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Improved real-time RT-PCR method for high-throughput measurements using second derivative calculation and double correction
 
Van Luu-The1, Nathalie Paquet1, Ezequiel Calvo1, Jean Cumps2
1, Laval University, Quebec, Canada
2, University of Louvain, Bruxelles, Belgium
BioTechniques, Vol. 38, No. 2, February 2005, pp. 287–293
Full Text (PDF)
Supplementary Material
Abstract

Quantification of mRNA expression levels using real-time reverse transcription PCR (RT-PCR) is increasingly used to validate results of DNA microarrays or GeneChips®. It requires an improved method that is more robust and more suitable for high-throughput measurements. In this report, we compare a user non-influent, second derivative method with that of a user influent, fit point method that is widely used in the literature. We also describe the advantage of using a double correction: one correction using the expression levels of a housekeeping gene of an experiment as an internal standard and a second using reference expression levels of the same housekeeping gene in the tissue or cells. The first correction permits one to decrease errors due to sample preparation and handling, while the second correction permits one to avoid the variation of the results with the variability of housekeeping in each tissue, especially in experiments using various treatments. The data indicate that the real-time PCR method is highly efficient with an efficiency coefficient close to the theoretical value of two. The results also show that the second derivative method is more accurate than the fit point method in quantifying low gene expression levels. Using triplicate experiments, we show that measurement variations using our method are low with a mean of variation coefficients of <1%.

Introduction

Real-time reverse transcription PCR (RT-PCR), a recently developed fluorescent method of mRNA quantification (1,2,3), has improved greatly the mRNA quantification performed with PCR. Real-time RT-PCR permits the rigorous control of PCR conditions, and quantification takes place within an exponential phase of the amplification curve (4,5). In fact, the efficiency coefficient is close to the theoretical value of 2, thus indicating that errors due to the PCR amplification process are very low. The most important causes of errors are the RNA preparation and handling (5) because they will be amplified exponentially in the amplification process. The important improvement of real-time RT-PCR compared to classical PCR is that real-time RT-PCR permits one to follow the kinetics of DNA production in real time and to quantify the initial amount of mRNA using a standard curve, resulting in much lower variability (6). In contrast, with classical PCR quantification, end-product signal that included the exponential amplified errors is measured (7), thus giving rise to high variability. In addition, real-time RT-PCR allows for the estimation of the absolute expression levels as copies of mRNA/microgram of total RNA and thus permits a quantitative appreciation of gene expression levels. This will help to better understand the role and function of the genes under investigation.

Two types of quantification can be performed using real-time PCR: a relative quantification based on the relative expression of a target versus a reference gene (8) and an absolute quantification (9) based either on an internal or an external calibration curve. The most frequently used method to investigate the physiological changes in gene expression is based on a relative expression ratio in order to avoid errors due to RNA and cDNA preparation. Absolute quantification, on the other hand, yields a quantitative estimate of the concentration of a target mRNA, which allows for a more precise assessment of the importance of its functional role in target tissues or cells.

Two modes of detection are generally used, one employing a gene-specific fluorescent hybridization probe in which fluorescent signal is increased (10,11) or decreased (12) by transfer of energy from one fluorescent dye to another [e.g., fluorescence resonance energy transfer (FRET)] and a second one using a common SYBR® Green I fluorescent dye that binds to a minor groove of DNA (13). With a proper choice of primers and amplification conditions assisted by informatics, it has been shown that real-time RT-PCR using SYBR Green I is a rapid, sensitive, and accurate method to quantify mRNA (4,13).

There are also two methods to determine a crossing point (Cp) value, which is a cycle number in a log-linear region ((Figure 1)) that is used to calculate the quantitative value of real-time RT-PCR. One method, namely fit point ((Figure 1)B; Reference 4), is performed by drawing a line parallel to the x-axis in the log-linear region of the real-time fluorescence intensity curve; a somewhat variable user-dependent value can be obtained by this method. The second, namely second derivative, calculates a second derivative (2,4,6) value of the real-time fluorescence intensity curve ((Figure 1)A), and only one value is obtained. The fit point method is the most currently used method, and the calculation is user-dependent. The second derivative calculation, on the other hand, does not involve any decision by the user because a positive peak corresponds to the beginning of the log-linear phase of the original data.

Figure 1.


Illustration of the second derivative (A) and fit point methods (B). Illustrations taken from a LightCycler manual (Hoffman-La Roche) showing the variation of fluorescence signal versus number of cycles and the methods to determine the crossing point (Cp) using second derivative peak (A) and fit point (B). In the second derivative method, a Cp corresponds to the first peak of a second derivative curve. This peak corresponds to the beginning of a log-linear phase (A). In the fit point method (B), a Cp is determined by the intersection of a parallel to the threshold line in the log-linear region.

GeneChips® (Affymetrix, Santa Clara, CA, USA) have been successfully used to monitor gene expression in unicellular model organisms and cell lines (14,15). However, when profiling more complex samples, such as human and murine tissue samples, more variability and false-positive/negative values are more likely to occur. This higher variability is probably related to the cellular heterogeneity of the tissues of mammals. The reliability of GeneChips to detect differences in expression levels following various treatments is also affected by several factors, including the quality of the probe sets, RNA extraction, and quality of the probe preparations and hybridization conditions (14). Even if GeneChip and DNA microarray data are quite reliable, they are not very precise, and thus genes identified as modulated must be validated and quantified. Northern blot hybridization or RNase protection assays are effective methods of validation, however, they often require large amounts of RNA. Classical RT-PCR requires much less RNA but lacks precision due to exponential amplification of potential errors during the PCR amplification process. The most appropriate method of validation is therefore real-time RT-PCR.

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