Fluorescence polarization-based method with bisulfite conversion-specific one-label extension for quantification of single CpG dinucleotide methylation
Bibliographic record
Abstract
To quantify the methylation at individual CpG dinucleotide sites in large biological or clinical samples, we developed a bisulfite conversion-specific one-label extension (BS-OLE) method using visualization by fluorescence polarization (FP) measurement of methylation at single CpG sites in small amounts of genomic DNA. Genomic DNA was treated with sodium bisulfite to convert unmethylated cytosine to uracil leaving 5-methylcytosine unaltered, and BS-PCR was used to generate DNA template containing target CpG sites. BS-OLE uses a BS-primer hybridized immediately upstream of the target CpG site being examined and then fluorescent dCTP or dUTP is incorporated into the methylated (CpG) or unmethylated (TpG) form of the target site through single-nucleotide chain extension, yielding an FP ratio between the fluorescent dCTP- and dUTP-incorporated products as a measure of methylation. This provides stable estimates of the methylation level of human genomic DNA and of a 250-bp plasmid DNA segment containing a single TCGA TaqI cleavage site, in accordance with the results of a combined bisulfite restriction analysis method. We used BS-OLE to measure dose-dependent DNA hypomethylation in human embryonic kidney 293T cells treated with the DNA methyltransferase inhibitor 5-aza-dC. BS-OLE is well suited to high-throughput multi-sample applications in biological and medical studies.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".