Effects of storage conditions on the stability of qPCR reagents: implications for environmental DNA detection
Bibliographic record
Abstract
OBJECTIVE: Environmental DNA (eDNA) detection is a transformative tool for ecological surveys which in many cases offers greater accuracy and cost-effectiveness for tracking low-density, cryptic species compared to conventional methods. For the use of targeted quantitative PCR (qPCR)-based eDNA detection, protocols typically require freshly prepared reagents for each sample, necessitating systematic evaluation of reagent stability within the functional context of eDNA standard curve preparation and environmental sample evaluation. Herein, we assessed the effects of long-term storage and freeze-thaw cycles on qPCR reagents for eDNA analysis across six assays. RESULTS: Results demonstrate qPCR plates (containing pre-made PCR mix, primer-probe, and DNA template) remain stable at 4 °C for three days before thermocycling without fidelity loss irrespective of qPCR assay used. Primer-probe mixes remain stable for five months of - 20 °C storage with monthly freeze-thaw cycles also irrespective of qPCR assay used. Synthetic DNA stocks maintain consistency in standard curves and sensitivity for three months under the same conditions. These findings enhance our comprehension of qPCR reagent stability, facilitating streamlined eDNA workflows by minimizing repetitive reagent preparations.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".