Real-Time Relative RT-PCR: How It's Done
| The information desired from most expression studies is not the absolute molar amount of an mRNA in an experimental sample, but how the relative level of gene expression varies between samples. For these relative quantitative experiments, real-time RT-PCR is both a cost-effective and time effective technique. |
Experimental Set-up
Typically, in real-time relative RT-PCR, a standard curve is generated from a dilution series constructed from a "reference" sample. The identity of the reference sample is not important (it can be a single RNA sample, pooled RNA, genomic DNA, cDNA, or even a cloned DNA), as long as the relevant PCR target is present. For accurate relative quantitation, it is essential that the dilution series from which the standard curve is generated be carefully prepared. The units used to describe the dilution series are relative, not absolute values, are based on the dilution factor, and can be expressed as such (e.g. 1 fold, 10 fold, 1000 fold, etc) or expressed as equivalent mass amounts (e.g. 100 ng, 10 ng, 1 ng, etc).
Real-time PCR is performed on both the experimental samples and reference standards. Relative values for target abundance in each experimental sample is extrapolated from the standard curve generated from the reference standard. While the absolute values calculated for the experimental samples are meaningless, the relative differences in mRNA abundance between samples are accurate. When analyzing numerous samples, one sample is typically designated as the "calibrator" (or 1X sample), and the relative expression levels of all other samples are then expressed relative to the calibrator sample.
Real-time PCR is performed on both the experimental samples and reference standards. Relative values for target abundance in each experimental sample is extrapolated from the standard curve generated from the reference standard. While the absolute values calculated for the experimental samples are meaningless, the relative differences in mRNA abundance between samples are accurate. When analyzing numerous samples, one sample is typically designated as the "calibrator" (or 1X sample), and the relative expression levels of all other samples are then expressed relative to the calibrator sample.
Improving Data Reliability by Including an Exogenous Control
The reliability of any relative RT-PCR experiment can be improved by including an invariant endogenous control in the assay to correct for sample to sample variations in RT-PCR efficiency and errors in sample quantitation. Because of its invariant expression across tissues and treatments, 18S rRNA is an ideal internal control for quantitative RNA analysis.
To perform real-time RT-PCR analysis with an invariant control, a second set of PCR reactions is performed for the invariant endogenous control on both the reference dilution series and experimental samples. Relative abundance values are then calculated for 18S rRNA as well as for the experimental sequence. For each experimental sample, the relative abundance value obtained is divided by the value derived from the control sequence (18S rRNA) in the corresponding PCR. The normalized values for different samples can then be directly compared as described above.
To perform real-time RT-PCR analysis with an invariant control, a second set of PCR reactions is performed for the invariant endogenous control on both the reference dilution series and experimental samples. Relative abundance values are then calculated for 18S rRNA as well as for the experimental sequence. For each experimental sample, the relative abundance value obtained is divided by the value derived from the control sequence (18S rRNA) in the corresponding PCR. The normalized values for different samples can then be directly compared as described above.
A Real Life Example
To demonstrate the utility of standard curve methodology and 18S rRNA normalization in real-time RT-PCR, an experiment was performed in which we quantified alpha-2 macroglobulin levels in mouse liver, spleen, kidney, and ovary RNA samples. Two standard curves (alpha-2 macroglobulin and 18S rRNA) were constructed from a dilution series of a reference cDNA sample (Figure 1). The raw abundance values for alpha-2 macroglobulin (a2 M, Table 1, column A) were divided by the 18S values for the same samples (column B) to derive a normalized value for each sample (column C). The kidney RNA sample was arbitrarily designated as the calibrator sample (abundance set to 1X) and the normalized values for the remaining samples are expressed as x-fold of 1X (column D). Note that without using 18S rRNA as a normalization standard, the error based on differences in amount of RNA present and variations in RT efficiency would be quite large (compare column A to column D).
Table 1. Relative Abundance of alpha-2 macroglobulin in Mouse Tissues Determined by Real-time RT-PCR.
Figure 1. Real-time RT-PCR Standard Curves. Standard Curves for alpha-2 macroglobulin and 18S rRNA derived from a dilution series of a reference RNA by real-time RT-PCR.
| | A | B | C | D |
|---|---|---|---|---|
| Raw Values | Normalized | Relative | ||
| a2 M | 18S | a2 M/18S | Value | |
| Sample 1: kidney | 82 | 3592 | 0.023 | 1.0 |
| Sample 2: liver | 18351 | 8966 | 2.05 | 90.0 |
| Sample 3: ovary | 44 | 1669 | 0.03 | 1.1 |
| Sample 4: spleen | 1 | 8 | 0.13 | 5.6 |
Table 1. Relative Abundance of alpha-2 macroglobulin in Mouse Tissues Determined by Real-time RT-PCR.
Figure 1. Real-time RT-PCR Standard Curves. Standard Curves for alpha-2 macroglobulin and 18S rRNA derived from a dilution series of a reference RNA by real-time RT-PCR.
