A new mathematical model for relative quantification in real-time RT-PCR

Abstract

Use of the real-time polymerase chain reaction (PCR) to amplify cDNA products reverse transcribed from mRNA is on the way to becoming a routine tool in molecular biology to study low abundance gene expression. Real-time PCR is easy to perform, provides the necessary accuracy and produces reliable as well as rapid quantification results. But accurate quantification of nucleic acids requires a reproducible methodology and an adequate mathematical model for data analysis. This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript. Therefore, a new mathematical model is presented. The relative expression ratio is calculated only from the real-time PCR efficiencies and the crossing point deviation of an unknown sample versus a control. This model needs no calibration curve. Control levels were included in the model to standardise each reaction run with respect to RNA integrity, sample loading and inter-PCR variations. High accuracy and reproducibility (<2.5% variation) were reached in LightCycler PCR using the established mathematical model.

Figures

Figure 1

Determination of real-time PCR efficiencies of reference gene (Gst), target gene 1 (TyrA) and target gene 2 (PyrB). CP cycles versus cDNA (reverse transcribed total RNA) concentration input were plotted to calculate the slope (mean ± SD; n = 3). The corresponding real-time PCR efficiencies were calculated according to the equation: E = 10[–1/slope] (18).

Figure 2

Real-time RT–PCR SYBR Green I fluorescence history versus cycle number of target gene 1 (TyrA), target gene 2 (PyrB) and reference gene (Gst) in sample cDNA and control cDNA. CP determination was done at fluorescence level 1.