Targeting of EZH2 to a defined genomic site is sufficient for recruitment of Dnmt3a but not de novo DNA methylation
Bibliographic record
Abstract
Polycomb-mediated gene silencing and DNA methylation underlie many epigenetic processes important in normal development as well as in cancer. An interaction between EZH2 of the Polycomb repressive complex 2 (PRC2), which trimethylates lysine 27 on Histone 3 (H3K27me3), and all three DNA methyltransferases (DNMTs) has been reported, implicating a role for PRC2 in directing DNA methylation. Interestingly, however, the majority of H3K27me3 marked genes lack DNA methylation in ES cells, indicating that EZH2 recruitment may not be sufficient to promote DNA methylation. Here, we employed a Gal4DBD/gal4UAS-based system to directly test if EZH2 binding at a defined genomic site is sufficient to promote de novo DNA methylation in a murine erythroleukaemia cell line. Targeting of a Gal4DBD-EZH2 fusion to an intergenic transgene bearing a gal4 binding-site array promoted localized recruitment of Suz12 and Bmi1, subunits of PRC2 and PRC1, respectively, and deposition of H3K27me3. Further analysis of the H3K27me3-marked site revealed the persistence of H3K4me2, a mark inversely correlated with DNA methylation. Strikingly, while Dnmt3a was also recruited in an EZH2-dependent manner, de novo DNA methylation of the transgene was not observed. Thus, while targeting of EZH2 to a specific genomic site is sufficient for recruitment of Dnmt3a, additional events are required for de novo DNA methylation.
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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 | 0.001 |
| 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".