How good is a PCR efficiency estimate: Recommendations for precise and robust qPCR efficiency assessments
Status PubMed-not-MEDLINE Jazyk angličtina Země Německo Médium electronic-ecollection
Typ dokumentu časopisecké články
PubMed
27077029
PubMed Central
PMC4822216
DOI
10.1016/j.bdq.2015.01.005
PII: S2214-7535(15)00016-9
Knihovny.cz E-zdroje
- Klíčová slova
- ANCOVA, analysis of covariance, Amplification efficiency, CLSI, Clinical and Laboratory Standards Institute, Cq, cycle of quantification, Dilution series, E, PCR efficiency, EPA, Environmental protection agency, FDA, food and Drug Administration, GMO, genetically modified organism, IEC, International Electrotechnical Commission, ISO, International Organization for Standardization, MIQE, minimum information for publication of quantitative real-time PCR experiments, NTC, no template control, RIN, RNA Integrity Number, RT-qPCR, reverse transcription-quantitative polymerase chain reaction, Real-time quantitative PCR, Standard curve, qPCR, qPCR assay validation,
- Publikační typ
- časopisecké články MeSH
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.
Faculty of Medicine Pilsen Charles University Pilsen Czech Republic
Physiology Weihenstephan TUM Technische Universität München Freising Germany
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Higuchi R. Simultaneous amplification and detection of specific DNA sequences. Biotechnology (N Y) 1992;10(4):413–417. PubMed
Kubista M. The real-time polymerase chain reaction. Mol Aspects Med. 2006;27(2–3):95–125. PubMed
Wittwer C.T. Continuous fluorescence monitoring of rapid cycle DNA amplification. Biotechniques. 1997;22(1):130–131. 134–8. PubMed
Hellemans J. qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol. 2007;8(2):R19. PubMed PMC
Pfaffl M.W. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res. 2001;29(9):e45. PubMed PMC
Boeuf P. CyProQuant-PCR: a real time RT-PCR technique for profiling human cytokines, based on external RNA standards, readily automatable for clinical use. BMC Immunol. 2005;6:5. PubMed PMC
Bustin S.A. Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. J Mol Endocrinol. 2000;25(2):169–193. PubMed
Larionov A., Krause A., Miller W. A standard curve based method for relative real time PCR data processing. BMC Bioinformatics. 2005;6:62. PubMed PMC
Stolovitzky G., Cecchi G. Efficiency of DNA replication in the polymerase chain reaction. Proc Natl Acad Sci U S A. 1996;93(23):12947–12952. PubMed PMC
Alvarez M.J. Model based analysis of real-time PCR data from DNA binding dye protocols. BMC Bioinformatics. 2007;8:85. PubMed PMC
Lalam N. Estimation of the reaction efficiency in polymerase chain reaction. J Theor Biol. 2006;242(4):947–953. PubMed
Roche . 2000. Overview of LightCycler quantification methods.
AppliedBiosystems . 2004. Amplification efficiency of TaqMan® gene expression assays.
Goll R. Evaluation of absolute quantitation by nonlinear regression in probe-based real-time PCR. BMC Bioinformatics. 2006;7:107. PubMed PMC
Tichopad A. Standardized determination of real-time PCR efficiency from a single reaction set-up. Nucleic Acids Res. 2003;31(20):e122. PubMed PMC
Bustin S.A. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem. 2009;55(4):611–622. PubMed
Bar T., Kubista M., Tichopad A. Validation of kinetics similarity in qPCR. Nucleic Acids Res. 2012;40(4):1395–1406. PubMed PMC
Sisti D. Shape based kinetic outlier detection in real-time PCR. BMC Bioinformatics. 2010;11:186. PubMed PMC
Tichopad A. Quality control for quantitative PCR based on amplification compatibility test. Methods. 2010;50(4):308–312. PubMed
Gevertz J.L., Dunn S.M., Roth C.M. Mathematical model of real-time PCR kinetics. Biotechnol Bioeng. 2005;92(3):346–355. PubMed
Mackay I.M. Horizon Scientific Press; 2007. Real-time PCR in microbiology: from diagnosis to characterization; p. 454.
Raghavachari R., Tan W. SPIE; San Jose, CA: 2001. Genomics and proteomics technologies.
Nolan T. SPUD: a quantitative PCR assay for the detection of inhibitors in nucleic acid preparations. Anal Biochem. 2006;351(2):308–310. PubMed
Svec D. Direct cell lysis for single-cell gene expression profiling. Front Oncol. 2013;3:274. PubMed PMC
Stahlberg A. Quantitative real-time PCR method for detection of B-lymphocyte monoclonality by comparison of kappa and lambda immunoglobulin light chain expression. Clin Chem. 2003;49(1):51–59. PubMed
Pfaffl M. In: Quantification strategies in real-time PCR, A–Z of quantitative PCR. Bustin S.A., editor. International University Line (IUL); La Jolla, CA, USA: 2004. pp. 87–112.
Good I.J. Statistical science. Institute of Mathematical Statistics; 1986. Some statistical applications of Poisson's work; pp. 157–170.
Peccoud J., Jacob C. Theoretical uncertainty of measurements using quantitative polymerase chain reaction. Biophys J. 1996;71(1):101–108. PubMed PMC
Bengtsson M. Quantification of mRNA in single cells and modelling of RT-qPCR induced noise. BMC Mol Biol. 2008;9:63. PubMed PMC
Murphy J., Bustin S.A. Reliability of real-time reverse-transcription PCR in clinical diagnostics: gold standard or substandard? Expert Rev Mol Diagn. 2009;9(2):187–197. PubMed
Baker S.C. The External RNA Controls Consortium: a progress report. Nat Methods. 2005;2(10):731–734. PubMed
FDA . Food and Drug Administration; 2005. Guidance for industry pharmacogenomic data submissions.
EPA . U.S. Environmental Protection Agency (EPA), Office of Ground Water and Drinking Water and the Office of Research and Development; 2004. Quality assurance/quality control guidance for laboratories performing PCR analyses on environmental samples.
CLSI . CLSI; 2006. Use of external RNA controls in gene expression assays.
Lavagnini I., Magno F. A statistical overview on univariate calibration, inverse regression, and detection limits: application to gas chromatography/mass spectrometry technique. Mass Spectrom Rev. 2007;26(1):1–18. PubMed
Andrade J.M. Classical linear regression by the least squares method. In: Andrade-Garda J.M., editor. Basic chemometric techniques in atomic spectroscopy. 2nd ed. Royal Society of Chemistry; 2013. pp. 52–66.
CLSI . 2003. CLSI document EP6-A: evaluation of the linearity of quantitative measurement procedures.
CLSI . 2nd ed. 2004. CLSI document EP5-A2: evaluation of precision performance of quantitative measurement methods.
Cuthbert D. Calibration designs for machines with carry-over and drift. J Qual Technol. 1975;7(3):103–108.
Kubista M. 2010. When to use interplate calibrator. Available from: http://www.tataa.com/products-page/quality-assessment/tataa-interplate-calibrator/