressed preferentially from the maternal allele in a DNA methylation-dependent manner.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".