Modeling and analysis of competitive RT-PCR

Journal of Molecular Medicine-jmm, 2006

For quantification of gene-specific mRNA, quantitative real-time RT-PCR has become one of the most frequently used methods over the last few years. This article focuses on the issue of real-time PCR data analysis and its mathematical background, offering a general concept for efficient, fast and precise data analysis superior to the commonly used comparative C T (ΔΔC T ) and the standard curve method, as it considers individual amplification efficiencies for every PCR. This concept is based on a novel formula for the calculation of relative gene expression ratios, termed GED (Gene Expression’s C T Difference) formula. Prerequisites for this formula, such as real-time PCR kinetics, the concept of PCR efficiency and its determination, are discussed. Additionally, this article offers some technical considerations and information on statistical analysis of real-time PCR data.

American Journal of Respiratory Cell and Molecular Biology, 1998

Progress toward complete sequencing of all human genes through the Human Genome Project has already resulted in a need for methods that allow quantitative expression measurement of multiple genes simultaneously. It is increasingly recognized that relative measurement of multiple genes will provide more mechanistic information regarding cell pathophysiology than measurement of individual genes one by one or by methods that do not allow direct intergene comparison. In this study, previously described quantitative reverse transcription-polymerase chain reaction methods were modified in an effort to provide a rapid, simple method for this purpose. Internal standard competitive templates (CTs) were prepared for each gene and were combined in a single solution containing CTs for more than 40 genes at defined concentrations relative to one another. Any subsequent dilution of the CT mixture did not alter the relationship of one CT to another. Because the same CT standard solution or a dilution of it was used in all experiments, data obtained from different experiments were easily compared. The use of multiple CT mixtures with different housekeeping gene to target gene ratios provided a linear dynamic range spanning the range of expression of all genes thus far evaluated. CT stock solutions were used to simultaneously quantify the expression of 25 genes relative to ␤-actin and glyceraldehyde-3-phosphate dehydrogenase in normal and malignant bronchial epithelial cells. Because the CT concentrations were known, data in the form of both absolute messenger RNA (mRNA) copy number and mRNA relative to housekeeping gene mRNA were obtained. The methods and reagents described will allow rapid, quantitative measurement of multiple genes simultaneously, using inexpensive and widely available equipment. Furthermore, the CT standard solution may be distributed to other investigators for interlaboratory standardization of experimental conditions. Willey, J.

BioTechniques, 2008

Following its invention 25 years ago, PCR has been adapted for numerous molecular biology applications. Gene expression analysis by reverse-transcription quantitative PCR (RT-qPCR) has been a key enabling technology of the post-genome era. Since the founding of BioTechniques, this journal has been a resource for the improvements in qPCR technology, experimental design, and data analysis. qPCR and, more specifically, real-time qPCR has become a routine and robust approach for measuring the expression of genes of interest, validating microarray experiments, and monitoring biomarkers. The use of real-time qPCR has nearly supplanted other approaches (e.g., Northern blotting, RNase protection assays). This review examines the current state of qPCR for gene expression analysis now that the method has reached a mature stage of development and implementation. Specifically, the different fluorescent reporter technologies of real-time qPCR are discussed as well as the selection of endogenous controls. The conceptual framework for data analysis methods is also presented to demystify these analysis techniques. The future of qPCR remains bright as the technology becomes more rapid, cost-effective, easier to use, and capable of higher throughput.

Molecular Cancer, 2004

Background: Probe based detection assays form the mainstay of transcript quantification. Problems with these assays include varying hybridization efficiencies of the probes used for transcript quantification and the expense involved. We examined the ability of a standardized competitive RT-PCR (StaRT PCR) assay to quantify transcripts of 4 cell cycle associated genes (RB, E2F1, CDKN2A and PCNA) in two cell lines (T24 & LD419) and compared its efficacy with the established Taqman real time quantitative RT-PCR assay. We also assessed the sensitivity, reproducibility and consistency of StaRT PCR. StaRT PCR assay is based on the incorporation of competitive templates (CT) in precisely standardized quantities along with the native template (NT) in a PCR reaction. This enables transcript quantification by comparing the NT and CT band intensities at the end of the PCR amplification. The CT serves as an ideal internal control. The transcript numbers are expressed as copies per million transcripts of a control gene such as β-actin (ACTB).

Analytical Biochemistry, 2005

Real competitive PCR (rcPCR) has been shown to have high sensitivity, reproducibility, and high-throughput potential. We describe further development and evaluation of this methodology as a tool for measuring nucleic acid abundance within a cell. Modifications to the original protocol allow analysis of gene expression levels using standard conditions regardless of mRNA abundance and assay type, thereby increasing throughput and ease of reaction setup while decreasing optimization time. In addition, we have developed a software package, TITAN, to automatically analyze the results. The details are relevant to researchers performing competitive PCR using any detection technique. The effectiveness of the described developments is demonstrated using 12 genes known to have differential expression in cell lines grown under normal and hypoxic conditions. Quantitative and qualitative comparisons to real-time PCR are presented. It is also demonstrated that the technique is capable of detecting submicroscopic chromosomal DNA deletions.

Clinical Chemistry, 2009

Background: Quantitative PCR (qPCR) is a valuable technique for accurately and reliably profiling and quantifying gene expression. Typically, samples obtained from the organism of study have to be processed via several preparative steps before qPCR.Method: We estimated the errors of sample withdrawal and extraction, reverse transcription (RT), and qPCR that are introduced into measurements of mRNA concentrations. We performed hierarchically arranged experiments with 3 animals, 3 samples, 3 RT reactions, and 3 qPCRs and quantified the expression of several genes in solid tissue, blood, cell culture, and single cells.Results: A nested ANOVA design was used to model the experiments, and relative and absolute errors were calculated with this model for each processing level in the hierarchical design. We found that intersubject differences became easily confounded by sample heterogeneity for single cells and solid tissue. In cell cultures and blood, the noise from the RT and qPCR steps c...

Biological Procedures Online, 2001

We describe a semiquantitative RT-PCR protocol optimized in our laboratory to extract RNA from as little as 10,000 cells and to measure the expression levels of several target mRNAs from each sample. This procedure was optimized on the human erythroleukemia cell line TF-1 but was successfully used on primary cells and on different cell lines. We describe the detailed procedure for the analysis of Bcl-2 levels. Aldolase A was used as an internal control to normalize for sample to sample variations in total RNA amounts and for reaction efficiency. As for all quantitative techniques, great care must be taken in all optimization steps: the necessary controls to ensure a rough quantitative (semi-quantitative) analysis are described here, together with an example from a study on the effects of TGF-β1 in TF-1 cells.

THE PLANT CELL ONLINE, 2009

Nucleic Acids Research, 2009

Despite the central role of quantitative PCR (qPCR) in the quantification of mRNA transcripts, most analyses of qPCR data are still delegated to the software that comes with the qPCR apparatus. This is especially true for the handling of the fluorescence baseline. This article shows that baseline estimation errors are directly reflected in the observed PCR efficiency values and are thus propagated exponentially in the estimated starting concentrations as well as 'fold-difference' results. Because of the unknown origin and kinetics of the baseline fluorescence, the fluorescence values monitored in the initial cycles of the PCR reaction cannot be used to estimate a useful baseline value. An algorithm that estimates the baseline by reconstructing the loglinear phase downward from the early plateau phase of the PCR reaction was developed and shown to lead to very reproducible PCR efficiency values. PCR efficiency values were determined per sample by fitting a regression line to a subset of data points in the log-linear phase. The variability, as well as the bias, in qPCR results was significantly reduced when the mean of these PCR efficiencies per amplicon was used in the calculation of an estimate of the starting concentration per sample.

of the target gene relative to some reference group The two most commonly used methods to analyze data from such as an untreated control or a sample at time zero real-time, quantitative PCR experiments are absolute quantifica-in a time-course study. tion and relative quantification. Absolute quantification deter-Absolute quantification should be performed in situ-mines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal ations where it is necessary to determine the absolute of the target transcript in a treatment group to that of another transcript copy number. Absolute quantification has sample such as an untreated control. The 2 CT method is a been combined with real-time PCR and numerous re-convenient way to analyze the relative changes in gene expression ports have appeared in the literature (6-9) including from real-time quantitative PCR experiments. The purpose of this two articles in this issue (10, 11). In some situations, report is to present the derivation, assumptions, and applications it may be unnecessary to determine the absolute tran-of the 2 CT method. In addition, we present the derivation and script copy number and reporting the relative change applications of two variations of the 2 CT method that may be useful in the analysis of real-time, quantitative PCR data. 2001 in gene expression will suffice. For example, stating Elsevier Science (USA) that a given treatment increased the expression of Key Words: reverse transcription polymerase chain reaction; gene x by 2.5-fold may be more relevant than stating quantitative polymerase chain reaction; relative quantification; that the treatment increased the expression of gene x real-time polymerase chain reaction; Taq Man. from 1000 copies to 2500 copies per cell. Quantifying the relative changes in gene expression using real-time PCR requires certain equations, assumptions , and the testing of these assumptions to Reserve transcription combined with the polymer-properly analyze the data. The 2 C T method may be ase chain reaction (RT-PCR) has proven to be a power-used to calculate relative changes in gene expression ful method to quantify gene expression (1-3). Real-determined from real-time quantitative PCR experi-time PCR technology has been adapted to perform ments. Derivation of the 2 C T equation, including quantitative RT-PCR (4, 5). Two different methods of assumptions, experimental design, and validation analyzing data from real-time, quantitative PCR ex-tests, have been described in Applied Biosystems User periments exist: absolute quantification and relative Bulletin No. 2 (P/N 4303859). Analyses of gene expres-quantification. Absolute quantification determines the sion data using the 2 C T method have appeared in input copy number of the transcript of interest, usually the literature (5, 6). The purpose of this report is to by relating the PCR signal to a standard curve. Rela-present the derivation of the 2 C T method, assump-tive quantification describes the change in expression tions involved in using the method, and applications of this method for the general literature. In addition, we present the derivation and application of two variations of the 2 C T method that may be useful in the 1 To whom requests for reprints should be addressed. Fax: (509) 335-5902. analysis of real-time quantitative PCR data. 402 1046-2023/01 $35.00 2001 Elsevier Science (USA) All rights reserved.