A PCR-based quantitative assay for the evaluation of mRNA integrity in rat samples
Bibliographic record
Abstract
Reverse Transcription quantitative real-time PCR (RT-qPCR) is applied to quantify gene transcript levels in a wide range of investigations. Proper assessment of RNA integrity is essential for reliable assessment of gene expression levels, as RNA molecules are acutely vulnerable to degradation. However, RNA quality control measures are still infrequently reported in rat toxicological studies, which impede proper evaluation of gene expression data reliability. The high operational cost of microfluidic capillary electrophoresis systems along with paucity of alternative methods for the quantitative assessment of rat RNA integrity constitute potential hurdles to the systematic implementation and reporting of RNA integrity assessment in rat studies. This manuscript describes the adaptation of an alternative RT-qPCR-based 3':5' assay as an additional option for the quantitative assessment of rat RNA integrity. Two PCR primer sets were designed on the 3' and 5' regions of a rat housekeeping gene to evaluate RNA integrity by measuring the relative expression (3':5' ratio) of these amplicons. The 3':5' ratios were then compared to Agilent Bioanalyzer's RNA integrity number (RIN) for a wide range of RNA samples originating from different tissues, cultured cell lines and rat strains that were prepared freshly, stored for years at -80 °C, purchased commercially or intentionally degraded. The 3':5' ratios and RIN values presented similar assessment of RNA integrity status from intact to heavily degraded samples. Based on the LOWESS regression of this large comparison dataset, 3':5' ratio threshold criteria equivalent to RIN cut-off values can be proposed for the selection of RNA samples for RT-qPCR analyses. This qPCR-based assay is easy to implement, cost-effective, and provides a reliable quantification of RNA integrity to assist in the selection of rat RNA samples suitable for downstream RT-qPCR gene expression 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 | 0.002 | 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".