Genotyping the BDNF rs6265 (val66met) polymorphism by one-step amplified refractory mutation system PCR
Bibliographic record
Abstract
BACKGROUND: The brain derived neutrophic factor (BDNF), a 27 kD polypeptide, is one of the most widely expressed neurotrophins in the brain, regulating neural development and plasticity. The BDNF gene contains a functional single-nucleotide polymorphism (rs6265), which results in a valine to methionine substitution (val66met), leading to reduced mature BDNF expression. This polymorphism has been widely implicated in a host of psychiatric disorders and is a focus of many ongoing psychiatric genetic studies. OBJECTIVE: To develop an efficient and rapid method to detect the val66met polymorphism in a one-step PCR reaction. METHOD AND RESULTS: We have designed four PCR primers that amplify the BDNF gene region containing rs6265. The specificity of the four primers in a single PCR reaction amplifies two allele-specific amplicons (253 and 201 bp) and the entire region (401 bp) as an internal control, which are easily distinguished on a polyacrylamide gel. The effectiveness and efficiency of the results are validated by traditional NlaIII restriction enzyme digestion, sequencing of resulting bands and confirmation on 308 genomic DNA samples. CONCLUSION: This new method describes a rapid, sensitive, cost effective and high throughput genotyping of the BDNF val66met polymorphism, ideal for large-scale genotyping 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".