Gene-specific timing and epigenetic memory in oocyte imprinting
Bibliographic record
Abstract
Imprinted genes are differentially marked during germ cell development to allow for their eventual parent-of-origin specific expression. A subset of imprinted genes becomes methylated during oocyte growth in both mouse and human. However the timing and mechanisms of methylation acquisition are unknown. Here, we examined the methylation of the Snrpn, Igf2r, Peg1 and Peg3 differentially methylated regions in postnatal growing mouse oocytes. Our findings indicate that methylation was acquired asynchronously at these different genes. Further analysis of Snrpn DMR1 revealed that parental alleles retain an epigenetic memory of their origin as the two alleles were recognized in a parental-specific manner in the absence of DNA methylation. In addition, we show that methylation acquisition was probably related to oocyte diameter and coincided with the accumulation of Dnmt3a, Dnmt3b and Dnmt3L transcripts. Methylation of the repetitive retroviral-like intracisternal A particle also occurred during this same window of oocyte growth. These findings contribute to our understanding of the epigenetic mechanisms underlying imprint acquisition during female germ cell development and have implications for the practice of assisted reproductive technologies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".