LTR retrotransposons transcribed in oocytes drive species-specific and heritable changes in DNA methylation
Bibliographic record
Abstract
De novo DNA methylation (DNAme) during mouse oogenesis occurs within transcribed regions enriched for H3K36me3. As many oocyte transcripts originate in long terminal repeats (LTRs), which are heterogeneous even between closely related mammals, we examined whether species-specific LTR-initiated transcription units (LITs) shape the oocyte methylome. Here we identify thousands of syntenic regions in mouse, rat, and human that show divergent DNAme associated with private LITs, many of which initiate in lineage-specific LTR retrotransposons. Furthermore, CpG island (CGI) promoters methylated in mouse and/or rat, but not human oocytes, are embedded within rodent-specific LITs and vice versa. Notably, at a subset of such CGI promoters, DNAme persists on the maternal genome in fertilized and parthenogenetic mouse blastocysts or in human placenta, indicative of species-specific epigenetic inheritance. Polymorphic LITs are also responsible for disparate DNAme at promoter CGIs in distantly related mouse strains, revealing that LITs also promote intra-species divergence in CGI DNAme.
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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 | 0.000 | 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) | 0.002 | 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".