Real-Time PCR for MicroRNAs

Table of Contents

Letter from the Editor
Index of Experts
Q1: How do you design suitable primers for miRNA? Do you use stem-loops or primer-extension?
Q2: How do you determine your cycle threshold? What is an ideal Ct?
Q3: How do you detect your miRNAs? Do you use SYBR green?
Q4: How do you determine your detection efficiency? What is a good efficiency rate?
Q5: How do you differentiate between precursor and mature miRNAs?
Q6: Do you supplement your real-time miRNA PCR studies with other quantitative assays?
List of Resources

Download the PDF version here

Letter from the Editor

For our technical guide series, PCR — especially real-time PCR — has been a hot topic. We have had four guides touching on different aspects of this handy laboratory technique: a general guide, two on real-time procedures, and one that took it into clinical labs. Moving in a slightly different direction, this issue of Genome Technology's reference guide series looks at another booming field, that of microRNA research.

Applying real-time PCR to the study of microRNAs is a powerful approach, as it can be used to see just how much microRNA you've got and can be applied to a wide range of fields, especially cancer research but also to fertility or circadian timing.

In this guide, our experts will give you their ideas, thoughts, and opinions on how to set up, execute, and confirm your real-time PCR analysis of microRNAs. As this field is just heating up, the questions we've posed cover various aspects of running microRNA PCR, but focus on the basics — such as how to design your primers, pick your cycle threshold, or tell your precursor microRNAs from mature ones. Don't miss out on the resource guide that includes journal articles and websites that our experts below rely on.

— Ciara Curtin

Index of Experts

Genome Technology would like to thank the following contributors for taking the time to respond to the questions in this tech guide.

Thomas Schmittgen

Associate Professor
The Ohio State University

Frank Slack

Associate Professor
Yale University

M. Azim Surani

Gurdon Institute
Cambridge University

Phong Trang

Yale University

Joanne Weidhaas

Assistant Professor
Yale University School of Medicine

Fuchou Tang

Research Associate
Gurdon Institute
Cambridge University

John Rasko

Group Head
Gene and Stem Cell Therapy Program
Centenary Institute

Stephane Flamant

Visiting Scientist
Gene and Stem Cell Therapy Program
Centenary Institute

Wei Yan

Assistant Professor
University of Nevada School of Medicine

Q1: How do you design suitable primers for miRNA? Do you use stem-loop primers or a primer-extension method?

Our method is based on the classical methodology used for small RNA cloning. Starting with total RNA, an adapter is first ligated to the 3'-end of the microRNA. A 3' adapter-specific primer is then used for reverse transcription (primer-extension method). The same primer is used again, together with a 5' microRNA-specific primer, for the quantitative PCR reaction. Because of the challenging size of microRNAs, there's not much room to play with in order to design suitable primers. We usually design a primer covering the first 15 to 17 nucleotides, leaving the last 6 unconstrained nucleotides for validation by sequencing.

— John Rasko and Stephane Flamant

We exclusively use the Applied Biosystems TaqMan assay (stem-loop) to measure the mature microRNA. These assays are pre-designed and validated.

— Thomas Schmittgen

We use the TaqMan assays. You want to use stemloop primers here since the microRNA is so short.

— Frank Slack, Phong Trang, and Joanne Weidhaas

We use stem-loop-structured primers for microRNA quantification. We design three primers for each microRNA: Individual reverse primer for the reverse transcription step, individual forward primer, and universal reverse primer for both the pre-PCR amplification step and the real-time PCR step. The individual reverse primer (42 to 44 nucleotides) has a fixed 36-nucleotide sequence at 5' end to form an eight-nucleotide stem and 20-nucleotide loop structure, and a six- to eight-nucleotide sequence at 3' end to complement the corresponding microRNA. The forward primer (25 to 32 nucleotides) has 11- to 18-nucleotide sequence at 3' end, complementary to cDNA of corresponding microRNA and 14 nucleotide flanking sequence at 5' end to have melting temperature greater than 65 degrees Celsius. The universal reverse primer has 23 nucleotide sequence that has 18 nucleotide corresponding to the stemloop structured part of individual reverse primer and five nucleotide flanking sequences at 5' end to have melting temperature greater than 65 degrees Celsius.

— M. Azim Surani and Fuchou Tang

Our microRNA PCR method uses small RNA cDNAs as templates. SrcDNAs are generated by polyadenylation of microRNAs followed by reverse transcription using the RTQ primer, which contains an adapter sequence, 100 nucleotides, at the 5' end followed by 25 oligo dTs and two degenerate nucleotides V (for A, G, or C) and N (for A, G, C, or T). Levels of srcDNAs for a specific microRNA can be analyzed by PCR using a microRNA-specific primer (as the forward primer) and a universal primer (as the reverse primer) corresponding to the adapter sequence at the 3' ends of the srcDNAs. When we design microRNA-specific primers, we avoid using the two nucleotides at the very 3' ends of microRNAs because they may represent the two degenerate nucleotides (VN) commonly used in microRNA cloning procedures. The entire microRNA sequence except the very last two nucleotides can be used as the forward primer and the reverse primer with matching melting temperature and GC content can then be chosen from the adapter sequence.

— Wei Yan

Q2: How do you determine your cycle threshold? What is an ideal Ct?

The cycle threshold is determined approximately in the middle of the exponential phase of the amplification, which is usually between 25 and 35 cycles, depending on the sample and the microRNA of interest. Each reaction is run in triplicate, with negative reverse transcription controls (prepared at the same time as the actual cDNAs). For each sample tested, we include one ubiquitously expressed microRNA, such as let-7a or miR-21, as an internal positive control.

— John Rasko and Stephane Flamant

We use the Applied Biosystems 7900 real-time PCR instrument. We generally use the default conditions on the software to calculate Ct. Ct’s in the 20s are good for mature microRNA (Ct values of 25 to 30 are typical). Many say that Ct greater than 35 represents background or noise. With TaqMan probes, there is usually very little background so it is possible that we are measuring low levels of microRNA. Another useful method is to present the real-time PCR data as "copies of microRNA per cell." This was described in Caifu Chen's 2005 paper in Nucleic Acids Research. There are several assumptions, but it gives a pretty good estimate of how many copies of microRNA there are per cell. This also helps with the background issue. Generally, microRNAs that have 10 copies or less per cell may be disregarded as background.

— Thomas Schmittgen

We always have the ABI TaqMan program choose the cycle threshold for us. If we have to pick it manually, I think we will need to base it off our positive and negative controls.

— Frank Slack, Phong Trang, and Joanne Weidhaas

We usually set detection threshold at constant 0.2 for profiling studies that is important for the comparison of different samples. Ideal Ct values are 10 to 28 for 18 cycles of pre-PCR amplified cDNA samples. If the Ct value is more than 32, it corresponds to a few copies of the cDNA templates in a real-time PCR reaction. Typically, the variations or standard deviations are relatively large for Ct values over 28.

— M. Azim Surani and Fuchou Tang

We use SYBR green and 7300 Real-time PCR System (Applied Biosystems) for our microRNA quantitative PCR analyses. Ct is the cycle number at which the fluorescence signal reaches the threshold level above background. A Ct value for each microRNA tested can be automatically calculated by setting a threshold level to be 0.1 to 0.3 with auto baseline. All Ct values depend on abundance of the target microRNAs. For example, average Ct values for let-7 isoforms range from 17 to 20 when 25 nanograms of srcDNAs is used.

— Wei Yan

Q3: How do you detect your miRNAs? Do you use SYBR green?

MicroRNAs are detected using a TaqMan probe specific for the portion of the adapter not involved in the 3' primer sequence.

— John Rasko and Stephane Flamant

We detect mature microRNA using TaqMan probes. For microRNA precursors, we use SYBR green or TaqMan probes.

— Thomas Schmittgen

We use ABI's TaqMan probe, since it is more specific than SYBR green. But it is a lot more expensive.

— Frank Slack, Phong Trang, and Joanne Weidhaas

We use TaqMan-probe-directed real-time PCR to detect microRNA expression. For the multiplex microRNA assays, using SYBR green real-time PCR will reduce the specificity and lower the detection sensitivity of the assays due to the potential primer dimer formation in pre-PCR amplification reaction.

— M. Azim Surani and Fuchou Tang

We detect microRNAs using our PCR-based small RNA detection and quantification method, in which small RNA cDNAs serve as the templates. SrcDNAs are generated by polyadenylation of microRNAs at their 3' ends followed by reverse transcription using an RTQ primer, consisting of an adapter sequence (100 nucleotides) at the 5' end followed by 25 oligo dTs and two degenerate nucleotides V (for A, G or C) and N (for A, G, C, or T) at the 3' end. Levels of srcDNAs for a specific microRNA are analyzed by PCR using a microRNA-specific and a universal primer derived from the adapter sequence at the 3' ends of the srcDNAs. For quantitative PCR assays, we use SYBR green because the SYBR-based Q-PCR assay is cheaper and equally accurate and reproducible comparing to the TaqMan-based qPCR method.

— Wei Yan

Q4: How do you determine your detection efficiency? What is a good efficiency rate?

To set up this protocol, we used 10-fold serial dilutions of a synthetic oligonucleotide for let-7f spiked in HL60 total RNA depleted of small RNAs. Let-7f could be detected when using as few as 70 femtograms of starting material.

— John Rasko and Stephane Flamant

Efficiency is a tough one, especially when profiling several hundreds of different microRNAs. Since the Applied Biosystems TaqMan assays are very similar compared to each other in terms of length and the PCR primers, the efficiency should be more or less the same. A quick and dirty way to estimate efficiency is to compare the shape of the real-time PCR plots. Similar shapes should have similar PCR efficiencies. When we do want to calculate PCR efficiency, amplify 10-fold serial dilutions of cDNA. Then plot the cycle threshold versus the log of the dilution. The slope of the line equals -(1/log efficiency). Efficiency in the range of 1.85 to 2.05 is acceptable.

— Thomas Schmittgen

We can determine the efficiency of your PCR assay by running a serial dilution standard for your microRNA. Every 3.3 cycle threshold should represent a 10-fold amplification, which is equal to 100 percent efficiency. If it takes more than 3.3 ct for a one-log amplification, then your efficiency is less. A good efficiency rate should be 90 percent or better.

— Frank Slack, Phong Trang, and Joanne Weidhaas

The detection efficiencies of reverse transcription reactions for only six to eight nucleotides of reverse primer matched to the 3' end of microRNA targets are very different. To quantitatively determine the absolute copy numbers of microRNAs per cell, one has to run a standard curve using serial dilution of synthetic microRNA templates. While the absolute detection efficiencies are very different, the slopes of the standard curves are very similar for different microRNAs. Therefore, the relative quantification is accurate for profiling studies since it is based on delta cycle threshold values that correspond to the expression fold changes between two samples.

— M. Azim Surani and Fuchou Tang

We determined PCR efficiency using a direct method by converting the slope produced by a qPCR standard curve to percent efficiency. The efficiency calculator can be found in (Stratagene). Good efficiencies range from 90 percent to 110 percent calculated from slopes between -3.1 and -3.6.

— Wei Yan

Q5: How do you differentiate between precursor and mature miRNAs?

Every microRNA analyzed using this method is first tested by "classical" RT-PCR using the same 5' microRNA-specific and 3' adapter-specific primers, followed by polyacrylamide gel electrophoresis. Only those primers that give one PCR product of the expected size, i.e. around 95 base pairs, are used to perform real-time PCR. If PCR products of higher size are obtained, we optimize PCR conditions and/or design new 5' primers.

— John Rasko and Stephane Flamant

In 2004, we published the first PCR method to quantify microRNAs. This assay was used to quantify the microRNA precursors. It was our intention that the precursors would approximate the amount of mature microRNA in a given cell or tissue and, in many instances, they do. However, as we performed more profiling, we have identified numerous cases where substantial amounts of precursor are present, but not the mature microRNA. So we continue to use our PCR assay to measure the precursors and use the Applied Biosystems TaqMan assay to measure the mature microRNA.

— Thomas Schmittgen

With TaqMan real-time assay, you need to design separate primer sets and probes to detect precursor and mature microRNAs. For mature microRNAs, you would use the stem-loop primers, but for the mature sequence, I think you can use the regular primer since the sequence is longer.

— Frank Slack, Phong Trang, and Joanne Weidhaas

We use stem-loop-structured primers for microRNA quantification, which is specific for mature microRNA only. It will not reverse transcribe primary or precursor microRNA at all. So pri-microRNA and premicroRNA will not be converted into cDNA and will not interfere with later quantification of mature microRNAs.

— M. Azim Surani and Fuchou Tang

After qPCR, all PCR products are run on a 2 percent agarose gel to see if they are a single band and if their size is correct. On the gel, mature microRNAs and precursor microRNAs can be differentiated by their size. PCR products containing microRNAs will be about 120 base pairs in size while products containing pre-microRNAs will be about 170 base pairs. However, our PCR method preferentially amplifies mature microRNAs. We have used our PCR method and analyzed the expression profiles for greater than140 microRNAs, but never detected pre-microRNAs.

— Wei Yan

Q6: Do you supplement your real-time microRNA PCR studies with other quantitative assays?

We actually use the real-time studies as a complement to classical RT-PCR reaction to get quantitative data, which otherwise could be obtained by semi-quantitative PCR using the same method. We also performed microRNA microarrays experiments, and again, we used real-time PCR to validate microRNA candidates.

— John Rasko and Stephane Flamant

Occasionally with northern blots. We use northern blots to help us determine if the precursor microRNA is present in the reaction. Since northern blotting has the ability to distinguish primary precursor from precursor, they are very useful for these studies.

— Thomas Schmittgen

I would want to use northern if I have enough sample and quantify it on a phospho-imager, given that the microRNA level is high enough for detection. Detection of microRNA by northern is also a gold standard.

— Frank Slack, Phong Trang, and Joanne Weidhaas

We usually use our real-time PCR-based microRNA pro-filing assay to check all known microRNA expression in target samples to find differentially expressed microRNA candidates. Then we will use one-plex real-time PCR with stem-loop-structured primer to check these candidate microRNAs in a broader range of samples to confirm the biological relevance of them.

— M. Azim Surani and Fuchou Tang

When quantitative PCR or semi-qPCR is performed for the first time, qPCR results should be confirmed with another quantitative assay, northern blot or RNA protection assay. At least three samples should be tested to see if the quantitative data can be reproduced by another method.

— Wei Yan

List of Resources

Can’t get enough? Here are lists of publications, websites, and books, many suggested or written by our experts, that might do the trick — or at least keep you going in the right direction.


Bandrés E, Cubedo E, Agirre X, Malumbres R, Zárate R, Ramirez N, Abajo A, Navarro A , Moreno I, Monzó M, García-Foncillas J. (2006). Identification by real-time PCR of 13 mature microRNAs differentially expressed in colorectal cancer and non-tumoral tissues. Molecular Cancer. 5(29).

Chen C, Ridzon DA, Broomer AJ, Zhou Z, Lee DH, Nguyen JT, Barbisin M, Xu NL, Mahuvakar VR, Andersen MR, Lao KQ, Livak KJ, Guegler KJ. (2005). Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Research. 33(20):e179.

Hwang HW, Wentzel EA, Mendell JT. (2007). A Hexanucleotide Element Directs MicroRNA Nuclear Import. Science. 315 (5808): 97-101.

Jiang J, Lee EJ, Gusev Y, Schmittgen TD. (2005). Real-time expression profiling of microRNA precursors in human cancer cell lines. Nucleic Acids Research. 33(17): 5394-5403.

Kye MJ, Liu T, Levy SF, Xu NL, Groves BB, Bonneau R, Lao K, Kosik KS. (2007). Somatodendritic microRNAs identified by laser capture and multiplex RT-PCR. RNA. 13(8):1224-34.

Liu T, Papagiannakopoulos T, Puskar K, Qi S, Santiago F, Clay W, Lao K, Lee Y, Nelson SF, Kornblum HI, Doyle F, Petzold L, Shraiman B, Kosik KS. (2007). Detection of a MicroRNA Signal in an In Vivo Expression Set of mRNAs. PLoS ONE. 2(8):e804.

Lu DP, Read RL, Humphreys DT, Battah FM, Martin DIK, Rasko JEJ. (2005). PCR-based expression analysis and identification of microRNAs. Journal of RNAi and Gene Silencing. 1(1): 44-49.

Mattie MD, Benz CC, Bowers J, Sensinger K, Wong L, Scott GK, Fedele V, Ginzinger D, Getts R, Haqq C. (2006). Optimized high-throughput microRNA expression profiling provides novel biomarker assessment of clinical prostate and breast cancer biopsies. Mol Cancer. 5: 24.

Mishima T, Mizuguchi Y, Kawahigashi Y, Takizawa T, Takizawa T. (2007). RT-PCR-based analysis of microRNA (miR-1 and -124) expression in mouse CNS. Brain Research. 1131: 37-43.

Raymond CK, Roberts BS, Garrett-Engele P, Lim LP, Johnson JM. (2005). Simple, quantitative primerextension PCR assay for direct monitoring of microRNAs and short-interfering RNAs. RNA. 11:1737-1744.

Ro S, Park C, Young D, Sanders KM, Yan W. (2007). Tissue-dependent paired expression of miRNA. Nucleic Acids Research. 35(17):5944-5953.

Ro S, Park C, Song R, Nguyen D, Jin J, Sanders KM, McCarrey JR, Yan W. (2007). Cloning and expression profiling of testis-expressed piRNAlike RNAs. RNA. 13: 1693-702.

Ro S, Park C, Jin J, Sanders KM, Yan W. (2006). A PCR-based method for detection and quantification of small RNAs. Biochemical and Biophysical Research Communications. 351(3): 756-63.

Schmittgen TD, Jiang J, Liu Q, Yang L. (2004). A high-throughput method to monitor the expression of microRNA precursors. Nucleic Acids Research. 32(4):e43.

Shi R, Chiang VL. (2005). Facile means for quantifying microRNA expression by real-time PCR. Biotechniques. 39(4):519-25.


5th Colmar Symposium: The New RNA Frontiers
Colmar Liberty and Alsace BioValley
November 8-9, 2007
CREF Congress Center
Colmar, France

MicroRNA in Human Disease and Development
Cambridge Healthtech Institute
March 10-11, 2008
Royal Sonesta Hotel
Cambridge, Massachusetts

High-Throughput MicroRNA Profiling
EMBO Course
April 7-12, 2008
Heidelberg, Germany

Quantitative PCR: Replicating and Validating Success
Cambridge Healthtech Institute
April 21-22, 2008
Hilton San Diego Resort
San Diego, California

Advances in qPCR / RNAi Europe
Select Biosciences
September 17-18, 2008
Stockholm International Fairs & Congress Center
Stockholm, Sweden

Regulatory RNA in Biology and Human Health
Miami Winter Symposium, Nature
February 2-6, 2008
University of Miami
Miami, Florida

RNAi, MicroRNA, and Non-Coding RNA
Keystone Symposia Conference
March 25-30, 2008
Whistler Resort
Whistler, British Columbia

RNAi World Congress
Select Biosciences
May 1-2, 2008
Hilton Boston Logan Airport
Boston, Massachusetts

PCR and MicroRNA in the Blogosphere

In a post entitled "Differences in Auditory Cortex Neurons and Prefrontal microRNA Expression in Schizophrenia" on the blog Neurocritic, the blogger summarizes two studies of schizophrenia, one of which found altered microRNAs in the prefrontal cortex in the brains of people affected by the disorder. The blogger concludes, "Certainly, one's environment, social circumstances, upbringing, stress levels, etc. do play a role in the expression of various mental illnesses, but so do genetics, brain structure, and brain function." es-in-auditory-cortex-neurons.html

In a blog post over at Omics! Omics!, Keith Robison writes about how to precisely measure the expression of a small number of genes. He contends that while micorarrays are good for a large-scale study, in smaller studies, "quantitative RT-PCR is the way to go." He also discusses the advantages of digital PCR.

For a good primer on PCR, check out Sandra Porter's series on the subject at her blog Discovering Biology in a Digital World. She begins with basic animations to illustrate how amplification works, and later in the series gets increasingly technical with posts about, for instance, how to use blastn to test primers in a PCR experiment. r_primers_with_blastn.php

Index of Names

Locate expert advice in
GT's technical guide series that span both RNAi and PCR topics.

Adams, Scottie, PCR I: 5, 7, 11, 13, 15
Andersen, Claus Lindbjerg, PCR I: 5, 7, 11
Beneš, Vladimir, PCR I: 5, 7, 9, 11, 13, 15, 16; III: 5, 7, 9, 10, 13, 18
Bustin, Stephen, PCR I: 5, 9, 11, 15, 16, 17; IV: 6, 9, 12, 17, 19
Cahill, Anne, shRNA: 5, 6, 8, 9, 10
Day, Philip, PCR IV: 6
Ding, Xinxin, PCR II: 19; III: 22
Flamant, Stephane, PCR V: 7, 9, 11, 12, 15, 17
Gilsbach, Ralf, PCR IV: 6-7, 12
Habermann, Bianca, siRNA: 5, 6-7, 8, 9, 10, 11, 12
Hartshorn, Cristina, PCR II: 5, 7, 12, 15, 17; III: 5, 7, 9, 10, 13, 18
Hofmann, Andreas, shRNA: 5, 6-7, 8, 9, 10, 11
Huggett, Jim, PCR II: 5, 7, 11, 12, 15, 17
Hunter, Tim, PCR II: 5, 7-8, 11, 12, 15, 17
Jiang, Ming, shRNA: 5, 6, 8, 9, 10, 11; siRNA: 5, 7, 8, 9, 10, 11
Kanda, Tatsuo, shRNA: 5, 6, 8, 9, 10, 11
Kubista, Mikael, PCR I: 5, 9, 11, 15-17; II 5, 8, 11, 13, 15, 17, 21-22; III: 5, 9, 11, 13-14, 17, 18, 20; IV: 7, 9, 12, 19
Levy, Shawn, PCR I: 5, 9, 15, 16, 17
Mackay, Ian, PCR IV: 7, 9, 12, 15, 17, 19
McNeill, Roisin, PCR IV: 7, 9-10, 12-13, 15, 19-20
Orlando, Claudio, PCR IV: 10, 13
Pandori, Mark, PCR IV: 10, 15
Pfaffl, Michael, PCR III: 5, 9, 11, 14, 17, 19
Pfeifer, Alexander, shRNA: 5, 6-7, 8, 9, 10, 11
Poon, Randy, shRNA: 5, 7, 8, 9, 10, 11
Rasko, John, PCR V: 7, 9, 11, 12, 15, 17
Rossi, John J., siRNA: 5, 7, 8, 9, 10, 11, 12
Sachidanandam, Ravi, shRNA: 5, 7, 9, 14
Sails, Andrew, PCR IV: 13, 15, 17, 20
Schmittgen, Thomas, PCR V: 7, 9, 11, 12, 15, 17
Shipley, Gregory, PCR III: 5, 7, 11, 17, 19, 20
Sjoback, Robert, PCR IV: 7, 9, 12, 19
Slack, Frank, PCR V: 7, 9, 11, 12, 15, 17
Sohail, Muhammad, siRNA: 5, 7, 8, 9, 10, 11, 12
Surani, M. Azim, PCR V: 7, 9, 11, 12, 15, 17
Tang, Fuchou, PCR V: 7, 9, 11, 12, 15, 17
Taxman, Debra, shRNA: 5, 7, 8, 10, 11, 14
Trang, Phong, PCR V: 7, 9, 11, 12, 15, 17
Vandesompele, Jo, PCR I: 5, 9, 15, 17; II: 5, 11, 13, 21, 22; III: 10; IV: 17, 20
Weidhaas, Joanne, PCR V: 7, 9, 11, 12, 15, 17
Wong, Marisa, PCR II: 5, 13, 21, 22
Yan, Wei, PCR V: 7, 9, 11, 12, 15, 17
Zhang, Xiulin, PCR II: 5, 13, 21; III: 5, 14, 19, 20
Zianni, Michael, PCR I: 5, 9, 15, 17
Zhao, Huifen, siRNA: 10, 11, 12


MicroRNA: Biology, Function & Expression
By Neil J. Clarke and Philippe Sanseau
(May 2006) DNA Press
ISBN 1933255196

MicroRNA Protocols (Methods in Molecular Biology)
Edited by Shao-Yao Ying
(April 2006) Humana Press
ISBN 1588295818

Real Time PCR
By Tevfik Dorak
(June 2006) Taylor & Francis
ISBN 041537734X