This document discusses methods for quantifying and analyzing microRNAs (miRNAs) using quantitative PCR (qPCR). It presents a new two-tailed RT-qPCR method that provides high sensitivity and specificity for detecting miRNAs, including discrimination of miRNA isoforms. The method allows unlimited multiplexing in the reverse transcription step followed by singleplex qPCR. The document benchmarks the two-tailed RT-qPCR method on biological samples, showing it can sensitively detect less than 10 molecules and maintain specificity across the entire miRNA sequence. It also demonstrates two-tube multiplexing of the method to profile expression levels of several miRNAs in different tissues.

1. Quality quantification with qPCR
Two-tailed PCR for ultrasensitive detection of
microRNAs

3. Analytical and preanalytical errors are expensive!

5. Blood DNA & RNA, Blood/Plasm ccfDNA
• Supported by the EFLM
(EFCC)
• Phase 1 Trials – Laboratories
used their workflows & tools
• Phase 2 Trials – Laboratories
will use SPIDIA’s optimized
workflows
• Isolated bioanalyties sent back
to SPIDIA’s laboratories –
intensive downstream testingMalentacchi F. et al. (2013). Clin Chim Acta 424: 274-286.
Malentacchi F. et al. (2015). Clin Chim Acta, accepted for publication
33%
of European routine
laboratories had quality
parameters “out of range”
European proficiency ring trials

6. Changes in mRNA levels in blood samples

7. Blood Collection Tube D
log2(RQ)*
PAX-RT EDTA-4°C EDTA-RT
-5
-4
-3
-2
-1
0
1
2
3
4
5
6
7
8
9
10
Blood Collection Tube D
log2(RQ)*
PAX-RT EDTA-4°C EDTA-RT
-14
-13
-12
-11
-10
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
1
2
3
4
5
Up-regulated FOSB mRNA level Down-regulated TNFRS mRNA level
Effect of stabilization
Malentacchi F et al. (2014). SPIDIA-RNA: Second External Quality Assessment for the Pre-Analytical Phase of Blood Samples Used for
RNA Based Analyses. PLoS ONE 9(11): e112293.
EDTA 2-8 °C EDTA RTStabilized RT * EDTA 2-8 °CStabilized RT * EDTA RT
* PAXgene Blood RNA
Zhan H et al. (2014). Biomarkers for Monitoring Pre-Analytical Quality Variation of mRNA in Blood Samples. . PLoS ONE 9(11): e111644.

8. Challenges expression profiling using biomarkers
• Impact of RNA quality?
• Impact of inhibition?
• Impact of genomic DNA background?
• Impact of inter-run variation?

9. Traditionally RNA integrity is tested by electrophoresis
RNA extracted from liver tissue. Left at room temperature and
analyzed (Bioanalyzer/Experion/Fragment Analyzer)
0min -------------------------------------------------->120min
Works quite well, but reflects ribosomal RNA integrity

10. Enzymatic and physical degradation of RNAs in the oocyte
Sidova et al., Effects of post-mortem and physical degradation
on RNA integrity and quality
Biomolecular Detection and Quantification 2015
Curtesy of Radek Šindelka, Insitute of Biotechnology, BTU,
Czech Academy of Sciences, CZ
Freeze-thaw, incubation in room temp Heat exposure of RNA

11. Physical/chemical degradation
Differential length amplicons (DAmp)
Target
Short (S)
Long (L)
0 2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 0 1 6 0 1 8 0 2 0 0 2 2 0 2 4 0
0
2
4
6
8
1 0
0
2
4
6
8
1 0
F o rm a lin e x p o s u re (m in )
DDAmpX-Y
RQI
L -S
E xp e rio n system
Björkman et al., Differential amplicons (ΔAmp)—a new molecular method to assess RNA integrity. Biomolecular Detection and Quantification 2015.

12. Enzymatic degradation
Endogeneous RNase
Resistant (ERR) marker
Stability
marker
0 2 0 4 0 6 0 8 0 1 0 0 1 2 0
0
2
4
6
8
1 0
0
2
4
6
8
1 0
C
T im e in R T (m in )
DDAmpERR
RQI
R Q I (P ie c e s )
P P IA - E R R m a rk e r (P ie c e s )
R Q I (P o w d e r)
P P IA - E R R m a rk e r (P o w d e r)
Björkman et al., Differential amplicons (ΔAmp)—a new molecular method to assess RNA integrity. Biomolecular Detection and Quantification 2015.

13. Paired samples (RNA):
Human FF (Fresh frozen) or FFPE
preserved
cDNA synthesis
qPCR Screening with 40+ Gene of Interest
(GOI) and DAmp S/L amplicons for:
ERR, 18S and B2M
QC of FFPE samples
2 5 3 0 3 5 4 0 4 5
-1
0
1
2
3
4
5
6
7
8
9
1 0
D A m p X -Y : E R R m a rk e r L a n d S a m p lic o n s
A vr C q a ll G O I
DDAmpX-Y
Y = 0 ,8 7 3 7 *X - 2 6 ,9 1
R
2
= 0 ,9 2 9 8
2 5 3 0 3 5 4 0 4 5
-1
0
1
2
3
4
5
6
7
8
9
1 0
D A m p X -Y E R R m a rk e r L a n d S a m p lic o n s
A vr C q a ll G O I
DDAmpX-Y
F F P E (L -S )
F F (L -S )

14. Spike in controls for inhibition
• Alien sequence (artificial gene) identical for RNA/DNA
RNA
DNA

15. PCR vs. RT inhibition

16. Compensate for gDNA background
ValidPrime
+ gDNA specific assay (ValidPrime)
+ Reference gDNA
Original data gene 1 gene 2 gene 3 gene 4 ValidPrime
sample 1 20.1 31.1 22.1 28.2 32.5
sample 2 20.5 31.2 22.5 28.9 33.2
sample 3 21 31.1 22.9 30.2 32.3
sample 4 23.1 31.8 22.5 32.3 34.2
sample 5 23.5 30.8 22.8 32 33.1
gDNA standard 25.8 26.9 26.7 26 27
Laurell et al., Nucleic Acids Research, 2012, 1–10; Drug Discovery World (2011)
 ValidPrime
gDNA
GOI
gDNA
ValidPrime
Sample
GOI
RT
CqCqCqCq 




    GOI
RT
GOI
RT
CqCqGOI
RNACq 22log2
More accurate and
more cost effective
than RT(-) controls
Measure gDNA signal in an RT- control reaction
•15% of human genes have pseudo genes
• Pseudo genes usually lack introns
• Pseudo genes are often present in multiple copies

17. Breaking up a large study into several plates
16 × 24 = 384 reactions
384/96 = 4 plates
Requires interplate
calibration

18. Interplate calibration: stability over time!
• Interplate calibrators should be measured with very high accuracy. Should be::
– Very stable assays
– Uncomplicated, purified template at fairly high concentration (20 <Cq < 25)
– Run in replicates (minimum triplicates)
– The Interplate calibrator shall be stable over time
TATAA IPC:

19. Challenges expression profiling using biomarkers
• RNA quality and it’s impact on generated data
 ∆AMP and ERR
• Sample data affected by inhibition?
 Exogenous controls (RNA/DNA spike)
• Impact of genomic DNA background?
 ValidPrime™
• Effects of between run variation?
 InterPlate calibrator
https://webshop.tataa.com/

20. Quality control and quality assessment
6426 citations

21. CEN and ISO Technical Specifications
Released guidelines (CEN 2015/16 in process at ISO)
• blood — Cellular RNA
• blood — Genomic DNA
• blood — Circulating cell free DNA
• FFPE tissue — DNA
• FFPE tissue — RNA
• FFPE tissue — Proteins
• frozen tissue — RNA
• frozen tissue — Proteins
• metabolomics in urine, serum and plasma
Guidelines in preparation
• Venous whole blood — CTCs: DNA, RNA, stains & proteins
• Venous whole blood – Exosomes: nucleic acids; ccfRNA
• Urine & other body fluids – cfDNA
• Saliva – Human DNA
• Saliva and stool – Microbiome DNA
• Frozen Tissue – DNA
• Fine Needle Aspirates (FNAs) – DNA, RNA, proteins
• Metabolomics of body fluids: International ISO Standard
• FFPE Tissue – in situ stainings incl. IHC

22. www.cancer-id.eu

23. Challenges analyzing miRNAs
• microRNAs are short (most 21-22 nt) and cannot fit
two conventional PCR primers
• There is no common sequence feature to use for the
enrichment and amplification.
• The mature miRNA sequence is present also in the
pre- and the pri-miRNAs
• miRNA isoforms (isomiRs) might evade capture, due
to terminal heterogeneity

24. Current methods make the microRNA longer
• Extension reduces sensitivity
• One probe only limits specificity

25. Two-tailed RT-qPCR

26. Design concept

27. Sensitivity and dynamic range
Sensitive to
detect <10
molecules!

28. Sequence specificity across the entire microRNA

29. Benchmarking in biological samples

30. 2-tube Multiplexing
Sample miR-122 miR-193a miR-1a miR-21a miR-24 miR-30c Let-7a
brain -0.12 0.93 1.26 2.41 0.11 -0.08 0.72
cereb. 0.09 0.99 1.67 2.17 0.20 0.28 0.85
heart -0.21 0.67 1.38 2.06 -0.34 -0.13 0.50
kidney 0.32 0.95 1.90 2.26 -0.14 0.07 0.25
liver -0.20 0.85 1.73 2.50 -0.28 -0.20 0.44
lung 0.02 0.96 1.47 2.36 0.04 0.44 0.76
muscle -0.11 0.87 1.70 2.33 -0.17 -0.23 1.24
average -0.03 0.89 1.59 2.30 -0.08 0.02 0.68
st.dev. 0.19 0.11 0.22 0.15 0.20 0.25 0.32
Δ Cq (relative to singleplex protocol)
8 different RT primers were pooled for multiplex reverse transcribed and subsequent
singleplex qPCR
1-tube RT-qPCR multiplexing
is also possible using probes

31. 2-tube Multiplexing
Sample miR-122 miR-193a miR-1a miR-21a miR-24 miR-30c Let-7a
brain -0.12 0.93 1.26 2.41 0.11 -0.08 0.72
cereb. 0.09 0.99 1.67 2.17 0.20 0.28 0.85
heart -0.21 0.67 1.38 2.06 -0.34 -0.13 0.50
kidney 0.32 0.95 1.90 2.26 -0.14 0.07 0.25
liver -0.20 0.85 1.73 2.50 -0.28 -0.20 0.44
lung 0.02 0.96 1.47 2.36 0.04 0.44 0.76
muscle -0.11 0.87 1.70 2.33 -0.17 -0.23 1.24
average -0.03 0.89 1.59 2.30 -0.08 0.02 0.68
st.dev. 0.19 0.11 0.22 0.15 0.20 0.25 0.32
Δ Cq (relative to singleplex protocol)
8 different RT primers were pooled for multiplex reverse transcribed and subsequent
singleplex qPCR
1-tube RT-qPCR multiplexing
is also possible using probes
Courtesy of Ben Ayer,
Adam McCoy and Luan
Le, Biosearch/LGC
10 replicates

32. Discrimination of isomiRs

33. Summary: Two-Tailed RT-PCR for microRNA
• New RT-qPCR method
• High sensitivity
• Wide dynamic range
• Very high specificity
• Unlimited multiplexing in RT with downstream singleplex qPCR
• RT-qPCR multiplexing with probes

34. Courses at TATAA
3 or 2 days Experimental
design and statistical data
analysis
3 or 2 days Hands-on
qPCR
1 day Immuno-qPCR
2 days Digital PCR
2 days NGS- Library
construction and QC
2 days Single cell
analysis
1 day Sample
preparation and quality
control
1 day Quality control of
qPCR in molecular
diagnostics
1 day Genotyping with
qPCR
1 day qPCR for miRNA
analysis
1 day Multiplex qPCR
1 day Quality control in
Molecular Diagnostics. New
CEN/ISO guidelines

35. WIN A MIC
For current schedule please visit: http://www.tataa.com/courses/upcoming-courses/