Medium throughput bisulfite sequencing for accurate detection of 5-methylcytosine and 5-hydroxymethylcytosine
Bibliographic record
Abstract
BACKGROUND: Epigenetic modifications of DNA, such as 5-methylcytosine and 5-hydroxymethycytosine, play important roles in development and disease. Here, we present a cost-effective and versatile methodology for the analysis of DNA methylation in targeted genomic regions, which comprises multiplexed, PCR-based preparation of bisulfite DNA libraries followed by customized MiSeq sequencing. RESULTS: Using bisulfite and oxidative bisulfite conversion of DNA, we have performed multiplexed targeted sequencing to analyse several kilobases of genomic DNA in up to 478 samples, and achieved high coverage data of 5-methylcytosine and 5-hydroxymethycytosine at single-base resolution. Our results demonstrate the ability of this methodology to detect all levels of cytosine modifications at greater than 100× coverage in large sample sets at low cost compared to other targeted methods. CONCLUSIONS: This approach can be applied to multiple settings, from candidate gene to clinical studies, and is especially useful for validation of differentially methylated or hydroxymethylated regions following whole-genome analyses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".