Effect of endogenous reference genes on digital PCR assessment of genetically engineered canola events
Bibliographic record
Abstract
Droplet digital PCR (ddPCR) has been used for absolute quantification of genetically engineered (GE) events. Absolute quantification of GE events by duplex ddPCR requires the use of appropriate primers and probes for target and reference gene sequences in order to accurately determine the amount of GE materials. Single copy reference genes are generally preferred for absolute quantification of GE events by ddPCR. Study has not been conducted on a comparison of reference genes for absolute quantification of GE canola events by ddPCR. The suitability of four endogenous reference sequences (HMG-I/Y, FatA(A), CruA and Ccf) for absolute quantification of GE canola events by ddPCR was investigated. The effect of DNA extraction methods and DNA quality on the assessment of reference gene copy numbers was also investigated. ddPCR results were affected by the use of single vs. two copy reference genes. The single copy, FatA(A), reference gene was found to be stable and suitable for absolute quantification of GE canola events by ddPCR. For the copy numbers measured, the HMG-I/Y reference gene was less consistent than FatA(A) reference gene. The expected ddPCR values were underestimated when CruA and Ccf (two copy endogenous Cruciferin sequences) were used because of high number of copies. It is important to make an adjustment if two copy reference genes are used for ddPCR in order to obtain accurate results. On the other hand, real-time quantitative PCR results were not affected by the use of single vs. two copy reference genes.
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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".