Regulation of DNA methylation turnover at LTR retrotransposons and imprinted loci by the histone methyltransferase Setdb1
Bibliographic record
Abstract
During mammalian development, DNA methylation patterns need to be reset in primordial germ cells (PGCs) and preimplantation embryos. However, many LTR retrotransposons and imprinted genes are impervious to such global epigenetic reprogramming via hitherto undefined mechanisms. Here, we report that a subset of such genomic regions are resistant to widespread erasure of DNA methylation in mouse embryonic stem cells (mESCs) lacking the de novo DNA methyltransferases (Dnmts) Dnmt3a and Dnmt3b. Intriguingly, these loci are enriched for H3K9me3 in mESCs, implicating this mark in DNA methylation homeostasis. Indeed, deletion of the H3K9 methyltransferase SET domain bifurcated 1 (Setdb1) results in reduced H3K9me3 and DNA methylation levels at specific loci, concomitant with increased 5-hydroxymethylation (5hmC) and ten-eleven translocation 1 binding. Taken together, these data reveal that Setdb1 promotes the persistence of DNA methylation in mESCs, likely reflecting one mechanism by which DNA methylation is maintained at LTR retrotransposons and imprinted genes during developmental stages when DNA methylation is reprogrammed.
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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".