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When calculating the results of your real-time PCR (qPCR) experiment, you can use either absolute or relative quantitation.
| Absolute vs. Relative Quantitation at a Glance | ||
| Absolute Quantitation | Relative Quantiation | |
| Overview
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In absolute quantitation, you quantitate unknowns based on a known quantity. First you create a standard curve; then you compare unknowns to the standard curve and extrapolate a value. | In relative quantitation, you analyze changes in gene expression in a given sample relative to another reference sample (such as an untreated control sample). |
| Example | Correlating viral copy number with a disease state. | Measuring gene expression in response to a drug. In this example, you would compare the level of gene expression of a particular gene of interest in a chemically treated sample relative to the level of gene expression in an untreated sample. |
Absolute Quantitation Using the Standard Curve Method
The standard curve method for absolute quantitation is similar to the standard curve method for relative quantitation, except the absolute quantities of the standards must first be known by some independent means.
| Figure 1: Amplification Plot and Standard Curve for Absolute Quantitation |
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Critical Guidelines
The guidelines below are critical for proper use of the standard curve method for absolute quantitation:
It is generally not possible to use DNA as a standard for absolute quantitation of RNA because there is no control for the efficiency of the reverse transcription step.
Standards
The absolute quantities of the standards must first be known by some independent means. Plasmid DNA and in vitro transcribed RNA are commonly used to prepare absolute standards. Concentration is measured by A260 and converted to the number of copies using the molecular weight of the DNA or RNA.
Relative Quantation
Calculation Methods for Relative Quantitation
Relative quantitation can be performed with data from all real-time PCR instruments. The calculation methods used for relative quantitation are:
| Figure 2: Relative Quantiation |
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Which Method Should I Use?
| Standard Curve Method | Comparative CT Method | |
| Overview | It is easy to prepare standard curves for relative quantitation because quantity is expressed relative to some basis sample (called a calibrator), such as an untreated control. For all experimental samples, you determine target quantity from the standard curve and divide by the target quantity of the calibrator. Thus, the calibrator becomes the 1× sample, and all other quantities are expressed as an n-fold difference relative to the calibrator. |
This method compares the Ct value of one target gene to another (using the formula: 2ΔΔCT)—for example, an internal control or reference gene (e.g., housekeeping gene)—in a single sample. |
| Advantages | Running the target and endogenous control amplifications in separate tubes and using the standard curve method of analysis requires the least amount of optimization and validation. |
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| Experimental Validation | See Advantages above. |
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| Critical Guidelines |
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For the comparative CT method to be valid, the efficiency of the target amplification (your gene of interest) and the efficiency of the reference amplification (your endogenous control) must be approximately equal. |
| Endogenous Control | Amplification of an endogenous control may be performed to standardize the amount of sample RNA or DNA added to a reaction. For the quantitation of gene expression, researchers have used ß-actin, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal RNA (rRNA), or other RNAs as an endogenous control. | |
| Standards | Because the sample quantity is divided by the calibrator quantity, the unit from the standard curve drops out. Thus, all that is required of the standards is that their relative dilutions be known. For relative quantitation, this means any stock RNA or DNA containing the appropriate target can be used to prepare standards. |