Retrotransposons as a major source of epigenetic variations in the mammalian genome
Bibliographic record
Abstract
Transcription of retrotransposons is usually repressed by DNA methylation, but a few elements, such as intracisternal A-particles (IAPs) associated with the Agouti and Axin-fused loci, partially escape this repression mechanism. The levels of this repression are also variable among individuals with an identical genome sequence, generating epigenetically different states of loci or 'epialleles.' In the current study, we tested the existence of additional retrotransposon-derived epialleles in the mouse genome. Using a series of bioinformatic approaches, 143 candidate epialleles were first identified from the mouse genome based on their promoter activity and association with active histone modification marks. Detailed analyses suggest that a subset of these elements showed variable levels of DNA methylation among the individual mice of an isogenic background, revealing their stochastic nature (metastability) of DNA methylation. The analyses also identified two opposite patterns of DNA methylation during development, progressive gaining vs. losing, confirming the dynamic nature of their DNA methylation patterns. qRT-PCR analyses demonstrated that the expression levels of these elements are indeed variable among the individual mice, suggesting functional consequences on their associated endogenous genes. Overall, these data confirm the presence of a number of new retrotransposon-derived epialleles with suggestions of the presence of more, and further identify retrotransposons as a major source of epigenetic variations in the mammalian genome.
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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) | 0.001 | 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".