Cell culture-induced aberrant methylation of the imprinted IG DMR in human lymphoblastoid cell lines
Bibliographic record
Abstract
DNA methylation patterns are often poorly conserved through cell culturing. To determine the effect of cell immortalization and culture on DNA methylation profiles, we analyzed methylation in the differentially methylated regions (DMR) of five imprinted domains: the intergenic (IG) DMR on chromosome 14q32; potassium voltage-gated channel, KQT-like subfamily, member 1, (KCNQ1); small nuclear ribonucleoprotein polypeptide N (SNRPN), mesoderm specific transcript homolog (MEST); and H19 in lymphoblastoid cell lines (LCLs). In the IG DMR we found an aberrant methylation pattern that was consistent through all the cell lines tested and significantly different from that of noncultured peripheral blood cells. Using a generalized linear mixed model to compare methylation profiles, we show that recently derived LCLs significantly differ from the CEPH LCLs. This implies a gradual cell-culture related deterioration of DNA methylation in the IG DMR with at least two steps that may be identified: loss of methylation at CG sites 1 and 8; and loss of allelic differences in DNA methylation. The IG DMR methylation profile also confirms the high level of clonality of the CEPH LCLs. We conclude that non-transformed primary cells may be less susceptible to epigenetic anomalies and therefore may provide a more accurate reflection of gene expression in vivo.
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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 | 0.001 | 0.001 |
| 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".