Elsevier

Neuroscience Letters

Volume 339, Issue 1, 13 March 2003, Pages 62-66
Neuroscience Letters

Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data

https://doi.org/10.1016/S0304-3940(02)01423-4Get rights and content

Abstract

Quantification of mRNAs using real-time polymerase chain reaction (PCR) by monitoring the product formation with the fluorescent dye SYBR Green I is being extensively used in neurosciences, developmental biology, and medical diagnostics. Most PCR data analysis procedures assume that the PCR efficiency for the amplicon of interest is constant or even, in the case of the comparative Ct method, equal to 2. The latter method already leads to a 4-fold error when the PCR efficiencies vary over just a 0.04 range. PCR efficiencies of amplicons are usually calculated from standard curves based on either known RNA inputs or on dilution series of a reference cDNA sample. In this paper we show that the first approach can lead to PCR efficiencies that vary over a 0.2 range, whereas the second approach may be off by 0.26. Therefore, we propose linear regression on the Log(fluorescence) per cycle number data as an assumption-free method to calculate starting concentrations of mRNAs and PCR efficiencies for each sample. A computer program to perform this calculation is available on request (e-mail: [email protected]; subject: LinRegPCR).

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Acknowledgements

We would like to thank Dr Marc Vos, Department of Cardiology, Academic Hospital Maastricht, and Dr Onno Bakker, Department of Endocrinology and Metabolism, Academic Medical Center, Amsterdam for their constructive support. This research is partly supported by the Netherlands Heart Foundation, grant NHS 98.042 (CR) and NHS 96.002 (RHLD) (AFMM).

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