Variations in DNA Methylation Patterns During the Cell Cycle of HeLa Cells
Bibliographic record
Abstract
DNA methylation has been viewed as a stable component of the epigenome, which is established during development and fixed thereafter. We show here using nearest neighbor analysis, immunocytochemistry, and high performance capillary electrophoresis that the DNA methylation pattern varies in HeLa cells during a single cell cycle. Immunocytochemical analysis in primary human fibroblasts shows similar variations. The global levels of DNA methylation decreased in G1 and increase during the S phase of the cell cycle. Since there was little change in the DNA methylation levels in repetitive sequences throughout the cell cycle, we examined the DNA methylation pattern of unique sequences using a human CpG island microarray. Hybridization with methylated DNA from G1 and S phase of the cell cycle revealed that 174 CG-containing sequences were differentially methylated between G1 and S. 75% of all the variations in DNA methylation detected in unique sequences represented hypomethylation at G0, with changes occurring in both CpG islands and non-CpG islands. Bisulfite mapping confirmed these changes in methylation in the regions identified by the microarray. This is the first demonstration of a dynamic DNA methylation pattern within a single cell cycle of a mature somatic cell. These data are important for our understanding of the stability of DNA methylation patterns in somatic cells.
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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".