TECH NOTE

Demonstration of a ΔΔCq Calculation
Method to Compute Relative
Gene Expression from qPCR Data
Josh Haimes, Melissa Kelley, Dharmacon, A Horizon Discovery Group Company, Lafayette, CO, USA

Abstract

RNAi-mediated gene silencing using small interfering RNAs (siRNAs) is aneffective technique used for varied applications from primary academic
research to therapeutic discovery. While phenotypic observations may
elucidate the effect of target-specific knockdown on biological systems,
silencing efficacy should be confirmed to ensure confidence in phenotypic
results. Efficacy is commonly reported as relative percent knockdown ofmRNA levels compared to controls and can be determined in high throughput
with easy-to-use, commercially available qPCR gene expression that aredesigned to deliver reliable expression data. This technical note outlines a∆∆Cq method for calculating experimental percent knockdown (%KD) from
Cq values obtained by probe-based qPCR analysis in an RNAi experiment toknockdown the gene expression of ALDOA in cell culture (Figure 1).
Overall, ∆∆C yields a normalized, relative gene expression value. This isaccomplished by normalization of a gene target with experimental treatment
to an endogenous reference gene(s) whose expression should remainunchanged by the treatment. Subsequently, this value is normalized to thetargeted gene’s expression detected in a separate control sample.
q

Several variations on calculating relative gene expression from qPCR dataexist; the method shown here is adapted for an experimental setup employing
cells treated in biological replicates. For a method employing technicalreplicates, please see Bustin1.

dharmacon.horizondiscovery.com• totRNA Isolation• cDNA Synthesis• qPCR Detection
7Fluorescence (483-533)

Introduction

siRNA Transfection

65432100510152025303540Cycle

qPCR Amplification Plot• ∆∆C q Calculation

Relative Gene Expression

This technical note demonstrates the utility of a ∆∆Cq method for calculating
relative gene expression and percent knockdown from quantification cycle(Cq) values obtained by quantitative real-time PCR (qPCR) analysis in an RNA
interference (RNAi) experiment. In this study, the human aldolase A (ALDOA)
message is silenced with the corresponding siGENOME™ SMARTpool™ siRNA.
To determine relative gene expression, probe-based qPCR is performed withcDNA synthesized from total RNA harvested from cell culture. Here, a ∆∆Cqmethod is demonstrated as a normalized determination of gene knockdown,
and the experimental controls it requires are described.

1.4
1.2
1
0.8
0.6
0.4
0.20siRNA DoseCurveControls

Relative Gene Expression

Figure 1. Experimental workflow. siGENOME SMARTpool siRNA targeting ALDOA wastransfected into HeLa cells and cDNA was synthesized from RNA isolated 48 hours posttransfection. ALDOA and reference genes’ cDNA was amplified by qPCR, and relative gene
expression was calculated from Cq values using a ΔΔCq method.

Materials and methods

ACell Culture, siRNA Transfection and RNA Isolation
HeLa cells (ATCC Cat. #CCL-2) were plated at 10,000 cells/well in a 96-wellformat and incubated overnight at 37 °C with 5% CO2. Cells were treated witheither siGENOME, SMARTpool siRNA targeting, ALDOA Cat. #M-010376-01) orsiGENOME Non-targeting siRNA Pool #1 (Cat. #D-001206-13) complexed with
the DharmaFECT ™ 1 transfection reagent (Cat. #T-2001). siRNA complexes weretransfected at 10, 1 and 0.1 nM final siRNA concentration in triplicate wells,
creating biological replicates. Triplicates of mock transfected (MT; transfection
reagent only) and untreated (UT) controls were also prepared.

B

ALDOA (TAR) qPCR Detection Amplification Plot

7

Fluorescence (483-533)

6

Total RNA was isolated from each well simultaneously with the vacuum
manifold-based Promega™ SV 96™ RNA Isolation System (Cat. #Z3500)
48 hours post-transfection. The RNA from each eluate was used in separate
reverse transcription reactions. RNA concentrations were not quantified as
the relative gene expression data from each sample were normalized to an
endogenous reference gene for each well.

GAPDH (REF) qPCR Dete

2.5
MT, UT, Non-targeting
0.1 nM siRNA
1 nM siRNA
10 nM siRNA

5All Samples

2Fluorescence (483-533)

.

4
3
21.5

10.5
1005

10

15

2025

30

35040

05CycleFluorescence (483-533)

Fluorescence (483-533)

GAPDH (REF) qPCR Detection Amplification PlotBA
ALDOA(TAR)Reaction
qPCR Detection Amplification Plot
Reverse Transcription - Quantitative Polymerase
Chain
2.5
Total RNA from each sample (5 µL) was reverse7transcribed with theThermo Scientific™ Verso™ cDNA synthesis kit (Cat. #AB-1453) using a
6MT, UT, Non-targeting
All Samples
3:1 (volume:volume) mixture of random hexamers to anchoredoligo-dT
0.1 nM siRNA
21 nM siRNAprimers in a 20 µL reaction according to the manufacturer’s
protocol. No
510 nM siRNAreverse transcriptase controls were prepared from untreated cells’ total RNA
1.54and no template controls were prepared with waterin place of total RNA toindicate potential genomic DNA contamination in isolated total RNA and3contamination of reagents, respectively. Each biologicalreplicate was assayed
1for the siRNA-targeted gene, ALDOA, as well as the endogenous reference
2genes GAPDH and RPS18 using Solaris™ qPCR Gene Expression Assays
0.5(Cat. #AX-010376-00, AX-011890-00, AX-004253-00,discontinued) and1™
Solaris qPCR Master Mix plus ROX (Cat. #AB-4350, discontinued). No reverse
0 assayed with qPCR detection
0transcriptase and no template controls were also
05101520253035400510152025303540for each target. Two µL of each three-fold diluted cDNA reaction wereused inCycle
Cycle
12 µL qPCR reactions and transferred into a white 384-well plate (Roche Cat.
#04729749001) with the aid of a PlateMate™ 2 × 3 liquid handler. qPCR thermalFigure 2. qPCR Amplification curves for ALDOA and GAPDH. Amplification curves
cycling and fluorescent data acquisition were performed with a Roche™
represent cDNA detected in samples treated for ALDOA siRNA knockdown (A.) or control™
qLightCycler 480 instrument and C values were called using the LightCycler
samples (B.) The ALDOA amplification curves exhibit siRNA dose-dependent message
480 software’s ‘Fit Points’ algorithm yielding amplification plots (Figure 2). Aknockdown, with higher Cq values representing lower expression, or more effective∆∆Cq method was then used to process these data to calculate relative genesilencing. For reference, a difference of one Cq value represents a 50% change in expression,expression for the RNAi experiment.
while differences of 3.3 and 6.6 Cq values represent approximately 90% and 99% changes,respectively. In contrast, amplification curves for all GAPDH reference samples yield similar Cqvalues, indicating GADPH expression was not significantly affected by the treatment.

∆∆Cq Calculations
In the RNAi experiment described here, expression of the siRNA-treated
ALDOA gene target (TAR) was normalized to non-targeted GAPDH or RSP18
reference gene (REF) expression levels within the same sample to determine∆Cq (Step 1, Box 1). This step serves to correct for non-treatment-related
variation among wells such as potential differences in cell number. Cq valuesof technical replicates can be averaged at this step if they were included in
the experimental design. For biological replicates in this experiment, the ∆Cqfor each replicate was exponentially transformed to the ∆Cq Expression (Step2) before averaging and determining the standard deviation (Step 3). The
mean was then normalized to the expression of ALDOA (TAR) from a separatewell treated with Non-targeting siRNA to find ∆∆Cq Expression (Step 4). Thisaccounted for any effects associated with the experimental procedure andwas expressed as the ratio of the targeted ∆Cq Expression to the non-targeted∆Cq Expression.
In an RNAi experiment, ∆Cq Expression is normalized to a corresponding
Non-targeting siRNA sample. In other experimental platforms – such as asmall molecule treatment – it may be appropriate to normalize to untreatedor vehicle-only control samples. Percent knockdown was calculated bysubtracting the normalized ∆∆Cq Expression from 1 (defined by the levelof expression for untreated sample) and multiplying by 100 (Step 5). Table
1 illustrates a complete list of values showing how to carry multiple data
points with biological replicates and mock transfected and untreated controls
through this ∆∆Cq method.

Step 1. Normalize to (REF): 		
∆Cq = Cq (TAR) – Cq (REF)
Step 2. Exponential expression transform:∆Cq Expression = 2–∆Cq
Step 3. Average replicates and calculate standard deviation
Step 4. Normalize to treatment control
Step 5. % KD = (1 – ∆∆Cq ) × 100

Given ValuesStep 1

Cq(REF) Cq (TAR) Cq (TAR)-(REF)

Step 2∆CqExpression

Step 4

Step 5∆∆Cq% KD

Non-targeting Control

21.9

23.1

1.2

0.43

1.00

–

TARALDOA

27.5

34.3

6.7

0.01

0.02

98

1015

Table 1. Detailed ΔΔCq example

123
4
5
67
8
9
10
1112
13
1415
16
1718
1920
21222324

A

B

siRNATreatment(Conc)

ALDOA

10 nM

1 nM

0.1 nM

NTC

10 nM

1 nM

0.1 nM

Mock
Transfected

N/A

Untreated

N/AC

DCqCq
GAPDH ALDOAEFGHIJK∆Cq∆CqExpressionMean ∆CqExpression∆Cq Expression
Std. Dev.

∆∆CqExpression∆∆Cq Expression
Std Dev.

%KD= (CqALDOA CqGAPDH)= 2-∆Cq

Average
Replicates

Std. Dev. Replicates

0.009

0.002

20.6

27.6

7.01

0.008

20.8

27.3

6.54

0.011

20.9
20.7

27.6
25.6

6.69
4.89

0.010
0.034

20.6

25.4

4.75

0.037

20.6
20.7

25.6
23.5

5.00
2.82

0.031
0.142

20.6

23.7

3.10

0.117

20.4
20.5

23.6
22.2

3.17
1.72

0.111
0.304

21.2

22.5

1.31

0.403

21.0
21.2

22.5
22.5

1.56
1.37

0.339
0.387

20.7

22.5

1.81

0.285

20.6
21.9

22.6
23.4

2.03
1.48

0.245
0.358

20.7

22.6

1.90

0.268

20.5
20.8
20.2
20.9
20.7

22.2
22.1

1.69
1.29

0.310
0.409

22.1

1.86

0.275

22.2
22.4

1.29
1.69

0.409
0.310

21.0

22.4

1.41

0.376

20.8

22.5

1.70

0.308

Column A:

Treatment on the cell.

Column B:

Final concentration (Conc) of siRNA [ALDOA or
Non-targeting Control (NTC)] or Not Applicable (N/A) and for
Mock Transfected and Untreated control samples.

Column C:

Cq value reported by software for GAPDH (REF)

Column D:

Cq value reported by software for ALDOA (TAR)

Column E:

Normalize Cq values for all TAR samples to the REF gene ofits corresponding sample. This is expressed as the differencein Cq values for target (Column D) and reference (Column C)
messages, ∆Cq.

Column F:

Exponentially transform ∆Cq to ∆Cq Expression for eachbiological replicate; 2 raised to the -∆Cq (Column E) yields∆Cq Expression. Note the base of 2 assumes 100% qPCR
amplification efficiency for all reactions, or a doubling ofamplicon with each subsequent qPCR cycle.

Column G:

Mean of ∆Cq Expression replicates (Column F).

Column H:

Standard deviation of the mean for ∆Cq Expression replicates.

0.034

0.123

0.349

0.306

0.312

0.364

0.331

0.003

0.016

0.051

0.073

0.045

0.077

0.039

Normalize to NTC
0.027

0.0057= G1/G10= H1/G10

0.111

0.010

= G4/G13= H4/G13

0.394

0.052

= G7/G16= H7/G16

1.0000.145= G10/G10= H10/G10

1.0000.239= G13/G13= H13/G13

1.0000.145= G16/G16= H16/G16

1.168

0.247

= G19/G16= H19/G16

1.062

0.125

= G22/G16= H22/G16= (1-∆∆Cq)*100
978961

Column I:

Normalize the TAR Mean ∆Cq Expression to that of theNon-targeting Control to obtain ∆∆Cq Expression. This isexpressed as the ratio of the targeted Mean ∆Cq Expression
to that of the non-targeted for samples of corresponding
concentration. For MT and UT controls – that do not haveassociation with concentration – normalize to the lowest
concentration NTC Mean ∆Cq Expression.

Column J:

To find the standard deviation of ∆∆Cq Expression, divide thestandard deviation of the targeted sample’s Mean ∆CqExpression (Column H) by that of the Non-targeting Control
sample of corresponding concentration (Column G). The
standard deviation of ∆∆Cq Expression for MT and UT controls
is found by dividing their Mean ∆Cq Expression standard
deviation’s (Column H) by the Mean ∆Cq Expression of thelowest concentration for the non-targeting group (Column G).

Column K:

Percent knockdown (%KD) is calculated by subtracting the 		normalized ∆∆Cq Expression from 1 (defined by the level ofexpression for untreated sample) and multiplying by 100.Results and conclusions

1.210.8
0.6
61 %

0.4
0.2

ALDOA

Reference
1. Bustin, Stephen A., ed. A-Z of Quantitative PCR. La Jolla, CA: International
University Line, 2004-2006.

Non-Targeting
Controls

UntreatedMock

Transfected

0.1 nM

1 nM

10 nM

0.1 nM

1 nM

089 %
97 %

10 nM

In summary, the utility of this ΔΔCq method has been demonstrated in thecontext of an RNAi experiment for calculating relative gene expression from
Cq values obtained from qPCR analysis. By normalizing changes between thetarget and reference genes within wells, and by normalizing this ΔCq
Expression to that of a control sample for the experimental treatment, themethod described here yields relative gene expression values that accountfor both experimental and non-experimental variation that may otherwise
introduce bias in results.

1.4

Relative Gene Expression

Calculations using the ∆∆Cq method described here revealed dose-dependentsilencing of ALDOA message with 61%, 89% and 97% knockdown whencells were treated with 0.1, 1 and 10 nM final concentration of the targeting
SMARTpool siRNA, respectively [normalized to GAPDH REF (Figure 3)].
Similar results were obtained with the REF gene, RPS18 (data not shown).
Comparison of mock transfected and Non-targeting siRNA samples tountreated samples indicated no significant impact of the transfection reagent
or siRNA treatment, respectively, on expression of the REF genes detected inthis experiment.

Controls

Figure 3. siRNA-mediated silencing of ALDOA was assessed using a ∆∆Cq method todetermine relative gene expression from qPCR data with GAPDH as an endogenous REF
gene. The cells exhibited siRNA dose-dependent knockdown of ALDOA message, withmRNA reduction by 61%, 89% and 97% when cells were treated with 0.1, 1 and 10 nM
final concentration of the targeting SMARTpool siRNA, respectively. Comparison of mocktransfected and Non-targeting siRNA to Untreated samples suggests that there is no
significant effect of transfection reagent or transfection reagent plus siRNA, respectively,on the cell.

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©2018 Horizon Discovery Group Company—All rights reserved. First published August 2014. UK Registered Head Office: Building 8100, Cambridge
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