Transcription is required for active DNA demethylation
Bibliographic record
Abstract
1052 A hallmark of vertebrate genes is that actively transcribed genes are hypomethylated in critical regulatory sequences. However the mechanisms that link gene transcription and DNA hypomethylation are unclear. Using a trichostatin A (TSA) induced replication-independent demethylation assay in HEK 293 cells and chromatin immuno-precipitation assays with pertinent histone modification antibodies and bisulfite mapping, we study the temporal and causal relationship between chromatin and active DNA demethylation. We show that RNA transcription is required for DNA demethylation. Histone acetylation precedes but is not sufficient to trigger DNA demethylation. Following histone acetylation, RNA polymerase II (RNAP II) interacts with the methylated promoter. Inhibition of RNAP II transcription with actinomycin D, a-amanitin, or CDK7 siRNA inhibits DNA demethylation. H3 trimethyl lysine 4 methylation, a marker of actively transcribed genes, was associated with the CMV promoter only after demethylation. TSA induced demethylation of the endogenous cancer testis gene GAGE follows a similar sequence of events and is dependent on RNA transcription as well. These data suggest that DNA demethylation follows rather than precedes early transcription and points towards a novel function for DNA demethylation - a memory of actively transcribed genes. We are currently investigating if SWI/SNF chromatin remodeling factors associated with transcription, which have been shown to set a platform for histone eviction by allowing a more open configuration of the chromatin, may favor DNA demethylase access to the DNA. Supported by a grant from the National Cancer Institute of Canada to MS. Shelley E. Brown is supported by a CIHR fellowship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".