Real-time PCR
handbook
Single-tube assays
96- and 384-well plates
384-well TaqMan Array Cards
OpenArray plates
Commonly used formats for real-time PCR.
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3
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	 Basics of real-time PCR
	 Digital PCR
	 Experimental design
	 Plate preparation
	 Data analysis
	Troubleshooting
Basics of real-time PCR
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1.1	Introduction	 2
1.2	 Overview of real-time PCR	 3
1.3	 Overview of real-time	 4
PCR components
1.4	 Real-time PCR analysis technology	 6
1.5	 Real-time PCR fluorescence	 10
detection systems
1.6	 Melting curve analysis	 14
1.7	 Passive reference dyes	 15
1.8	 Contamination prevention	 16
1.9	 Multiplex real-time PCR	 16
1.10	Internal controls and	 18
reference genes
1.11 Real-time PCR	 19
instrument calibration
1
Basics of real-time PCR
Contents
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1.1	Introduction
The polymerase chain reaction (PCR) is one of the most
powerful technologies in molecular biology. Using PCR,
specific sequences within a DNA or complementary
DNA (cDNA) template can be copied, or “amplified,”
many thousand- to million-fold using sequencespecific
oligonucleotides, heat-stable DNA polymerase,
and thermal cycling. In traditional (endpoint) PCR,
detection and quantification of the amplified sequence
are performed at the end of the reaction after the last
PCR cycle, and involve post-PCR analysis such as
gel electrophoresis and image analysis. In real-time
quantitative PCR (often shortened to real-time PCR or
qPCR), PCR product is measured at each cycle. By
monitoring reactions during the exponential amplification
phase of the reaction, users can determine the initial
quantity of the target with great precision.
PCR theoretically amplifies DNA exponentially, doubling
the number of target molecules with each amplification
cycle. When it was first developed, scientists reasoned
that the number of cycles and the amount of PCR endproduct
could be used to calculate the initial quantity of
genetic material by comparison with a known standard. To
address the need for robust quantification, the technique
of real-time PCR was developed. Currently, endpoint PCR
is used mostly to amplify specific DNA for sequencing,
cloning, and use in other molecular biology techniques.
In real-time PCR, the amount of DNA is measured after
each cycle via fluorescent dyes that yield increasing
fluorescent signal in direct proportion to the number of
PCR product molecules (amplicons) generated. Data
collected in the exponential phase of the reaction yield
quantitative information on the starting quantity of the
amplification target. Fluorescent reporters used in
real-time PCR include double-stranded DNA (dsDNA)–
binding dyes, or dye molecules attached to PCR
primers or probes that hybridize with PCR products
during amplification.
The change in fluorescence over the course of the
reaction is measured by an instrument that combines
thermal cycling with fluorescent dye scanning capability.
By plotting fluorescence against the cycle number, the
real-time PCR instrument generates an amplification plot
that represents the accumulation of product over the
duration of the entire PCR (Figure 1).
The advantages of real-time PCR include:
•	 Ability to monitor the progress of individual PCR
reactions as they occur in real time
•	 Ability to precisely measure the amount of amplicon at
each cycle, which allows highly accurate quantification
of the amount of starting material in samples
•	 An increased dynamic range of detection
•	 Amplification and detection occur in a single tube,
eliminating post-PCR manipulations
Over the past several years, real-time PCR has become
the leading tool for the detection and quantification of
DNA or RNA. Using these techniques allows precise
detection that is accurate within a 2-fold range, with a
dynamic range of input material covering 6 to 8 orders
of magnitude.
1.2	 Overview of real-time PCR
This section provides an overview of the steps involved
in performing real-time PCR. Real-time PCR is a variation
of the standard PCR technique that is commonly used
to quantify DNA or RNA in a sample. Using sequencespecific
primers, the number of copies of a particular DNA
or RNA sequence can be determined. By measuring the
amount of amplified product at each stage during the PCR
cycle, quantification is possible. If a particular sequence
(DNA or RNA) is abundant in the sample, amplification
is observed in earlier cycles; if the sequence is scarce,
amplification is observed in later cycles. Quantification of
amplified product is obtained using fluorescent probes
or fluorescent DNA-binding dyes and real-time PCR
instruments that measure fluorescence while performing
the thermal cycling for PCR.
Real-time PCR steps
There are three major steps that make up each cycle in
real-time PCR. Reactions are generally run for 40 cycles.
1.	Denaturation—high-temperature incubation is used to
“melt” dsDNA into single strands and loosen secondary
structure in single-stranded DNA (ssDNA). The highest
temperature that the DNA polymerase can withstand is
typically used (usually 95°C). The denaturation time can
be increased if template GC content is high.
2.	Annealing—during annealing, complementary
sequences have an opportunity to hybridize, so an
appropriate temperature is used that is based on the
calculated melting temperature (Tm
) of the primers
(typically 5°C below the Tm
of the primer).
3.	Extension—at 70–72°C, the activity of the DNA
polymerase is optimal, and primer extension occurs
at rates of up to 100 bases per second. When an
amplicon in real-time PCR is small, this step is often
combined with the annealing step, using 60°C as
the temperature.
Two-step qRT-PCR
Two-step quantitative reverse-transcription PCR (qRTPCR)
starts with the reverse transcription of either
total RNA or poly(A) RNA into cDNA using a reverse
transcriptase. This first-strand cDNA synthesis reaction
can be primed using random primers, oligo(dT), or genespecific
primers. To give an equal representation of all
targets in real-time PCR applications and to avoid the 3ʹ
bias of oligo(dT) primers, many researchers use random
primers or a mixture of oligo(dT) and random primers.
The temperature used for cDNA synthesis depends on the
reverse transcriptase chosen. After reverse transcription,
approximately 10% of the cDNA is transferred to a
separate tube for real-time PCR.
One-step qRT-PCR
One-step qRT-PCR combines the first-strand cDNA
synthesis reaction and real-time PCR reaction in the
same tube, simplifying reaction setup and reducing the
possibility of contamination. Gene-specific primers are
required. This is because using oligo(dT) or random
primers will generate nonspecific products in the one-step
procedure and reduce the amount of product of interest.
Figure 1. Relative fluorescence vs. cycle number. Amplification plots are created when the fluorescent signal from each sample is plotted
against cycle number; therefore, amplification plots represent the accumulation of product over the duration of the real-time PCR experiment.
The samples used to create the plots in this figure are a dilution series of the target DNA sequence. NTC, no-template control.
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1.3	 Overview of real-time PCR components
This section provides an overview of the major reaction
components and parameters involved in real-time PCR
experiments. A more detailed discussion of specific
components like reporter dyes, passive reference
dyes, and uracil DNA glycosylase (UDG) is provided in
subsequent sections of this handbook.
DNA polymerase
PCR performance is often related to the thermostable
DNA polymerase, so enzyme selection is critical to
success. One of the main factors affecting PCR specificity
is the fact that Taq DNA polymerase has residual activity
at low temperatures. Primers can anneal nonspecifically
to DNA during reaction setup, allowing the polymerase
to synthesize nonspecific product. The problem of
nonspecific products resulting from mispriming can be
minimized by using a “hot-start” enzyme. Using a hot-start
enzyme ensures that DNA polymerase is not active during
reaction setup and the initial DNA denaturation step.
Reverse transcriptase
The reverse transcriptase is as critical to the success
of qRT-PCR as the DNA polymerase. It is important to
choose a reverse transcriptase that not only provides high
yields of full-length cDNA, but also has good activity at
high temperatures. High-temperature performance is also
very important for denaturation of RNA with secondary
structure. In one-step qRT-PCR, a reverse transcriptase
that retains its activity at higher temperatures allows
use of a gene-specific primer with a high Tm
, increasing
specificity and reducing background.
dNTPs
It is a good idea to purchase both the dNTPs and the
thermostable DNA polymerase from the same vendor,
as it is not uncommon to see a loss in sensitivity of one
full threshold cycle (Ct
) in experiments that employ these
reagents from separate vendors.
Magnesium concentration
In real-time PCR, magnesium chloride or magnesium
sulfate is typically used at a final concentration of 3 mM.
This concentration works well for most targets; however,
the optimal magnesium concentration may vary between
3 and 6 mM.
Good experimental technique
Do not underestimate the importance of good laboratory
technique. It is best to use dedicated equipment and
solutions for each stage of the reactions, from preparation
of the template to post-PCR analysis. The use of aerosolbarrier
tips and screwcap tubes can help decrease
cross-contamination problems. To obtain tight data from
replicates (ideally, triplicates), prepare a master mix that
contains all the reaction components except sample. The
use of a master mix reduces the number of pipetting steps
and, consequently, reduces the chances of cross-well
contamination and other pipetting errors.
Template
Use 10 to 1,000 copies of template nucleic acid for each
real-time PCR reaction. This is equivalent to approximately
100 pg to 1 μg of genomic DNA (gDNA), or cDNA
generated from 1 pg to 100 ng of total RNA. Excess
template may also bring higher contaminant levels that
can greatly reduce PCR efficiency. Depending on the
specificity of the PCR primers for cDNA rather than gDNA,
it may be important to treat RNA templates to reduce the
chance that they contain gDNA contamination. One option
is to treat the template with DNase I.
Pure, intact RNA is essential for full-length, high-quality
cDNA synthesis and may be important for accurate
mRNA quantification. RNA should be devoid of any
RNase contamination, and aseptic conditions should be
maintained. Total RNA typically works well in qRT-PCR;
isolation of mRNA is typically not necessary, although it
may improve the yield of specific cDNAs.
Real-time PCR primer design
Good primer design is one of the most important
parameters in real-time PCR. This is why many
researchers choose to purchase Applied Biosystems™
TaqMan™
Assay products—primers and probes for
real-time PCR designed using a proven algorithm and
trusted by scientists around the world. When designing
real-time PCR primers, keep in mind that the amplicon
length should be approximately 50–150 bp, since longer
products do not amplify as efficiently.
In general, primers should be 18–24 nucleotides in length.
This provides for practical annealing temperatures.
Primers should be designed according to standard
PCR guidelines. They should be specific for the target
sequence and be free of internal secondary structure.
Primers should avoid stretches of homopolymer
sequences (e.g., poly(dG)) or repeating motifs, as these
can hybridize inappropriately.
Primer pairs should have compatible melting temperatures
(within 1°C) and contain approximately 50% GC content.
Primers with high GC content can form stable imperfect
hybrids. Conversely, high AT content depresses the Tm
of
perfectly matched hybrids. If possible, the 3ʹ end of the
primer should be GC-rich to enhance annealing of the end
that will be extended. Analyze primer pair sequences to
avoid complementarity and hybridization between primers
(primer-dimers).
For qRT-PCR, design primers that anneal to exons on
both sides of an intron (or span an exon/exon boundary of
the mRNA) to allow differentiation between amplification of
cDNA and potential contaminating gDNA by melting curve
analysis. To confirm the specificity of primers, perform a
BLAST™
search against public databases to be sure that
they only recognize the target of interest.
Optimal results may require a titration of primer
concentrations between 50 and 500 nM. A final
concentration of 200 nM for each primer is effective for
most reactions.
Primer design software
Primer design software programs, such as Invitrogen™
OligoPerfect™
designer and Applied Biosystems™
Primer
Express™
software, in addition to sequence analysis
software, such as Invitrogen™
Vector NTI™
Software, can
automatically evaluate a target sequence and design
primers for it based on the criteria previously discussed.
At a minimum, using primer design software will ensure
that primers are specific for the target sequence and free
of internal secondary structure, and avoid complementary
hybridization at 3ʹ ends within each primer and with each
other. As mentioned previously, good primer design
is especially critical when using DNA-binding dyes for
amplicon detection.
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1.4	 Real-time PCR analysis technology
This section defines the major terms used in real-time
PCR analysis.
Baseline
The baseline of the real-time PCR reaction refers to the
signal level during the initial cycles of PCR, usually cycles
3 to 15, in which there is little change in fluorescent signal.
The low-level signal of the baseline can be equated to the
background or the “noise” of the reaction (Figure 2). The
baseline in real-time PCR is determined empirically for
each reaction, by user analysis or automated analysis of
the amplification plot. The baseline should be set carefully
to allow accurate determination of the threshold cycle (Ct
),
defined below. The baseline determination should take
into account enough cycles to eliminate the background
found in the early cycles of amplification, but should not
include the cycles in which the amplification signal begins
to rise above background. When comparing different realtime
PCR reactions or experiments, the baseline should
be defined in the same way for each (Figure 2).
Threshold
The threshold of the real-time PCR reaction is the level
of signal that reflects a statistically significant increase
over the calculated baseline signal (Figure 2). It is set
to distinguish relevant amplification signal from the
background. Usually, real-time PCR instrument software
automatically sets the threshold at 10 times the standard
deviation of the fluorescence value of the baseline.
However, the position of the threshold can be set at any
point in the exponential phase of PCR.
Threshold cycle (Ct
)
Ct
is the cycle number at which the fluorescent signal
of the reaction crosses the threshold. The Ct
is used to
calculate the initial DNA copy number, because the Ct
value is inversely related to the starting amount of target.
For example, in comparing real-time PCR results from
samples containing different amounts of target, a sample
with twice the starting amount will yield a Ct
value one
cycle earlier than a sample with half the number of copies
of the target. This assumes that the PCR is operating
at 100% efficiency (i.e., the amount of product doubles
perfectly during each cycle) in both reactions.
As the template amount decreases, the cycle number at
which significant amplification is seen increases. With a
10-fold dilution series, the Ct
values are ~3.3 cycles apart
(Figure 3).
Standard curve
A dilution series of known template concentrations can
be used to establish a standard curve for determining
the initial starting amount of the target template in
experimental samples or for assessing the reaction
efficiency (Figure 4). The log of each known concentration
in the dilution series (x-axis) is plotted against the Ct
value for that concentration (y-axis). From this standard
curve, information about the performance of the reaction
as well as various reaction parameters (including slope,
y-intercept, and correlation coefficient) can be derived.
The concentrations chosen for the standard curve should
encompass the expected concentration range of the
target in the experimental samples.
Figure 2. The baseline and threshold of a real-time
PCR reaction.
Figure 3. Amplification plot for a 10-fold dilution series.
Correlation coefficient (R2
)
The correlation coefficient is a measure of how well the
data fit the standard curve. The R2
value reflects the
linearity of the standard curve. Ideally, R2
= 1, although
0.999 is generally the maximum value.
Y-intercept
The y-intercept corresponds to the theoretical limit of
detection of the reaction, or the Ct
value expected if the
lowest copy number of target molecules denoted on the
x-axis gave rise to statistically significant amplification.
Though PCR is theoretically capable of detecting a single
copy of a target, a copy number of 2–10 is commonly
specified as the lowest target level that can be reliably
quantified in real-time PCR applications. This limits the
usefulness of the y-intercept value as a direct measure of
sensitivity. However, the y-intercept value may be useful
for comparing different amplification systems and targets.
Exponential phase
It is important to quantify real-time PCR in the early part of
the exponential phase as opposed to in the later cycles or
when the reaction reaches the plateau. At the beginning
of the exponential phase, all reagents are still in excess,
the DNA polymerase is still highly efficient, and the
amplification product, which is present in a low amount,
will not compete with the primers’ annealing capabilities.
All of these factors contribute to more accurate data.
Slope
The slope of the log-linear phase of the amplification
reaction is a measure of reaction efficiency. To obtain
accurate and reproducible results, reactions should have
an efficiency as close to 100% as possible, equivalent to a
slope of –3.32 (see Efficiency, below, for more detail).
Efficiency
A PCR efficiency of 100% corresponds to a slope of
–3.32, as determined by the following equation:
Efficiency = 10(–1/slope)
– 1
Ideally, the efficiency of PCR should be 100%, meaning
the template doubles after each thermal cycle during
exponential amplification. The actual efficiency can give
valuable information about the reaction. Experimental
factors such as the length, secondary structure, and GC
content of the amplicon can influence efficiency. Other
conditions that may influence efficiency are the dynamics
of the reaction itself, the use of non-optimal reagent
concentrations, and enzyme quality, which can result in
efficiencies below 90%. The presence of PCR inhibitors
in one or more of the reagents can produce efficiencies
of greater than 110%. A good reaction should have an
efficiency between 90% and 110%, which corresponds to
a slope between –3.58 and –3.10.
Dynamic range
This is the range over which an increase in starting
material concentration results in a corresponding increase
in amplification product. Ideally, the dynamic range for
real-time PCR should be 7–8 orders of magnitude for
plasmid DNA and at least a 3–4 orders of magnitude for
cDNA or gDNA.
Absolute quantification
Absolute quantification describes a real-time PCR
experiment in which samples of known quantity are
serially diluted and then amplified to generate a standard
curve. Unknown samples are then quantified by
comparison with this curve.
Relative quantification
Relative quantification describes a real-time PCR
experiment in which the expression of a gene of interest
in one sample (i.e., treated) is compared to expression
of the same gene in another sample (i.e., untreated).
The results are expressed as fold change (increase or
decrease) in expression of the treated sample in relation to
the untreated sample. A normalizer gene (such as β-actin)
is used as a control for experimental variability in this type
of quantification.
Figure 4. Example of a standard curve of real-time PCR data.
A standard curve shows threshold cycle (Ct
) on the y-axis and
the starting quantity of RNA or DNA target on the x-axis. Slope,
y-intercept, and correlation coefficient values are used to provide
information about the performance of the reaction.
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Basics of real-time PCRBasics of real-time PCR
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Melting curve (dissociation curve)
A melting curve charts the change in fluorescence
observed when dsDNA with incorporated dye molecules
dissociates (“melts”) into single-stranded DNA (ssDNA)
as the temperature of the reaction is raised. For example,
when dsDNA bound with SYBR™
Green I dye is heated,
a sudden decrease in fluorescence is detected when the
melting temperature (Tm
) is reached, due to dissociation of
the DNA strands and subsequent release of the dye. The
fluorescence is plotted against temperature (Figure 5A),
and then the –ΔF/ΔT (change in fluorescence/change in
temperature) value is plotted against temperature to obtain
a clear view of the melting dynamics (Figure 5B).
Post-amplification melting-curve analysis is a simple,
straightforward way to check real-time PCR reactions for
primer-dimer artifacts and to ensure reaction specificity.
Because the melting temperature of nucleic acids is
affected by length, GC content, and the presence of base
mismatches, among other factors, different PCR products
can often be distinguished by their melting characteristics.
The characterization of reaction products (e.g., primerdimers
vs. amplicons) via melting curve analysis reduces
the need for time-consuming gel electrophoresis.
The typical real-time PCR data set shown in Figure 6
illustrates many of the terms that have been discussed.
Figure 6A illustrates a typical real-time PCR amplification
plot. During the early cycles of the PCR, there is little
change in the fluorescent signal. As the reaction
progresses, the level of fluorescence begins to increase
with each cycle. The reaction threshold is set above
the baseline in the exponential portion of the plot.
This threshold is used to assign the Ct
value of each
amplification reaction. Ct
values for a series of reactions
containing a known quantity of target can be used to
generate a standard curve. Quantification is performed
by comparing Ct
values for unknown samples against this
standard curve or, in the case of relative quantification,
against each other, with the standard curve serving as
an efficiency check. Ct
values are inversely related to the
amount of starting template: the higher the amount of
starting template in a reaction, the lower the Ct
value for
that reaction.
Figure 6B shows the standard curve generated from the
Ct
values in the amplification plot. The standard curve
provides important information regarding the amplification
efficiency, replicate consistency, and theoretical detection
limit of the reaction.
Figure 5. Melting curve analysis. (A) Melting curve and (B) –ΔF/ΔT
vs. temperature.
A
B
A
B
Figure 6. Amplification of RNase P DNA ranging from 1.25 x
103
to 2 x 104
copies. Real-time PCR of 2-fold serial dilutions of
human RNase P DNA was performed using a FAM™
dye–labeled
TaqMan Assay with Applied Biosystems™
TaqMan™
Universal Master
Mix II, under standard thermal cycling conditions on an Applied
Biosystems™
ViiA™
7 Real-Time PCR System. (A) Amplification plot.
(B) Standard curve showing copy number of template vs. Ct
.
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Basics of real-time PCRBasics of real-time PCR
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1.5	 Real-time PCR fluorescence detection systems
Real-time fluorescent PCR chemistries
Many real-time fluorescent PCR chemistries exist, but the
most widely used are 5ʹ nuclease assays such as TaqMan
Assays and SYBR Green dye–based assays (Figure 7).
The 5ʹ nuclease assay is named for the 5ʹ nuclease
activity associated with Taq DNA polymerase (Figure 8).
The 5ʹ nuclease domain has the ability to degrade DNA
bound to the template, downstream of DNA synthesis.
A second key element in the 5ʹ nuclease assay is a
phenomenon called fluorescence resonance energy
transfer (FRET). In FRET, the emissions of a fluorescent
dye can be strongly reduced by the presence of another
dye, often called the quencher, in close proximity.
FRET can be illustrated by two fluorescent dyes: green
and red (Figure 9). The green fluorescent dye has a higher
energy of emission compared to the red, because green
light has a shorter wavelength than red. If the red dye is in
close proximity to the green dye, excitation of the green
dye will cause its emitted energy to be transferred to the
red dye. In other words, energy is being transferred from a
higher to a lower level. Consequently, the signal from the
green dye will be suppressed or “quenched.” However,
if the two dyes are not in close proximity, FRET cannot
occur, so the green dye emits light with no loss of signal.
A 5ʹ nuclease assay for target detection or quantification
typically consists of two PCR primers and a TaqMan
probe (Figure 10).
Before PCR begins, the TaqMan probe is intact and has a
degree of flexibility. While the probe is intact, the reporter
and quencher have a natural affinity for each other,
allowing FRET to occur (Figure 11). The reporter signal is
quenched prior to PCR.
During PCR, the primers and probe anneal to the
target. DNA polymerase extends the primer upstream
of the probe. If the probe is bound to the correct target
sequence, the polymerase’s 5ʹ nuclease activity cleaves
the probe, releasing a fragment containing the reporter
dye. Once cleavage takes place, the reporter and
quencher dyes are no longer attracted to each other; the
released reporter molecule will no longer be quenched.
5ʹ nuclease assay specificity
Assay specificity is the degree to which the assay
includes signal from the target and excludes signal from
non-target in the results. Specificity is arguably the most
important aspect of any assay. The greatest threat to
assay specificity for 5ʹ nuclease assays is the presence
of homologs. Homologs are genes similar in sequence
to that of the target, but they are not the intended target
of the assay. Homologs are extremely common within
species and across related species.
Figure 7. Representation of a 5ʹ nuclease assay (left) and SYBR
Green dye binding to DNA (right).
Figure 8. A representation of Taq DNA polymerase. Each colored
sphere represents a protein domain.
Figure 9. Example of the FRET phenomenon. (A) FRET occurs
when a green light–emitting fluorescent dye is in close proximity to a
red light–emitting fluorescent dye. (B) FRET does not occur when the
two fluorescent dyes are not in close proximity.
5ʹ nuclease assays offer two tools for specificity: primers
and probes. A mismatch between the target and homolog
positioned at the 3ʹ-most base of the primer has maximal
impact on the specificity of the primer. A mismatch
further away from the 3ʹ end will have less impact on
specificity. In contrast, mismatches across most of the
length of an Applied Biosystems™
TaqMan™
MGB probe,
which is shorter than an Applied Biosystems™
TaqMan™
TAMRA™
probe, can have a strong impact on specificity—
TaqMan MGB probes are stronger tools for specificity
than primers.
For example, a 1- or 2-base random mismatch in
the primer binding site will very likely allow the DNA
polymerase to extend the primer bound to the homolog
with high efficiency. A 1- or 2-base extension by DNA
polymerase will stabilize the primer bound to the homolog,
so it is just as stably bound as primer bound to the
intended, fully complementary target. At that point, there
is nothing to prevent the DNA polymerase from continuing
synthesis to produce a copy of the homolog.
In contrast, mismatches on the 5ʹ end of the TaqMan
probe binding site cannot be stabilized by the DNA
polymerase due to the quencher block on the 3ʹ end.
Mismatches in a TaqMan MGB probe binding site will
reduce how tightly the probe is bound, so that instead
of cleavage, the intact probe is displaced. The intact
probe returns to its quenched configuration, so that when
data are collected at the end of the PCR cycle, signal is
produced from the target but not from the homolog, even
though the homolog is being amplified.
In addition to homologs, PCR may also amplify
nonspecific products produced by primers binding
to seemingly random locations in the sample DNA or
sometimes to themselves in so-called primer-dimers.
Since nonspecific products are unrelated to the target,
they do not have TaqMan probe binding sites, and thus
are not seen in the real-time PCR data.
TaqMan probe types
TaqMan probes may be divided into two types: MGB and
non-MGB. The first TaqMan probes could be classified as
non-MGB. They used TAMRA dye as the quencher. Early
in the development of real-time PCR, extensive testing
revealed that TaqMan probes required an annealing
temperature significantly higher than that of PCR primers
to allow cleavage to take place. TaqMan probes were
therefore longer than primers. A 1-base mismatch in
such long probes had a relatively mild effect on probe
binding, allowing cleavage to take place. However, for
many applications involving high genetic complexity, such
as eukaryotic gene expression and single-nucleotide
polymorphisms (SNPs), a higher degree of specificity
was desirable.
TaqMan MGB probes were a later refinement of the
TaqMan probe technology. TaqMan MGB probes possess
a minor-groove binding (MGB) molecule on the 3ʹ end.
Where the probe binds to the target, a short minor groove
is formed in the DNA, allowing the MGB molecule to bind
and increase the melting temperature, thus strengthening
probe binding. Consequently, TaqMan MGB probes can
be much shorter than PCR primers. Because of the MGB
moiety, these probes can be shorter than other TaqMan
probes and still have a high melting temperature. This
enables TaqMan MGB probes to bind to the target more
specifically than primers at higher temperatures. With
the shorter probe size, a 1-base mismatch has a much
greater impact on TaqMan MGB probe binding. And
because of this higher level of specificity, TaqMan MGB
probes are recommended for most applications involving
high genetic complexity.
Figure 10. TaqMan probe. The TaqMan probe has a gene-specific
sequence and is designed to bind the target between the two PCR
primers. Attached to the 5ʹ end of the TaqMan probe is the “reporter,”
which is a fluorescent dye that will report the amplification of the
target. On the 3ʹ end of the probe is a quencher, which quenches
fluorescence from the reporter in intact probes. The quencher also
blocks the 3ʹ end of the probe so that it cannot be extended by
thermostable DNA polymerase.
Figure 11. Representation of a TaqMan probe in solution. R is
the reporter dye, Q is the quencher molecule, and the orange line
represents the oligonucleotide.
Direction of DNA synthesis
Taq polymerase
5'-nuclease
domain
synthetic
domain
Excitation Excitation
Reporter dye Quencher
primer
primer
probe
probe
R
Q
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TaqMan probe signal production
Whether an MGB or non-MGB probe is chosen, both
follow the same pattern for signal production. In the early
PCR cycles, only the low, quenched reporter signal is
detected. This early signal, automatically subtracted to
zero in the real-time PCR software, is termed “baseline.”
If the sample contains a target, eventually enough of
the cleaved probe will accumulate to allow amplification
signal to emerge from the baseline. The point at which the
amplification signal becomes visible is inversely related to
the initial target quantity.
SYBR Green dye
SYBR Green I dye is a fluorescent DNA-binding dye that
binds to the minor groove of any dsDNA. Excitation of
DNA-bound SYBR Green dye produces a much stronger
fluorescent signal than unbound dye. A SYBR Green
dye–based assay typically consists of two PCR primers.
Under ideal conditions, a SYBR Green assay follows
an amplification pattern similar to that of a TaqMan
probe–based assay. In the early PCR cycles, a horizontal
baseline is observed. If the target was present in the
sample, sufficient accumulated PCR product will be
produced at some point so that an amplification signal
becomes visible.
SYBR Green assay specificity
Assay specificity testing is important for all assays,
but especially for those most vulnerable to specificity
problems. SYBR Green assays do not benefit from
the specificity of a TaqMan probe, making them more
vulnerable to specificity problems. SYBR Green dye will
bind to any amplified product, target or non-target, and all
such signals are summed, producing a single amplification
plot. SYBR Green amplification plot shape cannot be
used to assess specificity. Plots usually have the same
appearance, whether the amplification consists of target,
non-target, or a mixture. The fact that a SYBR Green
assay produced an amplification product should not be
automatically taken to mean the majority of the signal is
derived from the target.
Since amplification of non-target can vary from
sample to sample, at least one type of specificity
assessment should be performed for every SYBR Green
reaction. Most commonly, this ongoing assessment is
dissociation analysis.
SYBR Green dye dissociation
SYBR Green dissociation is the gradual melting of the
PCR products after PCR when using SYBR Green–
based detection. Dissociation is an attractive choice for
specificity assessment because it does not add cost to
the experiment and can be done right in the PCR reaction
vessel. However, dissociation does add more time to
the thermal protocol, requires additional analysis time, is
somewhat subjective, and has limited resolution.
The concept of SYBR Green dissociation is that if the
target is one defined genetic sequence, it should have
one specific Tm
, which is used to help identify the target
in samples. Some non-target products will have Tm
values
significantly different from that of the target, allowing
detection of those non-target amplifications.
The dissociation protocol is added after the final PCR
cycle. Following the melting process, the real-time PCR
software will plot the data as the negative first derivative,
which transforms the melting profile into a peak.
Accurate identification of the target peak depends on
amplification of pure target. Many samples such as
cellular RNA and gDNA exhibit high genetic complexity,
creating opportunities for non-target amplification that
may suppress the amplification of the target or, in some
cases, alter the shape of the melt peak. By starting with
pure target, the researcher will be able to associate a peak
Tm
and shape with a particular target after amplification.
Only one peak should be observed. The presumptive
target peak should be narrow, symmetrical, and devoid
of other anomalies, such as shoulders, humps, or splits.
These anomalies are strong indications that multiple
products of similar Tm
values were produced, casting
strong doubts about the specificity of those reactions.
Wells with dissociation anomalies should be omitted from
further analysis.
SYBR Green dissociation is low resolution and may not
differentiate between target and non-target with similar Tm
values (e.g., homologs). Therefore, one narrow, symmetric
peak should not be assumed to be the target, nor even a
single product, without additional supporting information.
Dissociation data should be evaluated for each well where
amplification was observed. If the sample contains a peak
that does not correspond to the pure target peak, the
conclusion is that target was not detected in that reaction.
If the sample contains a peak that appears to match
the Tm
and shape of the pure target peak, the target
may have been amplified in that reaction. Dissociation
data in isolation cannot be taken as definitive, but when
combined with other information, such as data from
target-negative samples, sequencing, or gels, can provide
more confidence in specificity.
Real-time PCR instrumentation
Many different models of real-time PCR instruments are
available. Each model must have an excitation source,
which excites the fluorescent dyes, and a detector to
detect the fluorescent emissions. In addition, each model
must have a thermal cycler. The thermal block may be
either fixed, as in the Applied Biosystems™
QuantStudio™
3, QuantStudio™
5, or StepOnePlus™
system or user
interchangeable, as in the ViiA 7 system, the Applied
Biosystems™
QuantStudio 6 and 7 Flex systems, and
the Applied Biosystems™
QuantStudio 12K Flex system.
Blocks are available to accept a variety of PCR reaction
vessels: 48-well plates, 96-well plates, 384-well plates,
384-microwell cards, 3,072–through-hole plates, etc. All
real-time PCR instruments also come with software for
data collection and analysis.
Dye differentiation
Most real-time PCR reactions contain multiple dyes,
including one or more reporter dyes, in some cases
a quencher dye, and, very often, a passive reference
dye. Multiple dyes in the same well can be measured
independently, either through optimized combinations
of excitation and emission filters or through a process
called multicomponenting.
Multicomponenting is a mathematical method to
measure dye intensity for each dye in the reaction.
Multicomponenting offers the benefits of easy
correction for dye designation errors, refreshing of
optical performance to factory standard without
hardware adjustment, and providing a source of
troubleshooting information.
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Basics of real-time PCRBasics of real-time PCR
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1.6	 Melting curve analysis
Melting curve analysis and detection systems
Melting curve analysis can only be performed with realtime
PCR detection technologies in which the fluorophore
remains associated with the amplicon. Amplifications
that have used SYBR Green I or SYBR GreenER™
dye
can be subjected to melting curve analysis. Dual-labeled
probe detection systems such as TaqMan probes are
not compatible because they produce an irreversible
change in signal by cleaving and releasing the fluorophore
into solution during the PCR; however, the increased
specificity of this method makes this less of a concern.
The level of fluorescence of both SYBR Green I and SYBR
GreenER dyes significantly increases upon binding to
dsDNA. By monitoring the dsDNA as it melts, a decrease
in fluorescence will be seen as soon as the DNA becomes
single-stranded and the dye dissociates from the DNA.
Importance of melting curve analysis
The specificity of a real-time PCR assay is determined by
the primers and reaction conditions used. However, there
is always the possibility that even well-designed primers
may form primer-dimers or amplify a nonspecific product
(Figure 12). There is also the possibility when performing
qRT-PCR that the RNA sample contains gDNA, which
may also be amplified. The specificity of the real-time PCR
reaction can be confirmed using melting curve analysis.
When melting curve analysis is not possible, additional
care must be used to establish that differences observed
in Ct
values between reactions are valid and not due to the
presence of nonspecific products.
Melting curve analysis and primer-dimers
Primer-dimers occur when two PCR primers (either samesense
primers or sense and antisense primers) bind to
each other instead of the target. Melting curve analysis
can identify the presence of primer-dimers because they
exhibit a lower melting temperature than the amplicon.
The presence of primer-dimers is not desirable in samples
that contain template, as it decreases PCR efficiency and
obscures analysis. The formation of primer-dimers most
often occurs in no-template controls, where there is an
abundance of primer and no template. The presence of
primer-dimers in the no-template control should serve
as an alert to the user that they may also be present
in reactions that include template. If there are primerdimers
in the no-template control, the primers should be
redesigned. Melting curve analysis of no-template controls
can discriminate between primer-dimers and spurious
amplification due to contaminating nucleic acids in the
reagent components.
How to perform melting curve analysis
To perform melting curve analysis, the real-time PCR
instrument can be programmed to include a melting
profile immediately following the thermal cycling protocol.
After amplification is complete, the instrument will reheat
the amplified products to give complete melting curve
data (Figure 13). Most real-time PCR instrument platforms
now incorporate this feature into their analysis packages.
Figure 12. Melting curve analysis can detect the presence of
nonspecific products, such as primer-dimers, as shown by the
additional peaks to the left of the peak for the amplified product.
Figure 13. Example of a melting curve thermal profile setup on
an Applied Biosystems instrument (rapid heating to 94°C to
denature the DNA, followed by cooling to 60°C).
1.7	 Passive reference dyes
Passive reference dyes are frequently used in real-time
PCR to normalize the fluorescent signal of reporter dyes
and correct for fluctuations in fluorescence that are
not PCR-based. Normalization is necessary to correct
for fluctuations from well to well caused by changes
in reaction concentration or volume and to correct for
variations in instrument scanning. Most real-time PCR
instruments use ROX™
dye as the passive reference dye,
because ROX dye does not affect real-time PCR reactions
and has a fluorescent signal that can be distinguished
from that of many reporter or quencher dyes used. An
exception is the Bio-Rad™
iCycler iQ™
instrument system,
which uses fluorescein as the reference dye.
Passive reference dye
A passive reference dye such as ROX dye is used to
normalize the fluorescent reporter signal in real-time PCR
on compatible instruments, such as Applied Biosystems
instruments. The use of a passive reference dye is an
effective tool for the normalization of fluorescent reporter
signal without modifying the instrument’s default analysis
parameters. TaqMan™
real-time PCR master mixes
contain a passive reference dye that serves as an internal
control to:
•	 Normalize for non–PCR-related fluctuations in
fluorescence (e.g., caused by variation in pipetting)
•	 Normalize for fluctuations in fluorescence resulting from
machine “noise”
•	 Compensate for variations in instrument excitation
and detection
•	 Provide a stable baseline for multiplex real-time PCR
and qRT-PCR
Fluorescein reference dye
Bio-Rad™
iCycler™
instruments require the collection of
“well factors” before each run to compensate for any
instrument or pipetting nonuniformity. Well factors for
experiments using SYBR Green I or SYBR GreenER dye
are calculated using an additional fluorophore, fluorescein.
Well factors are collected using either a separate plate
containing fluorescein dye in each well (for external well
factors) or the experimental plate with fluorescein spiked
into the real-time PCR master mix (for dynamic well
factors). The method must be selected when starting each
run on the iCycler instrument. The iCycler iQ™
5 and MyiQ™
systems allow saving the data from an external well factor
reading as a separate file, which can then be referenced
for future readings.
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1.8	 Contamination prevention
As with traditional PCR, real-time PCR can be affected
by nucleic acid contamination, leading to false positive
results. Some of the possible sources of contamination
are:
•	 Cross-contamination between samples
•	 Contamination from laboratory equipment
•	 Carryover contamination of amplification products and
primers from previous PCR runs. This is considered to
be the major source of false-positive PCR results
Uracil N-glycosylase (UNG)
UNG is used to reduce or prevent DNA carryover
contamination between PCR reactions by preventing the
amplification of DNA from previous reactions. The use of
UNG in PCR reduces false positives, in turn increasing the
efficiency of the real-time PCR reaction and the reliability
of data.
How UNG carryover prevention works
UNG for carryover prevention begins with the substitution
of dUTP for dTTP in real-time PCR master mixes.
Subsequent real-time PCR reaction mixes are then treated
with UNG, which degrades any contaminating uracilcontaining
PCR products, leaving the natural (thyminecontaining)
target DNA template unaffected.
With standard UNG, a short incubation at 50°C is
performed prior to the PCR thermal cycling so that
the enzyme can cleave the uracil residues in any
contaminating DNA. The removal of the uracil bases
causes fragmentation of the DNA, preventing its use as a
template in PCR. The UNG is then inactivated in the rampup
to 95°C in PCR. A heat-labile form of the enzyme is
also available, which is inactivated at 50°C, so that it can
be used in one-step qRT-PCR reaction mixes.
1.9	 Multiplex real-time PCR
Introduction to multiplexing
PCR multiplexing is the amplification and specific
detection of two or more genetic sequences in the same
reaction. To be successful, PCR multiplexing must be able
to produce sufficient amplified product for the detection of
all of the intended sequences. Real-time PCR multiplexing
may be used to produce quantitative or qualitative results.
For quantitative PCR multiplexing, all of the intended
sequences must produce sufficient exponential phase
signal. For qualitative results, if amplified products are
sufficient, an endpoint detection method such as gel
electrophoresis can be used.
The suffix “plex” is used in multiple terms. A singleplex
assay is designed to amplify a single genetic sequence.
A duplex is a combination of two assays designed to
amplify two genetic sequences. The most common type
of multiplex is a duplex, in which the assay for the target
gene is conducted in the same well as that for the control
or normalizer gene, but higher-order multiplexes are
also possible.
Some commercial real-time PCR kits are designed
and validated as a multiplex. For example, the Applied
Biosystems™
MicroSEQ™
E. coli O157:H7 Kit multiplexes
the E. coli target assay with an internal positive control
assay. For research applications, the scientist usually
chooses which assays to multiplex and is responsible for
multiplex validation. When considering whether to create
a multiplex assay, it is important to weigh the benefits
of multiplexing against the degree of effort needed
for validation.
Multiplexing benefits
Three benefits of multiplexing—increased throughput
(more samples potentially assayed per plate), reduced
sample usage, and reduced reagent usage—are
dependent on the number of targets in the experiment.
For example, if a quantitative experiment consists of only
one target assay, running the target assay as a duplex
with the normalizer assay, such as an endogenous control
assay, will increase throughput, reduce sample required,
and reduce reagent usage by half. If a quantitative
experiment consists of two target assays, it may be
possible to combine two target assays and the normalizer
assay in a triplex reaction. In that case, the throughput
increase, sample reduction, and reagent reduction will be
even greater.
If the target assay is multiplexed with the normalizer
assay, another benefit of multiplexing is minimizing pipette
precision errors. Target and normalizer data from the
same well are derived from a single sample addition,
so any pipette precision error should affect both the
target and normalizer results equally. In order to gain this
precision benefit, target data must be normalized by the
normalizer data from the same well before calculating
technical replicate precision. Comparing multiplex data
analyzed in a singleplex manner (without well-based
normalization) to an analysis done in a multiplex manner
demonstrates that the multiplex precision benefit can
be substantial, depending on the singleplex error. For
example, for samples with minimal singleplex precision
error, the multiplex precision benefit will be minimal
as well.
The precision benefit of multiplexing is especially valuable
for quantitative experiments requiring a higher degree
of precision. For example, in copy number variation
experiments, discriminating 1 copy from 2 copies of the
gene is a 2-fold difference, which requires good precision.
However, discriminating 2 copies from 3 copies is only a
1.5-fold difference, which requires even better precision.
Multiplexing is one recommended method to help
achieve the necessary degree of precision for this type
of experiment.
Instrumentation for multiplexing
Multiplex assays usually involve multiple dyes in the same
well. The real-time PCR instrument must be capable of
measuring those different dye signals in the same well
with accuracy. These measurements must remain specific
for each dye, even when one dye signal is significantly
higher than another. Proper instrument calibration is
necessary to accurately measure each dye contribution
within a multiplex assay.
Chemistry recommendations for multiplexing
The best fluorescent chemistries for real-time PCR
multiplexing are those that can assign different dyes
to detect each genetic sequence in the multiplex. The
vast majority of multiplexing is performed with multidye,
high-specificity chemistries, such as TaqMan
probe–based assays.
For multiplex assays involving RNA, two-step RT-PCR is
generally recommended over one-step RT-PCR. Onestep
RT-PCR requires the same primer concentration
for reverse transcription and PCR, reducing flexibility in
primer concentrations optimal for multiplexing. In two-step
RT-PCR, the PCR primer concentration may be optimized
for multiplexing without having any adverse affect on
reverse transcription.
Dye choices for multiplexing
Assuming a multi-dye real-time PCR fluorescence
chemistry is being used, each genetic sequence being
detected in the multiplex assay will require a different
reporter dye. The reporter dyes chosen must be
sufficiently excited and accurately detected when together
in the same well by the real-time PCR instrument. The
instrument manufacturer should be able to offer dye
recommendations. Note that Applied Biosystems real-time
PCR master mixes contain a red passive reference dye.
Whereas blue-only excitation instruments can excite this
ROX dye–based reference sufficiently to act as a passive
reference dye, blue excitation is generally not sufficient for
red dyes to act as a reporter.
Reporter dyes do not have to be assigned based on
the type of target gene or gene product, but following
a pattern in assigning dyes can simplify the creation of
a multiplex assay. For example, FAM dye is the most
common reporter dye used in TaqMan probes, so
following the pattern of assigning FAM dye as the reporter
for the target assay, VIC™
dye would be the reporter
for the normalizer assay. Using this pattern, multiple
duplex assays may be created by pairing a different FAM
dye–labeled target assay with the same VIC dye for the
normalizer assay. In a triplex assay, a third dye, such as
ABY™
dye or JUN™
dye, may be combined with FAM dye
and VIC dye. Note that if ABY dye is being used, TAMRA
dye should not be present in the same well, and if JUN
dye is used, MUSTANG PURPLE™
dye should be used
instead of ROX dye as a passive reference.
Multiplex PCR saturation
Multiplex PCR saturation is an undesirable phenomenon
that may occur in a multiplex assay when the amplification
of the more abundant gene saturates the thermostable
DNA polymerase, suppressing the amplification of the less
abundant gene. The remedy for saturation is a reduction
of the PCR primer concentration for the more abundant
target, termed “primer limitation.” The primer-limited
concentration should be sufficient to enable exponential
amplification, but sufficiently low that the primer is
exhausted before the PCR product accumulates to a level
that starves amplification of the less abundant target.
16 17
Basics of real-time PCRBasics of real-time PCR
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When planning a multiplex assay, the researcher should
identify which gene or genes in the multiplex have the
potential to cause saturation, which is based on the
absolute DNA or cDNA abundance of each gene or gene
product in the PCR reaction. In this regard, the three most
common duplex scenarios are listed below.
Duplex scenario 1
In this most common scenario, the more abundant gene
or gene product is the same in all samples. Only the assay
for the more abundant target requires primer limitation.
For example, the normalizer might be 18S ribosomal RNA
(rRNA), which is 20% of eukaryotic total RNA. The 18S
rRNA cDNA would be more abundant than any cDNA
derived from mRNA in every sample. Therefore, only the
18S assay would require primer limitation.
Duplex scenario 2
In this scenario, the two genes have approximately equal
abundance in all samples. Generally, a Ct
difference
between the two genes of 3 or higher, assuming the
same threshold, would not qualify for equal abundance.
gDNA applications, such as copy number variation, are
most likely to fall into this scenario. Primer limitation is
not necessary for scenario 2, because the two genes are
progressing through the exponential amplification phase
at approximately the same time.
Duplex scenario 3
In this scenario, either the gene or gene product has the
potential to be significantly more abundant than the other.
In this case, both assays should be primer limited.
Multiplex primer interactions
Another potential threat to multiplex assay performance
is unexpected primer interactions between primers from
different assays. The risk of primer interaction grows
with the number of assays in the reaction, because the
number of unique primer pairs increases dramatically
with the number of assays in the multiplex. For example,
in a duplex assay with 4 PCR primers there are 6 unique
primer pairs possible, and in a triplex assay with 6 PCR
primers there are 15 unique pairs possible. In singleplex,
each assay may perform well, but in a multiplex reaction
the primer interactions can create competitive products,
suppressing amplification. The chances of primer
interactions grow when the assays being multiplexed
have homology. If primer interaction does occur based on
the observation of significantly different Ct
values in the
singleplex vs. multiplex reaction, the remedy is to use a
different assay in the multiplex reaction.
1.10	 Internal controls and reference genes
Real-time PCR has become a method of choice for
gene expression analysis. To achieve accurate and
reproducible expression profiling of selected genes using
real-time PCR, it is critical to use reliable internal control
gene products for the normalization of expression levels
between experiments—typically expression products
from housekeeping genes are used. The target chosen
to be the internal standard (or endogenous control)
should be expressed at roughly the same level as the
experimental gene product. By using an endogenous
control as an active reference, quantification of an
mRNA target can be normalized for differences in the
amount of total RNA added to each reaction. Regardless
of the gene that is chosen to act as the endogenous
control, that gene must be tested to ensure that there is
consistent expression of the control gene under all desired
experimental conditions.
Relative gene expression analysis using
housekeeping genes
Relative gene expression comparisons work best when
the expression level of the chosen housekeeping gene
remains constant. The choice of the housekeeping
reference gene is reviewed in BioTechniques 29:332
(2000) and J Mol Endocrinol 25:169 (2000). Ideally, the
expression level of the chosen housekeeping gene should
be validated for each target cell or tissue type to confirm
that it remains constant at all points of the experiment.
For example, GAPDH expression has been shown to be
upregulated in proliferating cells, and 18S rRNA may not
always represent the overall cellular mRNA population.
1.11	 Real-time PCR instrument calibration
Timely, accurate calibration is critical for the proper
performance of any real-time PCR instrument. It preserves
data integrity and consistency over time. Real-time PCR
instruments should be calibrated as part of a regular
maintenance regimen and prior to using new dyes for the
first time, following the manufacturer’s instructions.
Excitation/emission difference corrections
The optical elements in real-time PCR instruments can be
divided into two main categories: the excitation source,
such as halogen lamps or LEDs, and the emission
detector, such as a CCD camera or photodiode. While
manufacturers can achieve excellent uniformity for
excitation strength and emission sensitivity across the
wells of the block, there will always be some variation.
This variation may increase with age and usage of the
instrument. Uncorrected excitation/emission differences
across the plate can cause shifts in Ct
values. However, if
a passive reference dye is present in the reaction, those
differences will affect the reporter and passive reference
signals to the same degree, so that normalization of the
reporter to the passive reference corrects the difference.
Universal optical fluctuations
In traditional plastic PCR plates and tubes, the liquid
reagents are at the bottom of the well, an air space is
above the liquid, and a plastic seal is over the well. With
this configuration, a number of temperature-related
phenomena occur.
During cycling, temperatures reach 95°C. At that high
temperature, water is volatilized into the air space in the
well. This water vapor or steam will condense on the
cooler walls of the tube, forming water droplets that return
to the reagents at the bottom. This entire process, called
“refluxing,” is continuous during PCR.
Second, at high temperature, air dissolved within the
liquid reagents will become less soluble, creating small
air bubbles.
Third, the pressure of the steam will exert force on
the plastic seal, causing it to change shape slightly
during PCR.
All of these temperature-related phenomena are in
the excitation and emission light path and can cause
fluctuations in fluorescent signal. The degree of these
fluctuations can vary, depending on factors such as how
much air was dissolved in the reagents and how well the
plate was sealed. Generally, universal fluctuations do not
produce obvious distortions in the reporter signal, but they
do affect the precision of replicates. If present, a passive
reference dye is in the same light path as the reporter,
so normalization of reporter to passive reference signals
corrects for these fluctuations.
Precision improvement
The correction effect of passive reference normalization
will improve the precision of real-time PCR data. The
degree of improvement will vary, depending on a
number of factors, such as how the reagents and plate
were prepared.
Atypical optical fluctuations
Atypical optical fluctuations are thermal-related anomalies
that are not universal across all reactions in the run and
produce an obvious distortion in the reporter signal. One
example of an atypical optical fluctuation is a significant
configuration change in the plate seal, which may be
termed “optical warping.” Optical warping occurs when
a well is inadequately sealed and then, during PCR, the
heat and pressure of the heated lid causes the seal to seat
properly. A second example is large bubbles that burst
during PCR.
Distortions in the amplification plot are likely to cause
baseline problems and may even affect Ct
values.
Normalization to a passive reference dye provides
excellent correction for optical warping, so the resulting
corrected amplification plot may appear completely
anomaly free. Normalization does not fully correct for a
large bubble bursting, but it can help minimize the data
distortion caused.
18 19
Basics of real-time PCRBasics of real-time PCR
Experimental design
2
2
2.1	Introduction	 22
2.2	 Real-time PCR assay types	 22
2.3	 Amplicon and primer	 23
design considerations
2.4	 Nucleic acid purification	 26
and quantitation
2.5	 Reverse transcription
considerations	28
2.6	Controls	 30
2.7	 Normalization methods	 30
2.8	 Using a standard curve to assess	 32
efficiency, sensitivity,
and reproducibility
21
Experimental design
Contents
22
2.1	Introduction
Successful real-time PCR assay design and development
are the foundation for accurate data. Up-front planning will
assist in managing any experimental variability observed
during this process.
Before embarking on experimental design, clearly
understand the goal of the assay; specifically, what
biological questions need to be answered. For example,
an experiment designed to determine the relative
expression level of a gene in a particular disease state
will be quite different from one designed to determine
viral copy number from that same disease state. After
determining the experimental goal, identify the appropriate
real-time PCR controls and opportunities for optimization.
This section describes the stages of real-time PCR assay
design and implementation. It will identify sources of
variability and the role they play in data accuracy, and
provide guidelines for optimization in the following areas:
•	 Target amplicon and primer design
•	 Nucleic acid purification
•	 Reverse transcription
•	 Controls and normalization
•	 Standard curve evaluation of efficiency, sensitivity,
and reproducibility
2.2	 Real-time PCR assay types
Gene expression profiling is a common use of real-time
PCR that assesses the relative abundance of transcripts
to determine gene expression patterns between samples.
RNA quality, reverse transcription efficiency, real-time
PCR efficiency, quantification strategy, and the choice of
a normalizer gene play particularly important roles in gene
expression experiments.
Viral titer determination assays can be complex to
design. Often, researchers want to quantify viral copy
numbers in samples. This is often accomplished by
comparison to a standard curve generated using known
genome equivalents or nucleic acid harvested from
a titered virus control. Success is dependent on the
accuracy of the material used to generate the standard
curve. Depending on the nature of the target—an RNA
or DNA virus—reverse transcription and real-time PCR
efficiency also play significant roles. Assay design will also
be influenced by whether the assay is intended to count
functional viral particles or the total number of particles.
Copy number variation analysis analyzes the genome
for duplications or deletions. The assay design, and
most specifically standard curve generation, will be
dictated by whether relative or absolute quantification
is desired. Assay design focuses on real-time PCR
efficiency and the accuracy necessary to discriminate
single-copy deviations.
Allelic discrimination assays can detect variation
down to the single-nucleotide level. Unlike the methods
described above, endpoint fluorescence is measured to
determine SNP genotypes. Primer and probe design play
particularly important roles to ensure a low incidence of
allele-specific cross-reactivity.
2.3	 Amplicon and primer design considerations
Target amplicon size, GC content, location,
and specificity
As will be discussed in more detail later in this guide,
reaction efficiency is paramount to the accuracy of realtime
PCR data. In a perfect scenario, each target copy in
a PCR reaction will be copied at each cycle, doubling the
number of full-length target molecules: this corresponds
to 100% amplification efficiency. Variations in efficiency
will be amplified as thermal cycling progresses. Thus, any
deviation from 100% efficiency can result in potentially
erroneous data.
One way to minimize efficiency bias is to amplify relatively
short targets. Amplifying a 100 bp region is much more
likely to result in complete synthesis in a given cycle
than, say, amplifying a 1,200 bp target. For this reason,
real-time PCR target lengths are generally 60–200 bp. In
addition, shorter amplicons are less affected by variations
in template integrity. If nucleic acid samples are slightly
degraded and the target sequence is long, upstream
and downstream primers will be less likely to find their
complementary sequence in the same DNA fragment.
Amplicon GC content and secondary structure can be
another cause of data inaccuracy. Less-than-perfect
target doubling at each cycle is more likely to occur
if secondary structure obstructs the path of the DNA
polymerase. Ideally, primers should be designed to anneal
with, and to amplify, a region of medium (50%) GC content
with no significant GC stretches. For amplifying cDNA, it
is best to locate amplicons near the 3ʹ ends of transcripts.
If RNA secondary structure prohibits full-length cDNA
synthesis in a percentage of the transcripts, these
amplicons are less likely to be impacted (Figure 14).
Target specificity is another important factor in data
accuracy. When designing real-time PCR primers, check
primers to be sure that their binding sites are unique in
the genome. This reduces the possibility that the primers
could amplify similar sequences elsewhere in the sample
genome. Primer design software programs automate
the process of screening target sequences against the
originating genome and masking homologous areas, thus
eliminating primer designs in these locations.
gDNA, pseudogenes, and allelic variants
gDNA carryover in an RNA sample may be a concern
when measuring gene expression levels. The gDNA may
be co-amplified with the target transcripts of interest,
resulting in invalid data. gDNA contamination is detected
by setting up control reactions that do not contain reverse
transcriptase (no-RT controls); if the Ct
for the no-RT
control is higher than the Ct
generated by the most
dilute target, it indicates that gDNA is not contributing to
signal generation. However, gDNA can compromise the
efficiency of the reaction due to competition for reaction
components such as dNTPs and primers.
The best method for avoiding gDNA interference in realtime
PCR is thoughtful primer (or primer/probe) design,
which takes advantage of the introns present in gDNA
that are absent in mRNA. Whenever possible, Applied
Biosystems™
TaqMan™
Gene Expression Assays are
designed so that the TaqMan probe spans an exonexon
boundary. Primer sets for SYBR Green dye–based
detection should be designed to anneal in adjacent
exons or with one of the primers spanning an exon/exon
junction. When upstream and downstream PCR primers
anneal within the same exon, they can amplify target
from both DNA and RNA. Conversely, when primers
anneal in adjacent exons, only cDNA will be amplified in
most cases, because the amplicon from gDNA would
include intron sequence, resulting in an amplicon that is
too long to amplify efficiently in the conditions used for
real-time PCR.
Pseudogenes, or silent genes, are other transcript variants
to consider when designing primers. These are derivatives
of existing genes that have become nonfunctional due
to mutations and/or rearrangements in the promoter or
gene itself. Primer design software programs can perform
BLAST™
searches to avoid pseudogenes and their
mRNA products.
Allelic variants are two or more unique forms of a gene
that occupy the same chromosomal locus. Transcripts
originating from these variants can vary by one or more
mutations. Allelic variants should be considered when
Figure 14. An RNA molecule with a high degree of secondary
structure.
5´ 3´
22 23
Experimental designExperimental design
22
designing primers, depending on whether one or more
variants are being studied. In addition, GC-content
differences between variants may alter amplification
efficiencies and generate separate peaks on a melt
curve, which can be incorrectly diagnosed as off-target
amplification. Alternately spliced variants should also be
considered when designing primers.
Specificity, dimerization, and self-folding in primers
and probes
Primer-dimers are most often caused by an interaction
between forward and reverse primers, but can also be
the result of forward-forward or reverse-reverse primer
annealing, or a single primer folding upon itself. Primerdimers
are of greater concern in more complex reactions
such as multiplex real-time PCR. If the dimerization
occurs in a staggered manner, as often is the case, some
extension can occur, resulting in products that approach
the size of the intended amplicon and become more
abundant as cycling progresses. Typically, the lower the
amount of target at the start of the PCR, the more likely
primer-dimer formation will be. The positive side of this
potential problem is that the interaction of primer-dimers
is usually less favorable than the intended primer-template
interaction, and there are many ways to minimize or
eliminate this phenomenon.
The main concern with primer-dimers is that they may
cause false-positive results. This is of particular concern
with reactions that use DNA-binding dyes such as
SYBR Green I dye. Another problem is that the resulting
competition for reaction components can contribute
to a reaction efficiency outside the desirable range
of 90–110%. The last major concern, also related to
efficiency, is that the dynamic range of the reaction may
shrink, impacting reaction sensitivity. Even if signal is not
generated from the primer-dimers themselves (as is the
case with TaqMan Assays), efficiency and dynamic range
may still be affected.
Several free software programs are available to analyze
real-time PCR primer designs and determine if they
will be prone to dimerize or fold upon themselves. The
AutoDimer software program (authored by P.M. Vallone,
National Institute of Standards and Technology, USA) is a
bioinformatics tool that can analyze a full list of primers at
the same time (Figure 15). This is especially helpful with
multiplexing applications. However, while bioinformatics
analysis of primer sequences can greatly minimize the
risk of dimer formation, it is still necessary to monitor
dimerization experimentally.
The traditional method of screening for primer-dimers
is gel electrophoresis. Primer-dimers appear as diffuse,
smudgy bands near the bottom of the gel (Figure 16). One
concern with gel validation is that it is not very sensitive
and therefore may be inconclusive. However, gel analysis
is useful for validating data obtained from a melting/
dissociation curve, which is considered the best method
for detecting primer-dimers.
Melting or dissociation curves should be generated
following any real-time PCR run that uses DNA-binding
dyes for detection. In brief, the instrument ramps from
low temperature, in which DNA is double-stranded and
fluorescence is high, to high temperature, which denatures
DNA and results in lower fluorescence. A sharp decrease
in fluorescence will be observed at the Tm
for each product
generated during the PCR. The melting curve peak
obtained for the no-template control can be compared to
the peak obtained from the target to determine whether
primer-dimers are present in the reaction.
Figure 15. A screen capture from AutoDimer software. This
software is used to analyze primer sequences and report areas of
potential secondary structure within primers (which could lead to
individual primers folding on themselves) or stretches of sequence
that would allow primers to anneal to each other.
Figure 16. Agarose gel analysis to investigate primer-dimer
formation. Prior to the thermal cycling reaction, the nucleic acid
sample was serially diluted and added to the components of a PCR
mix, and the same volume from each mixture was loaded on an
agarose gel. Primer-dimers appear as diffuse bands at the bottom of
the gel.
Ideally, a single distinct peak should be observed for
each reaction containing template, and no peaks should
be present in the no-template controls. Smaller, broader
peaks at a lower melting temperature than that of the
desired amplicon and also appearing in the no-template
control reactions are quite often dimers. Again, gel runs
of product can often validate the size of the product
corresponding to the melting peak.
There are situations in which primer-dimers are present,
but they may not affect the overall accuracy of the realtime
PCR assay. A common observation is that primerdimers
are present in the no-template control but do not
appear in reactions containing template DNA. This is not
surprising because in the absence of template, primers
are much more likely to interact with each other. When
template is present, primer-dimer formation is not favored.
As long as the peak seen in the no-template control is
absent in the plus-template dissociation curve, primerdimers
are not an issue.
Primer-dimers are part of a broad category of nonspecific
PCR products that includes amplicons created when
a primer anneals to an unexpected location with an
imperfect match. Amplification of nonspecific products is
of concern because they can contribute to fluorescence,
which in turn artificially shifts the Ct
of the reaction. They
can influence reaction efficiency through competition for
reaction components, resulting in a decreased dynamic
range and decreased data accuracy. Nonspecific
products are an even greater concern in absolute
quantification assays, in which precise copy numbers
are reported.
Standard gel electrophoresis is generally the first step
in any analysis of real-time PCR specificity. While it can
help to identify products that differ in size from a target
amplicon, a band may still mask similar-sized amplicons
and have limited sensitivity. Due to its accuracy and
sensitivity, melting curve analysis provides the most
confidence in confirming gel electrophoretic assessment
of primer specificity.
While nonspecific amplification should always be
eliminated when possible, there are some cases in which
the presence of these secondary products is not a major
concern. For example, if alternate isoforms or multiple
alleles that differ in GC content are knowingly targeted,
multiple products are expected.
Primer design considerations
The following recommendations are offered for designing
primers for real-time PCR: Applied Biosystems™
Primer
Express™
Software, Invitrogen™
OligoPerfect™
Designer
web-based tool, and Invitrogen™
Vector NTI™
Software.
Note that primer design software programs, such as
our web-based OligoPerfect Designer and Vector NTI
Software, are seamlessly connected to our online ordering
system, so there’s no need to cut and paste sequences.
These programs can automatically design primers for
specific genes or target sequences using algorithms
that incorporate the following guidelines and can also
perform genome-wide BLAST searches for known
sequence homologies.
•	 In general, design primers that are 18–28 nucleotides
in length
•	 Avoid stretches of repeated nucleotides
•	 Aim for 50% GC content, which helps to prevent
mismatch stabilization
•	 Choose primers that have compatible Tm
values (within
1°C of each other)
•	 Avoid sequence complementarity between all primers
employed in an assay and within each primer
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Experimental designExperimental design
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2.4	 Nucleic acid purification and quantitation
Real-time PCR nucleic acid purification methods
Prior to purifying nucleic acid, the source material (cells
or tissue) and potential technique limitations must be
considered. DNA and RNA isolation techniques vary
in ease of use, need for organic solvents, and resulting
nucleic acid purity with regards to carryover of DNA (in the
case of RNA isolation), protein, and organic solvents.
This section will primarily discuss RNA isolation,
though most of the same guidelines also hold true for
DNA isolation.
One-step reagent-based organic extraction is a very
effective method for purifying RNA from a wide variety
of cell and tissue types. Many protocols use a phenol
and guanidine isothiocyanate mixture to disrupt cells and
dissolve cell components while maintaining the integrity
of the nucleic acids by protecting them from RNases.
Guanidine isothiocyanate is a chaotropic salt that protects
RNA from endogenous RNases (Biochemistry 18:5294
(1979)). Typically, chloroform is then added and the
mixture is separated into aqueous and organic phases by
centrifugation. RNA remains exclusively in the aqueous
phase in the presence of guanidine isothiocyanate, while
DNA and protein are driven into the organic phase and
interphase. The RNA is then recovered from the aqueous
phase by precipitation with isopropyl alcohol.
This process is relatively fast and can yield high levels
of RNA, but requires the use of toxic chemicals and
may result in higher DNA carryover compared to other
techniques. Residual guanidine, phenol, or alcohol can
also dramatically reduce cDNA synthesis efficiency.
With most methods based on silica beads or filters,
samples are lysed and homogenized in the presence of
guanidine isothiocyanate. After homogenization, ethanol
is added to the sample, RNA is bound to silica-based
beads or filters, and impurities are effectively removed
by washing (Proc Natl Acad Sci USA 76:615 (1979)). The
purified total RNA is eluted in water.
This method is even less time-consuming than organic
extraction and does not require phenol. The RNA yield
may not be quite as high, but the purity with regards to
protein, lipids, polysaccharides, DNA, and purification
reagents is generally better. Guanidine and ethanol
carryover due to incomplete washing can still occur, with
the same deleterious effects on cDNA synthesis efficiency.
Lastly, methods combining organic lysis with silica
columns can offer the benefits of good sample lysis with
the ease, speed, and purity of silica-binding methods.
Assessing RNA quality
In assessing RNA quality and quantity, there are a few key
points to focus on. Ensure that the ratio of UV absorbance
at 260 nm to the absorbance at 280 nm (A260
/A280
ratio)
is between 1.8 and 2.0. A ratio below 1.8 can indicate
protein contamination, which can lower reaction efficiency.
The A260
/A230
ratio is helpful in evaluating the carryover
of components containing phenol rings such as the
chaotropic salt guanidine isothiocyanate and phenol itself,
which are inhibitory to enzymatic reactions. Assess RNA
integrity on a denaturing gel or on an instrument such as
the Agilent™
Bioanalyzer™
system (Figure 17).
The Bioanalyzer system takes RNA quality determination
one step further with the assignment of an RNA integrity
number (RIN) value. The RIN value is calculated from
the overall trace, including degraded products, which in
general is better than assessing the rRNA peaks alone.
Researchers are then able to compare RIN values for RNA
from different tissue types to assess standardization of
quality and maintenance of consistency.
Figure 17. Agilent Bioanalyzer system trace and gel image
displaying RNA integrity. Intact mammalian total RNA shows two
bands or peaks representing the 18S and 28S rRNA species. In
general, the 28S rRNA is twice as bright (or has twice the area under
the peak in the Bioanalyzer system trace) as the 18S rRNA. MM:
Invitrogen™
Millenium™
RNA Markers.
Quantitation accuracy
For quantitation of RNA, fluorescent dyes such as
Invitrogen™
RiboGreen™
and PicoGreen™
dyes are
superior to UV absorbance measurements because
they are designed to have higher sensitivity, higher
accuracy, and high-throughput capability. UV absorbance
measurements cannot distinguish between nucleic
acids and free nucleotides. In fact, free nucleotides
absorb more at 260 nm than do nucleic acids. Similarly,
UV absorbance measurements cannot distinguish
between RNA and DNA in the same sample. In addition,
contaminants commonly present in samples of purified
nucleic acid contribute to UV absorbance readings.
Finally, most UV absorbance readers consume a
considerable amount of the sample for the measurement
itself. With the wide variety of fluorescent dyes available,
it is possible to find reagents that overcome all of these
limitations: dyes that can distinguish nucleic acids from
free nucleotides, dyes that can distinguish DNA from
RNA in the same sample, and dyes that are insensitive to
common sample contaminants. The Invitrogen™
Qubit™
quantitation platform uses Quant-iT™
fluorescence
technology, with advanced fluorophores that become
fluorescent upon binding to DNA, RNA, or protein. This
specificity enables more accurate results than with UV
absorbance readings, because Quant-iT™
assay kits only
report the concentration of the molecule of interest (not
contaminants). And, in general, quantitation methods
using fluorescent dyes are very sensitive and only require
small amounts of sample.
gDNA carryover in expression studies
A previous discussion described how primer design is the
first step toward eliminating DNA amplification in realtime
RT-PCR. DNase treatment of the sample at the RNA
isolation stage is a method by which DNA can be controlled
at the source. An option in addition to traditional DNase
I is super-active Invitrogen™
TURBO™
DNase, which is
catalytically superior to wild type DNase I. It can remove
even trace quantities of DNA, which can plague RT-PCR.
DNase treatment can occur either in solution or on column,
depending on the isolation method. On-column DNase
treatments are common with silica matrix extraction, and,
unlike in-solution treatments, they do not need to be heatinactivated
in the presence of EDTA, because salt washes
remove the enzyme. The drawback is that on-column
reactions require much more enzyme.
In-solution DNase reactions have traditionally required
heat-inactivation of the DNase at 65°C. Free magnesium,
required for the reaction, can cause magnesiumdependent
RNA hydrolysis at this temperature. Invitrogen™
DNA-free™
and TURBO DNA-free™
kits help circumvent
these problems by using a unique DNase inactivation
reagent. In addition to removing DNase from reactions,
the inactivation reagent also binds and removes divalent
cations from the reaction buffer. This alleviates concerns
about introducing divalent cations into RT-PCR reactions,
where they can affect reaction efficiency.
26 27
Experimental designExperimental design
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2.5	 Reverse transcription considerations
The drawbacks of two-step qRT-PCR include:
•	 Reverse transcriptases and buffers can inhibit
real-time PCR— typically, only 10% of the cDNA
synthesis reaction is used in real-time PCR, because
the reverse transcriptase and associated buffer
components may inhibit the DNA polymerase if not
diluted properly. The specific level of inhibition will
depend on the reverse transcriptase, the relative
abundance of the target, and the robustness of the
amplification reaction.
•	 Less convenience—two-step reactions
require more handling and are less amenable to
high-throughput applications
•	 Contamination risk—increased risk of contamination
due to the use of separate tubes for each step
RNA priming strategies
Reverse transcription is typically the most variable
step in qRT-PCR. The first-strand synthesis reaction
can use gene-specific, oligo(dT), or random primers
(Figure 18), and primer selection can play a large role
in reverse transcription efficiency and consistency and,
consequently, data accuracy.
Random primers are great for generating large pools of
cDNA, and therefore can offer the highest sensitivity in
real-time PCR. They are also ideal for non-polyadenylated
RNA, such as bacterial RNA. Because they anneal
throughout the target molecule, degraded transcripts and
secondary structure do not pose as much of a problem as
they do with gene-specific primers and oligo(dT) primers.
While increased yield is a benefit, data have shown
that random primers can overestimate copy number.
Employing a combination of random and oligo(dT) primers
can sometimes increase data quality by combining the
benefits of both in the same reverse transcription reaction.
Random primers are used only in two-step qRT-PCR.
Oligo(dT) primers are a favorite choice for two-step
reactions because of their specificity for mRNA and
because many different targets can be analyzed from
the same cDNA pool when they are used to prime
reactions. However, because they always initiate reverse
transcription at the 3ʹ end of the transcript, difficult
secondary structure may lead to incomplete cDNA
generation. Oligo(dT) priming of fragmented RNA, such
as that isolated from formalin-fixed, paraffin-embedded
samples, may also be problematic. Nonetheless, as long
as the real-time PCR primers are designed near the 3ʹ end
of the target, premature termination downstream of this
location is not generally an important concern.
Multiple types of oligo(dT) primers are available.
Oligo(dT)20
is a homogeneous mixture of 20-mer
thymidines, while oligo(dT)12–18
is a mixture of 12-mer
to 18-mer thymidines. Anchored oligo(dT) primers are
designed to avoid poly(A) slippage by annealing at the
3ʹ untranslated region (UTR)/poly(A) junction. Choosing the
best oligo(dT) primer may depend in part on the reaction
temperature. More thermostable reverse transcriptases
may perform better with longer primers, which remain
more tightly annealed at elevated temperatures compared
to their shorter counterparts. Oligo(dT) primers are not
recommended if 18S rRNA is used for normalization.
Sequence-specific primers offer the greatest specificity
and have been shown to be the most consistent of the
primer options for reverse transcription. However, they do
not offer the flexibility of oligo(dT) and random primers,
in that they only produce a cDNA copy of the target
gene product. Because of this, gene-specific primers
are typically not the best choice for studies involving
scarce or precious samples. One-step qRT-PCR always
employs a gene-specific primer for first-strand synthesis,
whereas other primer options are compatible with
two-step reactions.
Each primer type presents unique theoretical benefits and
drawbacks. In addition, individual targets may respond
differently to one primer choice over another. Ideally, each
primer option should be evaluated during the initial assay
validation stage to determine which provides optimal
sensitivity and accuracy.
Factors influencing reverse transcription efficiency
The reverse transcription stage of a qRT-PCR reaction
is less consistent than the PCR stage. This is due to
a combination of factors associated with the startingFigure 18. Graphical representation of commonly used RNApriming
strategies.
mRNA
First-strand cDNA
Oligo(dT) primer
AAAAAAAA 3´5´
TTTTTTTT 5´3´
mRNA
First-strand cDNA
Random primer
AAAAAAAA 3´5´
N6 N6 N6 N6 N6 N6
mRNA
First-strand cDNA
Sequence-specific primer ( )
AAAAAAAA 3´5´
5´3´
The benefits of one-step qRT-PCR include the following:
•	 Contamination prevention—the closed-tube system
prevents introduction of contaminants between the
reverse transcription and PCR stages
•	 Convenience—the number of pipetting steps is
reduced and hands-on time is minimized
•	 High-throughput sample screening—for the
reasons mentioned above
•	 Sensitivity—one-step reactions may be more
sensitive than two-step reactions because all the
first-strand cDNA created is available for real-time
PCR amplification
The drawbacks of one-step qRT-PCR include:
•	 Increased risk of primer-dimer formation—forward
and reverse gene-specific primers, present from the
start in one-step reactions, have a greater tendency
to dimerize under the 42–50°C reverse transcription
conditions. This can be especially problematic in
reactions that use DNA-binding dyes for detection
•	 cDNA is not available for other real-time PCR
reactions—one-step reactions use all the cDNA from
the reverse transcription step, so if the reaction fails, the
sample is lost
In two-step qRT-PCR, the reverse transcription
is performed in a buffer optimized for the reverse
transcriptase. Once complete, approximately 10% of the
cDNA is transferred into each real-time PCR reaction, also
in its optimal buffer.
The benefits of two-step qRT-PCR include:
•	 cDNA may be archived and used for additional
real-time PCR reactions—two-step qRT-PCR
produces enough cDNA for multiple real-time PCR
reactions, making it optimal for rare or limited samples
•	 Sensitivity—two-step reactions may be more
sensitive than one-step reactions because the
reverse transcription and real-time PCR reactions are
performed in their individually optimized buffers
•	 Multiple targets—depending on the reverse
transcription primers used, multiple targets can be
interrogated from a single RNA sample
Reverse transcriptases
Most reverse transcriptases employed in qRT-PCR are
derived from avian myeloblastosis virus (AMV) or Moloney
murine leukemia virus (M-MLV). Native AMV reverse
transcriptase is generally more thermostable than M-MLV,
but produces lower yields. However, manipulations of
these native enzymes have resulted in variants with ideal
properties for qRT-PCR. An ideal reverse transcriptase will
exhibit the following attributes:
•	 Thermostability—as discussed earlier, secondary
structure can have a major impact on the sensitivity
of a reaction. Native reverse transcriptases perform
ideally between 42°C and 50°C, whereas thermostable
reverse transcriptases function at the higher end of
(or above) this range and allow for successful reverse
transcription of GC-rich regions.
•	 Reduced RNase H activity—the RNase H domain is
present in common native reverse transcriptases and
functions in vivo to cleave the RNA strand of RNA-DNA
heteroduplexes for the next stage of replication. For
qRT-PCR applications, RNase H activity can drastically
reduce the yield of full-length cDNA, which translates
to poor sensitivity. Several reverse transcriptases,
most notably Invitrogen™
SuperScript™
VILO™
, II and
III Reverse Transcriptases, have been engineered for
reduced RNase H activity.
One-step and two-step qRT-PCR
The choice between one-step and two-step qRT-PCR
comes down to convenience, sensitivity, and assay
design. The advantages and disadvantages of each
technique must be evaluated for each experiment.
In a one-step reaction, the reverse transcriptase and
thermostable DNA polymerase are both present during
reverse transcription, and the reverse transcriptase is
inactivated in the high-temperature DNA polymerase
activation stage (the so-called hot start). Normally, the
reverse transcriptase is favored by a buffer that is not
optimal for the DNA polymerase. Thus, one-step buffers
are a compromise solution that provide acceptable but
not optimal functionality of both enzymes. This slightly
lower functionality is compensated by the fact that, using
this single-tube procedure, all cDNA produced is amplified
in the PCR stage.
28 29
Experimental designExperimental design
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2.6	Controls
Controls in real-time PCR reactions prove that signals
obtained from experimental samples represent the
amplicon of interest, thereby validating specificity. All
experiments should include a no-template control, and
qRT-PCR reactions should also include a no-reverse
transcriptase (no-RT) control.
No-template controls should contain all reaction
components except the DNA or cDNA sample.
Amplification detected in these wells is due to either
primer-dimers or contamination with amplified PCR
product. This type of contamination can make expression
levels look higher than they actually are.
No-RT reactions should contain all reaction components
except the reverse transcriptase. If amplification products
are seen in no-RT control reactions, it indicates that DNA
was amplified rather than cDNA. This can also artificially
inflate apparent expression levels in experimental samples.
sample, which the thermostable DNA polymerase isn’t
normally tested with. These factors include:
Differences in RNA integrity—the degradation level
of a particular RNA sample has a direct impact on the
percentage of mRNA target that is converted into cDNA
and therefore quantified. Depending on the first-strand
primer used, degradation may prevent the reverse
transcriptase from creating cDNA that corresponds
with full-length target amplicon. The lower the reverse
transcription efficiency, the less sensitive the PCR assay
will be. Efficiency variations that are not normalized can
result in inaccurate conclusions.
GC content, RNA sample complexity, and reverse
transcriptase employed—RNA expression level
comparisons are more accurate if the RT is less sensitive
to the inevitable differences between samples. For
example, data have shown that sample complexity alone,
meaning all the background nucleic acid not compatible
with the reverse transcription primer, can result in as much
as a 10-fold difference in reaction efficiency. Reverse
transcriptases capable of consistent cDNA synthesis in
this background are ideal.
Carryover of organic solvents and chaotropic salts—
ethanol and guanidine are necessary for RNA capture but
can inhibit enzymatic reactions. Variations in the levels
of these contaminants between RNA samples can affect
sample comparison. Therefore, it is important to use an
RNA isolation method that results in consistently low
levels of these byproducts. We also recommend using a
validated normalizer gene for real-time PCR.
2.7	 Normalization methods
Earlier in this guide, eliminating experimental
inconsistencies was mentioned as a paramount concern
for real-time PCR experimental design. Deviating from
the experimental plan can limit researchers’ ability to
compare data and could lead to erroneous conclusions if
deviations are not accounted for in the analysis. Sources
of experimental variability include the nature and amount
of starting sample, the RNA isolation process, reverse
transcription, and, of course, real-time PCR amplification.
Normalization is essentially the process of neutralizing the
effects of variability from these sources. While there are
individual normalization strategies at each stage of realtime
PCR, some are more effective than others. These
strategies include:
Normalizing to sample quantity—initiating the RNA or
DNA isolation with a similar amount of sample (e.g., tissue
or cells) can minimize variability, but it is only approximate
and does not address biases in RNA isolation.
Normalizing to RNA or DNA quantity—precise
quantification and quality assessment of the RNA or DNA
samples are necessary, but fall short as the only methods
for normalization, because they do not control for
differences in efficiency in reverse transcription and realtime
PCR reactions. For example, minute differences in
the levels of contaminants can affect reverse transcription
and lower amplification efficiency. Any variation in samples
is then amplified during PCR, with the potential to result
in drastic fold-changes unrelated to biological conditions
Figure 19. Gene expression levels of commonly used
endogenous controls and the importance of normalization.
In this example, two treatment groups and a normal group were
analyzed for the expression levels of common reference genes,
which were amplified in addition to an internal positive control
(IPC). The IPC provides a standard for normal reaction-to-reaction
variability. The bars represent up- or downregulation of the
normalizer in each treatment group as compared to the normal
sample, which is represented by a ΔCt
of 0. The goal is to find a
normalizer that mimics the changes exhibited by the IPC.
Ct
is reached, the normalizer itself will impede target
amplification, causing a higher target Ct
, thus defeating
its purpose. Alternatively, the normalizer reaction can
be assembled with primer-limited conditions to mimic a
lower expression level. Most TaqMan endogenous control
assays are available with primer-limited configuration.
Real-time PCR assays for normalizer targets should have
a similar amplification efficiency to assays for experimental
targets; this can be evaluated using a standard curve.
Although correction factors can be applied when
comparing reactions with different efficiencies, accuracy
is enhanced when the reaction efficiencies are close to
one another.
Last and most important, expression of the normalizer
should be consistent, regardless of the treatment or
disease state of the sample. This must be experimentally
determined, as shown in Figure 19.
While multiple replicates should be performed to ensure
accuracy, it is clear that PPIA, TBP, and HPRT1 would not
be good normalizer choices for these treatment groups
within samples. Pipetting is also subject to operator
variation, and there is no normalization to compensate for
it in post-purification RNA analysis.
Normalizing to a reference gene—the use of a
normalizer gene (also called a reference gene or
endogenous control) is the most thorough method of
addressing almost every source of variability in realtime
PCR. However, for this method to work, the gene
must be present at a consistent level in all samples
being compared. An effective normalizer gene controls
for RNA quality and quantity, and differences in both
reverse transcription and real-time PCR amplification
efficiencies. If the reverse transcriptase transcribes or the
DNA polymerase amplifies a target at different rates in
two different samples, the normalizer transcript will reflect
that variability. Endogenous reference genes, such as a
housekeeping gene, or exogenous nucleic acid targets
can be used.
Endogenous controls
Common endogenous normalizers in real-time
PCR include the genes encoding:
•	 β-actin: cytoskeletal component
•	 18S rRNA: ribosomal subunit
•	 Cyclophilin A (PPIA): serine-threonine phosphatase
inhibitor
•	 Glyceraldehyde 3-phosphate dehydrogenase (GAPDH):
glycolysis pathway
•	 β-2-microglobulin (B2M): major histocompatibility
complex
•	 β-glucuronidase (GUS): exoglycosidase in lysosomes
•	 Hypoxanthine ribosyltransferase (HPRT1): purine
salvage pathway
•	 TATA-box binding protein (TBP): RNA transcription
Because every real-time PCR experiment is different,
thought and careful planning should go into selecting a
normalizer. Instead of choosing a normalizer based on
what others in the lab use, choose one that best supports
the quantification strategy of the specific target.
The first requirement of a quality normalizer is that it is
similar in abundance to the target gene product. This
is especially important when multiplexing, because
if the normalizer reaction plateaus before the target
30 31
Experimental designExperimental design
22
because they appear to be downregulated with treatment.
The expression levels of even the most common reference
genes can be altered under certain conditions and
therefore should always be validated:
•	 GAPDH is a common normalizer that has been shown
to be consistent in many cases. However, GAPDH is
upregulated in some cancerous cells, in cells treated
with tumor suppressors, under hypoxic conditions, and
in manganese- or insulin-treated samples.
•	 β-actin is another commonly employed housekeeping
gene because it exhibits moderately abundant
expression in most cell types. However, its consistency
has been questioned in breast epithelial cells,
blastomeres, porcine tissues, and canine myocardium.
•	 18S rRNA constitutes 85–90% of total cellular RNA
and has been shown to be quite consistent in rat
liver, human skin fibroblasts, and human and mouse
malignant cell lines. However, its level of abundance
makes it a problematic normalizer for medium- and
low-expression targets. Often it is difficult to find a
concentration of RNA at which 18S rRNA provides a
wide enough baseline and also at which the target of
interest generates a Ct
within 40 cycles. In addition,
multiplexing may necessitate limiting the concentration
of 18S primers so that the normalizer doesn’t sequester
all the reaction components and make PCR conditions
unfavorable for the target of interest.
Alternative methods exist that do not rely on the accuracy
of a single reference gene, but rather the geometric mean
of multiple validated normalizers. This use of multiple
consistent normalizers may prove to be a better buffer
against the Ct
fluctuations of any single gene, thereby
increasing assay and sample type flexibility.
Figure 20. Bias effect caused by different amplification
efficiencies. Four different real-time PCR reactions are shown
that range from 70% to 100% efficiency. The divergence is not
necessarily apparent in the early cycles. However, after 30 cycles,
there is a 100-fold difference in reported copy number between
a reaction with 70% efficiency and one with 100% efficiency.
Differences in efficiency become more important in reactions with
more cycles and in assays that require greater sensitivity.
Figure 21. Example standard curve used to evaluate the
efficiency of real-time PCR.
2.8	 Using a standard curve to assess efficiency,
sensitivity, and reproducibility
The final stage of experimental design is validating that
the parameters discussed up to this point result in a highly
efficient, sensitive, and reproducible experiment.
Reaction efficiency
As discussed previously, the overall efficiency of real-time
PCR depends on the individual efficiencies of the reverse
transcription reaction and the PCR amplification reaction.
Reverse transcription efficiency is determined by the
percentage of target RNA that is converted into cDNA.
Low conversion rates can affect sensitivity, but variation
in the conversion percentage across samples is of
greater concern.
PCR amplification efficiency is the most consistent factor
in a real-time PCR reaction. However, this amplification
cDNA input (ng)
Gene.Quantification@wzw.tuj.de ©2002
Slope
-3.10
-3.32
-3.58
Slope
Efficiency
110%
100%
90%
Cyclenumberofcrossingpoint(CP)
35
30
25
20
15
10
0.025 0.05 0.01 0.25 0.5 1 2.5 5 10 25 50
Exogenous normalizers
Exogenous normalizers are not as commonly employed,
but are a viable alternative if a highly consistent
endogenous normalizer cannot be found for a specific
sample set. An exogenous reference gene is a synthetic
or in vitro–transcribed RNA with a sequence that is
not present in the experimental samples. Due to its
exogenous origin, it does not undergo the normal
biological fluctuations that can occur in a cell under
different conditions or treatments. When using exogenous
normalizers, the earlier they are added to the experimental
workflow, the more steps they can control. For example, if
an exogenous transcript is added to the cell lysis buffer, it
can be used as a normalizer for cell lysis, RNA purification,
and subsequent reverse transcription and PCR reactions.
An example of an exogenous normalizer is an in vitro–
transcribed RNA specific to plant processes, such
as a photosynthetic gene. This could be spiked into
mammalian samples because those cells would not have
this same transcript endogenously.
The drawbacks to employing an exogenous
normalizer are:
•	 It is not endogenous; maximize the utility of exogenous
normalizers by spiking them into the workflow early, for
example into the cell lysis buffer
•	 Accuracy is subject to pipetting variability when
introducing the normalizer
•	 Transcript stability may be affected by prolonged
storage and multiple freeze-thaws; therefore, copy
number should be routinely assessed to ensure it has
not shifted over time
exponentially magnifies slight variations in reverse
transcription efficiency, potentially resulting in misleading
data. An efficiency of 100% corresponds to a perfect
doubling of template at every cycle, but the acceptable
range is 90–110% for assay validation. This efficiency
range corresponds to standard curve slopes of –3.6 to
–3.1. The graph in Figure 20 shows the measurement bias
resulting solely from differences in reaction efficiency.
Validating the reaction efficiency for all targets being
compared (e.g., reference genes and genes of interest),
optimizing those efficiencies to be as similar as possible,
and employing efficiency corrections during data analysis
can reduce these effects. These strategies will be
discussed further in the data analysis section.
Reaction efficiency is best assessed through the
generation of a standard curve. A standard curve is
generated by creating a dilution series of sample nucleic
acid and performing real-time PCR. Then, results are
plotted with input nucleic acid quantity on the x-axis
and Ct
on the y-axis. Samples used to generate the
standard curve should match (as closely as possible)
those that will be used for the experiment (i.e., the same
total RNA or DNA sample). The dilution range, or dynamic
range analyzed for the standard curve, should span
the concentration range expected for the experimental
samples. The slope of the curve is used to determine
the reaction efficiency, which, as noted previously, most
scientists agree should be between 90% and 110%.
In Figure 21, standard curves generated for three different
targets are shown. The parallel nature of the red and blue
curves indicates that they have similar efficiencies and
therefore can be accurately compared at any dilution.
An example of this type of comparison would be when
a normalizer gene is compared against a target gene
to adjust for non-biological variability from sample to
sample. The purple curve, however, becomes less
efficient at the lower concentrations and therefore cannot
accurately be used for comparison purposes at these
lower concentrations.
In addition to assessing the experimental conditions and
providing an efficiency value for relative quantitation,
standard curves can also be used to determine whether
the problem with a particular reaction is due to inhibition
or lack of optimization. This will be discussed in more
detail in the troubleshooting section.
Sensitivity and reproducibility
A standard curve with an efficiency within the desirable
window of 90–110% defines the range of input template
quantities that may be measured in real-time PCR. To
some, sensitivity is measured by how early a target Ct
appears in the amplification plot. However, the true gauge
of sensitivity of an assay is whether a given low amount
of template fits the standard curve while maintaining a
desirable amplification efficiency. The most dilute sample
that fits determines reaction sensitivity.
The standard curve also includes an R2
value, which is a
measure of replicate reproducibility. Standard curves may
be repeated over time to assess whether the consistency,
and therefore the data accuracy for the samples,
is maintained.
32 33
Experimental designExperimental design
Plate preparation
3
Plate preparation
3
31	Mixing	 36
3.2	 Plate loading	 36
3.3	 Plate sealing	 36
3.4	 Plate insertion	 37
Contents
35
Plate preparationPlate preparation
3 3
3.4	 Plate insertion
Once the plate is ready, it may be loaded into the real-time
PCR instrument, following the manufacturer’s instructions.
Plates containing DNA or cDNA template and Applied
Biosystems™
AmpliTaq Gold™
reagents are very stable
at ambient temperature. They can be routinely stored at
room temperature under normal laboratory lighting for
days without ill effect. Avoid direct exposure of loaded
plates to sunlight; this can compromise the fluorescent
dyes in the mixture. If a plate needs to be transported
outside, wrap it in aluminum foil to protect it from sunlight.
For instruments with interchangeable thermal cycling
blocks, be sure that the block matching the plate type is
installed. Note that a 96-well standard block and 96-well
Fast block are not the same. Standard 96-well plates and
standard tubes have a 0.2 mL capacity, whereas Fast
96-well plates and Fast tubes can accommodate 0.1 mL.
Fast plastics must be used with a Fast block, even if Fast
mode is not being used.
The loading process varies with the model of instrument.
Some instruments have a drawer system: the drawer is
pulled out, the plate is placed in the block or holder, and
the drawer is pushed back in. For some instruments, the
plate is placed on an arm, which is computer controlled.
3.1	Mixing
It is a good idea to briefly mix, then centrifuge all realtime
PCR reaction components just before assembling
reactions. Gently swirl enzyme-containing master mixes
and briefly (1–2 seconds) vortex other components such
as PCR primer pairs or TaqMan Assays, and thawed
nucleic acid samples. Since real-time PCR master
mixes are typically denser than the other real-time PCR
reaction components, it is important to adequately mix
reaction mixtures, because otherwise, precision could
be compromised. Gently inverting tubes a few times
or lightly vortexing for 1–2 seconds are highly efficient
mixing methods. However, avoid overvortexing, because
it can cause bubbles to form that could interfere with
fluorescence detection, and can reduce enzyme activity,
which could reduce amplification efficiency. Always
centrifuge briefly to collect the contents at the bottom
of the container and eliminate any air bubbles from
the solutions.
3.2	 Plate loading
Base the order of reagent addition into reaction plates
or tubes on the nature of the experiment. For example,
to analyze the expression of 5 genes in 20 different RNA
samples, it would make more sense to dispense assay
mix into the reaction plate or tube first and then add
sample. On the other hand, to analyze the expression of
20 genes in only 5 different RNA samples, it would be
easier to first dispense the RNA samples, then add assay
master mix. Regardless of the order of reagent addition,
plan your pipetting to avoid cross-contamination of
samples and assays. Mixing fully assembled reactions is
not necessary, because nucleic acids are hydrophilic and
will quickly mix with all other reaction components.
3.3	 Plate sealing
Plastic PCR plates may be sealed with optical caps
or optical covers, which are thin sheets of plastic with
adhesive on one side. The adhesive is protected by a
white backing. On the ends of the cover are rectangular
tabs delineated with perforations. Use these tabs to
handle the cover without touching the cover itself. Remove
the white backing and place the cover on top of the plate,
inside the raised edges. A square plastic installing tool
is provided with the covers. Use it to smooth down the
cover, especially along the four edges at the top of the
plate. The edge of the installing tool may also be used
to hold down each end of the cover as the white strips
are removed by the perforation, so as not to pull up the
cover. Inspect the top of the plate to verify that the cover
is in good contact with the plate, especially along the four
upper edges.
Once the plate has been sealed, hold it up and inspect the
bottom, looking for any anomalies, such as unintended
empty wells, drops of liquid adhering to the walls of the
well, and air bubbles at the bottom of the well. Note any
empty wells or wells with abnormal volumes. Centrifuge
the plate briefly to correct any adherent drop and bottombubble
problems.
Plates may be safely labeled along the skirt. Alternatively,
plates are available with bar codes. Do not write on
the surface of the plate over well positions, as this will
interefere with fluorescence excitation and reading. Also,
do not write on the bottom of plates, as the ink could be
transferred to the block in the real-time PCR instrument.
Significant block contamination by colored or fluorescent
substances can adversely affect real-time PCR data.
36 37
Data analysis
4
Data analysis
4
4.1	Introduction	 40
4.2	 Absolute quantification	 40
4.3	 Comparative quantification	 42
4.4	 High resolution melting	 44
curve analysis
4.5	 Multiplex real-time PCR analysis	 46
Contents
39
Data analysisData analysis
4 4
heterogeneous environment and help to balance reaction
efficiency. It has been shown that background RNA can
suppress the cDNA synthesis rate as much as 10-fold.
Standard curve application—complementary
RNA (cRNA)
To demonstrate how the recommendations for an
absolute quantification standard curve should be applied,
this section will walk step by step through the creation of a
cRNA standard curve for this method of quantification.
T7 RNA polymerase can be used to generate a
homogeneous pool of the transcript of interest from a
plasmid or a PCR product.
Because it has an extended limit of detection and
better accuracy, fluorometric measurement of cRNA
is recommended over UV absorbance measurement.
Another precise method of quantification is digital PCR.
With the copy number determined, unrelated yeast tRNA
can be added at a 1:100 cRNA to tRNA ratio to mimic the
normal background of biological samples. This standard
is then diluted over at least 5 to 6 orders of magnitude for
use in Ct
determination by real-time PCR.
Pipetting inaccuracies can have a significant effect on
absolute quantification data. Appropriate precautions can
minimize this effect. As can be seen in the plate setup
in Figure 24, three separate cRNA dilution series are
prepared, and each dilution within each series is amplified
in duplicate. It is important that the dilution series
encompass all possible template quantities that may be
encountered in the experimental samples. For example,
the lowest point in the standard curve should not contain
100 template copies if it is possible that an unknown test
sample may contain only 10 copies.
For each dilution, six Ct
values will be obtained. The high
and low Ct
values are discarded, and the remaining four
Ct
values are averaged. Focusing on the 10-4
dilution in
this example (Figure 24), it can be seen how the Ct
values
for a given sample vary by as many as 2 cycles. This is
minimized by assigning this dilution, which corresponds to
a particular copy number, the average Ct
value of 21.4.
Figure 23. Schematic diagram of the in vitro transcription
protocol. The PCR product generated from the real-time PCR itself
can be reamplified with a 5´ T7 promoter-containing sequence and a
3´ poly(T)-containing reverse primer. The in vitro transcription reaction
produces polyadenylated sense mRNA. After purification, it will be
accurately quantified and diluted for the standard curve.
Figure 24. Plate setup for standard curve generation. When
calculating the average Ct
value, the highest and lowest values
obtained from replicate reactions can be discarded.
4.2	 Absolute quantification
Absolute quantification is the real-time PCR analysis
of choice for researchers who need to determine the
actual copy number of the target under investigation. To
perform absolute quantification, a target template solution
of known concentration is diluted over several orders of
magnitude, amplified by real-time PCR, and the data are
used to generate a standard curve in which each target
concentration is plotted against the resulting Ct
value.
The unknown sample Ct
values are then compared to this
standard curve to determine their copy number.
Standard curve generation—overview
With an absolute standard curve, the copy number of
the target of interest must be known. This dictates that,
prior to curve generation, the template must be accurately
quantified. Figure 22 highlights a standard curve setup. A
sample of the target of interest is accurately determined
to contain 2 x 1011
copies. The sample is diluted 10-fold
eight times, down to 2 x 103
copies, and real-time PCR is
performed on each dilution, using at least three replicates.
The resulting standard curve correlates each copy
number with a particular Ct
. The copy number values for
the unknown samples are then derived by comparison to
this standard curve. The accuracy of the quantification is
directly related to the quality of the standard curve.
In absolute quantification, consider the following:
1.	The template for standard curve generation and
the method used to quantify that template are the
foundations for the experiment. Pipetting accuracy for
the dilution series is essential. Also remember that realtime
PCR sensitivity amplifies minute human error.
2.	Similar reverse transcription and PCR efficiencies for
the target template and dilution series of the actual
samples are critical.
Template choice for standard curve generation
As mentioned, the template used for absolute standard
curve generation will determine the accuracy of the data.
Although a homogeneous, pure template may be needed
for initial copy number determination, for generation of
the standard curve, it is best to use target template that
is as similar to the experimental samples as possible.
Because steps such as nucleic acid isolation and reverse
transcription play a role in reaction dynamics, this includes
subjecting it to most of the same processing steps as the
experimental samples. The following types of template
have been used as absolute quantification standards:
1.	DNA standards—PCR amplicon of the target
of interest, or plasmid clone containing the target
of interest.
Pros: Easy to generate, quantify, and maintain stability
with proper storage
Cons: Cannot undergo the reverse transcription
step of qRT-PCR, which can impact reaction
efficiency significantly
2.	RNA standards—in vitro–transcribed RNA of the
target of interest (Figure 23).
Pros: Incorporates reverse transcriptase efficiency and
mimics the target of interest most similarly
Cons: Time-consuming to generate and difficult to
maintain accuracy over time due to instability
The homogeneous nature of each of the RNA and DNA
standards means that they will often exhibit higher
efficiencies than experimental samples. Therefore,
background RNA, such as yeast tRNA, can be spiked
into the standard template to create a more realistic
4.1	Introduction
As mentioned in the beginning of the experimental design section, selecting the right quantification method depends on
the goals of the experiment.
•	 Absolute quantification determines actual copy numbers of target, but is also the most labor-intensive and difficult
form of quantitation. This method requires thoughtful planning and a highly accurate standard curve. Absolute
quantitation is often used for determining viral titer.
•	 Comparative quantification still requires careful planning, but the data generated are for relative abundance rather
than exact copy number. This is the method of choice for gene expression studies, and it offers two main options for
quantification: ΔΔCt
and standard curve quantification.
Figure 22. Workflow for standard curve setup for absolute
quantification.
Starting quantity = 2 x 1011
molecules
y = mx + b
Copy number
Dilution
y = Ct
m = slope
b = y-intercept
x = copy number
10-1
2 x 1010
10-2
2 x 109
10-3
2 x 108
10-4
2 x 107
10-5
2 x 106
10-6
2 x 105
10-7
2 x 104
10-8
2 x 103
40 41
Data analysisData analysis
4 4
4.3	 Comparative quantification
Comparative quantification, while still technically
challenging, is not quite as rigorous as absolute
quantification. In this technique, which applies to most
gene expression studies, the expression level of a gene
of interest is assayed for up- or downregulation in a
calibrator (normal) sample and one or more experimental
samples. Precise copy number determination is not
necessary with this technique, which instead focuses on
fold change compared to the calibrator sample.
Here the common methods of comparative quantification
and how variability is controlled in each are outlined.
Comparative quantification algorithms—ΔCt
This is comparative quantification in its most basic form.
Ct
values are obtained for expression of the gene of
interest from both a test and calibrator sample, and the
difference between them is the ΔCt
. The fold difference is
then simply 2 to the power of ΔCt
.
Fold difference = 2ΔCt
This basic method is inadequate because it does not
control for differences in sample quantity, sample quality,
or reaction efficiency (Figure 25).
Comparative quantification algorithms—ΔΔCt
The ΔΔCt
method is a very popular technique that
compares results from experimental samples with both
a calibrator (e.g., untreated or wild type sample) and a
normalizer (e.g., housekeeping gene). With this method,
Ct
values for the gene of interest (GOI) in both the test
sample(s) and calibrator sample are now adjusted in
relation to a normalizer (norm) gene Ct
from the same
two samples. The resulting ΔΔCt
value is incorporated to
determine the fold difference in expression.
Fold difference = 2–ΔΔCt
ΔCt sample
– ΔCt calibrator
= ΔΔCt
Ct GOI
s
– Ct norm
s
= ΔCt sample
Ct GOI
c
– Ct norm
c
= ΔCt calibrator
The requirement for the ΔΔCt
method is that the
efficiencies for both the normalizer and target gene are
identical. Of course, the obvious question is: what range
of deviation is acceptable? The way to determine this
is to generate a standard curve for both the normalizer
gene and target gene of interest using the same samples
(Figure 26). The average ΔCt
between the normalizer and
target gene can be obtained for each dilution. The value
itself is not important; it is the consistency of that value
across each dilution that matters.
To some researchers, this small deviation in efficiency still
opens the door to inaccuracies. Employing a correction
for both the gene of interest and the normalizer minimizes
the effects of variation in amplification efficiency.
Comparative quantification algorithms—standard
curve method
The standard curve method of comparative quantification
employs the Ct
difference between the target gene in the
test and calibrator samples, normalized to the reference
gene Ct
values and adjusted for minute variations in
amplification efficiency. A standard curve to determine
amplification efficiency for both the normalizer and the
gene of interest is necessary with this method, but it does
avoid the assumptions made with previous techniques. A
requirement of this technique is that the normalizer gene
be the same across all samples in the analysis.
Figure 25. Comparative quantification of expression in a
treated sample and calibrator. The treated sample and calibrator
were run in duplicate; the calibrator Ct
was 6 and it was 12 for
the treated sample. According to the ΔCt
method, the calculated
relative expression level of the target gene in the treated sample
is 64-fold lower than that of the calibrator. However, because a
normalizer was not employed, the effects of experimental variability
on this result are unknown, and thus the conclusion cannot be
considered trustworthy.
In Figure 27,
Fold difference = (Etarget
)ΔCt target
/(Enormalizer
)ΔCt normalizer
E = efficiency from standard curve E = 10[–1/slope]
ΔCt target
= Ct GOI
c
– Ct GOI
s
ΔCt normalizer
= Ct norm
c
– Ct norm
s
Fold difference equation derived from M.W. Pfaffl in A-Z of Quantitative PCR.
In order to capture the most accurate efficiency value
for the calculation, choose the calibrator sample for the
standard curve carefully. This calibrator sample should
undergo the same purification procedure, be involved
in the same reactions, and have similar complexity
to the experimental samples. Therefore, the perfect
calibrator sample is one of the heterogeneous samples
containing the target of interest—for example, total RNA
from the cell line or tissue being studied. Keep in mind
that any differences between the calibrator sample and
the experimental samples may result in an inaccurate
efficiency correction and therefore inaccurate calculations
for fold changes in gene expression. Because copy
number is irrelevant, the dilutions or values given to those
dilutions can be arbitrary.
While the same setup for the amplification curves from the
ΔΔCt
method are used in this technique, efficiency values
from standard curves (ideally run on the same plate) are
now incorporated to adjust the normalizer and geneof-interest
Ct
values. Efficiencies are derived from both
slopes (Figure 27).
In summary, the first step in choosing a quantification
strategy is to determine whether absolute or relative
quantification will best address the questions to be
answered. To find out how many target molecules are
in the sample, a precise standard curve using known
quantities of target template must be generated. In
most cases, relative quantification will be the method of
choice. The ΔCt
method does not employ a normalizer,
while the ΔΔCt
method involves one or more reference
genes to normalize for real-time PCR processing
variability. Employing a normalizer gives the option of
fold-change calculations, with or without an adjustment in
reaction efficiency.
Figure 26. Relative efficiency plot. The ΔCt
ranges from 2.0 to
2.5. When plotted against dilution or input amount of RNA, a slope
is obtained. While a perfectly flat line (slope = 0) indicates identical
efficiency across all input concentrations, a slope of <0.1 is generally
considered acceptable when employing the ΔΔCt
method.
Figure 27. Efficiency values are obtained from standard curves
to adjust the normalizer and gene-of-interest Ct
values. HeLa
RNA was diluted over 6 orders of magnitude, and real-time PCR was
performed to generate standard curves for both the normalizer and
gene of interest (GOI).
42 43
Data analysisData analysis
4 4
4.4	 High resolution melting curve analysis
High resolution melting curve analysis is a homogeneous,
closed-tube post-PCR method for identifying SNPs, novel
mutations, and methylation patterns. High resolution
melting curve analysis is a more sensitive approach
than traditional melting curve profiling, in which dsDNA
is monitored for the temperature at which it dissociates
into ssDNA, its Tm
. High resolution melting curve profiling
requires a real-time PCR instrument with upgraded
optical and thermal capabilities as well as analysis
software for extremely fast data acquisition and highly
accurate thermal control and consistency. The Applied
Biosystems™
QuantStudio™
3, 5, 6 Flex, 7 Flex, 12K
Flex, ViiA™
7, 7900HT Fast, 7500 Fast, StepOnePlus™
,
and StepOne™
real-time PCR systems; the Qiagen™
Rotor-Gene™
6000 System; and the Roche Diagnostics™
LightCycler™
480 System are commercially available
instruments currently set up to perform high resolution
melting curve analysis.
In this type of analysis, approximately 80–250 bp
fragments of genes are amplified using PCR in mixtures
that contain a high-performance dsDNA-binding dye.
The Applied Biosystems™
MeltDoctor™
HRM Master Mix
employs MeltDoctor HRM Dye, a thermostabilized form
of the fluorescent SYTO™
9 dye with low background
fluorescence and high brightness in the presence of
dsDNA. After 40 cycles, the amplification products
are annealed and highly fluorescent. When the high
resolution melting curve analysis begins, the real-time
PCR instrument slowly ramps the temperature higher
while simultaneously recording fluorescence data from
the amplicons. As the PCR products begin to denature
(or melt), their fluorescence will slowly decrease due to
the fluorescent dye being released, until the temperature
approaches the PCR product’s Tm
. Very close to the Tm
,
a dramatic decrease in fluorescence is observed as the
sample transitions from dsDNA to ssDNA (Figure 28).
High resolution melting curve applications
The most widely used high resolution melting curve
application is gene scanning. Gene scanning is the search
for the presence of unknown variations in PCR amplicons
prior to, or as an alternative to, sequencing. Mutations in
PCR products are detectable by high resolution melting
curve analysis because they lead to changes in the shape
of DNA melting curves. When amplified and melted,
heteroduplex DNA samples show melting curves with
different profiles than those derived from homozygous
wild type or mutant samples.
Some common applications of high resolution melting
curve analysis include:
•	 Gene scanning (mutation discovery)
•	 Mutation analysis
•	 SNP detection
•	 Heterozygosity studies
•	 Species identification
•	 Methylation analysis
These applications traditionally required a unique
fluorogenic probe for each target, which was expensive,
time-consuming to design, and inflexible. High resolution
melting curve analysis using dsDNA-binding dyes offers
the same capabilities as probe-based analysis in a more
inexpensive and flexible format.
While many applications exist for high resolution melting
curve analysis, discrimination at the single-nucleotide level
is one of the more challenging, due to the minute Tm
shifts
that must be detected.
Figure 28. Characteristics of the melt-curve profile for a PCR
amplicon. Specific DNA sequences have characteristic melt-curve
profiles. Mutations can be detected as either a shift in Tm
or a change
in shape of the melting curve. In contrast to traditional melting curve
analysis, high resolution melting curve analysis can distinguish
between amplicons with just a single-nucleotide difference. This
technique has opened the door to many new applications for dsDNAbinding
dyes.
High resolution melting curve analysis chemistry
In addition to a specialized instrument and software, high
resolution melting curve analysis requires dsDNA-binding
dyes that are capable of distinguishing the melting points
of amplicons that differ by a single nucleotide.
Dyes that have been successfully used for high resolution
melting curve analysis include:
•	 MeltDoctor HRM Dye
•	 SYTO 9 dye
•	 BioFire™
Defense LCGreen™
and LCGreen™
Plus+
reagents
•	 Biotium™
EvaGreen™
dye
Keys to successful high resolution melting
curve assays
•	 Set an appropriate ramp rate for the instrument. This
will typically result in 10–20 data collection points per
°C, which is needed for high resolution melting curve
analysis.
•	 Keep amplicons short for highest sensitivity. Compared
to larger amplicons, those around 100 bp will allow
easier detection of single-nucleotide melt events.
•	 Ensure specificity of the PCR amplicon. Mispriming
products and primer-dimers can complicate data
interpretation. Primer concentrations lower than
200 nM, MgCl2
in the 1.5 mM to 3 mM range, and use
of a hot-start DNA polymerase will help to obtain high
specificity. Assess mispriming using a standard low
resolution melting curve. No-template control melting
curves are important for evaluating specificity.
•	 Avoid amplifying across regions that could contain
variations other than those of interest. Check for
species homology, exon/intron boundaries, splice
sites, and secondary structure and folding of the
PCR product.
•	 Maintain similar fluorescent plateaus, and therefore
similar PCR product quantities, for all targets being
analyzed. Differences in quantity between the samples
being compared can affect melting temperatures and
confound analysis. Starting with similar amounts of
template can be helpful.
•	 Ensure that enough template is used in the reaction.
In general, Ct
values should be below 30 to generate
sufficient material for accurate melting curve analysis.
•	 Provide a sufficient melt data collection window. For
example, the window should have a range of 10°C
on either side of the melting temperature of the
amplicon (Tm
± 10°C). Sufficient pre- and post-melting
temperature data are required for accurate curve
normalization and high replicate correlation.
•	 It is also recommended, for some instruments, to
insert a pre-hold step at 50°C following amplification
(but prior to melting) to ensure that all products have
reassociated and to encourage heteroduplex formation.
Use a mix, such as MeltDoctor HRM Master Mix, that
offers sensitive and unbiased amplification of the gene
fragments of interest.
44 45
Data analysisData analysis
4 4
4.5	 Multiplex real-time PCR analysis
Multiplexing is a technique in which more than one target
is analyzed in the same real-time PCR reaction. Each
target is distinguished by a particular dye, conjugated
to the fluorogenic probe or primer pair specific for
that target. Typically, multiplex reactions are used to
amplify a normalizer gene and a gene of interest in the
same reaction.
Theoretically, the number of targets that can be amplified
in a given reaction is limited only by the number of
available spectrally distinct dyes and the number of dyes
that can be excited and detected by the real-time PCR
instrument. However, other experimental hurdles exist:
the different primer pairs and/or probes in a reaction
must not interact with each other, and these primers and
probes have to share available PCR components, such as
dNTPs and thermostable DNA polymerase. While more
time-consuming to optimize, multiplexing offers several
distinct advantages:
•	 Less variability, more consistency—multiplexing
a normalizer and gene of interest in the same tube
eliminates well-to-well variability that could arise if those
same two targets were amplified in different (even
adjacent) wells
•	 Less reagent usage, less cost—multiplexing requires
fewer reactions to analyze the same number of targets
•	 Higher throughput—more targets can be analyzed per
real-time PCR run and per sample
Keys to a successful multiplex assay
A successful multiplex reaction must take many factors
into consideration, including:
•	 Primer and probe design
•	 Reagent optimization (including primer concentration,
target abundance, reaction components, and
fluorophore/quencher combinations)
•	 Validation of the multiplex assay
Primer and probe design
Primer and probe design is arguably the most critical
factor in a multiplex assay. As reaction complexity
increases, so does the probability that primers and
probes will dimerize or that competition for reaction
components will limit the amplification of one or more
targets. The following are particularly important factors
that will maximize performance while minimizing
competitive effects:
•	 Keep amplicons short. Designing primers to amplify a
segment ranging from 60 bp to 150 bp will enhance
reaction efficiency.
•	 Design primers with Tm
values within 1°C of each
another. Remember, all primers and probes will be
annealing at one temperature. Mismatched Tm
values
will result in an efficiency bias.
•	 Perform BLAST searches with primer and probe
designs to ensure their specificity for the targets
of interest.
•	 Use primer design software to determine whether
any of the primer or probe sequences are prone to
dimerization. One such free program, AutoDimer
(authored by P.M. Vallone, National Institute of
Standards and Technology, USA), can analyze all the
primer designs in a given multiplex reaction for their
propensity to dimerize in any combination. Another
program, Multiple Primer Analyzer, is available on the
Thermo Fisher Scientific website.
Reagent optimization
A critical concern in multiplex reactions is the competition
for reagents among the different targets being
amplified. Ensuring a high efficiency of amplification
requires reducing the amount of primers, increasing
the concentrations of all components, or both. Most
optimization experiments begin by testing different
primer concentrations.
Primer concentration and target abundance
Not all amplicons in a multiplex reaction are present in
the same numbers nor amplify at the same efficiency.
Limiting the primer concentration for those targets that
are easier to amplify or more abundant can allow more
consistent amplification across targets. For example,
if β-actin (a high-copy normalizer) is multiplexed with a
low-abundance target, it may exhaust the shared reaction
components in the early cycles. Reducing the amount
of primers for β-actin limits its rate of amplification,
allowing the less-abundant target to be amplified in an
unhindered manner. In general, for higher-abundance
targets, use the lowest primer concentration that does not
increase Ct
values.
Reaction component concentrations
Every multiplexing reaction is different, but adjusting
primer concentrations is most likely to result in Ct
values
that are consistent between singleplex and multiplex
reactions. Other alternatives include increasing the
amounts of Taq DNA polymerase, magnesium, and
dNTPs and increasing the buffer strength to try to
boost the sensitivity and amplification efficiency of all
targets involved.
Fluorophore/quencher combinations
The reporter fluorophores in a multiplex reaction must
be spectrally distinct so that the fluorescence signal
arising from each is detected in a single channel. With
compatible dyes, the real-time PCR instrument excitation
and emission optics are able to filter the wavelengths so
that little, if any, fluorescence is attributed to the wrong
fluorophore (such interference is also called cross-talk).
Similarly, the choice of quencher for each duallabeled
fluorescent probe becomes more important
as the number of probes being multiplexed increases.
Fluorescent quenchers such as TAMRA™
dye, a common
quencher for FAM™
dye, work by releasing the energy of
the fluorophore at a different wavelength. In a multiplex
reaction, quenchers of this type result in multiple signals
at different wavelengths, which can complicate filtering
and possibly data integrity. Dark quenchers such as
nonfluorescent quenchers or QSY™
quenchers, on the
other hand, release energy in the form of heat rather than
fluorescence, and therefore keep the overall fluorescent
background lower. Choose appropriate multiplex dye
combinations based on the detection capabilities of the
instrument being used.
Validating the multiplex assay
As with singleplex real-time PCR assays, a standard
curve should be completed to assess the reaction
efficiencies of all the targets in a multiplex reaction prior
to running the assay. There are two main stages in this
validation process:
1.	Validating the primers and/or probes for each target
and determining their individual efficiencies. This is the
initial assessment of primer and probe design.
2.	Optimizing the efficiency of the overall multiplex assay.
Evaluate each primer and probe set on an individual basis
to determine the designs and conditions that are ideal for
the target. This is accomplished through a dilution series
standard curve, again trying to achieve close to 100%
efficiency. After each primer/probe combination has been
functionally validated, move on to multiplex optimization. It
is important to keep in mind that the singleplex conditions
for primer/probe concentrations may not be optimal when
the targets are multiplexed. When building a multiplex
panel, it is also advisable to add targets one at a time
rather than combining all targets in the first experiment,
if possible.
Using the same standard curve methodology, combine
all primers and probes and perform the multiplex reaction
for each dilution. Compare the resulting efficiency for
each target with its corresponding singleplex real-time
PCR reaction efficiency. Ideally, there will be little change
between single and multiplex reaction standard curves. If
the reaction efficiencies for the multiplexed targets vary by
greater than 5% or fall outside the desirable range of 90–
110%, optimization of the primer/probe concentrations or
other components in the multiplex assay will be required.
The Ct
values in the multiplexed reaction should be
comparable to those obtained in the singleplex reactions
so that the sensitivity is not compromised.
46 47
Troubleshooting
5
Troubleshooting
5
5.1	Introduction	 50
5.2	 Frequently asked questions	 59
Contents
49
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55
5.1	Introduction
Part of implementing an ideal real-time PCR assay
involves optimization to ensure that all parameters
of the reaction are finely tuned for accurate results.
Assay validation accompanied by any required reaction
adjustments should be performed any time a new gene is
being studied or assay parameters are altered. This could
involve adjusting primer concentrations and thermocycling
temperatures and times, and then confirming the
parameters through a standard curve assessment.
While optimization does take time, it is time well spent.
The resulting assay will have the highest sensitivity and
dynamic range, a high efficiency (which correlates with
high accuracy), and excellent reproducibility. These factors
all lead to confidence in the data and ultimately to results
accepted by the research community.
Troubleshooting a real-time PCR reaction can seem
daunting. However, assuming proper assay design
was taken into consideration, common real-time PCR
difficulties can be grouped into four main areas:
•	 Formation of primer-dimers
•	 Storage of primers and probes
•	 Real-time PCR inhibition and poor reaction efficiency
•	 Software analysis settings
Formation of primer-dimers
Primer-dimers form when partial sequence homology
exists between the members of the primer pair. If the
primers anneal to each other during PCR, the Taq DNA
polymerase may be able to extend them and create a
product larger than the original primers and one that is
more prone to anneal erroneously as cycling progresses.
Depending on its length, it is also possible for a primer
to fold upon itself and therefore set up a competitive
environment with the template. Reaction complexity,
especially that present in multiplex reactions, increases
the opportunity for these unwanted interactions to occur.
Primer-dimer formation is one of the most common
problems that requires troubleshooting during real-time
PCR design and validation, but many opportunities
exist to eliminate them from real-time PCR reactions.
Before discussing how this is done, it is first important
to understand why dimer formation should be minimized
or reduced.
Problems caused by primer-dimers
The effect that primer-dimers can have on a reaction
depends largely on the chemistry being employed.
Fluorogenic probe–based reactions tend not to be
influenced as much by primer-dimers because a probe
annealing and being cleaved in a primer-dimer region is an
extremely rare event. In this case, competition for primers
is the main factor for consideration. Reactions that rely
on dsDNA-binding dyes, on the other hand, are highly
dependent upon primer-dimers being absent, because
the dye would bind to them nonspecifically and therefore
contribute to fluorescence signal being monitored during
the reaction. This in turn shifts the Ct
and skews results.
While the extraneous signal is the most important factor,
competition within a reaction well also has a direct impact
on reaction efficiency. As mentioned earlier, poor reaction
efficiency shrinks the dynamic range, which in turn
decreases sensitivity.
It is best to take simple precautions during primer design
to avoid dimerization in the first place. There are several
free tools available to assist with this. One such tool is
AutoDimer (authored by P.M. Vallone, National Institute
of Standards and Technology, USA), which analyzes
the sequences of primer pairs and flags those that
theoretically have a tendency to dimerize.
Although bioinformatics-based primer design can reduce
the likelihood of dimer formation, it is still necessary to
monitor dimerization experimentally.
Determining if primer-dimers are present
Gel electrophoresis is a great way to visualize primerdimers.
Primer-dimers appear as diffuse bands near the
bottom of the gel, usually below 100 bp (Figure 29). During
PCR, there is competition between dimer formation and
template annealing and extension. As template decreases,
primer-dimers often increase.
The downside to gel analysis as the sole method of
validation is that its sensitivity is in the low nanogram
range and therefore may be inconclusive. The advantage
of gel analysis is that the size of the product can help in
the overall interpretation when melting curve data are
also available.
Melting curves, also referred to as dissociation curves,
are a standard part of reaction thermal profiles that
employ dsDNA-binding dyes. A very specific amplification
will result in a single, tight peak on the melting curve
for each well on the real-time PCR plate. Primer-dimers
manifest themselves as lower-fluorescence, broader
“waves” that indicate melting in the 70°C range. Peak
shape and melting temperature are attributable to the
small and variable sizes of primer-dimers. As mentioned
in the data analysis section, if there is any doubt whether
primer-dimers are present in a melting curve, compare the
observation with the no-template control well. A primerdimer
peak is much more common when template is
absent (Figure 30).
Reducing or removing primer-dimers
If primer-dimers are a concern, there are many options for
reducing or eliminating their occurrence in a reaction.
1.	The first is optimization of the thermal cycling
conditions, which mainly involves raising the annealing
temperature. In most cases, primers are designed
so that they anneal successfully at 60°C, because
two-step cycling (a 95°C denaturation step that goes
directly to a 60°C annealing and extension step)
facilitates robust amplification.
2.	Primer concentration can always be lowered, and even
employing different ratios of forward primer to reverse
primer may help. In most cases, a final concentration of
200 nM per primer is ideal, but this can be reduced to
60 nM if necessary.
3.	Magnesium is usually best at a concentration of about
3 mM. Primer-dimers are favored at concentrations
above this.
Figure 30. Amplification plots and melting profiles highlighting
(A) specific amplification and (B) primer-dimer effects. The
primer-dimer can be identified in (B) by the signal produced by
the no-template control sample in the amplification plot, and by
additional peaks in the melting profile.
A
B
50 51
Figure 29. Agarose gel analysis to investigate primer-dimer
formation. Prior to thermal cycling, the nucleic acid sample was
serially diluted and added to the components of a PCR mix, and
the same volume from each mixture was loaded on an agarose gel.
Dimers appear as diffuse bands at the bottom of the gel.
Troubleshooting Troubleshooting
55
4.	If primers were not evaluated for their propensity
toward dimerization, evaluate them and consider
redesigning if necessary. And, as usual, hot-start
DNA polymerases and reaction setup on ice are
also preferable.
5.	Ideally, more than one primer set for the same target
should be tested concurrently. This can actually
save much time that would otherwise be spent on
optimization if one of the pairs works immediately.
Keep in mind that dimers may be more of a concern in
one-step qRT-PCR due to the lower temperature of the
reverse transcriptase reaction in the presence of the
primer pair. Also note that there are times when primerdimers
are not a concern; for example, if they only appear
in the no-template control wells, or if the ΔCt
between the
samples and the no-template control well is >10 (since this
means that the contribution of any fluorescence from the
primer-dimers to the overall signal is negligible).
Storage of primers and probes
Although often overlooked, primer and probe storage
can have a major effect on the long-term success and
consistency of a real-time PCR assay. The main factors
that affect primer and probe stability are the storage
temperature, length of time in storage, whether they have
undergone prolonged exposure to light, the concentration
of the stored primer or probe, and the composition of the
storage solution.
Problems caused by poor storage of primers
and probes
Improper storage of primers and probes can cause them
to degrade and lose specificity, which in turn affects the
reaction efficiency. In assays that rely on fluorescently
labeled primers and probes, a degraded probe releases
free dye, which increases background and decreases
the signal-to-noise ratio. This can manifest as very
rough amplification curves due to the low fluorescence.
Fluorescent dyes attached to primers and probes can
also undergo photobleaching over time, making them less
detectable in the real-time PCR instrument.
Determining if primer or probe integrity
is compromised
The first preventive measure to ensure primer and probe
stability is simple monitoring of the storage time. In many
cases, primers and probes are stable for up to a year (or
more). However, under suboptimal conditions, storagerelated
effects may be observed within 6 months.
B
Figure 31. Amplification plots showing effects of (A) poorly
stored primers (shown by the melting curve and background
fluorescence) vs. (B) properly stored primers.
The best method to evaluate primer integrity is consistent
employment of standard curves. Replicate inaccuracy and
multiple peaks in the dissociation curve, especially if not
seen previously, are common signs that stability is low.
In the case of fluorescently labeled probes and primers,
observing a higher-than-normal level of background
fluorescence on the instrument’s multicomponent view is
indicative of probe degradation.
If the fluorescent probe or primer is not degraded but the
dye itself is, an ethidium bromide–stained gel can show
when product is made, but not detected by the real-time
PCR instrument.
Figure 31 shows standard curves highlighting the effects
of poorly stored primers. The amplification plot in Figure
31A is negatively affected by degraded primers, while
the curves in Figure 31B are what would be expected
from properly stored primers. The melting curve provides
additional detail, showing that multiple nonspecific
products are present.
Maintaining primer and probe stability over time
There are four keys to maintaining primer and probe
stability. Lyophilized primers have more flexibility
with respect to storage time and temperature. Once
reconstituted, primers should be kept at –20°C and
should be monitored for signs of decreased functionality
beyond a year or so. For labeled primers and probes,
measures that protect the labels from light (such as the
use of opaque tubes and dark storage) extend their life.
Lastly, primer concentration can have an effect on
stability. Storing primers at a concentration below 10 μM
is not recommended; in fact, primer concentrations of
100 μM are easier to work with in most cases. Primers
and probes should also be stored in aliquots to minimize
freeze-thaw cycles, especially when labeled. Tris-EDTA
(TE) buffer creates a more stable environment than water.
Moreover, TE that contains 0.1 mM EDTA (compared to
1 mM EDTA in standard TE) is a good choice because of
the sensitivity of some PCR reactions to EDTA that may be
carried over.
No-template control amplification
As discussed in the previous section, amplification signal
can be observed in no-template control reactions that
use dsDNA-binding dyes when primer-dimers form. But
there is another case in which amplification may be seen
in no-template control wells. For both probe-based and
dsDNA-binding dye–based reactions, late amplification
can be due to contamination. This can be a random
event in which not every no-template control will show
amplification, and thus this is often due to pipetting errors.
If amplification products are seen in every no-template
control well, then it is likely that one or more of the
reagents has become contaminated. Here are some steps
to take to prevent or remove contamination:
1.	Use clean work spaces, including wiping down
surfaces and reagents with nucleic acid–degrading
solutions as needed.
2.	To avoid contamination from previous PCR reactions,
use master mixes containing dUTP and UDG, so that
PCR products from previous reactions are degraded.
3.	To determine which reagent is problematic, swap
out the reagent with a new tube or different source
when possible.
4.	When possible, set up reactions in a different location,
especially when plasmid controls are in use (which can
be very easily spread but hard to remove).
Real-time PCR inhibition and poor
reaction efficiency
At this point, the importance of reaction efficiency should
be well understood among the critical factors in realtime
PCR assay design and optimization. To review, a
standard curve (generated from a dilution series of the
target template) is used to obtain an efficiency value.
This efficiency value acts as a marker of overall reaction
“health.” Low efficiency leads to one diagnosis, and high
efficiency, to a different diagnosis. Steps to improve these
scenarios will be quite different. While the ideal reaction
efficiency is 100%, the widely accepted range is 90–110%.
Causes of high or low efficiency
Inhibition occurring in the reaction is indicated by an
efficiency above 110%. Causes of inhibition include poor
RNA or DNA quality, high template concentration, and
carryover from nucleic acid purification. For example,
if silica columns are employed, chaotropic salts used
to bind the DNA or RNA might inhibit the Taq DNA
polymerase. If organic extraction is used, phenol and
ethanol carryover would have the same effect.
Poor reaction efficiency, which is an efficiency below
90%, is normally more common than inhibition. Causes
include suboptimal reagent concentrations (mainly
primers, magnesium, and Taq DNA polymerase, especially
for multiplex experiments). Other factors contributing to
poor reaction efficiency include primer Tm
values being
A
52 53
Troubleshooting Troubleshooting
55
more than 5°C different from each other and suboptimal
thermocycling conditions. As mentioned earlier,
competition for resources in the tube can produce an
inefficient reaction.
Whether an efficiency for a target is high or low, matching
efficiencies between a target and a normalizer is quite
important for maintaining data accuracy. For example, an
efficiency of 95% for target A and 96% for normalizer B is
more desirable than an efficiency of 99% for target A and
92% for normalizer B.
The problem with skewed efficiency
Efficiencies outside the range of 90–110% may artificially
skew results and lead to false conclusions, mainly
because targets for comparison will have different
efficiencies. In addition, inhibition and poor efficiency can
affect assay sensitivity, leading to a smaller dynamic range
and decreased versatility (Figure 32).
Determining if efficiency is skewed
As mentioned earlier, the best method for determining
whether a particular assay is inefficient is to generate a
standard curve of template diluted over the range of what
will be encountered with the unknown samples and look
at the efficiency over that range. It should be as close to
100% as possible.
A melting curve or gel showing multiple peaks or
products means there is a competition for reaction
resources that almost certainly will have an effect on the
reaction efficiency.
Resolving poor efficiency or inhibition
Once it has been determined that the reaction is inhibited
or is operating with poor efficiency, there are some steps
that can be taken to bring the efficiency value back into
the desirable range.
1.	For inhibition, those wells with the highest
concentration of template can be removed and the
standard curve reanalyzed. If the efficiency improves
back to under 110%, the assay is fine. Just keep
in mind that any concentrations removed from
the standard curve may not be used during the
actual assay.
2.	Another solution involves repurifying the template.
Remember to allow extra drying time to remove ethanol
from ethanol precipitations or to employ additional
on-column washes to remove chaotropic salts from
silica-based purifications.
3.	Poor efficiency is resolved through assay optimization.
Sometimes the process can be relatively pain-free,
but in other situations, as assay complexity increases,
optimization can be laborious.
4.	Raising the magnesium concentration as high as 6 mM
can improve efficiency in situations where a single
product is amplified, but lowering the magnesium may
help in cases where competition is occurring.
5.	In some circumstances, mainly multiplexing reactions,
a primer and probe optimization matrix is necessary.
In this application, different ratios or concentrations of
forward primer to reverse primer, and sometimes even
probe ratios, are tested to find the ideal concentration
combination for a given assay. The ideal primer
concentration can be anywhere from 100 to 600 nM,
while probe concentrations can be between 100 nM
and 400 nM.
6.	Ensure that the thermal cycling conditions (especially
the annealing temperature) are favorable based on
the Tm
values of the primers, and that the primers are
designed to have similar Tm
values.
In some cases, issues that appear to be reactionrelated
may in fact be software-related. Validating and/or
optimizing software settings can often bring results back
in line with expectations.
Figure 33. Amplification plots showing (A) an incorrectly set baseline and (B) a correctly set baseline.
A B
Software analysis settings
As mentioned, there are cases in which the instrument
analysis may be masking an otherwise successful
assay. Analysis settings that play the largest role in data
accuracy are:
•	 Amplification curve baseline linearity
•	 Baseline range settings
•	 Threshold
•	 Reference dyes
The amplification curve baseline linearity is one
parameter that can affect results. The instrument software
is usually good at automatically setting the baseline within
the flat portion of the curve. However, in cases where a
very early Ct
is observed, such as in cases where 18S
rRNA is used as a normalizer, the baseline can mistakenly
be placed to include a region that is no longer flat. Figure
33 shows the same plot with different baseline settings.
Figure 33A shows a plot with a baseline that spans cycles
1 through 14, which is too wide because fluorescence is
detected as early as cycle 10. The result is a curve that
dips down and pushes the Ct
later. Figure 33B shows the
baseline reset to the linear range of cycles 2 through 8,
which returns the curve and Ct
to their accurate locations.
A
D
B
E
C
F
Figure 34. Comparison of baseline setting methods to achieve acceptable reaction efficiencies. (A and D) The baseline in these plots
is manually set very wide and the slope of the standard curve is poor: only –2.81, which is well outside the preferred range of –3.58 to –3.10
(corresponding to 90–110% efficiency). (C and F) The same curves as in panels A and D, but with a baseline that the instrument automatically
chose. The slope is now inside the ideal window and the assay is now validated across this dynamic range. (B and E) These plots were manually
adjusted to have the baseline incorporate 4 to 5 additional cycles, and the slope improved even further to nearly 100% efficiency.
54 55
Figure 32. Template dilution series to assess reaction efficiency.
Dilutions with earlier Ct
values exhibit compressed Ct
values and
abnormal curve shapes. As the template becomes more dilute,
inhibition vanishes and the curves take on the more characteristic
exponential phase shape.
Troubleshooting Troubleshooting
55
Baseline range settings are not often considered but
can have an effect on the reaction efficiency. As shown in
Figure 34, the instrument default settings are more often
than not acceptable for a given assay. However, manual
adjustment can sometimes improve results even further.
The threshold (the level of fluorescence deemed
above background and used to determine Ct
) is another
parameter set automatically by the software, but one that
may also be manually adjusted (Figure 35).
When evaluating more than one kit or chemistry on
the same run, the following situation can often occur.
The software will automatically select a threshold that
is ideal for the curves with the higher plateau (the blue
plots in Figure 35). This would bias the Ct
values for the
red plots in that data set because the ideal threshold is
much lower. Therefore, each data set should be studied
independently so that the ideal threshold may be selected
for each situation.
Again, while the default settings are often very appropriate,
the threshold can be manually dragged to the middle of
the exponential phase for greater accuracy if needed.
Standard curve dynamic range validation determines
what template concentrations are acceptable in a given
assay. Concentrations from the high and/or low ends of
a standard curve can also be removed to improve the
efficiency of a reaction, as long as those concentrations
are never employed during the actual assay (Figure 36).
In general, it is OK to push the limits of detection from
very high template to very low template, knowing that
terminal data points can always be removed if efficiency
is compromised.
Figure 37. Correction for reference dye. (A) A high level of a passive reference dye such as ROX™
dye can lead to poor target signal returns.
(B) Once the signal from ROX dye is removed from the analysis, the target signals fall within the expected range.
A B
Employing reference dyes such as ROX dye and
fluorescein is a powerful method of insulating against
some instrument- and user-related errors. It has become
so common that this “behind-the-scenes” factor is often
forgotten or assumed not to have a negative impact on
a reaction. However, it is important to understand the
relationship between the instrument software and the
dye itself.
For instruments that employ a reference dye, the
software reports the fluorescence signal at Rn
(normalized reporter value), which is the reporter dye
signal divided by the reference dye signal. Therefore, if
the level of ROX dye, for example, is too high, it can result
in very poor target signal returns, which manifest as
jagged and inconsistent amplification plots (Figure 37).
Visually, it seems as if the reaction failed and much
optimization is necessary, but where to start? If the ROX
dye channel is switched off as the normalizer and data
are reanalyzed, it can be seen that the data are actually
just fine (Figure 37B); it is a reference dye normalization
issue. Along the same lines, if a mix was used that did
not have ROX dye, it is important to make sure that the
reference dye option in the software is set to “None” for
the analysis.
As mentioned, the default instrument software settings
are fine in most situations. However, verification of these
settings can increase confidence in data accuracy.
Ensure that the baseline chosen by the software is only
in the flat range of the amplification curve, and increase
or decrease the baseline range as necessary. Look at the
amplification curves in the log plot view and verify that
the threshold is set near the middle of the exponential
phase of the curve. Adjust the y-axis to be appropriately
scaled for the fluorescence plateau intensity, and keep
in mind that outliers and whole dilution sets may be
removed from the standard curve to improve efficiency
and R2
values (as long as those dilutions will not be used
when evaluating the “unknown” samples).
Lastly, keep in mind that threshold settings need to be
identical for a particular assay when comparing across a
data set.
Troubleshooting is an inevitable aspect of real-time
PCR assay validation and employment. However, by
categorizing and understanding the key issues, this can
be a relatively simple process:
•	 Ensure that primer-dimers are not contributing to
signal or poor reaction efficiency
•	 Take the steps necessary to maintain primer and
probe stability
•	 Make standard curve validation the final step in the
reaction assessment process
•	 Understand that efficiencies below 90% will be
addressed very differently from values above 110%
•	 Verify and adjust instrument analysis settings
as necessary
Figure 35. A log plot screen shot showing an example of two
sets of curves with differing plateau heights and therefore
different exponential phases. The most accurate portion of an
amplification curve for Ct
determination is directly in the middle of
the exponential phase when viewing the log plot. The ideal threshold
setting is sometimes unique for each set of data.
Figure 36. Improvement of standard curve slope achieved by
excluding outlier data. Amplification was performed on a dilution
series over 5 orders of magnitude. Across this range, the slope is
only –2.9, which is outside the desired efficiency window. The curves
represented by the lower panels have had the highest dilutions
omitted from the standard curve, and the efficiency reanalyzed. The
slope has improved to –3.1, which is considered efficient enough to
validate the assay.
56 57
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55
5.2	 Frequently asked questions
Q:	How many copies are in a given amount of human
gDNA?
A: 1 genome copy = 3 x 109
bp
1 bp = 618 g/mol
1 genome copy = (3 x 109
bp) x (618 g/mol/bp)
= 1.85 x 1012
g/mol = (1.85 x 1012
g/mol) x (1 mole/6.02
x 1023
[Avogadro’s number])
= 3.08 x 10-12
g
Each somatic cell has 6.16 pg of DNA (sperm and
egg cells have 3.08 pg). There is one copy of every
non-repeated sequence per 3.08 pg of human DNA.
Therefore, 100 ng of gDNA would have: (100,000 pg
of DNA)/3.08 pg = ~33,000 copies; 1 ng of DNA has
330 copies.
Q: Why do I have to be concerned about the efficiency
of my real-time PCR assay?
A: If you want to compare the expression levels of two
genes (for example, in cases where a normalizer gene
is employed), you need to know something about the
efficiencies of the PCR to confirm that the Ct
values
you are observing are not being influenced by contaminants
in the PCR reagents or are not arising from a
poorly optimized assay.
Q: I have found that my more concentrated template
samples give me less efficient amplification
curves: Dilute sample gives a slope of –3.4
and an R2
value of 0.99; concentrated sample
gives a slope of –2.5 and an R2
value 0.84. Why?
A: Something in your sample is inhibiting the PCR. The
reason you get better efficiency with the more diluted
samples is because the inhibitor (salt or some other
component) has been diluted below its inhibitory effect.
Here are some references that explain this:
•	 Ramakers C, Ruijter JM, Deprez RH et al. (2003)
Assumption-free analysis of quantitative real-time
polymerase chain reaction (PCR) data. Neurosci Lett
339:62–66.
•	 Liu W and Saint DA (2002) A new quantitative
method of real time reverse transcription polymerase
chain reaction assay based on simulation of
polymerase chain reaction kinetics. Anal Biochem
302:52–59.
•	 Bar T, Ståhlberg A, Muszta A et al. (2003) Kinetic
outlier detection (KOD) in real-time PCR. Nucleic
Acids Res 31:e105.
Q: Can I compare Ct
values of PCR reactions with
different efficiencies?
A: You should not compare Ct
values of PCR reactions
with different efficiencies, because the ΔΔCt
calculation
method works on the assumption that PCR efficiencies
are comparable. This is why you should optimize your
system before trying to quantify unknown samples.
The standard curve method of comparative quantification
with efficiency correction can be employed.
Q: What are quenchers, and why are they used in
real-time PCR?
A: Quenchers are moieties attached to primers or probes
so that they can quench the emission from a fluorophore
that is also attached to that primer or probe.
Quenchers are generally used in probe-based assays
to extinguish or change the wavelength of the fluorescence
emitted by the fluorophore when both are
attached to the same oligonucleotide. They usually
do this by fluorescence resonance energy transfer
(FRET). When the fluorophore gets excited, it passes
on the energy to the quencher, which emits the light at
a different (higher) wavelength. Common quenchers
are TAMRA dye, or nonfluorescent quenchers such as
MGB-NFQ, QSY, or Biosearch Technologies™
Black
Hole Quencher™
dyes.
Q: When would I use one-step as opposed to twostep
qRT-PCR?
A: Two-step qRT-PCR is popular and useful for detecting
multiple messages from a single RNA sample. It
also allows the archiving of cDNA for further analysis.
However, one-step qRT-PCR is easier to use when
processing large numbers of samples and helps minimize
carryover contamination, since tubes do not need
to be opened between cDNA synthesis and amplification.
Since the entire cDNA sample is amplified, onestep
qRT-PCR can provide greater sensitivity, down to
0.1 pg total RNA.
Q: What is MGB-NFQ? What is the benefit of it
as a quencher?
A: MGB-NFQ stands for minor groove binder–nonfluorescent
quencher. The MGB moiety increases the Tm
of
the probe, thus allowing for the design of shorter, more
specific probes. In general, the TaqMan MGB probes
exhibit great differences in Tm
values between matched
and mismatched probes, which enables more accurate
allelic discrimination and makes for a more sensitive
real-time PCR assay.
No amplification
One final problem that may occur is a complete lack of
amplification using a given assay. After verifying that all
the steps above have been addressed, other causes of
no amplification include: low expression, problems with
reverse transcription, or problems with assay design.
Problems with low expression
The common cDNA input for gene expression analysis is
1 to 100 ng, but if the gene of interest is of low abundance
in the sample, more may be needed. Test a range of input,
or ideally, run against a positive control sample to confirm
that the assay is functioning properly. If unsure about the
expected level of expression, check the literature or the
NCBI Unigene database for expression data that can give
an estimate of expected levels in different tissues.
Problems with reverse transcription
Related to low expression, if the gene of interest is of low
abundance in the sample, it may be necessary to increase
the sensitivity of the assay. Check that the real-time
PCR reaction is not overloaded with cDNA (maximum
load is 20% v/v), as this can introduce inhibitors into the
reaction and thus reduce the efficiency. Also check the
type of reverse transcriptase and primers being used.
Random primers typically yield more cDNA than oligo(dT)based
methods. Additionally, some enzymes, such as
Invitrogen™
SuperScript™
III Reverse Transcriptase, have
been engineered to be more thermostable, which will
also increase yield. Check the reaction components
to see if any of these elements can be optimized to
improve amplification.
Problems with assay design
If no amplification is observed in the assay, it is possible
that a primer or probe is not designed to the right target.
Check sequence databases such as NCBI for variants
of the gene of interest. It is possible that the assay is
designed to only one variant, which may not be expressed
in the samples being studied. Also check where the
primers and probe fall along the target sequence. Is it in
a coding region or intron? Assays targeting the 5´ UTR of
a gene, for example, will not detect an exogenous gene
target from a transfected cell (since the UTR region would
not have been included in the plasmid for transfection).
Likewise, an assay sitting within an intron sequence will
not amplify a cDNA sample.
58 59
Advanced topics
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Advanced topics
6
6.1	 Digital PCR	 62
6.2	 Digital PCR attributes	 64
6.3	 Digital PCR applications	 65
6.4	 Beginning a digital	 68
PCR experiment
Contents
61
Advanced topicsAdvanced topics
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6.1	 Digital PCR
Digital PCR compared to traditional real-time PCR
Digital PCR employs the same primer sets, fluorescent
labels, and enzymatic reagents as traditional real-time
PCR. TaqMan Assays are ideally suited to perform digital
PCR; however, SYBR Green dye has demonstrated
compatibility. The primary difference between real-time
PCR and digital PCR is that in digital PCR, a sample is
partitioned into thousands of individual PCR reactions—
in essence generating a limiting dilution. Other key
differences are detailed in Table 1. In contrast to real-time
PCR, digital PCR offers a highly precise and sensitive
approach without the need for a reference or standard
curve. These key attributes are driven by the number of
partitions and volume sampled in digital PCR. The Applied
Biosystems™
QuantStudio™
3D Digital PCR System
leverages a chip-based technology, optimally partitioning
a standard PCR reaction mix into 20,000 individual PCR
reactions (Figure 38). Upfront sample dilution ensures that
a portion of these partitions contain the target molecule,
while other partitions do not, leading to positive and
negative reactions, respectively. Following amplification
on a dual flat-block thermal cycler, the fraction of negative
reactions is used to generate an absolute count of the
number of target molecules in the sample, all without
reference to standards or controls. Figure 39 shows the
basic procedure used in digital PCR.
Target quantification in digital PCR
Quantification by digital PCR is achieved using fairly
simple statistical analysis. Since each reaction is expected
to contain zero, one, or a few molecules, the ratio of
positive and negative signals will follow a classical Poisson
distribution. For example, for a viral DNA sample in a
digital PCR reagent mixture that contains 20,000 copies
of the viral target, when the mixture is split into 20,000
partitions, mathematically the expectation is to have
approximately 1 copy in each reaction. Of course, by
chance, there would be a significant number of reactions
that contain zero, two, or more than two copies—the
probability of these outcomes is described by the
Poisson model.
Figure 40 shows the Poisson distribution model.
Continuing with this example, if 20% of the 20,000
digital PCR reactions gave a negative signal, the number
of target copies in each can be identified by finding
20% on the x-axis and identifying the corresponding
average copies per reaction based on the dashed line
on the graph. In this example, the result is 1.59 copies/
reaction. Since the calculation is based on a percentage,
the answer will be the same regardless of the number
of reactions. The difference, however, is that with more
reactions, the confidence interval is narrower so the
statistical reliability of the data is improved.
Figure 38. QuantStudio 3D Digital PCR 20K Chip. Each chip is designed with 48 subarrays x 64 through-holes/subarray. Hydrophilic and
hydrophobic coatings on plates enable reagents to stay in the bottomless through-holes via capillary action.
Conventional real-time PCR Digital PCR
Output from experiment Ct
, ΔCt
, or ΔΔCt
Copies per µL
Quantification Relative quantification Absolute quantification
Results can be affected by the: Detection chemistry (e.g., TaqMan
Assays or SYBR Green dyes)
None of these factors
Real-time PCR instrument used
Amplification efficiency of PCR
primers/probe
Figure 39. Digital PCR employs a simple workflow and uses familiar techniques.
Figure 40. Poisson equation used to calculate target quantity from digital PCR data.
Table 1. Comparison of conventional real-time PCR to digital PCR.
Percent of PCR reactions that are negative
Copies/reaction (λ)
Percentdeviation(upperandlower
95%confidenceboundary)
20
15
10
5
0
-5
-10
-15
-20
0.11 0.22 0.36 0.51 0.69 0.92 1.20 1.61 2.30
100 90 80 70 60 50 40 30 20 10 0
Sample partitioned
into many reactions
Copies/µL
Positive reactions
Negative reactions
Prepare sample Partition sample Amplify DNA Derive answer
60 µm
62 63
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66
6.2	 Digital PCR attributes
Detection of low levels of pathogen
Digital PCR extends the performance of TaqMan Assays
by enabling additional attributes that go beyond the limits
of real-time PCR. These attributes represent three main
categories­—increased precision, increased sensitivity, and
increased specificity, with the ability to perform absolute
quantification without a standard curve.
How does digital PCR manage this extra sensitivity,
specificity, and precision?
Sensitivity is driven by total volume interrogated. It’s
actually not that different from real-time PCR; however,
digital PCR yields a statistical perspective via its large
number of replicates for the target, giving greater visibility
to whether or not the target of interest is detectable.
Imagine a container full of balls (Figure 41). The chances
of capturing a particular ball of interest from the container
are increased with a greater number of balls taken out of
the container.
Specificity is driven by the assay and number of replicates
run. By individualizing the reaction, digital PCR enables
extending the performance of current TaqMan real-time
PCR assays in order to drive additional specificity. For
example, a sample containing 99 wild type molecules
and 1 mutated molecule equates to the mutation being
present at 1 in 100 or 1%. Using Applied Biosystems™
TaqMan™
SNP Genotyping Assays in standard real-time
PCR mode, the single mutant is lost in a sea of wild type
copies (Figure 42A). By first partitioning the sample,
competing wild type sequences in any reaction containing
a mutant are reduced, effectively decreasing background
noise. If sufficient partitions are used, the reaction wells
reach a point where the wild type signal no longer
overwhelms the mutant signal. In the example in Figure
42B, dividing the sample into twenty digital partitions
reduces the sample complexity within each partition
to 1 in 5 or 20%—theoretically a 20-fold improvement
compared to the starting sample.
Precision is driven by the number of replicates that
are run. Increasing replicates increases the statistical
significance of the answer, thereby giving more confidence
that the value determined represents the actual target
quantity in the sample. For maximum precision, the
percentage of negative reactions should be targeted
between 5% and 80%.
Figure 41. The Poisson principle assumes an appropriate
volume of the total pool is sampled. Increasing the amount
sampled from the total pool increases the ability to accurately
determine the number of targets.
Figure 42. By individualizing the reaction, digital PCR extends
the performance of current TaqMan real-time PCR assays in
order to drive additional specificity.
A
B
6.3	 Digital PCR applications
Precise copy number variation (CNV)
CNV is defined as a modification in the genome where
the number of copies of a gDNA sequence differs from
a reference or standard. Genomic alterations such as
insertions, deletions, inversions, or translocations can
lead to biallelic or multiallelic CNVs. CNVs are linked
to susceptibility or resistance to disease, and thus are
an important area for detailed study. Many methods of
CNV detection exist today, including fluorescent in situ
hybridization, comparative genomic hybridization, array
comparative genomic hybridization, real-time PCR, and
next-generation sequencing.
Despite advances in some of these technologies, in
many cases, measurements are not sufficiently precise
for determining copy number differences where the
ratios between the target and reference are very small.
Digital PCR, a technology capable of highly precise
measurements, enables low-percent copy number
differences to be detected and accurately quantified.
A representative panel of nine gDNA samples, procured
from the Coriell repository, was analyzed using the
QuantStudio 3D system and a standard Applied
Biosystems™
TaqMan™
Copy Number Assay specific
to the CCL3L1 genetic locus found on the long arm of
human chromosome 17, 6, or 8. Replicate measurements
indicated that the samples represent copy number
variations from 0 to 8 copies per genome (Figure 43A).
A statistically significant difference between samples
containing 7 and 8 copies was clearly discernable as a
result of the high degree of precision achieved, confirming
that digital PCR can differentiate less than a 1.2-fold
difference (Figure 43B).
Figure 43. Precision demonstrated for copy number analysis
of the CCL3L1 genetic locus on chromosome 17. (A) Copy
number was measured across nine DNA samples. The CV (column
6) was below 2.6% for each set of replicates, demonstrating a high
degree of measurement reproducibility within each replicate group.
(B) As demonstrated by nonoverlapping error bars, the achieved
measurement precision enables statistical discernment of the
CCL3L1 copy number in samples containing 7 and 8 copies.
A
B
Sample
Number of
replicates
Expected
copy number
Detected copy
number (mean)
Standard
deviation CV (%)
NA17245 6 0 0.08 0.06 N/A
NA17251 6 1 0.98 0.02 2.21
NA17258 6 2 1.96 0.05 2.47
NA17132 6 3 2.98 0.06 1.85
NA19194 8 4 4.00 0.05 1.22
NA18507 8 5 5.11 0.13 2.50
NA17110 8 6 5.91 0.12 2.07
NA17202 8 7 7.02 0.07 1.02
NA18854 8 8 7.95 0.20 2.55
0
NA17245
NA17258
NA17251
NA17132
NA19194
NA18507
NA17110
NA17202
NA18854
Samples
Copynumber
6
7
8
9
5
4
3
2
1
0
1:5 Partitions
64 65
Advanced topicsAdvanced topics
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Rare-allele detection
Rare-mutation detection has great implications in areas
such as cancer research because the accumulation
of mutations in crucial regulatory genes, such as
oncogenes or tumor suppressor genes, is an important
aspect of tumorigenesis. Acquisition of these mutations
in a tiny subset of somatic cells can be sufficient for
cancer initiation or progression.
Since these mutations are so rare, they require an assay
that delivers high signal-to-noise ratios and low rates of
false positives to false negatives.
Common SNP genotyping technologies, such as
capillary electrophoresis sequencing and real-time
PCR, are most effective at detecting mutant cells with a
prevalence no lower than about 20% (or approximately
1 in 5 cells). By combining real-time PCR chemistries,
such as TaqMan Assays, with digital PCR methodology,
researchers are now able to detect mutant cell
prevalence down to 1%—and below (Figure 44).
Digital PCR works by partitioning a sample into many
individual reactions prior to amplification, reducing
competing wild type sequences in any reaction
containing a mutation and effectively decreasing
background noise. If sufficient partitions are used, the
reaction wells reach a point where the wild type signal
no longer overwhelms the mutant signal. Because each
data point is generated digitally, the total count of each
allele, mutant and wild type, can be calculated and a
ratio determined (Figure 45).
Absolute quantification of next-generation
sequencing libraries
Next-generation sequencing libraries can be quantified
with minimal sample handling and without the need
to generate a standard curve using digital PCR.
This method enables accurate and precise library
quantification, a critical step in both the Ion Torrent™
and
other next-generation sequencing workflows, allowing for
maximizing sequencing yields downstream. To achieve
this high degree of precision, a TaqMan Assay, designed
to span both the forward and reverse adapters specific
to each library, is available.
This approach limits quantification to library constructs
that contain both adapter sequences. Ultimately, using
digital PCR to quantify next-generation sequencing
Figure 44. Rare-allele measurement using spike-recovery
method. Differing amounts of DNA from three different oncogenic
KRAS alleles were spiked into a constant amount of normal DNA.
Note the excellent correlation between input concentration and
measured concentration; the linear slope indicates that the amounts
of mutant allele were accurately measured.
Figure 45. Allelic chimerism in bone marrow transplant
samples. Two alternate alleles that differentiated a bone marrow
donor from a recipient were chosen. Samples were collected
pre–stem cell transplant (pre-SCT) and at the indicated times after
transplant. Note the recipient’s allele starts to reappear after 101
days, and is obvious by 118 days, indicating a relapse.
Figure 46. Digital PCR precisely and accurately quantifies
standards without the use of a standard curve. (A) Four standards
were measured in duplicate, and results determined in absolute
copies per microliter by digital PCR. The tight error bars demonstrate
very high precision in the measurement of each sample. (B) For
sample 600-T, an additional 10-fold dilution series over 4 orders of
magnitude was constructed. Copies per reaction for each dilution
were calculated and demonstrate excellent correlation (0.9991), with
extremely tight precision for each dilution.
libraries decreases overall sequencing costs by ensuring
an accurate quantification upfront, minimizing the need
to rerun or repeat sequencing of samples. For more
information about this application, go to
thermofisher.com/dpcrngs
Absolute quantification of nucleic acid standards
Accurate genetic measurements often require
comparison to reference samples and assay standards.
Standardization of references is especially important
in the field of metrology. For many organisms or
applications, there is often no suitable reference sample
available. Generation of reference standards using
conventional real-time PCR requires consideration of
how the reference sample will initially be calibrated,
its long-term stability, and whether there is sufficient
reference material for completion of all future studies. In
addition, the lack of broadly adopted standards impacts
comparison between laboratories.
Digital PCR does not rely on a reference sample or assay
standard; it can be used for absolute quantification,
measuring the exact copy number of a nucleic acid
target of interest (Figure 46). This capability is especially
useful for calibrating reference samples and assay
standards when none exist. Through direct copy number
determination, digitally measured assay standards
can enable laboratories to compare results, with the
assurance that measurements are based on the same
absolute baseline.
Low-level fold change of gene expression
Real-time PCR is commonly used to detect differential
gene expression; however, this approach is generally
limited to detecting changes that vary by 2-fold or more.
For some studies, detection of expression changes less
than 2-fold may be required. Furthermore, it is often
necessary to express differential gene expression with
respect to a reference gene, such as a housekeeping
gene like actin.
A
B
600-A 600-C 600-G 600-T
Copies/µL(x1010
)
2.5
2.0
1.5
1.0
0.5
0
R2
= 0.9991
Copies/reaction
Dilution from stock
10
1
0.1
0.01
0.001
0.0001
10-6
10-7
10-8
10-9
10-6
10-7
10-8
10-9
y = 1.1006x + 0.0436
R2
= 0.9968
Concentrationmeasured(%)
Concentration input (%)
10
10
100
1
1
0.1
0.1
0.01
0.01
Q7823: Donor
Q7938: +25 days Q7960: +41 days
Q8092: +101 days Q8133: +118 days
Q7832: Recipient pre-SCT
66 67
Advanced topics
6
6.4	 Beginning a digital PCR experiment
To perform a digital PCR experiment, the sample must
be diluted such that each reaction contains one or zero
molecules. First establish the starting concentration using
a spectrophotometer and convert the concentration in
ng/µL into copies/µL. Next, use this value to calculate the
volume of sample needed to target 20,000 copies/chip
for each sample. If the target copy number per genome
of the samples is known, dilute the samples so that, when
loaded on a QuantStudio 3D Digital PCR 20K Chip, each
through-hole reaction will contain approximately 0.6 to 1.6
copies of the target sequence. For example, assuming
3.3 pg/copy of a given gene is present per genome and
a 865 pL reaction well volume, the stock gDNA in a given
sample would be diluted down to 600 copies/μL or 1.98
ng/μL in the final reaction to give 0.6 copies per reaction
well. Refer to the QuantStudio 3D Digital PCR System
product manual to learn how to determine target copy
number per genome.
Each application has its own set of factors to consider when
setting up a digital PCR experiment. Please refer to the
QuantStudio 3D Digital PCR System Experimental Design
Guide for more detailed application-specific instructions. This
can be found at thermofisher.com/quantstudio3d
or in the community on the digital PCR forum at
thermofisher.com/dpcrcommunity
With the ability to achieve highly precise measurements
of ±10% or better, digital PCR is capable of resolving
changes of 2-fold or less (Figure 47).
In addition, the ability of digital PCR to determine absolute
quantification of a transcript obviates the need for a
reference gene. Like real-time PCR, digital PCR requires
the conversion of RNA to cDNA. Offering the efficiency of
conversion that is so important to experimental sensitivity,
the Applied Biosystems™
High-Capacity cDNA Reverse
Transcription Kit seamlessly integrates into a digital PCR
gene expression workflow.
Figure 47. Quantitation precision comparison between (A) digital PCR and (B) real-time PCR. Samples 1 through 5 are mixtures of
synthetic miRNAs hsa-miR-19b and hsa-miR-92 at different ratios: sample 1, 100%; sample 2, 95%; sample 3, 90%; sample 4, 75%; sample 5,
50%. After reverse transcription, cDNA was measured by real-time PCR and digital PCR on the QuantStudio 3D system. ΔCt
values of realtime
PCR between hsa-miR-19b and hsa-miR-92 were reported for each sample. The relative quantitation from digital PCR results is reported
in percentiles for each sample. Digital PCR with the QuantStudio 3D system is able to discriminate a 5% difference between samples 1 and 2
(indicated by nonoverlapping circles by Tukey-Kramer HSD test), while real-time real-time PCR was not able to discriminate even a 10% difference
between samples 1 and 3. Tukey-Kramer HSD test was done within JMP software with experimental replicates.
A B
RQ
Sample No.
100%
90%
80%
70%
All Pairs
Tukey-Kramer
0.05
60%
50%
40%
∆Ct
Sample No.
–0.8
-1.0
-1.2
–1.4
All Pairs
Tukey-Kramer
0.05
–1.6
–1.8
–2.0
1 2 3 4 5 1 2 3 4 5
68
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