Methylated DNA Immunoprecipitation
Bibliographic record
Abstract
The identification of DNA methylation patterns is a common procedure in the study of epigenetics, as methylation is known to have significant effects on gene expression, and is involved with normal development as well as disease. Thus, the ability to discriminate between methylated DNA and non-methylated DNA is essential for generating methylation profiles for such studies. Methylated DNA immunoprecipitation (MeDIP) is an efficient technique for the extraction of methylated DNA from a sample of interest. A sample of as little as 200 ng of DNA is sufficient for the antibody, or immunoprecipitation (IP), reaction. DNA is sonicated into fragments ranging in size from 300-1000 bp, and is divided into immunoprecipitated (IP) and input (IN) portions. IP DNA is subsequently heat denatured and then incubated with anti-5'mC, allowing the monoclonal antibody to bind methylated DNA. After this, magnetic beads containing a secondary antibody with affinity for the primary antibody are added, and incubated. These bead-linked antibodies will bind the monoclonal antibody used in the first step. DNA bound to the antibody complex (methylated DNA) is separated from the rest of the DNA by using a magnet to pull the complexes out of solution. Several washes using IP buffer are then performed to remove the unbound, non-methylated DNA. The methylated DNA/antibody complexes are then digested with Proteinase K to digest the antibodies leaving only the methylated DNA intact. The enriched DNA is purified by phenol:chloroform extraction to remove the protein matter and then precipitated and resuspended in water for later use. PCR techniques can be used to validate the efficiency of the MeDIP procedure by analyzing the amplification products of IP and IN DNA for regions known to lack and known to contain methylated sequences. The purified methylated DNA can then be used for locus-specific (PCR) or genome-wide (microarray and sequencing) methylation studies, and is particularly useful when applied in conjunction with other research tools such as gene expression profiling and array comparative genome hybridization (CGH). Further investigation into DNA methylation will lead to the discovery of new epigenetic targets, which in turn, may be useful in developing new therapeutic or prognostic research tools for diseases such as cancer that are characterized by aberrantly methylated DNA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.034 | 0.035 |
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".