RNA quality control in miRNA expression analysis Application Not

Christiane Becker

Martina Reiter

Michael W. Pfaffl

Tu München Ziel

CiteSeerX

RNA quality control in miRNA 
expression analysis
Abstract
It is generally known that total RNA quality has a distinct influence on the validity and
reliability of quantitative PCR results. In addition, the recently published MIQE 
guidelines focus on the pre-PCR steps and state the importance of RNA quality
assessment. 
Various studies showed the impairing effect of ongoing RNA degradation on mRNA
expression results. Therefore, the verification of RNA integrity prior to downstream
applications like RT-qPCR and mircroarrays is indispensable. A fast and reliable
assessment of RNA integrity can be done with the Eukaryote Total RNA Nano Assay
of the Agilent 2100 Bioanalyzer.
The importance of RNA quality should also be considered in new applications such as
the investigation of miRNA expression profiles. With the Agilent Small RNA Assay,
Agilent is offering one of the few possibilities for selectively estimating miRNA before
expression analysis. However, by now little is known about factors affecting miRNA
analysis. Herein, the important impact of total RNA quality on quantification of mRNA
and miRNA should be considered.
Authors
Christiane Becker, Michael W. Pfaffl 
TU München, ZIEL
Physiology Weihenstephan
Weihenstephaner Berg 3
85384 Freising, Germany
Martina Reiter, Michael W. Pfaffl 
BioEPS GmbH, Lise-Meitner-Str. 30
85354 Freising, Germany  
Application Note
Genomics2
Introduction
After extraction, RNAs are very unsta-
ble and sensitive to degradation due to
the ubiquitous occurrence of nucleases.
It is well known that expression profil-
ing using microarrays or qPCR is influ-
enced by RNA quality1, 2. Therefore, this
hazard has to be considered during all
preprocessing steps and should be min-
imized with cautious handling. The
recently published MIQE Guidelines3
recommend which data are essential
for scientific publication. These guide-
lines focused on the pre-PCR steps and
stated the importance of RNA quality.
The term RNA quality is defined by the
composition of RNA purity and RNA
integrity. Therefore, the RNA purity
should be tested by the estimation of
the OD260/280 and the OD260/230 using
photometrical methods. A fast and reli-
able analysis of total RNA integrity can
be performed with the lab-on-a-chip
technology of the Agilent 2100
Bioanalyzer using automated capillary
electrophoresis. This is the current gold
standard for standardized RNA integrity
assessment. 
The measurement of RNA quality
should also be integrated in the routine
analysis of new applications like the
investigation of microRNAs (miRNAs)4.
miRNAs are non-coding, regulatory
RNA molecules with a length of approx-
imately 22 bp. There is interest in
miRNA expression profiles especially in
clinical diagnostics because these
could be used as biomarkers in pre-
diagnosis of cancer and other diseases.
miRNAs belong to the nucleic acids
group, so they are quantified with the
same analytical methods as long RNAs,
such as mRNAs. Currently, little is
known about factors compromising
miRNA analysis4, 5. Therefore, this
study determined the influence of RNA
quality on quantitative expression
analysis.
RNA quality and miRNA 
concentration measurement
Challenges start with concentration
measurement of miRNAs because pho-
tometrical methods do not allow the
discrimination between different RNA
fractions. The Agilent Small RNA Assay
is one of the few analyzers available
that can measure miRNA concentra-
tion. This chip can selectively quantify
miRNAs in absolute amounts [pg/µL]
and as a relative percentage of small
RNA [%]. In addition to these numerical
results, the Small RNA Assay also pro-
vides an electropherogram and an elec-
tronic virtual gel-like image (Figures 1A
and 1B) of the measured samples. 
Recent results showed that RNA degra-
dation has a significant effect on mRNA
and miRNA fragmentation patterns. A
negative correlation between the
miRNA percentage and total RNA
integrity was shown for all investigated
tissues. This relationship was also
demonstrated for the absolute miRNA
concentration in liver and white blood
cells (WBC)4. 
With ongoing total RNA degradation,
the amount of smaller RNA fragments
increases, whereas longer RNA mole-
cules decrease (Figures 1A and 1B).
These unspecific fragments reach the
analytical range of the Small RNA
Assay and thereby lead to an overesti-
mation of the absolute miRNA amount.
Consequently, the miRNA should not be 
considered as a single fraction, but as a
part of the entire total RNA. It is recom-
mended therefore, to combine the
Small RNA Assay and the Eukaryote
Total RNA Nano Assay for a complete
evaluation of every total RNA sample.
Figure 1
Results from WBC in 11 degradation steps. Gel-like image generated by
the 2100 Expert Software for the (a) Eukaryote Total RNA Nano Assay
and the (b) Small RNA Assay. 
1A
1B3
RNA quality and mRNA 
expression analysis
Previous studies indicated a distinct
effect of RNA quality on the perfor-
mance of later reverse transcription
quantitative PCR (RT-qPCR). Different
samples showing a degradation gradi-
ent with several steps of intact RNA
down to degraded RNA were analyzed
using RT-qPCR. With ongoing RNA
degradation a highly significant rise in
the quantification cycle (Cq) value
occurs for all analyzed mRNAs 
(Figure 2) independent of tissue type2.
The expression data then demonstrates
an apparent high expression level for
intact starting material and in contrast
a low expression level for degraded
RNA samples. Each amplified gene was
tissue specifically influenced by RNA
integrity demonstrating an incompre-
hensible tissue-matrix effect between
RNA integrity and the type of tissue
and the analyzed transcript1, 4. Also, the
influence of RNA integrity on single-run
PCR efficiency was determined as
minor compared to its influence on
Cq1,2. Additionally, the effect of the
length of amplified product was tested.
In this analysis, samples with different
levels of RNA integrity were amplified
using primers producing PCR product of
different lengths. Best results could be
obtained for samples with RIN values
higher than 5 and PCR amplicon
lengths of lower than 200 bp2. 
The impairing effect of low RNA integri-
ty on the results of gene expression
analysis can partly be reduced by a
valid normalization method. For mRNA,
a reference gene (RG) index calculated
as the geometric mean of multiple ref-
erence genes selected by Genorm6,
Normfinder7 or GenEx software (MultiD,
Gothenburg) is generally accepted8.
This strategy has been used for mRNA
expression results. For nearly all genes
and all tissue, a significant reduction of
the technical variance due to different
RNA integrity levels could be shown
after normalization1, 4. 
Figure 2
Highly significant, negative correlation between the RIN and the Cq in liver tissue with p<0.001 for all
analyzed mRNAs4.
Figure 3
Highly significant, negative correlation between the RIN and the Cq in liver tissue with p<0.001 for all
analyzed miRNAs4.www.agilent.com/chem/2100-rna
© Agilent Technologies, Inc., 2010 
April 1, 2010
Publication Number 5990-5557EN
these degradation steps from the calcu-
lation. Therefore, the previously deter-
mined threshold level for gaining reli-
able PCR results2 (RIN=5) was con-
firmed for mRNA and stated for
miRNA4. Samples with a lower RIN are
not recommended for expression analy-
sis because the results may not be reli-
able.
Conclusion
In conclusion, it is shown that sustain-
ing high quality RNA is critical for valid
and reliable quantification results in
miRNA and mRNA expression analysis.
The specific concentration measure-
ment of miRNAs is challenging and reli-
able for nondegraded samples with high
overall RNA quality. It is recommended
to consider miRNA in combination with
the total RNA, as opposed to a single
fraction.
The performance of RT-qPCR is
impaired by decreasing RNA quality for
miRNA similar to mRNA, but to a lower
magnitude. The use of biological sam-
ples showing a RIN higher than 5, and
primers producing short PCR product
are recommended. The application of an
appropriate normalization method can
partly reduce the degradation problem
in RT-qPCR.
References
1. 
"Comparison of relative mRNA quantifi-
cation models and the impact of RNA
integrity in quantitative real-time RT-
PCR," Biotechnol.Lett. 19, 1601-1613,
2006
2. 
"RNA integrity and the effect on the
real-time qRT-PCR performance," Mol.
Aspects Med. 2-3, 126-139, 2006
3. 
"The MIQE guidelines: minimum infor-
mation for publication of quantitative
real-time PCR experiments," Clin.Chem.
4, 611-622, 2009
4. 
"mRNA and microRNA quality control
for RT-qPCR analysis," Methods, 2010
5. 
"RNA degradation compromises the
reliability of microRNA expression pro-
filing," BMC.Biotechnol. 1, 102, 2009
6. 
"Accurate normalization of real-time
quantitative RT-PCR data by geometric
averaging of multiple internal control
genes," Genome Biol. 7,
RESEARCH0034, 2002
7. 
"Normalization of real-time quantitative
reverse transcription-PCR data: a
model-based variance estimation
approach to identify genes suited for
normalization, applied to bladder and
colon cancer data sets," Cancer Res.
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"A novel and universal method for
microRNA RT-qPCR data normalization"
Genome Biol. 6, R64, 2009
Therefore, the application of a valid
normalization method is indispensable
in the processing of RT-qPCR expres-
sion data.
RNA quality and miRNA expres-
sion analysis
This test also illustrated a distinct influ-
ence of RNA degradation on miRNA
expression analysis. Eight different
miRNAs were quantified using RT-
qPCR. For all tissues and in all eight
genes, a highly significant, negative
correlation (p<0.001) between the RIN
and Cq occured. The results gained for
liver tissue are shown in Figure 3. With
ongoing RNA degradation the Cq
increased, showing an impairing influ-
ence of the RNA integrity on the perfor-
mance of the qPCR. As represented by
the lower slope of the regression line,
the expression analysis of miRNAs is
influenced by RNA integrity to a lesser
degree than mRNA expression (1.521
vs. 0.709, respectively). Due to their
small length, miRNAs4 seem to be less
susceptible to degradation because
they show less binding sites for nucle-
ases. Consequently, it can be assumed
that the amplification of miRNA in
qPCR might be less affected by a low
RNA integrity compared to the longer
mRNAs. Currently, there are no precise
recommendations for the normalization
of miRNA expression data. Two strate-
gies of normalization have been applied
for testing. RG comparable to that of
mRNA were determined for miRNA
using GenEx software. Normalization
using the geometric mean expression,
as it is used for microarray data analy-
sis, has been used as a second strate-
gy. Both methods could minimize the
bias of low RNA quality, but a highly
significant correlation between the RIN
and the Δ Cq remains despite normal-
ization for all subsets. It is obvious that
the linearity is interrupted only by sam-
ples with very low RNA quality (degra-
dation step 10/11). There is no shared
trend between the RIN and the Cq
value after eliminating the results of

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