Variable DNA methylation of transposable elements: The case study of mouse Early Transposons
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Phenotypic variation stems from both genetic and epigenetic differences between individuals. In order to elucidate how phenotypes are determined, it is necessary to understand the forces that generate variation in genome sequence as well as its epigenetic state. In both contexts, transposable elements (TEs) may play an important role. It is well established that TE activity is a major generator of genetic variation, but recent research also suggests that TEs contribute to epigenetic variation. Stochastic epigenetic silencing of some TE insertions in mice has been shown to cause phenotypic variability between individuals. However, the prevalence of this phenomenon has never been evaluated. Here, we use 18 insertions of a mouse Endogenous Retrovirus (ERV) family, the Early Transposons (ETns), to detect insertion-dependent determinants of DNA methylation levels and variability between both cells and individuals. We show that the structure and age of insertions influence methylation levels and variability, resulting in a subgroup of loci that displays unexpectedly high variability in methylation and suggesting stochastic events during methylation establishment. Despite variation in methylation according to the age and structure of each locus, homologous CpG sites show similar tendencies in methylation levels across loci, emphasizing the role of the insertion's sequence in methylation determination. Our results show that differences in methylation of ETns between individuals is not a sporadic phenomenon and support the hypothesis that ERVs contribute to phenotypic variability through their stochastic silencing.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it