RT-qPCR for RNA quantification

RT-qPCR for RNA quantification

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I'm really new to RT-qPCR and probably I've just a minor problem than I think.

So, what's my problem about.

I want to quantify a virus by a specific area within a gene on its genome. I've specific primer which are working fine with the extracted virus rna from my samples. But now I need a template for a dilution series to quantify this virus. And there's my little problem. And maybe you can help me.

So I know that the genome of my virus is a negative sense single stranded RNA, so -ssRNA, and moreover I know the virus strain and the gene, which RNA I want to synthesize for the quantification. So I looked it up on ncib and I found the sequence of the gene, but it is listed as the complete cds of the gene and not the RNA sequence. And as I'm right the cds is the same sequence as the positive sense RNA, with Us instead of the Ts?!? So is it right for synthesizing, that I have to translate the cds first in +ssRNA and then in -ssRNA and this -ssRNA sequence I have to synthesize to get a standard?

If the cds would be: ATG , the +ssRNA would be: AUG and therefore the -ssRNA would be: UAC and this UAC , I would have to synthesize? Sorry for this stupid question but I am a lil bit confused at the moment with the difference of - and + ssRNA regardind the RT-qPCR. Another question would be, whether the Reverse transcriptase with Random hexamer primer is specific for -ssRNA or +ssRNA. It isn't ? So my quantification would also work with the AUG as a template for a standard curve?

Thanks a lot!


To start off with your last question, strandedness is something the reverse transcriptase does not care about. If you use random hexamers it will simply translate your -ssRNA into a + single stranded cDNA. Perhaps this diagram from Wikipedia makes things more clear, it is for an mRNA but the principle is the same:

This cDNA will then serve as a template for your primers in the qPCR which will turn it into a double stranded DNA molecule. In other words, after one round of amplication in a PCR reaction the DNA products of the + and the - RNA strand would be indistinguishable!

It therefore does not matter which strand you synthesise as DNA to make your standard curve. It will be double stranded so you just need to compensate for the other strand being a template in the PCR as well.

Development and validation of an RT-qPCR assay for rapid detection and quantification of hepatitis C virus RNA for routine testing in Moroccan clinical specimens

A one-step reverse transcription quantitative PCR (RT-qPCR) assay in combination with rapid RNA extraction was evaluated for routine testing of hepatitis C virus (HCV) RNA. Specific primers and probes were designed for the detection of a 150 bp sequence located in the 5'untranslated region (5'UTR) of HCV RNA. The target sequence was selected as the most conserved region between the six known HCV subtype sequences following an alignment. The assay was able to quantify a dynamic linear range of 10 8 to 10 1 plasmid copies/reaction (r 2 = 0.98) containing the target sequence. Two copies of this HCV plasmid corresponds to one international unit (IU) measured using a standard obtained by serial dilutions of the World Health Organization (WHO) standard. The detection limit of the assay was about 10 IU/mL of HCV RNA (20 copies/mL) in plasma samples. The assay was comparable to Cobas AmpliPrep/Cobas TaqMan® HCV Test, v2.0 Quantitative assay (Roche Molecular Systems, Inc., Branchburg, NJ) with correlation coefficient r 2 = 0.98. The present assay could be completed within 3 hours from RNA extraction to data analysis of at least 30 plasma samples. Our test provides sufficient sensitivity, specificity, and reproducibility and proved to be fast, labor-saving, and cost-effective. Indeed, our system will definitely allow low-income countries to monitor accurately this viral infection and to efficiently treat their infected patients.

Keywords: Hepatitis C RT-qPCR molecular diagnostic viral load quantification.


Quantitative viral load assays have revolutionized our ability to manage viral diseases 1 , 2 , 3 , 4 , 5 , 6 . While not yet widely available for SARS-CoV-2, quantitative assays could advance our understanding of COVID-19 biology and inform infection prevention and control measures 7 , 8 . Most SARS-CoV-2 molecular diagnostic assays however, which use real-time reverse transcriptase PCR (RT-PCR) to detect one or more SARS-CoV-2 genomic targets using sequence-specific primers coupled with a fluorescent probe, are only semi-quantitative. These tests produce cycle threshold (Ct) values as readouts, which represent the PCR cycle where the sample began to produce fluorescent signal above background. While each Ct value decrement corresponds to a roughly two-fold higher viral load (due to the exponential nature of PCR amplification), Ct values cannot be directly interpreted as SARS-CoV-2 viral loads without calibration to a quantitative standard 9 , 10 . Rather, Ct values are interpreted as positive, indeterminate or negative based on assay-specific cutoffs and evolving clinical guidelines. Due to differences in nucleic acid extraction method, viral target and other parameters, Ct values are also not directly comparable across assays or technology platforms.

Reverse transcriptase droplet digital PCR (RT-ddPCR) offers an attractive platform for SARS-CoV-2 RNA quantification 11 , 12 . Like real-time RT-PCR, ddPCR employs target-specific primers coupled with a fluorescent probe, making it relatively straightforward to adapt assays. In ddPCR however, each reaction is fractionated into 20,000 nanolitre-sized droplets prior to massively parallel PCR amplification. At end-point, each droplet is categorized as positive (target present) or negative (target absent), allowing for absolute target quantification using Poisson statistics. This sensitive and versatile technology has been used for mutation detection and copy number determination in the human genome 13 , target verification following genome editing 14 , and copy number quantification for viral pathogens 15 , 16 , 17 , 18 , 19 , 20 , 21 . Several real-time RT-PCR SARS-CoV-2-specific primer/probe sets have been used in RT-ddPCR ( 11 , 12 , 22 , 23 and manufacturer protocol) with results achieving high sensitivity in some reports 12 , 22 , 24 , 25 , 26 , but few studies have rigorously evaluated SARS-CoV-2-specific primer/probe set performance in RT-ddPCR using RNA as a template. Furthermore, no studies to our knowledge have calibrated SARS-CoV-2 viral loads to diagnostic test Ct values. Here, we evaluate eight SARS-CoV-2-specific primer/probe sets originally developed for real-time RT-PCR 27 , for use in RT-ddPCR. We also derive a linear equation relating RT-ddPCR-derived SARS-CoV-2 viral loads and real-time RT-PCR-derived Ct values for a commercial diagnostic assay, the LightMix Modular SARS-CoV (COVID19) E-gene assay, allowing conversion of existing COVID-19 diagnostic results to viral loads.



Coronavirus disease 2019 (COVID-19) is a global pandemic caused by a novel virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The viral load of SARS-CoV-2 is associated with mortality in COVID-19 patients. Measurement of viral load requires the use of reverse transcription quantitative PCR (RT-qPCR), which in turn requires advanced equipment and techniques. In this study, we aimed to evaluate the viral load measurement using reverse transcription loop-mediated isothermal amplification (RT-LAMP), which is a simpler procedure compared to RT-qPCR.

Materials and methods

RNA was extracted by using the QIAamp Viral RNA Mini Kit. The RT-LAMP assay was performed by using the Loopamp® 2019-SARS-CoV-2 detection reagent kit and 10-fold serial dilutions of known viral load RT-LAMP were used to measure Tt, which is the time until the turbidity exceeds the threshold. Based on the relationship between viral load and Tt, the linearity and detection sensitivity of the calibration curve were evaluated. In addition, 117 clinical specimens were measured, and RT-qPCR and RT-LAMP assay results were compared.


The dilution linearity of the calibration curve was maintained at five orders of magnitude 1.0× 10 6 to 1.0 × 10 1 copies/μL, and was confirmed to be detectable down to 1.0 × 10 0 copies/μL. The limit of quantification of RNA extracted from clinical specimens using RT-LAMP correlated well with that obtained using RT-qPCR (r 2 = 0.930).


The findings indicate that RT-LAMP is an effective method to determine the viral load of SARS-CoV-2.

RT-qPCR for RNA quantification - Biology

Data normalisation in microRNA experiments using qRT-PCR is a new challenge in gene quantification analysis. The reliability of any relative RT-PCR experiment can be improved by including an invariant endogenous control (reference gene) in the assay to correct for sample to sample variations in the qRT-PCR efficiency and errors in sample quantification. A biologically meaningful reporting of target mRNA copy numbers requires accurate and relevant normalisation to some standard and is strongly recommended in microRNA qRT-PCR.

=> But the quality of normalized quantitative expression data cannot be better than the quality of the normalizer itself.
=> Which are the best endogen microRNA normalizers ?
=> Can we apply a comparable normalising strategy as done for mRNAs ?

Any variation in the normalizer will obscure real changes and produce artifactual changes. Real-time RT-PCR-specific errors in the quantification of microRNA transcripts are easily compounded with any variation in the amount of starting material between the samples, e.g. caused by sample-to-sample variation and cDNA sample loading variation. This is especially relevant when the samples have been obtained from different individuals, different tissues and different time courses, and will result in the misinterpretation of the derived expression profile of the target genes.

=> Therefore, normalisation of target gene expression levels must be performed to compensate intra- and inter-kinetic RT-PCR variations (sample-to-sample & run-to-run variations).

Data normalisation can be carried out against one or more endogenous unregulated reference gene transcript or against total cellular DNA or RNA content (molecules/g total DNA/RNA and concentrations/g total DNA/RNA). Normalisation according the total cellular RNA content is increasingly used, but little is known about the total RNA content of cells or even about the microRNA or mRNA concentrations. The content per cell or per gram tissue may vary in different tissues in vivo, in cell culture (in vitro), between individuals and under different experimental conditions. Nevertheless, it has been shown that normalisation to total cellular RNA is the least unreliable method. It requires an accurate quantification of the isolated total RNA or mRNA or microRNA fraction by optical density at 260 nm, Lab-on-Chip capillary electrophoresis instruments, or Ribogreen RNA Quantification Kit.

To normalize the absolute amount according to a single reference gene (or better a set of multiple stable reference genes), further sets of kinetic PCR reactions has to be performed for the invariant endogenous control(s) on all experimental samples and the relative abundance values are calculated for internal control as well as for the target gene. For each target gene sample, the relative abundance value obtained is divided by the value derived from the control sequence in the corresponding target gene. The normalized values for different biological samples can then directly be compared.

Profound Effect of Profiling Platform and Normalization Strategy on Detection of Differentially Expressed MicroRNAs -- A Comparative Study.
Meyer SU, Kaiser S, Wagner C, Thirion C, Pfaffl MW.
Physiology Weihenstephan, ZIEL Research Center for Nutrition and Food Sciences Technische Universität München, Freising, Germany.
PLoS One. 20127(6):e38946

CONCLUSIONS/SIGNIFICANCE: We recommend the application of loess, or loessM, and GPA normalization for miRNA Agilent arrays and qPCR cards as these normalization approaches showed to (i) effectively reduce standard deviations, (ii) increase sensitivity and accuracy of differential miRNA expression detection as well as (iii) increase inter-platform concordance. Results showed the successful adoption of loessM and generalized procrustes analysis to one-color miRNA profiling experiments.
Data Normalization Strategies for MicroRNA Quantification.
Schwarzenbach H, da Silva AM, Calin G, Pantel K
Clin Chem. 2015 61(11): 1333-13342

Identification of reference microRNAs and suitability of archived hemopoietic samples for robust microRNA expression profiling.
Viprey VF, Corrias MV, Burchill SA.
Children's Cancer Research Group, Leeds Institute of Molecular Medicine, Section of Experimental Oncology, Leeds LS9 7TF, UK
Anal Biochem. 2012 Feb 15421(2): 566-572

Identification of suitable reference genes for qPCR analysis of serum microRNA in gastric cancer patients.
Song J, Bai Z, Han W, Zhang J, Meng H, Bi J, Ma X, Han S, Zhang Z.
Department of General Surgery, Beijing Friendship Hospital, Capital Medical University, 95 Yongan Road, Xuanwu District, Beijing 100050, People's Republic of China.
Dig Dis Sci. 2012 Apr57(4): 897-904

Suitable reference genes for relative quantification of miRNA expression in prostate cancer.
Schaefer A, Jung M, Miller K, Lein M, Kristiansen G, Erbersdobler A, Jung K.
Department of Urology, University Hospital Charité, Berlin, Germany.
Exp Mol Med. 2010 Nov 3042(11): 749-758.

Comprehensive human adipose tissue mRNA and microRNA endogenous control selection for quantitative real-time-PCR normalization.
Neville MJ, Collins JM, Gloyn AL, McCarthy MI, Karpe F.
Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
Obesity (Silver Spring). 2011 Apr19(4): 888-892

supplement files
MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer.
Chang KH, Mestdagh P, Vandesompele J, Kerin MJ, Miller N.
Department of Surgery, National University of Ireland, Galway, Republic of Ireland.
BMC Cancer. 2010 Apr 2910:173

miRNA expression profiling - from reference genes to global mean normalization.
Barbara D’haene1, Pieter Mestdagh2, Jan Hellemans1, Jo Vandesompele1,2
1 Biogazelle, Zwijnaarde, Belgium 2 Center for Medical Genetics, Ghent University, Ghent, Belgium

MicroRNAs (miRNAs) are an important class of gene regulators, acting on several aspects of cellular function such as differentiation, cell cycle control and stemness. These master regulators constitute an invaluable source of biomarkers, and several miRNA signatures correlating with patient diagnosis, prognosis and response to treatment have been identified. Within this exciting field of research, whole-genome RT-qPCR based miRNA profiling in combination with a global mean normalization strategy has proven to be the most sensitive and accurate approach for high-throughput miRNA profiling (Mestdagh et al., Genome Biology, 2009). In this chapter, we summarize the power of the previously described global mean normalization method in comparison to the multiple reference gene normalization method using the most stably expressed small RNA controls. In addition, we compare the original global mean method to a modified global mean normalization strategy based on the attribution of equal weight to each individual miRNA during normalization. This modified algorithm is implemented in Biogazelle’s qbasePLUS software and is presented here for the first time.
Identification by Real-time PCR of 13 mature microRNAs differentially expressed in colorectal cancer and non-tumoral tissues.
Molecular Cancer 2006, 5:29
E Bandrés*1, E Cubedo1, X Agirre2, R Malumbres1, R Zárate1, N Ramirez1,
A Abajo1, A Navarro3, I Moreno4, M Monzó3 and J García-Foncillas1

A single-molecule method for the quantitation of microRNA gene expression.
Neely LA, Patel S, Garver J, Gallo M, Hackett M, McLaughlin S, Nadel M, Harris J, Gullans S, Rooke J.
US Genomics, 12 Gill Street, Suite 4700, Woburn, Massachusetts 01801, USA
Nat Methods. 2006 (1): 41-46

MicroRNAs (miRNAs) are small noncoding RNAs whose function has been implicated in a wide range of fundamental cellular processes including cell proliferation, cell differentiation, and cell death. Quantitation of miRNA gene expression levels has become an essential step in understanding these mechanisms, and has shown great promise in identifying effective biomarkers correlative with human disease1,2. Applied Biosystems has developed an extensive set of TaqMan® MicroRNA Assays, novel stem-loop RT and real-time PCR assays, for the quantitation of mature miRNA expression3. TaqMan® Assays are the ideal choice for these applications because of their unsurpassed sensitivity, specificity, and wide dynamic range. Additionally, far less input material is required compared to microarrays and other alternative technologies. When performing these experiments,variation in the amount of starting material, sample collection, RNA preparation and quality, and reverse transcription (RT) efficiency can contribute to quantification errors. Normalization to endogenous control genes is currently the most accurate method to correct for potential RNA input or RT efficiency biases. Careful selection of an appropriate control or set of controls is extremely important as significant variation has been observed between samples, even for the most commonly used housekeeping genes, including ACTB (ß-Actin) and GAPDH4. An ideal endogenous control generally demonstrates gene expression that is relatively constant and highly abundant across tissues and cell types. However, one must still validate the chosen endogenous control or set of controls for the target cell, tissue, or treatment5, as no single control can serveas a universal endogenous control for all experimental conditions. When considering endogenous controls suitable for use with TaqMan MicroRNA Assays, it is important that they share similar properties, such as RNA stability and size, and are amenable to the miRNA assay design. A number of reports indicate that other classes of small non-coding RNAs (ncRNAs) are expressed both abundantly and stably, making them good endogenous control candidates. We have performed a systematic study of a set of human ncRNA species ranging in size from 45 to 200 nucleotides, including transfer RNA (tRNA), small nuclear RNA (snRNA) and small nucleolar RNA (snoRNA) 6 across a relatively wide variety of tissues and cell lines to determine their suitability as endogenous controls when quantitating miRNA expression levels using real-time PCR methods.
Normalization strategy is critical for the outcome of miRNA expression analyses in the rat heart.
Brattelid T, Aarnes EK, Helgeland E, Guvaåg S, Eichele H, Jonassen AK.
Department of Biomedicine, Faculty of Medicine and Dentistry, University of Bergen, Norway.
Physiol Genomics. 2011 43(10): 604-610

Since normalization strategies plays a pivotal role for obtaining reliable results when performing quantitative PCR (qPCR) analyses, this study investigated several miRNA normalization candidates in regards to their efficiency as normalization standards in the ischemic reperfused ex vivo rat heart, with special reference to regulation of the miRNAs miR-1 and miR-101b. The possibility of including primers for several miRNAs in one reverse transcription (RT) reaction was also investigated. Langendorff perfused rat hearts were subjected to 30 min regional ischemia and 0, 1, 5, 15, or 120 min reperfusion. Total RNA was isolated and reverse transcribed for miRNA qPCR analysis. Normalization candidates were evaluated by the NormFinder and geNorm algorithms and the following stability expression rank order was obtained: sno202 < U6B < U87 < snoRNA < 4.5S RNA A < Y1 < 4.5S RNA B < GAPDH. Applying U6B as a normalizer it was found that miR-1 and miR-101b was downregulated in the ischemic reperfused myocardium. Furthermore, up to three primers could be included in one RT reaction by replacing RNase-free water with two supplemental sets of primers in the TaqMan MicroRNA assay protocol. This study demonstrates the importance of validating normalization standards when performing miRNA expression analyses by qPCR, and that miR-1 and miR-101b may play an important role during early reperfusion of the ischemic rat heart.
The use of microRNAs as reference genes for quantitative polymerase chain reaction in soybean.
Kulcheski FR, Marcelino-Guimaraes FC, Nepomuceno AL, Abdelnoor RV, Margis R.
Centre of Biotechnology, Laboratory of Genomes and Plant Population, Federal University of Rio Grande do Sul-UFRGS, CEP 91501-970, Porto Alegre, RS, Brazil.
Anal Biochem. 2010 Nov 15406(2): 185-192

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a robust and widely applied technique used to investigate gene expression. However, for correct analysis and interpretation of results, the choice of a suitable gene to use as an internal control is a crucial factor. These genes, such as housekeeping genes, should have a constant expression level in different tissues and across different conditions. The advances in genome sequencing have provided high-throughput gene expression analysis and have contributed to the identification of new genes, including microRNAs (miRNAs). The miRNAs are fundamental regulatory genes of eukaryotic genomes, acting on several biological functions. In this study, miRNA expression stability was investigated in different soybean tissues and genotypes as well as after abiotic or biotic stress treatments. The present study represents the first investigation into the suitability of miRNAs as housekeeping genes in plants. The transcript stability of 10 miRNAs was compared to those of six previously reported housekeeping genes for the soybean. In this study, we provide evidence that the expression stabilities of miR156b and miR1520d were the highest across the soybean experiments. Furthermore, these miRNAs genes were more stable than the most commonly protein-coding genes used in soybean gene expression studies involving RT-qPCR.

microRNA normalisation of microRNA arrays

How to choose a normalization strategy for miRNA quantitative real-time (qPCR) arrays
Deo A, Carlsson J, Lindlöf A.
Systems Biology Research Centre, University of Skövde, Box 408 Skövde, 541 28, Sweden
J Bioinform Comput Biol. 2011 9(6):795-812.

Quality assessment and data analysis for microRNA expression arrays.
Sarkar D, Parkin R, Wyman S, Bendoraite A, Sather C, Delrow J, Godwin AK, Drescher C, Huber W, Gentleman R, Tewari M.
Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA.
Nucleic Acids Res. 2009 Feb37(2):e17

MicroRNAs are small (approximately 22 nt) RNAs that regulate gene expression and play important roles in both normal and disease physiology. The use of microarrays for global characterization of microRNA expression is becoming increasingly popular and has the potential to be a widely used and valuable research tool. However, microarray profiling of microRNA expression raises a number of data analytic challenges that must be addressed in order to obtain reliable results. We introduce here a universal reference microRNA reagent set as well as a series of nonhuman spiked-in synthetic microRNA controls, and demonstrate their use for quality control and between-array normalization of microRNA expression data. We also introduce diagnostic plots designed to assess and compare various normalization methods. We anticipate that the reagents and analytic approach presented here will be useful for improving the reliability of microRNA microarray experiments.
Evaluation of normalization methods for two-channel microRNA microarrays.
Zhao Y, Wang E, Liu H, Rotunno M, Koshiol J, Marincola FM, Landi MT, McShane LM.
Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
J Transl Med. 2010 Jul 218:69.

BACKGROUND: MiR arrays distinguish themselves from gene expression arrays by their more limited number of probes, and the shorter and less flexible sequence in probe design. Robust data processing and analysis methods tailored to the unique characteristics of miR arrays are greatly needed. Assumptions underlying commonly used normalization methods for gene expression microarrays containing tens of thousands or more probes may not hold for miR microarrays. Findings from previous studies have sometimes been inconclusive or contradictory. Further studies to determine optimal normalization methods for miR microarrays are needed.
METHODS: We evaluated many different normalization methods for data generated with a custom-made two channel miR microarray using two data sets that have technical replicates from several different cell lines. The impact of each normalization method was examined on both within miR error variance (between replicate arrays) and between miR variance to determine which normalization methods minimized differences between replicate samples while preserving differences between biologically distinct miRs.
RESULTS: Lowess normalization generally did not perform as well as the other methods, and quantile normalization based on an invariant set showed the best performance in many cases unless restricted to a very small invariant set. Global median and global mean methods performed reasonably well in both data sets and have the advantage of computational simplicity.
CONCLUSIONS: Researchers need to consider carefully which assumptions underlying the different normalization methods appear most reasonable for their experimental setting and possibly consider more than one normalization approach to determine the sensitivity of their results to normalization method used.

A comparison of normalization techniques for microRNA microarray data.
Rao Y, Lee Y, Jarjoura D, Ruppert AS, Liu CG, Hsu JC, Hagan JP. The Ohio State University, USA.
Stat Appl Genet Mol Biol. 20087(1): Article 22

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Using PrimeScript reverse transcriptase for qRT-PCR to detect low abundance RNA

PrimeScript reverse transcriptase is a highly sensitive and specific RNase H minus recombinant RTase derived from Moloney Murine Leukemia Virus (MMLV). The sensitivity of PrimeScript RTase is well-documented for example, the enzyme allows detection of zeptomole amounts of miRNA, even in pools of total RNA, while its specificity allows differentiation of miRNAs containing single base mismatches (Yao, B. et al. (2009) RNA 15:1787&ndash1794). Several kits for qRT-PCR using PrimeScript RTase are available, as described in the table below:

Quantification of Active MiRNA: MiRNA Activity Reporters

While total miRNA quantification is thought to provide an approximation of active miRNA, recent studies show that miRNAs can be silenced by mono nucleotide addition, or bound to proteins, making them unavailable for post-transcriptional suppression of mRNAs (Chung et al., 2017). These changes in miRNA sequence or availability are not captured in amplification, sequencing or hybridization-based assays. MiRNA activity reporters provide a more accurate snapshot of the amount of active miRNA, in some cases without lysis of cells, allowing for a time resolved or in-patient assessment of miRNA activity. Fluorescence or bioluminescence based optical imaging, magnetic resonance imaging (MRI) and positron emission tomography (PET) provide more or less long-time live cell monitoring of miRNA activity (Oh and Do Won Hwang, 2013).

Luciferase and GFP Based MiRNA Reporters

MiRNA Transcription and Target Site Reporters

The application of luciferase assays in miRNA research is 2-fold. On the one hand, miRNA expression can be investigated by fusing miRNA promoter to the reporter system. On the other hand, miRNA targets can be validated using the same system, by fusing the 3′UTR of a target gene to the reporter. In luciferase based reporter assays, the enzyme luciferase converts the substrate D-luciferin into oxyluciferin, thereby emitting light ( Figure 4 ) (Haugwitz et al., 2008 Oh and Do Won Hwang, 2013). These reporters are used to monitor miRNA transcription and identify miRNA binding sites. Firefly (Fluc), Renilla (Rluc), and Gaussia luciferase (Gluc) are the most commonly used bioluminescent reporters due to their high sensitivity (Tannous et al., 2005 Haugwitz et al., 2008).

Luciferase reporter assay. A luciferase reporter gene is fused to the promoter sequence of a gene of interest, e.g., the promoter for a specific miRNA, or a target mRNA. Luciferase is transcribed when the native promoter is active, and activity of the reporter protein is detected by converting luciferin substrate to a detectable bioluminescence.

To monitor miRNA expression using a luciferase reporter, transcription of miRNAs and their precursors can be surveyed by fusing the promoter controlling specific miRNA expression to reporter genes. For example, both the 3′-end (miR-9) and the 5′-end (miR-9 * ) of the brain-specific miR-9 function biologically in brain development. Their expression was investigated by separately fusing the Fluc and Gluc genes to the upstream promoter regions of the 3′-end of miR-9 and 5′-end of miR-9 * in P19 cells. Differential expression patterns of miR-9 and miR-9 * were measured during neuronal cells differentiation (Ko et al., 2008).

As mentioned above, luciferase reporters are also utilized to verify predicted miRNA binding sites on miRNA target genes by monitoring both miRNA and target mRNA transcription. To validate miRNA targets, the 3′ UTR of the target mRNA is fused to the luciferase gene and can be probed in the presence (e.g., transfection of additional miRNAs or different growth conditions) and absence of a miRNA. In this case, miRNA binding to the UTR will decrease Luciferase production.

Dual reporter constructs allow for a simultaneous analysis of miRNAs and target mRNA. For example, expression of a Fluc and Rluc dual reporter construct was used to test the interaction between miR-138 with the 3′-UTR of its target rhoC mRNA, identifying the miRNA targeting sites in the coding region of the 3′-UTR (Jin et al., 2013). Fluc and Rluc mediated dual-reporter assays were also utilized to identify the multiple roles of miR-29b (Clément et al., 2015), and miR-529b (Moyle et al., 2017). A dual-fluorescence assay allowed for the detection of subtle changes in miRNAs and successfully identified mutations in targets sites of miR-212 in cardiac disorders (Goldoni et al., 2012). Dual reporter systems provide an efficient way to verify miRNA target sites, and gene regulation of miRNA expression. A large number of fluorescent reporters emitting at different wavelengths can be used to localize e.g., transcription sites and are useful molecular imaging tools (Wessels et al., 2010 Wang et al., 2011).

Strengths and Limitations

Luciferase-based reporters are exceedingly useful to investigate the expression of miRNAs or their target genes and generally do not require specialized equipment but are, in nature, low throughput and laborious assays. Furthermore, luciferase-based assays require the addition of luciferin, which makes them less suitable for a time resolved analysis of miRNA expression or activity.

In vivo MiRNA Activity Reporters

We recently developed a reporter gene construct that directly measures the activity on miRNAs over time and during different developmental stages. In these reporter constructs, the green fluorescence protein (GFP) gene is fused to a 3′UTR with specific miRNAs binding sites, making GFP expression responsive to changes in miRNA activity. While luciferase-based assays provide a similar reporter for miRNA activity, in contrast to luciferase expression, GFP expression can be monitored over time, allowing for a time and space resolved analysis of miRNA activity and fewer experimental steps than luciferase-based assays. This reporter was used to successfully measure cellular levels of miRNA let-7a and miR-122 in real-time (Turk et al., 2018). Here, GFP was fused to the 3′-UTR of the oncogene Ras, which encodes let-7a binding sites. GFP fluorescence showed an inverse relationship to let-7a levels ( Figure 5 ). This system allows for the direct measurement of miRNA activity in living cells in a time resolved manner. The GFP reporter system could be expanded in its applications to match the dual reporter assays described above, fusing GFP to the 3′ UTR of a potential target mRNA, while fusing the miRNA promoter to a yellow fluorescent protein (YFP) or red fluorescent protein (RFP), further expanding the toolbox of time resolved miRNA assays.

Green fluorescence protein reporter assay. A green fluorescence protein (GFP) reporter gene is fused to a 3′-UTR encoding miRNA binding sites. GFP mRNA translation is controlled by, and responsive to, changes in miRNA activity. Binding of the miRNA to the 3′-UTR of the reporter construct decreases the production of GFP and detectable fluorescence.

Strengths and Limitations

Similar to the luciferase-based assays, the GFP based assays are low throughput and time intensive, but do not require specialized equipment. Nonetheless, these assays provide a time resolved report on miRNA activity in cell lines, which is not easily accessible with alternate methods.

Molecular Beacon (MB) in vivo Imaging System

Optical reporter strategies, especially promoter studies, at times cannot differentiate whether the reduced fluorescence signals stem from deregulated gene expression or should be attributed to cellular loss. Plasmid based fluorescence reporters can also usually not be applied as a diagnostic in a living patient. To overcome these limitations, a molecular beacon (MB) in vivo imaging system was developed to trace miRNA biogenesis. The MB is a hairpin shaped oligonucleotide structure fused to a fluorescent dye at the 5′ end and a quencher at the 3′ end. In its hairpin form in the absence of miRNA, the fluorescent signal is quenched. Upon binding to the complementary sequence of a target miRNA, the quencher is displaced and a fluorescent signal emitted. MB-based emissions offer excellent tissue penetration and allow for molecular imaging to monitor miRNAs, as has been demonstrated for miR-26a and miR-206 dynamics in muscular cells (Kang et al., 2011). This general method was applied to image miR-124 expression by non-invasive magnetic resonance imaging (MRI). Magnetic nanoparticles conjugated to a fluorescent dye were attached to a double stranded oligonucleotide encoding a miR-124 binding site in one strand and a quencher on the complementary strand, effectively quenching fluorescence in the stem-loop, miRNA free form in the absence of the targets. Upon binding to the miR-124, quencher molecule is dispatched and results in enhancement of fluorescence signal which evaluates the level of miRNA expression. Moreover, magnetic nanoparticles offer in vivo cell tracking by imaging miRNA (Hwang et al., 2010 Hernandez et al., 2013). Recently, MRI has been applied to trace circulating miRNAs in serum and allowed for disease prognosis (Regev et al., 2017). Positron emission tomography (PET) imaging was used to localize specific miRNAs using radiolabeled tracer oligonucleotides complementary to the target miRNAs (Mäkilä et al., 2019).

Strengths and Limitations

Activity, localization and distribution of miRNA are disease biomarkers (Cheng et al., 2015 Cui et al., 2018), and the above mentioned methods effectively visualize miRNAs in patients as non-invasive imaging systems.

Practical Methods for Determining mRNA Levels in Alcohol-Exposed Tissues and Its Application to Experimental Pathology


We have developed a rapid and highly sensitive quantitative RT-PCR method which could also possibly be applied in a range of other tissues. This method is based on the simultaneous amplification of the mRNA of interest and an endogenous mRNA as an internal control. The amount of PCR product has been reduced by both reducing the concentration of control primers and delaying the addition of control primers. Evaluation of this protocol showed a tube-to-tube variation that was smaller than sample-to-sample variation in animal experiments. This method has been successfully applied to the routine assay for relative gene expression of low abundance mRNAs.

Watch the video: Reverse Transcription PCR (August 2022).