How good is a PCR efficiency estimate: Recommendations for precise and robust qPCR efficiency assessments

0523128 - BTÚ 2020 RIV NL eng J - Journal Article
Švec, David - Tichopád, A. - Novosadová, Vendula - Pfaffl, M. W. - Kubista, Mikael
How good is a PCR efficiency estimate: Recommendations for precise and robust qPCR efficiency assessments.
Biomolecular Detection and Quantification. Roč. 3, March 01 (2015), s. 9-16. ISSN 2214-7535
R&D Projects: GA ČR GA13-02154S; GA MŠMT(CZ) ED1.1.00/02.0109
Institutional support: RVO:86652036
Keywords : Amplification efficiency * Dilution series * qpcr * QPCR assay validation * Real-time quantitative PCR * Standard curve
OECD category: Biochemistry and molecular biology
Method of publishing: Open access
https://www.sciencedirect.com/science/article/pii/S2214753515000169?via%3Dihub

We have examined the imprecision in the estimation of PCR efficiency by means of standard curves based on strategic experimental design with large number of technical replicates. In particular, how robust this estimation is in terms of a commonly varying factors: the instrument used, the number of technical replicates performed and the effect of the volume transferred throughout the dilution series. We used six different qPCR instruments, we performed 1-16 qPCR replicates per concentration and we tested 2-10. μl volume of analyte transferred, respectively. We find that the estimated PCR efficiency varies significantly across different instruments. Using a Monte Carlo approach, we find the uncertainty in the PCR efficiency estimation may be as large as 42.5% (95% CI) if standard curve with only one qPCR replicate is used in 16 different plates. Based on our investigation we propose recommendations for the precise estimation of PCR efficiency: (1) one robust standard curve with at least 3-4 qPCR replicates at each concentration shall be generated, (2) the efficiency is instrument dependent, but reproducibly stable on one platform, and (3) using a larger volume when constructing serial dilution series reduces sampling error and enables calibration across a wider dynamic range.
Permanent Link: http://hdl.handle.net/11104/0307524