Relative
Quantification or Comparative Quantification
in qPCR
Relative
quantification determines the changes in steady-state mRNA levels of
a gene across multiple samples and expresses it relative to the levels
of an internal control RNA. This reference gene is often a housekeeping
gene and can be co-amplified in the same tube in a multiplex assay or
can
be amplified in a separate tube. Therefore, relative quantification
does
not require standards with known concentrations and the reference can
be
any transcript, as long as its sequence is known. Relative
quantification
is based on the expression levels of a target gene versus one or more
reference
gene(s)
and in many experiments it is adequate for investigating physiological
changes
in gene expression levels. To calculate the expression of a target gene
in relation to an adequate reference gene various mathematical models
are
established. Calculations are based on the comparison of the distinct
cycle
determined by various methods, e.g. crossing points (CP) and cycle
threshold
values
(Ct) at a constant level of fluorescence; or CP acquisition according
to
established mathematic algorithm. To date several calculation
mathematical models have
been
developed
calculating the relative expression ratio.
A new mathematical
model for relative quantification in
real-time RT-PCR
Pfaffl
Michael W.
Nucleic
Acids Res. 2001 29(9): E45
| Use of the real-time
polymerase chain reaction (PCR) to amplify cDNA products reverse
transcribed from mRNA is on the way to becoming a routine tool in
molecular biology to study low abundance gene expression. Real-time PCR
is easy to perform, provides the necessary accuracy and produces
reliable as well as rapid quantification results. But accurate
quantification of nucleic acids requires a reproducible methodology and
an adequate mathematical model for data analysis. This study enters
into the particular topics of the relative quantification in real-time
RT–PCR of a target gene transcript in comparison to a reference gene
transcript. Therefore, a new mathematical model is presented. The
relative expression ratio is calculated only from the real-time PCR
efficiencies and the crossing point deviation of an unknown sample
versus a control. This model needs no calibration curve. Control levels
were included in the model to standardise each reaction run with
respect to RNA integrity, sample loading and inter-PCR variations. High
accuracy and reproducibility (<2.5% variation) were reached in
LightCycler PCR using the established mathematical model. |
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Relative Expression
Software Tool
(REST©) for group wise comparison
and statistical analysis of relative expression results in real-time
PCR.
Michael W.
Pfaffl,
Graham W. Horgan & Leo Dempfle (2002)
Nucleic Acids
Research 2002 30(9): E36
Summary
Use of
the real-time polymerase chain reaction (PCR) to amplify cDNA products
reverse transcribed
from mRNA (RT) is on the way to become a routine tool
used in molecular biology to study low abundant gene expression. Real-time PCR is easy
to perform, provides the necessary exactness and produces reliable
as well as rapid quantification results. But accurate quantification of
nucleic acids requires a reproducible methodology and an adequate mathematical model for
data analysis. This study enters into the particular topics of the relative quantification
in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript.
Therefore a new mathematical model is presented. The relative expression ratio
is
calculated only from the real-time PCR efficiencies and the crossing point deviation of
an unknown sample versus a control. This model needs no calibration curve. Control
levels were included in the model to standardise each reaction run with respect to
RNA integrity,
sample loading and inter-PCR variations. High accuracy and
reproducibility (<2.5% variation) were reached in LightCycler PCRusing the established
mathematical model.
Introduction
The
reverse transcription (RT) followed by polymerase chain reaction (PCR)
is the technique of choice to analyse mRNA expression derived from various
sources. Real-time RT-PCR is high sensitive and allow a quantification of rare
transcripts and small changes in gene expression. Beside this
it is easy to perform, provides the necessary exactness and produces reliable as well
as rapid quantification results. The simplest detection technique of newly synthesized
PCR products in real-time PCR uses SYBR Green I fluorescence dye, that bind
specifically to the minor groove double-stranded DNA. The quantification method of
choice depends on the target sequence, the expected range of the mRNA
amount present in the tissue, the degree of accuracy required, and
whether quantification needs to be relative or absolute.
Generally two
quantification types in real-time RT-PCR are possible:
|
(A)
|
A relative
quantification based on the relative expression of a target gene
versus
a reference gene. To
investigate the physiological changes in gene expression,
the relative expression ratio
is adequate for the most purposes.
|
|
(B)
|
An absolute
quantification, based either on an internally or an externally calibration curve.
link => absolute quantification
|
Using such a
calibration curve, the methododology has to be highly validated and the
identical
LightCycler PCR amplificationefficiencies for standard material and
target cDNA
must be confirmed. Nevertheless is the generation of stable and reliable standard material,
either recombinant DNA or recombinant RNA, very time consuming and it must be
precisely quantified. Further a normalisation of the target gene with an endogenous
standard is recommended. Therefore mainly non regulated reference genes or
house keeping genes like glyceraldehyde-3-phosphate dehydrogenase
(G3PDH
or GAPDH), albumin, actins, tubulins, cyclophilin, 18S rRNA or 28S
rRNA were applicable. House keeping genes are present in all nucleated
cell types since they are necessary for basis cell survival. The mRNA synthesis of these
genes is considered to be stable and secure in various tissues, even under
experimental treatments. But numerous studies have already shown that the
mentioned house keeping genes are regulated and vary under experimental
conditions. To circumvent the high expenditure of design and production of standard
material, as well as optimisation and validation of a calibration curve based
quantification model, and finally the needed normalisation of the target
transcripts to an endogenous housekeeping transcript, an reliable and accurate
relative quantification model in real-time (RT-) PCR is needed. This study enters into the
particular topics of the relative quantification of a target gene in comparison to a
reference gene. A new and simple mathematical model for data analysis was
established, the application of the new model was tested and compared with available
mathematical calculation models. Derived reproducibility, based on intra- and inter test
variation of this relative quantification, and accuracy of the model will be discussed.
Real-time PCR
amplification efficiencies and linearity
Real-time
PCR efficiencies were calculated from the given slopes in LightCycler
software. The
corresponding real-time PCR efficiency (E) of one cycle in the
exponential phase was calculated according to the
equation:
E = 10 ^[–1/slope]
(Figure 1)
Link => alternative efficiency calculation
methods and algorithm
Investigated
transcripts showed high real-time PCR efficiency rates for TyrA (E = 2.09), PyrB (E =
2.16)
and Gst (E = 1.99) in the investigated range from 0.40 pg to 50 ng cDNA
input
(n = 3) with high linearity (Pearson cor. coef. r>0.95).
Intra-assay and inter-assay
variation
To
confirm precision and reproducibility of real-time PCR the intra-assay
precision was determined in 3 repeats within one LightCycler run.
Inter-assay variation was investigated in 3 different experiment runs performed on 3
days using 3 different premix cups of LightCycler – Fast Start DNA Master SYBR
Green I kit (Roche
Diagnostics). Determination of variation was done in 20 ng reverse transcribed total RNA (Table
1).
Test reproducibility for all investigated transcripts was low in inter-test
experiment (<3.91%)
and even lower in intra-test experiment (<2.16%). The calculation of
test precision and test variability is based on the CP variation from the CP mean
value.
Mathematical model for
relative quantification in real-time PCR
A new
mathematical model was presented to determine the relative
quantification of a target gene in comparison to a reference gene. The
relative expression ratio ( R ) of a target gene is computed
based on E and the CP deviation of a unknown sample versus a control (Equation
1), and expressed in comparison to a reference gene.
This
reference gene could be a stable and secure unregulated transcript,
e.g. a house keeping
gene transcript. For the calculation of R, the individual real-time PCR
efficiencies
(E) and the CD deviation (delta CP) of the investigated transcripts must be known. Real-time PCR
efficiencies were calculated, according to E = 10 [–1/slope]
as shown
in Figure 1 [Etarget = real-time PCR efficiency of target
gene transcript; Eref = real-time PCR efficiency of reference gene
transcript]. CP deviations of control cDNA minus sample of
the target gene and reference genes were calculated according to the
derived CP values [delta CPtarget = CP of control - CP of
sample;delta
CPref = CP of control - sample]. Mean CP, variation of CP
and delta CP values
between control and sample of investigated transcripts are listed in
Table 2.
Beside this, the influence of differing cDNA input concentrations on
delta CP are shown. Intended cDNA input concentration variation of control and
sample were compared at different levels (low level: 3.2 ng, 4.0 ng, 4.8 ng cDNA;
high level: 16
ng, 20 ng and 24 ng cDNA). They resulted in stable and
constant delta CP cycle numbers. In Table 3 the correspondent ratios ( R ) of
target genes in comparison to the reference gene were calculated, through to
the established mathematical model (Equation 1). The expression
ratios of target genes remain stable,
even under intended –20% or +20% cDNA variation and low and high cDNA input levels,
performed in two runs. A minimal coefficient of variation (CV) of 2.50% and
1.74% was observed, respectively.
Discussion
Reverse
transcription followed by PCR is the most powerful tool to amplify
small amounts
of mRNA. Because of its high ramping rates, limited annealing and elongation time, the rapid
cycle PCR in the LightCycler system offers stringent reaction conditions
to
all PCR components and leads to a primer sensitive and template specific
PCR. The application of fluorescence techniques to real-time PCR combines the
PCR amplification, product detection and quantification of newly
synthesised DNA, as well as the verification in the melting curve analysis. This
led
to the development of new kinetic RT-PCR methodologies that are
revolutionising the possibilities of mRNA quantification.
We
focused in this paper on the relative quantification of target gene
transcripts in
comparison to a reference gene transcript. A new mathematical model for
data analysis
was presented to calculate the relative expression ratio on the basis of the PCR efficiency and
crossing point deviation of the investigated
transcripts (Equation
1). The concept of the threshold fluorescence is the
basis of an accurate
and reproducible quantification using fluorescence based RT-PCR methodologies.
Threshold fluorescence is defined as the point at which the fluorescence rises appreciably
above the background fluorescence. In the used “Fit Point Method” the
threshold fluorescence and therefore the DNA amount in the capillaries is
identical for all samples. A linear relationship between the CP, crossing the threshold
fluorescence, and the log of the start molecules input in the reaction is given.
Therefore quantification will always occur during exponential phase, and it will
be not affected by any reaction components becoming limited in the plateau
phase. In the established model the relative expression ratio of an
target gene is normalized with the expression of an endogenous desirable
unregulated reference gene transcript to compensate inter PCR variations
between the runs. Is the CP of the chosen reference gene equal in
the control as well as in the sample (delta CP = 0), stable and
constant reference gene mRNA levels are given. Under this considerations of an
unregulated reference gene transcript no normalisation is needed and Equation
1 can be shortened to Equation 2 and 3.
Two other
mathematical models are available for the relative quantification during real-time PCR. The “Efficiency
calibrated mathematical method for the relative expression ratio
in real-time PCR” is presented by Roche Diagnostics in a truncated form in an
internal publication. The complete equation is in principle the same and results in
identical relative expression ratio like our model (Equation 4).
But, the way of
calculation in the described mathematical model is hard to understand. The second model available, the
“delta-delta Ct method” for comparing relative expression results between
treatments in real-time PCR (Equation 4) is presented by PE Applied Biosystems
(Perkin
Elmer, Forster City, CA, USA). The model presumes an optimal and
identical real-time amplification efficiencies of target and reference gene of E =
2. “Delta-delta Ct method” is only applicable for a quick estimation of the
relative expression ratio. For such an quick estimation also equation 1 can be
shortened and
transferred in Equation 4,
under the
condition that
Etarget = Eref =
2
Our presented
formula 1 combines both models in order to better understanding
the mode of CP
data analysis and for a more reliable and
exact relative gene expression.
Relative
quantification is always based on an reference transcript.
Normalisation of the target gene with an endogenous standard was done via the
reference gene expression, to compensate inter-PCR variations. Beside this
further control
levels were
included in the mathematical model to standardise
each reaction run with respect to RNA integrity, RT efficiency or cDNA sample
loading variations.The reproducibility of the RT step varies greatly between
tissues, the applied RT isolation methodology (25) and the used RT enzymes (26).
Different cDNA inputconcentrations were tested on low and high cDNA input
ranges, to mimic different RT efficiencies (± 20%) at
different quantification
levels. In the applied two-step RT-PCR, using random hexamer primers,
all possible interferences during RT will influence all target transcripts as well as
the internal reference transcript in parallel. Occurring background interferences
retrieved from extracted tissues components, like enzyme inhibitors, and cDNA
synthesis efficiency were related to target and reference similarly. All
products underwent identical reaction conditions during RT and variations only
disappear during
real-time PCR. Any source of error during RT will be compensated through
the model itself. Widely distributed single-step RT-PCR models are not
applicable, because in each reaction set-up and for each investigated factor individual
and slightly different RT conditions will occur. Therefore the variation in a
two-step RT-PCR will always be lower and the reproducibility of the assay
will be higher, that in a single-step RT-PCR (8). Reproducibility of the
developed mathematical model was dependent on the exact determination of
real-time amplification efficiencies and on the given low LightCycler CP
variability. In our mathematical model the needed reliability and reproducibility was given,
which was confirmed by high accuracy and a relative error of <2.5% using low and
high template concentration input.
Conclusion
LightCycler
real-time PCR using SYBR Green I fluorescence dye is a rapid and
sensitive method
to detect low amounts of mRNA molecules and therefore offers important physiological insights on mRNA
expression level. The established mathematical model is presented in order for
a better understanding the mode of analysis in relative quantification in
real-time RT-PCR. It is only dependent on DCP and amplification efficiency of the
transcripts. No additional artificial nucleic acids, like recombinant nucleic acid
constructs in external calibration curve models, are needed. Reproducibility of
LightCycler RT-PCR in general and the minimal error rate of the model allows for an
accurate determination of the relative expression ratio. Even different cDNA input
resulted in minor variations. Relative expression is adequate for the most relevant
physiological expression changes. In future it is not necessary to establish more
complex and time consuming quantification models based on calibration curves.
For
the differential display of mRNA the relative expression ratio is an ideal and simple
tool for the verification of RNA or DNA array chip technology results.
=> Relative Expression Software Tool (
REST © ) <=
=> download REST
© <=
Analysis of relative
gene expression
data using real-time quantitative PCR and the
2^[ -delta delta Ct ] method.
Livak KJ
& Schmittgen TD. Methods 2001 Dec;25(4): 402-408
Applied
Biosystems, Foster City, California 94404, USA.
The two most
commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute
quantification and relative quantification. Absolute quantification
determines the input copy number, usually by relating the PCR signal to a standard
curve. Relative quantification relates the PCR signal of the target transcript
in
a treatment group to that of another sample such as an untreated control.
The 2(-delta delta Ct) method is a convenient way to analyze the relative
changes in gene expression from real-time quantitative PCR experiments.
The purpose of this report is to present the derivation, assumptions, and
applications of the 2(-delta delta Ct) method. In addition, we present the
derivation and applications of two variations of the 2(-delta delta Ct) method that
may be useful in the analysis of real-time, quantitative PCR data.
A quantitative real-time
PCR method for detection of B-Lymphocyte Monoclonality
by comparison of kappa and lambda
Immunoglobulin Light Chain Expression
Anders
Stahlberg,1 Pierre Aman, Börje Ridell, Petter
Mostad, and Mikael Kubista
Clinical Chemistry 49(1): 51-59
Background: An abnormal IgL
kappa / IgLlambda ratio
has long been used as a clinical criterion for Hodgkin
B-cell lymphomas. As a first step towards a quantitative real-time PCR
based multi marker diagnostic analysis of
lymphomas, we have developed a method for determination of
IgL kappa / IgLlambda ratio in clinical samples.
Methods: Light-up probe based real-time PCR was used
to quantify
,IgL kappa and IgLlambda cDNA from 20
clinical samples. The samples were also investigated by routine
immunohistochemical analysis and flow cytometry analysis.
Results: The classification of patient samples by
Q-PCR
correlated well with the routine diagnostic
data.
To account for sample and template specific PCR inhibition in the
biological samples, we developed a method for in
situ calibration to determine sample specific Q-PCR
efficiencies of the reactions being compared. This increased
considerably the accuracy of the Q-PCR
method. We also designed an approach to classify patient samples based
on average PCR efficiencies. This allowed faster
and
more cost efficient classification suitable for a first
gross classification in high throughput screens.
Conclusions: This work is a first step towards
analyzing clinical
samples using quantitative light-up probe based
real-time PCR. Our results shows that Q-PCR
based methods are highly suitable for high
throughput screens of suspected tumor samples by determining
anomalous gene expression that are characteristic
for tumor cells.
Real-Time PCR Technology for Cancer
Diagnostics
Philip S. Bernard and Carl T. Wittwer
Clinical Chemistry 48: 8 1178–1185 (2002)
Background:
Advances in the biological sciences and technology are providing
molecular targets for diagnosing and treating cancer. Current
classifications in surgical pathology for staging malignancies are
based primarily on anatomic features (e.g., tumor-nodemetastasis) and
histopathology (e.g., grade). Microarrays together with clustering
algorithms are revealing a molecular diversity among cancers that
promises to form a new taxonomy with prognostic and, more importantly,
therapeutic significance. The challenge for pathology will be the
development and implementation of these molecular classifications for
routine clinical practice. in the clinical laboratory.
Quantitative real-time PCR can determine gene duplications or
deletions. Furthermore, melting curve analysis immediately after PCR
can identify small mutations, down to single base changes. These
techniques are becoming easier and faster and can be multiplexed.
Real-time PCR methods are a favorable option for the analysis of cancer
markers.
Approach: This article
discusses the benefits, challenges, and
possibilities for solid-tumor profiling in the clinical laboratory with
an emphasis on DNA-based PCR techniques. Content: Molecular markers can
be used to provide accurate prognosis and to predict response,
resistance, or toxicity to therapy. The diversity of genomic
alterations involved in malignancy necessitates a variety of assays for
complete tumor profiling. Some new molecular classifications of tumors
are based on gene expression,
requiring a paradigm shift in specimen processing to preserve the
integrity of RNA for analysis. More stable markers (i.e., DNA and
protein)
are readily handled.
Summary: There is a
need to translate recent discoveries in oncology
research into clinical practice. This requires objective, robust, and
cost-effective molecular techniques for clinical trials and,
eventually, routine use. Real-time PCR has attractive features for
tumor profiling in the clinical laboratory.
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