Introduction

Reverse transcription (RT) followed by a polymerase chain reaction (PCR) represents the most powerful technology to amplify and detect trace amounts of mRNA (Heid et al., 1996; Lockey, 1998). To quantify these low abundant expressed genes in any biological matrix the real-time quantitative RT-PCR (qRT-PCR) is the method of choice. Real-time qRT-PCR has advantages compared with conventionally performed 'semi-quantitative end point' RT-PCR, because of its high sensitivity, high specificity, good reproducibility, and wide dynamic quantification range (Higuchi et al., 1993; Gibson et al, 1996; Orland et al, 1998; Freeman et al, 1999; Schmittgen et al, 2000; Bustin, 2000). qRT-PCR is the most sensitive and most reliable method, in particular for low abundant transcripts in tissues with low RNA concentrations, partly degraded RNA, and from limited tissue sample (Freeman et al., 1999; Steuerwald et al., 1999; Mackay et al., 2002). While real-time RT-PCR has a tremendous potential for analytical and quantitative applications in transcriptome analysis, a comprehensive understanding of its underlying quantification principles is important. High reaction fidelity and reliable results of the performed mRNA quantification process is associated with standardized pre-analytical steps (tissue sampling and storage, RNA extraction and storage, RNA quantity and quality control), optimized RT and PCR performance (in terms of specificity, sensitivity, reproducibility, and robustness) and exact post-PCT data procession (data acquisition, evaluation, calculation and statistics) (Bustin, 2004; Pfaffl, 2004; Burkardt, 2000).

The question which might be the 'best RT-PCR quantification strategy' to express the exact mRNA content in a sample has still not been answered to universal satisfaction. Numerous papers have been published, proposing various terms, like 'absolute', 'relative', or 'comparative' quantification. Two general types of quantification strategies can be performed in qRT-PCR. The levels of expressed genes may be measured by an 'absolute' quantification or by a relative or comparative real-time qRT-PCR (Pfaffl, 2004). The 'absolute' quantification approach relates the PCR signal to input copy number using a calibration curve (Bustin, 2000; Pfaffl and Hageleit, 2001; Fronhoffs et al., 2002). Calibration curves can be derived from diluted PCR products, recombinant DNA or RNA, linearized plasmids, or spiked tissue samples. The reliability of such a an absolute real-time RT-PCR assay depends on the condition of 'identical' amplification efficiencies for both the native mRNA target and the target RNA or DNA used in the calibration curve (Souaze et al., 1996; Pfaffl, 2001). The so-called 'absolute' quantification is misleading, because the quantification is shown relative to the used calibration curve. The mRNA copy numbers must be correlated to some biological parameters, like mass of tissue, amount of total RNA or DNA, a defined amount of cells, or compared with a reference gene copy number (e.g. ribosomal RNA, or commonly used house keeping genes (HKG)). The 'absolute' quantification strategy using various calibration curves and applications are summarized elsewhere in detail (Pfaffl and Hageleit, 2001; Donald et al., 2005; Lai et al., 2005; Pfaffl et al., 2002).

This chapter describes the relative quantification strategies in quantitative real-time RT-PCR with a special focus of relative quantification models and newly developed relative quantification software tools.

0 0

Post a comment