Practical approach to quantification of mRNA abundance using RT-qPCR, normalization of experimental data and MIQE
Reverse transcription and quantitative polymerase chain reaction (RT-qPCR) has become the most common method for characterizing expression patterns of individual mRNAs due to a large dynamic range of linear quantification, high speed, sensitivity, resolution and cost-effectiveness. However, the comp...
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irk-123456789-1528282019-06-14T01:26:01Z Practical approach to quantification of mRNA abundance using RT-qPCR, normalization of experimental data and MIQE Obolenskaya, M.Yu. Kuklin, A.V. Rodrigez, R.R. Martsenyuk, O.P. Korneyeva, K.L. Docenko, V.A. Draguschenko, O.O. Reviews Reverse transcription and quantitative polymerase chain reaction (RT-qPCR) has become the most common method for characterizing expression patterns of individual mRNAs due to a large dynamic range of linear quantification, high speed, sensitivity, resolution and cost-effectiveness. However, the complexity of the protocol, variability of reagents, an inconsistent quality of biological samples, and the absence of standardized methods of data quantification may produce inconsistent results. In an effort to to standardize ithe procedure and assure high reliability of data, the minimum information for publication of quantitative real-time PCR experiments (MIQE) guidelines was defined and further extended by Prof. Bustin and colleagues (2004). These guidelines have been followed by the development of an XML-based real-time PCR data markup language (RDML) and a RDML data base for consistent reporting of RT-qPCR data created by the RDML consortium. Here we follow the RT-qPCR procedure step by step in compliance with MIQE requirements, local facilities and resources and our own experience in application of RT-qPCR methodology. Реакція зворотної транскрипції і ланцюгової полімеризації в реальному часі (ЗТ-кПЛР) стала найбільш уживаним методом для характеристики профілів експресії індивідуальних мРНК через можливості оцінки концентрацій в широкому діапазоні, відносної швидкості реакції, чутливості, роздільності і відносно невеликої вартості. Однак, багатоступеневий характер реакції, різні реактиви, різна якість біологічних зразків і відсутність стандартних приписів для проведення реакції приховують небезпеку отримати викривлені результати. Для стандартизації кожного з етапів методу і підвищення надійності результатів проф. С. Бустіним із співробітниками [2004] була розроблена методична інструкція, що містила мінімальну інформацію, яка необхідна для публікації результатів, отриманих за допомогою ЗТ-кПЛР. Крім того, RDML консорціумом на основі XML ( розширювана мова розмічання) створені спеціальна мова RDML і база даних RDML для збору і аналізу результатів ЗТ-кПЛР экспериментів. В цій статті ми описуємо весь процес ЗТ-кПЛР по етапах згідно вимог методичної інструкції MIQE і нашим власним досвідом у застосуванні цього методу. Реакция обратной транскрипции и количественной цепной полимеризации (ОТ-кПЦР) стала наиболее используемым методом для характеристики профиля экспрессии индивидуальных мРНК благодаря широкому диапазону измеряемых концентраций, малой затратности по времени исполнения, чувствительности, разрешающей способности и относительно небольшой стоимости. Однако, многоступенчатый характер реакции, разнообразие используемых реактивов, разное качество биологических образцов и отсутствие стандартных подходов для количественной оценки результатов таит опасность получить искаженные результаты. Для максимальной стандартизации каждого из этапов реакции и повышения надежности результатов проф. С. Бустиным с сотрудниками [2004] была разработана методическая инструкция с указанием минимальной информации (MIQE), необходимой для публикации данных, которые были получены с помощью ОТ-кПЦР. Кроме того, RDML консорциумом на основе XML (расширяемый язык разметки) разработан специальный язык RDML и создана база данных RDML для сбора и анализа результатов ОТ-кПЦР экспериментов. В этой статье мы описываем поэтапно весь процесс ОТ-кПЦР в соответствии с требованиями методической инструкции MIQE и нашим опытом в области применения этого метода. 2016 Article Practical approach to quantification of mRNA abundance using RT-qPCR, normalization of experimental data and MIQE / M.Yu. Obolenskaya, A.V. Kuklin, R.R. Rodrigez, O.P. Martsenyuk, K.L. Korneyeva, V.A. Docenko, O.O. Draguschenko // Вiopolymers and Cell. — 2016. — Т. 32, № 3. — С. 161-172. — Бібліогр.: 46 назв. — англ. 0233-7657 DOI: http://dx.doi.org/10.7124/bc.00091A http://dspace.nbuv.gov.ua/handle/123456789/152828 577.214.6 en Вiopolymers and Cell Інститут молекулярної біології і генетики НАН України |
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Digital Library of Periodicals of National Academy of Sciences of Ukraine |
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Reviews Reviews |
| spellingShingle |
Reviews Reviews Obolenskaya, M.Yu. Kuklin, A.V. Rodrigez, R.R. Martsenyuk, O.P. Korneyeva, K.L. Docenko, V.A. Draguschenko, O.O. Practical approach to quantification of mRNA abundance using RT-qPCR, normalization of experimental data and MIQE Вiopolymers and Cell |
| description |
Reverse transcription and quantitative polymerase chain reaction (RT-qPCR) has become the most common method for characterizing expression patterns of individual mRNAs due to a large dynamic range of linear quantification, high speed, sensitivity, resolution and cost-effectiveness. However, the complexity of the protocol, variability of reagents, an inconsistent quality of biological samples, and the absence of standardized methods of data quantification may produce inconsistent results. In an effort to to standardize ithe procedure and assure high reliability of data, the minimum information for publication of quantitative real-time PCR experiments (MIQE) guidelines was defined and further extended by Prof. Bustin and colleagues (2004). These guidelines have been followed by the development of an XML-based real-time PCR data markup language (RDML) and a RDML data base for consistent reporting of RT-qPCR data created by the RDML consortium. Here we follow the RT-qPCR procedure step by step in compliance with MIQE requirements, local facilities and resources and our own experience in application of RT-qPCR methodology. |
| format |
Article |
| author |
Obolenskaya, M.Yu. Kuklin, A.V. Rodrigez, R.R. Martsenyuk, O.P. Korneyeva, K.L. Docenko, V.A. Draguschenko, O.O. |
| author_facet |
Obolenskaya, M.Yu. Kuklin, A.V. Rodrigez, R.R. Martsenyuk, O.P. Korneyeva, K.L. Docenko, V.A. Draguschenko, O.O. |
| author_sort |
Obolenskaya, M.Yu. |
| title |
Practical approach to quantification of mRNA abundance using RT-qPCR, normalization of experimental data and MIQE |
| title_short |
Practical approach to quantification of mRNA abundance using RT-qPCR, normalization of experimental data and MIQE |
| title_full |
Practical approach to quantification of mRNA abundance using RT-qPCR, normalization of experimental data and MIQE |
| title_fullStr |
Practical approach to quantification of mRNA abundance using RT-qPCR, normalization of experimental data and MIQE |
| title_full_unstemmed |
Practical approach to quantification of mRNA abundance using RT-qPCR, normalization of experimental data and MIQE |
| title_sort |
practical approach to quantification of mrna abundance using rt-qpcr, normalization of experimental data and miqe |
| publisher |
Інститут молекулярної біології і генетики НАН України |
| publishDate |
2016 |
| topic_facet |
Reviews |
| url |
http://dspace.nbuv.gov.ua/handle/123456789/152828 |
| citation_txt |
Practical approach to quantification of mRNA abundance using RT-qPCR, normalization of experimental data and MIQE / M.Yu. Obolenskaya, A.V. Kuklin, R.R. Rodrigez, O.P. Martsenyuk, K.L. Korneyeva, V.A. Docenko, O.O. Draguschenko // Вiopolymers and Cell. — 2016. — Т. 32, № 3. — С. 161-172. — Бібліогр.: 46 назв. — англ. |
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161
M. Yu. Obolenskaya, A. V. Kuklin, R. R. Rodrigez
© 2016 M. Yu. Obolenskaya et al.; Published by the Institute of Molecular Biology and Genetics, NAS of Ukraine on behalf of Biopolymers and Cell.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/),
which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited
UDC 577.214.6
Practical approach to quantification of mRNA abundance using
RT‑qPCR, normalization of experimental data and MIQE
M. Yu. Obolenskaya, A. V. Kuklin, R.R. Rodrigez, O. P. Martsenyuk,
K. L. Korneyeva, V. A. Docenko, O. O. Draguschenko
Institute of Molecular Biology and Genetics, NAS of Ukraine
150, Akademika Zabolotnoho Str., Kyiv, Ukraine, 03680
m.obolenska@gmail.com
Reverse transcription and quantitative polymerase chain reaction (RT-qPCR) has become the most common
method for characterizing expression patterns of individual mRNAs due to a large dynamic range of linear
quantification, high speed, sensitivity, resolution and cost-effectiveness. However, the complexity of the pro-
tocol, variability of reagents, an inconsistent quality of biological samples, and the absence of standardized
methods of data quantification may produce inconsistent results. In an effort to to standardize ithe procedure
and assure high reliability of data, the minimum information for publication of quantitative real-time PCR
experiments (MIQE) guidelines was defined and further extended by Prof. Bustin and colleagues (2004).
These guidelines have been followed by the development of an XML-based real-time PCR data markup lan-
guage (RDML) and a RDML data base for consistent reporting of RT-qPCR data. Here we follow the RT-qPCR
procedure step by step in compliance with MIQE requirements, local facilities and resources and our own
experience in application of RT-qPCR methodology.
K e y w o r d s: RT-qPCR, normalization and standardization of data, MIQE
“Garbage in, garbage out” a teaching mantra by George Fuechsel, an IBM 305 RAMAC
technician/instructor, N.Y. 50s XX c. (Early programmers were required to test virtually each program step)
This paper is written to comment step by step the
widely accepted conventional experimental protocol
of RT-qPCR procedure and to present various cur-
rently available methodological solutions at each
step of procedure in accordance with mandatory
minimum information for publication of quantitative
real-time PCR experiments (MIQE) guidelines. The
following of these guidelines provide the standard-
ization of procedure, the ability to validate experi-
ments, to consider the conclusion as reliable and to
share and compare the results with other colleagues.
Since 1988 when the RT-qPCR was applied for
the first time for assaying the transcriptional pheno-
type of macrophages during normal healing [1] it has
become the most common method for characterizing
expression patterns of individual mRNAs in biologi-
cal samples. It has nearly supplanted other similar
approaches (e.g., Northern blotting, RNase protec-
tion assays) due to its large dynamic range of linear
quantification, high speed, sensitivity, resolution and
cost-effectiveness. The requirements for RT-qPCR
procedure and presentation are formulated in MIQE
that is a practical implementation of minimum stan-
dard guidelines for fluorescence-based quantitative
real-time PCR experiments [2, 3]. In fact these com-
monsense guidelines are in line with the last year
campaign organized by the US National Institutes of
Health, Nature and Science against a very low repro-
Reviews ISSN 1993-6842 (on-line); ISSN 0233-7657 (print)
Biopolymers and Cell. 2016. Vol. 32. N 3. P 161–172
doi: http://dx.doi.org/10.7124/bc.00091A
162
M. Yu. Obolenskaya, A. V. Kuklin, R. R. Rodrigez et al.
ducibility for articles published in scientific journals,
often as low as 10 – 30 % [4, 5; www.nature.com/
news/1.16259]. The reliability of molecular technol-
ogy and gene expression profiling becomes critically
important when it is applicable to diagnostics and
predictions for the disease outcome, as well as the
choice of the therapy [6].
Here we are not presenting a comprehensive re-
view on RT-qPCR methodology and its widespread
application in different fields of contemporary biolo-
gy as many papers on the subject and detailed guides
from the leaders in molecular biological industry may
be found in the literature and internet [e.g. 2, 3, 7–15].
Instead we are going to follow the procedure step by
step in compliance with MIQE requirements, local fa-
cilities and resources along with the currently avail-
able at the market using our own experience in appli-
cation of RT-qPCR methodology. To make the expres-
sion results valuable and comparable between runs,
real-time RT-qPCR platforms, and between different
laboratories worldwide the researchers have to me-
ticulously standardize each step of procedure, starting
from the biological sample to the final data analysis.
1. Experimental design
The illustration of different stages of RT-qPCR pro-
cedure is based on the experiments conducted in the
laboratory of systems biology (Institute of molecular
biology and genetics, National Academy of sciences,
Kyiv, Ukraine) on the gene expression in rat liver,
primary hepatocytes, mouse brain and human pla-
centa at different (patho)physiological states at the
steady state and in the course of time [16–20]. Male
Wistar rats (200–250 g) at different time points after
partial hepatectomy and laparotomy, male BALB/c
mice (~ 20 g) and human placenta from midfirst- and
third trimesters of gestation were used in the studies.
The animals’ tissue samples were snap-frozen in liq-
uid nitrogen immediately after collection of organs
and tissue dissection; the samples of placental vil-
lous tissue were collected immediately after abortion
or delivery, rinsed with cold sterile 0.9% NaCl solu-
tion and frozen in liquid nitrogen. The samples were
stored at –80 °C before processing.
2. RNA isolation
A prerequisite for the performance of RT-PCR is an
efficient method for RNA extraction. Currently there
are numerous methods that can be used to isolate and
purify RNA for RT-qPCR [21]. Here we will focus
on the cheapest and more accessible method of RNA
extraction based on “TRIzol reagent”. The total
RNA was isolated from approximately 100 mg of
liver tissue, mouse brain, human term placenta and
villous tissue from the midfirst trimester of gesta-
tion. The samples were ground in liquid nitrogen
with mortar and pestle; one ml of homemade “TRIzol
reagent”was added and the samples were homoge-
nized using power homogenizer (IKA T10, Cole
Parmer LabGen, USA) (for a receipt of homemade
“TRIzol reagent” see the Supplement). The liver ly-
sate was additionally passed through 22 G needle
five times to shear chromatin. All sequential proce-
dures followed the protocols described in the manual
from Thermo Fisher Scientific (USA) for TRIzol®
Reagent [http://tools.lifetechnologies.com/content/
sfs/manuals/trizol_reagent.pdf]. Briefly, the homog-
enized samples were processed through separation
of aqueous, intermediate and phenol-chloroform
phases, containing RNA, DNA and DNA and pro-
teins; correspondingly; RNA precipitation with iso-
propanol; two washes with 70 % ethanol and dis-
solving RNA in DEPC-treated water.
The yield of RNA, its purity and integrity are as-
sessed by the conventional methods, particularly in
our lab, by spectrophotometry on a NanoDrop
ND-2000 device (Life Technologies, USA) and de-
naturing formaldehyde 1 % agarose electrophoresis
with image analysis using Gel-Pro 3.1 software
(Media Cybernetics, Inc., USA). The A260/A280 ra-
tio around 2.0 and the A260/A230 ratio around 2.2
evidence the sufficient purity from proteins, phenol,
and aromatic compounds or carbohydrates, respec-
tively [22, 23]. The ratio of 28S/18S bands intensities
near 2.0 at electrophoregram the integrity of RNA. At
this step the RNA may be stored eithe r at – 80 °C or
may be precipitated with 3 vol. of 96 % ethanol – 0.1
vol. 3 M NaAc and stored at – 20 °C before the fur-
ther procedure.
163
Normalization and standardization of RT-qPCR data
We have to note here that the main disadvantage
of general UV spectrophotometry for RNA quantifi-
cation is low sensitivity (≥ 4 µg/ml) and the contri-
bution of signals from DNA, degraded RNA and
salts. The use of an ultrasensitive fluorescent
RiboGreen® (RNA detection range: 5 ng/ml – 50 ng/
ml) alleviates this problem [24]. The RiboGreen® re-
agent is nonfluorescent when free in solution; upon
binding to RNA, the fluorescence of the RiboGreen®
reagent increases more than 1000-fold. The RNA-
bound RiboGreen® reagent has an excitation maxi-
mum of approximately 500 nm and an emission
maximum of approximately 525 nm. The results
may be read either with Fluorescence Microplate
Reader or with Thermo Scientific NanoDropTM
3300 Fluorospectrometer. RiboGreen® is produced
by Invtirogen, sold as a RiboGreen®RNA Reagent
(#R11491) and within a kit (#R11490).
The routine assessment of RNA integrity with de-
naturing formaldehyde agarose electrophoresis is
low-sensitive, time-consuming, laborious and haz-
ardous technique. This method using EtBr as a fluo-
rescent intercalating agent requires approximately
200 ng of RNA to make an accurate assessment of its
integrity. The amount needed can be reduced by us-
ing alternative fluorescent dyes such as SYBR® and
SYBR® Green II RNA gel stain (Invitrogen
Corporation). However, when RNA quantity is very
limited (e.g. RNA from biopsies), agarose gel analy-
sis may not be possible. A major improvement in
RNA analysis occurred with the introduction of a
system combining microfluidics, capillary electro-
phoresis, and fluorescence to evaluate both RNA
concentration and integrity [25]. There are the
Experion automated elecltrophoresis system (Bio-
Rad Laboratories, Inc.) and the Agilent 2100
Bioanalyzer (Agilent Technologies, Inc.) at the mar-
ket. This technology requires very small inputs due
to Chip format, allowing user to assay RNA quality
in limiting samples. Bio-Rad introduced the RNA
quality index (RQI) in Experion software and the
Agilent Technologies provide the freely available
RNA integrity number (RIN) algorithm software
that assess the RNA integrity by the numbers from 1
(highly degraded) to 10 (intatct RNA) [26, 27]. Such
method favors the standardization of the whole pro-
cedure. The example of electrophoregrams obtained
with routine and advanced method is represented in
the Fig. S1.
3. Elimination of genomic DNA from RNA
samples
The isolated RNA usually contains different amount
of genomic DNA, sometimes up to 50 %, that could
result in false measurement of RNA concentration
by UV spectrophotometry and induce the variability
of results. The kits and reagents for elimination of
genomic DNA by RNAse free DNAse I treatment
are provided by different vendors that propose
DNAses active at somewhat different concentration
of Tris, MgCl2, CaCl2or MnCl2 (compare kits
from Life Technologies, USA, Cat.# AM1906,
Cat.# EN0525 and Cat.# EN0521 and one from
Promega, USA, Cat.# M6101) and possessing dif-
ferent enzymatic activities. The vendors’ recommen-
dations are usually given in the units of enzyme per
reaction, from roughly one unit for 1 µg of RNA (en-
zyme #EN0525) to two units per 10 µg of RNA
(enzyme#AM1907).
Though the time and the temperature during enzy-
matic treatment are uniform throughout, the ways
for the effective DNAse I removal are various. This
step is especially critical when the RNA will be used
directly to synthesize cDNA according to the recom-
mendations of several producers [http://www.
b i o m a r t . c n / u p l o a d / a s s e t / a t t a c h m e n t /
fermentas%E4%B8%AD%E5%9B%BD/coa_
en0521.pdf]. DNAse I may be removed by routine
phenol/chloroform extraction; irreversible enzyme
inactivation for 10 min at 65 °C in the presence of
2.5 mM EDTA [28]; conventional precipitation with
isopropanol [29] or ethanol and column clean up
systems (e.g. GeneJET RNA Cleanup and
Concentration Micro Kit, #K0841 from Thermo
Fisher Scientific). There is also a novel DNAse
Removal Reagent at the market (Ambion’s DNA-
freeTM, #1906, It sequesters and precipitates
DNAse I and cations in minutes at room temperature
164
M. Yu. Obolenskaya, A. V. Kuklin, R. R. Rodrigez et al.
and thus RNA cannot be degraded while inactivation
of DNAse I by heating in the presence of divalent
cations can partially degrade RNA.
The disadvantage of the whole step of DNA elim-
ination is a risk to overestimate the initial amount of
RNA for PCR and to inhibit reverse transcriptase if
the reaction mixes after DNAse I inactivation are
used directly to cDNA synthesis. In our lab we con-
trol the concentration and integrity of the RNA after
DNAse I treatment and selectively check the effi-
ciency of DNA elimination by the ratio of 18S rDNA
products after minus RT – qPCR and 18S rRNA
products after RT – qPCR. While before DNAse
treatment up to ≥50 % of isolated putative RNA is
represented by DNA then after DNAse I treatment
the traces of DNA usually comprise < 0.5 % (for de-
tails see Supplement).
4. The synthesis of Luc RNA as an external
standard
Now the preprocessing of RNA is over and the RNA
is ready for the main step of RT-qPCR analysis. To
maximally diminish the preprocessing related vari-
ability, which affects cDNA synthesis, the exoge-
nous RNA (spike RNA) as an external standard can
be used. Here we present our procedure of the exter-
nal standard synthesis [20]. The fragment of firefly
luciferase gene (Luc), irrelevant to the mammalian
genomes, was cut out from the pGL3-Basic plasmid
(Promega, Wisconsin, USA) by XbaI and HindIII
restriction enzymes and cloned into the same restric-
tion sites of the pGEM-3Z vector(Promega,
Wisconsin, USA) according to the routine proce-
dures. The pGEM®-3Z Vector is intended for use as
a standard cloning vector, as well as for the highly
efficient synthesis of RNA in vitro. The obtained
product was referred to as pGEM-3ZLuc and was
subjected to in vitro transcription. The final mix of
100 μl contained 1 μg of pGEM-3ZLuc DNA line-
arized by EcoRI, 2 mM NTP, 10 μl 10x IVT Buffer,
50 U of RiboLockTMRNAse inhibitor, 30 U SP6
polymerase (Thermo Fisher Scientific, USA). The
reaction lasted for 2 h at 37 °C and was followed by
subsequent phenol/chlorophorm extraction of RNA.
The Luc RNA was dissolved in 40 μl of DEPC treat-
ed water, its concentration was detected with a
NanoDrop ND-2000 device and its integrity and
specificity was confirmed by non-denaturing elec-
trophoresis in 1% agarose gel. The main steps of ex-
ternal RNA synthesis are illustrated in Fig. 1. The
obtained probe was aliquoted and stored at – 80 °C.
The Luc RNA has very high PCR efficiency in the
absence of inhibitors (E > 95 %) and does not pro-
duce the primer-dimer products (no PD signal in
40 cycles). The amount of the Luc RNA template for
RT-qPCR was adapted for genes of interest in a way
that both Cq would be in the same range.
There are several ready spikes available at the mar-
ket, such as Universal RNA Spike from TATAA
Biocenter (http://www.tataa.com/products-page/qua-
lity-assessment/tataa-universal-rna-spike/) or SPUD
from Sigma-Aldrich, which are very effective tools
for the quality control throughout entire RT-qPCR ex-
perimental workflow [30]. Both have a synthetic se-
quence that is not present in any known living organ-
ism, and mimic eukaryotic mRNA. In the presence of
a “clean” sample, the quantification or threshold cy-
cles (Cq, aka Ct) of spike will remain the same as their
control whereas in the presence of a contaminated
sample, the Cq will shift to higher cycles.
There is another approach to check whether a sam-
ple contains inhibitors. For10X difference in concen-
tration of starting template, the difference between
Cqs should be approximately equal to PCR slope.
The greatly reduced difference in Cqs after 10 to 1
dilutions compared to the expected difference indi-
cates the presence of inhibitors. For more detailed
information how to check the presence of inhibitors
and to eliminate them see [Pennington R. Dealing
with Amplification Inhibitors: Reagent Choice
Matters. 2014 (https://www.promega.com)].
5. Design of primers and target sequence
The quantification of target cDNA during real-time
PCR is accomplished by the DNA binding fluores-
cent dye SYBR Green I or TaqMan hydrolysis
probes. We describe here the first approach as it is
easier to design, faster to set up, more cost-effective
165
Normalization and standardization of RT-qPCR data
and applicable for estimation of different genes ex-
pression from the same cDNA sample if it is ob-
tained with the random primers but not with the tar-
get specific ones.
Both primers and target sequence may affect the
efficiency and specificity of amplification. A number
of free and commercial programs are available for
the primers design and control of their specifity:
PrimerQuest software (Integrated DNA Technologies,
http://eu.idtdna.com/scitools/applications/primer-
quest/ default.aspx), Primer3Plus (http://www.bioin-
formatics.nl/cgi-bin/primer3plus/ primer3plus.cgi)
or Primer-Blast (http://www.ncbi.nlm.nih.gov/tools/
primer-blast/), OligoAnalyzer 3.1, Primer-BLAST,
Vector NTIAdvanceTM10.0) [31]. In silico PCR on
UCSC Genome Browser is very useful to check for
non-specific binding. There is also an integrative
publicly available database for the storage, retrieval
and analysis of primer and probe information -
RTPrimerDB (http://www.rtprimerdb.org) [15]. It
contains primers and probe sequences used in real-
time PCR assays employing popular chemistries
(SYBR Green I, Taqman, Hybridisation Probes,
Molecular Beacon). It was organized to avoid time-
consuming primer design and experimental optimi-
zation, and to introduce a certain level of uniformity
and standardisation among different laboratories.
The database is linked with the reference databases to
allow the submission of assays for all genes and or-
ganisms officially registered in Entrez Gene and
RefSeq. The submission of own tested primers to
RTprimerDB is strongly encouraged.
To avoid amplification of genomic DNA the in-
tron spanning primers are designed with at least one
incorporated exon-exon junction (Fig. 2). The prim-
ers have not to be placed on polymorphic sites and
splice forms of RNA. The secondary structure of the
RNA fragment that is reverse transcribed may have
also a substantial impact on the efficiency of
RT-qPCR. Therefore, RNA sequences and primers
should be checked with nucleic acid–folding soft-
ware, MFOLD program [32]. According to MIQE
Fig. 1. Synthesis of Luc RNA as an exter-
nal standard. A – Plasmid pGEM-2z LUC
containing the fragment of firefly lucifer-
ase gene Luc; XbaI and HindIII are the
cloning sites for Luc insert; EcoRI – a site
for linearization. B – Transcript of the Luc
fragment (1700b) loaded next to the total
RNA from rat liver. C – Scheme of the Luc
transcript and location of primers. D –
Electrophoregramof Luc PCR prod-
uct: M – 100bp DNA Ladder (Thermo
Scientific.
166
M. Yu. Obolenskaya, A. V. Kuklin, R. R. Rodrigez et al.
the folding structures should be ideally made avail-
able to reviewers as well.
We design the primers using Vector NTIAdvance
TM10.0 program, check their specificity with Primer-
BLASTprogram (http://www.ncbi.nlm.nih.gov/tools/
primer-blast/) and secondary structure with MFOLD.
The target sites for restriction endonucleases within
amplicon are found withVector NTI Advance® 11.5.4
software (ThermoFisher Scientific, USA).
All new primers have to be tested by qPCR using a
3-fold serial dilution of cDNA in order to determine
the amplification efficiency of the cDNA fragment, to
validate the specificity of amplicons and the presence/
absence of primer dimers after qPCR [32]. The ampli-
fication efficiency for each pair of primers is deter-
mined from the linear slope of standard curve; only
primers with a standard curve slope between –2.92
and –3.92 (efficiency 100 ± 20 %) are used for further
quantification. Efficiency 100% is defined by a slope
of − 3.32 and a 2-fold change for each change in Cq of
the 10 fold dilution (Fig. S2) [33]. If the slope is be-
low –3.92, then the PCR has poor efficiency. The ef-
ficiency of amplification may be optimized by chang-
ing the concentration of MgCl2 and dNTP, adjusting
the temperature and time of annealing. If these proce-
dures do not improve the efficiency of amplification
the primers have to be redesigned.
The amplicon specificity is validated by the length
of the amplicon and its restriction fragments (For ex-
ample see Table 1 and Fig. 3). Due to the critical
importance of the above mentioned characterristics
of primers, the information regarding their sequence,
location on cDNA, specific restriction endonucleas-
es for an amplicon, the length of restriction frag-
ments and their experimental approval must be pro-
vided in the papers according to the MIQE guide-
lines. The sequence of amplicon is appreciated by
many reviewers [2].
6. Reverse transcription and Real time PCR
The reverse transcription and real time PCR are con-
ducted according to the conventional protocols for
specific enzymes. In our lab the first-strand cDNA
synthesis from total RNA is carried out with the spike
RNA Luc and RiboLock RNase Inhibitor. For every-
thing else the procedure follows the protocol of
ReverseTranscriptase producer (in our case RevertAid
ReverseTranscriptase, cat. #EP0441, Thermo Fisher
Scientific, USA). After termination of the reaction the
mixture is diluted with sterile DEPC-treated water to
the concentration of 25–50 ng/μl, aliquoted and stored
at – 80 °C.
Fig. 3. Specificity of amplicons proved by restriction analysis.
Lanes: 1 – Tbp, 2 – 18S, 3 – Ifnα, 4 – Isg15, 5 – Ube1l, 6 – Ube2l6,
7 – Trim25, 8 – Usp18, 9 – Irf7, M-50bp DNA Ladder (Thermo
Scientific, USA) Compare experimental results with theoretical-
ly predicted (Table 1).
Fig. 2. Location of primers for PCR amplification of Ube 2L6 cDNA.
Note: the amplicon includes the junction between third and fourth exons
167
Normalization and standardization of RT-qPCR data
The amplification of individual mRNA is performed
in triplicate with real-time PCR at different types of
Real-Time PCR Detection Systems. We use Bio-Rad
CFX96 Real-Time PCR Detection System (Bio-Rad
Laboratories Ltd., USA). The mandatory requirement
includes the presence on each plate the samples of in-
terest and ‘No Template’ control in each RT- q PCR
plate. Also, there has to be a set of corresponding di-
luted standards (amplicons in our case) for the stan-
dard curve if the absolute quantification is used.
The specificity of amplification is confirmed with
the same device by the melt-curve analysis (Fig. S3).
For the methodological details see Sup plement.
7. Absolute vs relative quantification
There are two strategies to quantify the level of gene
expression – by absolute or relative RT-qPCR. The
first one relates on a calibration curve and the ob-
tained results are represented in amount of mRNA in
ng, nanomoles or copies per one unit of total RNA,
per cell or per g of tissue while the second reflects
the relative changes in the mRNA expression level
between the samples and the results are represented
by relative units.
The standard curve method determines the input
mRNA levels of a gene by relating the PCR signal to
a standard curve. It requires the production of a high
quality standard and a high quality RNA. A purified
specific RT-PCR product, recombinant DNA or re-
combinant RNA, may serve as standards. The pro-
duction of the specific RT-PCR product or amplicon
by ordinary RT-PCR reaction with subsequent puri-
fication is rather simple but the standard may be not
very stable therefore its integrity has to be checked
from time to time. The production of recDNA is
much more time consuming and cost effective, how-
ever, it is more stable than a short RT-PCR product.
The recRNA best of all mimics the RT-PCR proce-
dure of natural RNA but the standard is very unsta-
ble and its preparation is rather complicate and ex-
Table 1. Characteristics of primers and amplicons [Kuklin et al., 2015]
mRNA
(Refseq) Primers Amplicon
location, bp
Restriction analysis of amplicon
Enzyme Restricts, bp**
Tbp
(NM_001004198.1)
F 5’- TCAGTCCAATGATGCCTTACG - 3’
R 5’- CTGCTGCTGCTGTCTTTGTT - 3’ 348–448 Hpy 1881 50; 51
18 S
(NR_046237.1)
F 5’- GTTCCGACCATAAACGATGC-3’
R5’- CGCTCCACCAACTAAGAACG -3’ 1078–1341 HinfI 175; 67; 44
Ifna* F 5’ - CTGCTGTCTAGGATGTGACCTGC -3’
R 5’ - TTGAGCCTTCTGGATCTGCTG - 3’ 57–225 HinfI 81; 46; 42
Isg15
(NM_001106700.1)
F 5΄ - ССTCTGAGCATCCTGGTGAG- 3’
R5΄ - CAGTGGCTCTTT GTCCTCCA - 3’ 376–546 PvuII 58; 113
Ube1l
(NM_001106856)
F 5΄ - GGGCCTGGGAGTTAGGGATAATGG- 3’΄
R 5΄ - CGTCCACCCTGGAGAAGAAGTCGT - 3’ 1492–1730 Ear I 90; 149
Ube2L6
(NM_001024755.1)
F 5΄ -ACCAACTTCCCTATCGCCTCAAGG- 3’
R 5΄ - GAGGTCAGCTAGTTCCAAACGCACA- 3’ 591–850 Bgl II 95; 165
Trim25
(NM_001009536.1)
F 5΄ - CGCAAATGTTCCAGGCACAACC- 3’
R 5΄ -CATCCTCCAGTGCTTTGCTCGCT - 3’ 521–725 Rsal 10; 195
Usp18
(NM_001014058.1)
F 5΄ - ATACAACGTGC CATTGTTTGTCC- 3’
R 5΄ - TCGGTCCAGATTGT GAACAGATC- 3’ 496–627 EarI 48; 84
Irf7
(NM_001033691.1)
F 5’- GCTGAGCGAAGAGGCTGGAAGA - 3’
R 5’- CCAGAAAGCAGAGGGCTTGG - 3’ 650–918 HaeII 58; 113
Note: For Ifna indicated with an asterisk (*), the primers are common for Ifna1, NM_001014786.1; Ifna2, NM_001271218.1;Ifna4,
NM_001106667.1 and Ifna16l, XM_575856.1. Double asterisks (**) denote the length ofr theoretically predicted length of restricts.
168
M. Yu. Obolenskaya, A. V. Kuklin, R. R. Rodrigez et al.
pensive. The standard curve method has several ad-
vantages: representation of dilutions for the standard
curve at each PCR plate provides the routine valida-
tion for methodology; it substantially simplifies all
calculations and comparison of the expression levels
between different mRNAs in the same sample or be-
tween different samples [12]; it does not require a
laborious work for validation of reference genes; the
results have the absolute values and thus are easily
comparable between different laboratories world-
wide. The disadvantage of the method is a require-
ment for production of high quality standards and
more stringent requirements for maximal standard-
ization of the whole procedure (especially the high
standards for RNA quality taken for RT – qPCR). An
example of using the standard curve for assessment
of mRNA abundance is represented in the Fig. S2.
Relative quantification relates the PCR signal of
the target transcript in one sample to that of another
sample chosen as a control or calibrator. The choice
of calibrator depends on the gene expression experi-
ments. It may be an untreated sample in the experi-
ment with treatment; a control sample in the study of
some disease; a sample at time zero in the time
course study of gene expression; a sample for one
tissue that is compared with other tissue.
The relative quantification is mostly applied to
steady–state conditions and an endogenous presu-
mably invariant reference transcript is used to dimi-
nish the variability between the samples. Occurring
background interferences retrieved from the extracted
tissue components and the cDNA synthesis efficiency
relate to target and internal reference similarly so all
the variations preceding PCR are compensated by the
calculations after amplification. The relative quantifi-
cation method is dependent on the determination of
real time amplification efficiency of the target and re-
fe rence templates. To date, two types of relative quan-
tification models are available. In the first one the cor-
rection of amplification efficiencies is not required if
they are near 100 % and within 5% of both target and
reference template. But it is required in the second
model where the amplification efficiencies of target
and reference templates differ for more than 5 % of
each other values [12, 13, 34]. The advantages of the
relative quantification method consist of no need to
produce the standard material, to optimize and to va-
li date the standard curve. The disadvantages of the
method relate to the necessity to validate the internal
standards, low standardization of the method and the
difficulties to compare the results obtained by diffe-
rent research groups as the references are usually cho-
sen according to the own preferences of each re-
searcher. Frequently, to find the invariable referent
gene is problematic.
8. Data normalization
Several strategies have been proposed for normaliz-
ing RT-qPCR data. They range from the calculation of
individual mRNA content per unit of sample, per unit
of investigated RNA, either total or its fraction, to us-
ing an internal housekeeping gene as a reference.
These approaches are not mutually exclusive and can
be incorporated into a protocol at many stages. The
relative merits of different normalization strategies
are explicitly represented in multiple reviews [35–39].
The choice of the normalization strategy strictly
depends on the goal of experiment and the essence
of biological sample(s) under the study whether they
are in the steady or dynamical state. Calculations of
mRNA amount per total RNA and per internal refer-
ence gene(s) are applicable to steady state situation.
In dynamical systems the qualitative and quantita-
tive composition of total RNA changes in the course
of time. So it is difficult to find out the internal refer-
ence gene with constant concentration particularly
when the rRNA : mRNA ratio varies.
In our lab we explore the gene expression in two
dynamical systems – regenerating rat liver and hu-
man placenta in the midfirst and third trimesters of
gestation. We have shown that the concentration of
18S rRNA and TBP mRNA encoding TATA-binding
protein, both widely used as internal reference tem-
plates, gradually increase during the first 12 h after
partial hepatectomy and gradually decrease during
the same time after sham operation [20]. Another
group of researchers propose different pairs of refer-
ence templates for eight types of hepatic cells in re-
169
Normalization and standardization of RT-qPCR data
generating liver [40] Given that isolated RNA re-
flects the composition of liver RNA in vivo we pres-
ent the target mRNA abundance in copies per mass
unit of total liver RNA [16, 20]. Somewhat similar
situation is observed with placental samples at dif-
ferent time points of gestation. The abundance of
18S rRNA and YWHAZ template, recommended as
placental internal standards [38], is invariable either
in the first or in the third trimester of gestation, how-
ever, the values are nearly two times less in the third
trimester in comparison to the first one making these
templates inconsistent for inter-trimesters compari-
son. So we also use the absolute values in copies of
mRNA per mass of total RNA [17, 18].
To mitigate the variability during preprocessing
of RNA we additionally normalize the data accord-
ing to Luc RNA recovery. We added an external Luc
RNA spike together with total RNA to the reaction
of reverse transcription. The 100 % value of Luc re-
covery corresponds to the copies of amplified Luc
RNA in the absence of cDNA of interest. The recov-
ery of less than 85 % of Luc RNA, when it was pro-
cessed together with the sample RNA points to the
presence of inhibitors in the RNA sample. Such sam-
ples are either additionally purified or RNA isolation
is repeated (Table S1). Ideally, it is possible to in-
clude the additional artificial RNA at the very begin-
ning of procedure to follow all the steps of manipu-
lation with the target mRNAs.
During the last decade the captious exploration of
the reference genes reliability has completely
changed the opinion about their applicability. The
most commonly used housekeeping genes in époque
of Northern blot and semiquantitative examination
of mRNA level like glyceraldehyde-3-phosphate de-
hydrogenase (GADPH), β-actin and 18S ribosomal
RNA became inadequate in most cases of RT-qPCR
due to their variability in different tissues, presence
of pseudogenes that may misleads the results, incon-
sistency of their expression under different treat-
ments or in comparison of control with disease etc.
[37–39, 42, 43]. Moreover it is considered that the
choice of housekeeping genes is highly specific for
particular experiment [37].
To facilitate and standardize the selection of ref-
erence genes, a lot of methods have been developed.
The geNorm VBA applet for Microsoft Excel calcu-
lates a gene expression normalization factor for
each tissue sample based on the geometric mean of
a user-defined number of reference genes [44].
There are already geNorm Kits at the market (https://
genorm.cmgg.be/). BestKeeper (www.gene-quanti-
fication.de/bestkeeper.html) also selects the least
variable genes using the geometric mean but uses
the raw data instead of the data converted to a copy
number as geNorm[13]. NormFinder (http://www.
multid.se/genex/hs410.htm) measures the variation
and ranks the potential reference genes according to
the grouping of samples, such as untreated/treat-
ment, etc. [45].
The standardized exchange of qPCR data is al-
ready a reality
The demand for a standardized qPCR data format
stimulated the emergence of two innovations. A set
of guidelines that describe the minimum information
necessary for evaluating qPCR experiments, MIQE,
was proposed by Professor S. Bustin with col-
leagues [2], and the XML-based Real-Time PCR
Data Markup Language (RDML) was developed by
the RDML consortium [15]. The MIQE provides this
approach with a checklist that contains 85 parame-
ters to assure quality results. The detailed practical
approach to RT-qPCR—publishing data that con-
form to the MIQE guidelines may be found in the
mini review by Dr. S.Taylor with colleagues [11]
and contain the mandatory and elective parameters.
The RDML was created to enable the straightfor-
ward exchange of raw fluorescence data free of
smoothing or baseline subtraction, as they allow
quality control, the evaluation and reevaluation of
the validity of conclusions if new approaches be-
come available. Recently the new RDML version
1.2 was published [46], which includes the open
source editor RDML-Ninja (http://sourceforge.net/
projects/qpcr-ninja/) and the database RDMLdb
(http://www.rdmldb.org).The editor allows research-
er to visualize, edit and validate the RDML files. The
database RDMLdb is an online repository for RDML
170
M. Yu. Obolenskaya, A. V. Kuklin, R. R. Rodrigez et al.
files. Authors may upload their RDML files into this
database and provide the matching IDs in the article,
as it is customarily done for the microarray and RNA
sequencing. This new RDML infrastructure is the
foundation for the standardized qPCR data exchange
among scientists and research groups, and for the
meta-analysis of gene expression assessed by RT-
qPCR in foreseeable future.
The accurate following the protocol of the RT-qPCR
workflow with maximal standardization of each step
is critical for producing the reliable, comparable and
reproducible results. The extension of obtained results
via specified open access databases is highly appreci-
ated for dissemination of new knowledge and
strengthening the contacts within scientific commu-
nity for the further scientific achievements.
Supplementary material
Details of the analysis are provided in the Supplement
http://biopolymers.org.ua/content/32/3/161/
Acknowledgements
This work was supported by the National Academy
of Sciences of Ukraine (Project N 2.2.4.18, 2011–
2015). The authors are thankful to Prof. Stephen
Bustin (Postgraduate Medical Institute, London,
UK) and Dr. Nadiya Teplyuk (Harvard Medical
School, Boston, USA) for helpful comments.
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До питання про визначення концентрації індивідуаль‑
них мРНК, нормалізацію експериментальних даних
і мінімальну інформацію, необхідну для їх публікації
М. Ю. Оболенська, А. В. Куклін, Р. Р. Родрігес,
О. П. Марценюк, К. Л. Корнєєва, В. А. Доценко,
О. О. Драгущенко
Реакція зворотної транскрипції і ланцюгової полімеризації в
реальному часі (ЗТ-кПЛР) стала найбільш уживаним методом
для характеристики профілів експресії індивідуальних мРНК
через можливості оцінки концентрацій в широкому діапазоні,
172
M. Yu. Obolenskaya, A. V. Kuklin, R. R. Rodrigez et al.
відносної швидкості реакції, чутливості, роздільності і віднос-
но невеликої вартості. Однак, багатоступеневий характер реак-
ції, різні реактиви, різна якість біологічних зразків і відсутність
стандартних приписів для проведення реакції приховують не-
безпеку отримати викривлені результати. Для стандартизації
кожного з етапів методу і підвищення надійності результатів
проф. С. Бустіним із співробітниками [2004] була розроблена
методична інструкція, що містила мінімальну інформацію, яка
необхідна для публікації результатів, отриманих за допомогою
ЗТ-кПЛР. Крім того, RDML консорціумом на основі XML (роз-
ширювана мова розмічання) створені спеціальна мова RDML і
база даних RDML для збору і аналізу результатів ЗТ-кПЛР
экспериментів. В цій статті ми описуємо весь процес ЗТ-кПЛР
по етапах згідно вимог методичної інструкції MIQE і нашим
власним досвідом у застосуванні цього методу.
К л юч ов і с л ов а: ЗТ-кПЛР, нормалізація і стандартизація
даних, MIQE
К вопросу об определении концентрации индивидуаль‑
ных мРНК с помощью ОТ‑кПЦР, нормализации экспе‑
риментальных данных и минимальной информации,
необходимой для их публикации
М. Ю. Оболенская, А. В. Куклин, Р. Р. Родригес,
О. П. Марценюк, К. Л. Корнеева, В. А. Доценко,
Е. О. Драгущенко
Реакция обратной транскрипции и количественной цепной
полимеризации (ОТ-кПЦР) стала наиболее используемым
методом для характеристики профиля экспрессии индиви-
дуальных мРНК благодаря широкому диапазону измеряе-
мых концентраций, малой затратности по времени испол-
нения, чувствительности, разрешающей способности и
относительно небольшой стоимости. Однако, многосту-
пенчатый характер реакции, разнообразие используемых
реактивов, разное качество биологических образцов и от-
сутствие стандартных подходов для количественной оцен-
ки результатов таит опасность получить искаженные ре-
зультаты. Для максимальной стандартизации каждого из
этапов реакции и повышения надежности результатов
проф. С. Бустиным с сотрудниками [2004] была разработа-
на методическая инструкция с указанием минимальной
информации (MIQE), необходимой для публикации дан-
ных, которые были получены с помощью ОТ-кПЦР. Кроме
того, RDML консорциумом на основе XML (расширяемый
язык разметки) разработан специальный язык RDML и со-
здана база данных RDML для сбора и анализа результатов
ОТ-кПЦР экспериментов. В этой статье мы описываем по-
этапно весь процесс ОТ-кПЦР в соответствии с требовани-
ями методической инструкции MIQE и нашим опытом в
области применения этого метода.
К л юч е в ы е с л ов а: ОТ-кПЦР, нормализация и стандарти-
зация данных, MIQE
Received 23.09.2015
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