CHAPTER 38
Concepts of Real‐Time PCR Data Analysis

RK Choudhary

School of Animal Biotechnology, GADVASU, Ludhiana

38.1 INTRODUCTION

Real‐time quantitative polymerase chain reaction (RT‐qPCR) is used for various applications in basic research, including analyses of gene expression, detection of single nucleotide polymorphism (SNP), and cancer screening. In contrast to conventional PCR, where amplicon is identified by running gel after completion of PCR, in RT‐qPCR, the end production is visualized in “real time” as the product is amplified in the PCR machine. Real‐time detection of amplified product is made possible by the addition of fluorescent dyes in a primer/probe/reaction mixture that reports amplified DNA following each cycle. The intensity of the fluorescent signal is proportional to the amount of template cDNA.

38.2 GETTING STARTED WITH RT‐qPCR

38.2.1 How it works

To understand how RT‐qPCR works, let us consider an example of a sample’s amplification plot (Figure 38.1). Features of amplification plots are:

  1. The X‐axis represents the number of PCR cycles, and the Y‐axis represents fluorescence generated from the PCR reaction.
  2. Phases of amplification plot comprising two phases:
    • exponential: the amount of qPCR‐product is doubled in each cycle;
    • non‐exponential phase: the reaction reaches a plateau, due to exhaustion of one or more PCR‐ingredients in the reaction mixture.
  3. The threshold cycle (Ct) or quantitation cycle (Cq) value: initially, although the product is amplified exponentially, fluorescence is non‐detectable (from 1–18 cycles in this figure) unless a threshold level of PCR products is achieved. The cycle number (here, 21 cycles of PCR) at which the accumulated product is detectable is called the threshold cycle or Ct value (or Cq = 21 cycles in figure 38.1).
  4. Ct or Cq value is determined by the amount of template present in the reaction. The higher the amount of template, the earlier the Ct, value and vice versa. This forms the basis of quantification of nucleic acid in RT‐qPCR.
Amplification plot of RT‐qPCR with an S-shaped curve through the exponential and non-exponential plateau phases (left and right portions) with arrow depicting the Cq value and a dashed line depicting the threshold line.

FIGURE 38.1 Amplification plot of RT‐qPCR.

38.2.2 Hallmarks of RT‐qPCR

For accurate and reproducible quantification, an optimal PCR assay is required. An optimized PCR assay should have:

  1. Linear standard curve, determined by coefficient of determination (R2) = 0.98.
  2. High amplification efficiency = 95–105%.
  3. The consistency of Ct value across all replicates (usually three replicates).

To access PCR optimization, a ten‐fold serial dilution of cDNA is employed. A perfect doubling occurs after each amplification cycle; then the span of two consecutive fluorescence will be 2n = dilution factor. If the dilution factor is ten‐fold then 2n = 10 or n = log2(10) = 3.32. This means that the Ct value should be separated by 3.32 cycles, if amplification is perfect. An amplification efficiency of < 90% or > 105% needs optimization of qPCR.

log10(template) line fit plot displaying square plots representing predicted Ct(Gene1) and diamond plots representing Ct(Gene1) lying on a negative slope solid line representing linear (predicted Ct(Gene1)).

FIGURE 38.2 Construction of standard curve. Construct standard curves for both target and reference genes individually, by plotting Ct values (through the Y‐axis) against the log10(template amount or dilution) along the X‐axis.

38.3 PCR FLUORESCENCE CHEMISTRY

Select the appropriate fluorescent dye to monitor the amplification signal. Two types of fluorescent reporters are available:

  • DNA‐binding dyes, e.g., SYBR green.
  • fluorescent dye‐labeled oligonucleotide probes/primers (molecular beacons, TaqMan, scorpion, LUX, Eclips and other newer dyes).

Of these, TaqMan hydrolysis probes are the most common dye‐labeled chemistries used.

SYBR Green is the most commonly used DNA‐binding dye used in real‐time qPCR chemistry. SYBR is a fluorophore that binds to the minor groove of double‐stranded DNA. It is used in quantitative PCR (qPCR) to determine the amount of amplicon generated following each cycle. When SYBR green dye is free in solution that is unbound to DNA, it emits a small signal. However, when the dye is bound with double‐stranded DNA, it emits a fluorescence signal that is 1000 times more intense.

Schematic of the binding of SYBR Green fluorophore with double-stranded DBA, displaying 4-point stars and horizontal lines representing the SYBR Green and DNA, respectively, with downward dashed arrow labeled PCR.

FIGURE 38.3 SYBR Green fluorophore binds with double‐stranded DNA (PCR amplicon). The amount of DNA amplified is proportional to fluorescence intensity.

The SYBR Green1 assay includes PCR primers that amplify a target gene or region of the gene, and SYBR green dye to detect amplified product. Students can refer to the previous chapter for information on primer designing. A SYBR Green assay reaction mixture contains the following reagents:

  1. PCR master mix with SYBR green;
  2. template (your cDNA samples);
  3. a pair of primers (gene‐specific).

Identify melting temperature for gene‐specific primer and construct a standard curve to know your PCR efficiency, before you proceed with your real assay of entire samples.

38.4 RT‐qPCR DATA ANALYSIS: GENE EXPRESSION ANALYSIS

Real‐time qPCR is a method to determine the amount of nucleic acid in a sample. However, merely knowing the amount of nucleic acid (say, 10 000 mRNA molecule of prolactin) in one sample is not meaningful. Rather, biologists need to know how much more mRNA is present in normal vs. diseased sample, or fold change of mRNA in normal vs. diseased sample. There are two methods for identification of nucleic acid in samples – absolute and relative quantification.

38.4.1 Absolute quantification

This compares the Ct value of test samples with a standard curve. The result of this analysis would be copy number or μg of mRNA per cell, or per μg of total RNA. A known amount of cDNA or DNA or PCR product could be used to make a standard curve. This standard curve generates a regression line on which basis the amount of unknown samples can be determined (Figure 38.4). The absolute quantification method is used when we are interested in determining the intrinsic property of a sample. The quantity of virus particles per ml of blood, for example, is a quantitative description of a sample.

Log starting quantity vs. Cq displaying a negative slope line with circles and “x” markers representing standard and unknown, respectively.

FIGURE 38.4 Absolute quantification of the transcript using the standard curve method. Using a known amount of DNA, a standard curve is made, and unknown samples are plotted on a regression line of known samples.

38.4.2 Relative quantification

In relative quantification, the result is a ratio of Sample A vs. Sample B, expressed in terms of fold change. Suppose a researcher wants to know the relative amount (fold change) of c‐Myc gene (an oncogene) in a normal sample vs. a suspected case of cancer sample. There are two approaches to this:

  1. Relative quantification against unit mass (say, cell number or μg of RNA).
  2. Relative quantification, normalized to reference gene.

Example of relative quantification against unit mass: to determine the relative expression of the c‐Myc gene in normal vs. cancer tissue, obtain RNA from an equal number of cells or tissue mass. Determine Ct value of the test sample (cancer cells) from a calibrator sample (normal cells). If the efficiency of PCR reaction is 100%, then the amount of product amplified in each cycle is doubled (i.e., E = 2).

Cycles vs. RFU displaying ascending solid curves and two ascending curves with triangle markers and a horizontal solid line.

FIGURE 38.5 Relative quantification of RT‐qPCR transcript measurement, always expressed in terms of two samples (say, sample A in comparison to Sample B). Relative expression is measured in terms of fold change (either positive or negative fold change). Positive fold change indicates upregulation of genes in the A vs. B sample, whereas negative fold change indicates downregulation of genes in the A vs. B sample.

images
  1. Cancer cells = 50 ng of RNA; normal cell = 50 ng of RNA – keep same amount of RNA (remember the concept of unit mass!).
  2. C t of cancer cell (test) = 12 and Ct of normal cell (calibrator) = 15.
  3. Then, Ratio(test/calibrator) = 2(15–12) = 8

This means there is eight‐fold higher expression of the c‐Myc gene in the cancer sample.

Relative quantification normalized to reference genes (e.g., beta‐actin, GAPDH) circumvents the use of an equal amount of starting material (RNA) from the samples. This method is preferred if the starting material is in limited quantity. However, knowledge of reference genes, in this case, is needed. In contrast to two Ct values that were needed with relative quantification with unit mass, four Ct values are needed.

TestCalibrator
Target geneCt (target, test)Ct (target, calibrator)
Reference geneCt (Reference, test)Ct (Reference, calibrator)

This can be analyzed using three different methods:

  1. Livak method or 2–ΔΔCt method (Livak and Schmittgen, 2001).
  2. ΔCt method using reference gene (Schmittgen and Livak, 2008).
  3. Pfaffl method (Pfaffl, 2001).

This chapter describes only the Livak method (or 2–ΔΔCt method).

images

2−ΔΔCt = normalized expression ratio

See the example below to understand this better:

SampleCt (c‐Myc) = TargetCt (GAPDH) = Reference
Normal (calibrator)1516.5
Cancer (test)1215.9
images

Finally, normalized expression ratio = 2 –ΔΔCt = 2 –(–2.4) = 5.3

Therefore, the tumor cell (test samples) is expressing c‐Myc gene 5.3 times higher than the normal cell.

An overview of the workflow of real‐time qPCR experiment is given in Figure 38.6 (obtained from the Web).

Analytical flow diagram of the use of real‐time PCR starting from “Experiment Design” to “qPCR run”, to “Statistical data analysis” and to “Graphical visualization.”

FIGURE 38.6 Analytical flow diagram of the use of real‐time PCR.

38.5 QUESTIONS

  1. 1. Define the Ct value.
  2. 2. What is the difference between PCR and RT‐qPCR?
  3. 3. Explain the difference between relative and absolute quantification of gene expression in RT‐qPCR.
  4. 4. Describe how to generate a standard curve in qPCR analyses.
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