What is qPCR Analysis? And How Does a qPCR Machine Work?

The ability to detect specific genetic material has been a cornerstone of progress in numerous fields, from genome engineering to contaminant detection, and not least in diagnostic testing. With the development of the quantitative polymerase chain reaction (qPCR), also sometimes called quantitative real time polymerase chain reaction, these capabilities were extended from traditional PCR, offering improved sensitivity and specificity of detection and importantly, accurate quantification of target sequences.

In this article, we will consider how qPCR works, experimental requirements, data analysis and applications of the technique.

What is qPCR?

qPCR is a technique for the selective amplification and quantitative detection of regions of DNA or complimentary DNA (cDNA). Oligonucleotide primers flanking a region of interest are used to amplify the sequence utilizing a DNA polymerase enzyme.¹ Repeated cycling of the amplification process leads to exponential expansion of the number of copies of the target region which is tracked either using an intercalating dye or sequence-specific probe whose fluorescence is then detected in the qPCR machine and plotted on an output graph.

What’s the difference between qPCR and RT-qPCR?

RT-qPCR stands for quantitative reverse transcription polymerase chain reaction, the “RT” not to be mistaken for “real time”.² Unlike qPCR that uses a DNA template, the starting material for RT-qPCR is RNA.³ Therefore, protocols incorporate a reverse transcription step to convert the RNA to cDNA before the normal qPCR amplification process commences. This may be done all in one reaction tube (one-step) or sequentially with reverse transcription taking place in a separate reaction to the qPCR amplification (two-step) (Figure 1).

Figure 1: Diagram demonstrating the difference between one-step and two-step RT-qPCR.

How does a qPCR machine work?

Like a standard PCR machine, a qPCR machine consists of a heated block and lid that facilitates the rapid transition of samples between temperatures to enable amplification of a DNA or cDNA template (Figure 2). However, a qPCR machine also incorporates a fluorescent source and fluorometer to excite the fluorophores and detect the fluorescent output generated during cycles of qPCR amplification (Figure 3). The machine typically has or is linked to a computer that records the fluorimeter output and uses software to interpret the experimental results based on user-defined information such as control wells and standards.

Figure 2: Illustration of how the amplification process works in PCR and qPCR. qPCR protocols typically incorporate around 30–40 amplification cycles, with copy numbers doubling each time.

Figure 3: Fluorescent signal generation by dye-based and probe-based qPCR assays.

Example of a qPCR protocol

A qPCR reaction contains:

• DNA or cDNA – provides the template for amplification
• Sequence-specific primers – binds to and forms the basis of new copies of the target region
• DNA polymerase enzyme – incorporates complimentary bases into the new amplicons
• Deoxynucleoside triphosphates (dNTP’s) – nucleotide building blocks for the new DNA strands
• Probe or dye – enables detection of target amplification
• Buffers – optimize reaction conditions

In many cases, a premixed solution is used that contains the polymerase, dNTPs, buffers and (if applicable) dye.

1) A master mix containing all the reaction components except the template is gently mixed and aliquoted into reaction tubes (often a 96-well plate). The template (or water in the case of a no template control – see “qPCR controls”), is then carefully added to the relevant wells and the plate or tubes sealed. It is advisable to run samples in duplicate or triplicate, if possible, to improve result reliability.

Passive reference dyes (such as ROX) are included in many premade master mixes. They provide an internal reference to which the reporter dye signal can be normalized during data analysis, correcting for variations in concentration or volume. These may be omitted where quantitation is not required.

2) Information regarding the well contents and location, dye or probe chemistry being used, any standards or controls included and cycling conditions are provided to the computer/control unit by the user.

3) The template DNA or cDNA is heated, causing denaturation and producing single stranded DNA (ssDNA) (Figure 2). Bound intercalating dyes (if present) also dissociate, returning to ground state.

4) Sequence-specific primers bind to their target sequence (annealing) and complimentary bases are added to the sequence by DNA polymerase to produce a complimentary copy (primer extension). During this process, the fluorophores in the assay absorb light at one wavelength and re-emit it at a longer, lower energy wavelength if it is not quenched. The wavelength of excitation and emission will depend on the fluorophore(s) used.

- In the case of dye-based protocols, the intercalating dye will bind the newly formed dsDNA, emitting light when it does so.

- There are a number of different probe-based chemistries, however, they generally work on a similar principle. Some form of fluorescence quenching ensures that fluorescence only occurs when target sequences are present, resulting in light emission during amplification.

5) The fluorescence produced is then detected by the fluorimeter and recorded by the computer. With a probe-based assay, the fluorescent signal is therefore proportional to the number of ssDNA fragments being amplified that are complimentary to the probe, and with dye-based assays proportional to the number of double stranded (dsDNA) copies.

6) Once amplification is complete, melt curve analysis may be performed on intercalating dye-based assay products which assesses the dissociation characteristics of the dsDNA products. With intercalating dyes, fluorescence will reduce as the dsDNA strands dissociate. The temperature at which 50% of DNA is denatured is known as the melting temperature and will be impacted by the sequences of the qPCR products. Samples are incrementally heated, typically over a range from 65 °C to 95 °C, and the effect on fluorescence recorded. Melt curve analysis can help to differentiate off-target amplification. This approach cannot be used for probe-based assays, where fluorescence is produced during the amplification process. The use of post-amplification probes may, however, facilitate amplicon differentiation using melt curve analysis and is even able to detect single base variations.^{4, 5}

How to design primers for qPCR

Many of the same rules for designing PCR primers also apply to qPCR primers, such as:

• Primers are designed in pairs (one on the forward strand and one on the reverse) that specifically flank the target region
• Primer sequences must be chosen to target the unique sequence of interest, avoiding off-target binding to similar sequences
• Primers should have similar melting temperatures (ideally 60–64 °C) to enable efficient amplification. This is affected by the proportions of guanine (G) or cytosine (C) compared to adenine (A) or thymine (T), with higher GC contents increasing melting temperatures. Adjusting primer lengths can help to address mismatches in primer pairs
• Annealing temperatures of the two primers should be similar and no more than 5 °C below the primer melting temperature to avoid non-specific amplification. Again, this is impacted by the primer length and composition
• Aim, where possible, to use G’s or C’s at primer ends as they form stronger (triple) bonds than A’s or T’s (double), improving primer binding
• Primer sequences should, if possible, avoid regions likely to dimerize or form secondary structures. This can be assessed using freely available primer design tools
• Primers should be approximately 15–30 bp in length

However, there are some differences:

• Amplicons are typically smaller (80–150 bp) than for standard PCR
• It’s imperative that there is no off-target amplification as this will confound quantification, particularly for dye-based assays

Dye-based qPCR (SYBR Green qPCR) vs probes

Dyes

In dye-based qPCR, an intercalating dye is used that displays weak fluorescence in its unbound form, increasing to a strong fluorescent signal when bound to dsDNA (Figure 3). SYBR® Green⁶ is one of the most commonly used dsDNA binding dyes.^{7, 8} Fluorescence is directly proportional to the amount of dsDNA present, enabling the original template amount to be calculated.

Intercalating dyes are not sequence-specific so do not need to be tailored to individual assays, simplifying assay design. This also makes them cheaper. However, it means that they will fluoresce in response to the amplification of off-target or non-specific products as well as the desired target, reducing specificity. The facility for melt curve analysis can help here, especially when evaluating new assays. Dyes cannot be used for multiplexed reactions as, unlike probes, the signals cannot be differentiated. Therefore, multiple reaction wells with separate primer sets must be set up to evaluate different targets.

Probes

There are a number of different types of fluorescent probe and primer chemistries available for qPCR, but most rely on some form of covalently attached fluorescence quencher molecule that is released in the presence of a specific target sequence.

Unlike intercalating dyes, probes are sequence-specific and so must be designed for each assay, increasing assay setup complexity and cost. This does however mean they also improve assay specificity. Different probes can emit fluorescence of differing wavelengths by using different fluorophores, so they can be multiplexed provided compatible probes are selected and the machine possess the required filters. While initial assay development time may be longer and more complex, multiplexing can reduce subsequent set up time and reagent use by running multiple tests in a single well.

Common fluorescent probes include:

Hydrolysis probes⁹ – Also called TaqMan or 5' nuclease, hydrolysis probes include a sequence-specific fluorescently labeled oligonucleotide probe with a fluorescent reporter at one end and a quencher at the other. When intact, the quencher suppresses the florescent signal. The 5' to 3' exonuclease activity of certain polymerases cleaves the probe during target amplification, so the fluorescent reporter is no longer near the quencher, resulting in fluorescent signal (Figure 4).

This is one of the most commonly used probe types.

Figure 4: Diagram showing how hydrolysis probes function. The fluorescent reporter (R) is shown in green and the quencher (Q) in purple, target DNA in grey, amplified sequence in yellow (heavy line weight) and primers in yellow (fine line).

Molecular beacons¹⁰ – Like hydrolysis probes, molecular beacons are sequence-specific fluorescently labeled oligonucleotide probes. However, they have complimentary bases (five or six) near their ends that form a hairpin structure, bringing the quencher close to the reporter and quenching the signal. When the probe binds its target sequence, the stem denatures, moving the reporter and quencher apart, resulting in a signal (Figure 5). Due to their structure, molecular beacon probes are harder to design than hydrolysis probes.

Figure 5: Diagram showing how molecular beacons function. The fluorescent reporter (R) is shown in green and the quencher (Q) in purple, target DNA in grey and primers in yellow.

Dual hybridization probes¹¹ – Also called LightCycler or FRET probes, this technique uses a pair of probes designed to bind adjacent sequences, labeled with a donor and acceptor dye pair that exhibit fluorescence resonance energy transfer (FRET). When the probes bind their target sequence, the donor and acceptor dyes come into close proximity, FRET occurs and the acceptor emits fluorescence (Figure 6).

Figure 6: Diagram showing how dual hybridization probes function. The donor fluorophore (R1) is shown in pink and the acceptor fluorophore (R2) in green, target DNA in grey and primers in yellow.

Minor groove binder (MGB) probes¹² – Also called Eclipse probes, they have a fluorophore and quencher on either end like hydrolysis probes. However, they also have a MGB near the quencher. In the absence of the target, MGB probes coil randomly, bringing the fluorophore and quencher into close proximity. When the probe binds its target, aided by the MGB, the probe linearizes, allowing the fluorophore to emit light (Figure 7).

Figure 7: Diagram showing how MGB probes function. The fluorescent reporter (R) is shown in green and the quencher (Q) in purple, the MGB in orange, target DNA in grey and primers in yellow.

Amplifluor assays¹³ – Here, the “probe” is known as a UniPrimer. The UniPrimer has a fluorescence reporter on one end and quencher on the other, forming a hairpin loop in its unbound state that quenches the signal. In the first round of amplification, one of the target-specific primer pair (called the Z primer) anneals and extends to create a product. In the second round, the other primer of the pair attaches to the newly formed product and extends to create the second strand. This then serves as a template for the UniPrimer which binds the Z primer sequence. Extension causes the UniPrimer to unfold, releasing the fluorophore from quenching (Figure 8).

Figure 8: Diagram showing how Amplifluor assays work. The fluorescent reporter (R) is shown in green and the quencher (Q) in purple, target DNA in grey, amplified sequence in dark yellow and primers in yellow with the Z primer, in black, indicated.

Scorpion probes¹⁴ – Here, one of the primers also serves as the probe. It has a fluorescent reporter and quencher on opposing ends, forming a stem loop structure that quenches the signal when not bound to its target. A section of sequence complimentary to a region downstream of the primer binding site and within the amplicon is incorporated within the loop. During amplification, this region binds to its target, causing the loop to break open, liberating the fluorescent reporter from the quencher’s influence (Figure 9).

Figure 9: Diagram showing how Scorpion probes function. The fluorescent reporter (R) is shown in green and the quencher (Q) in purple, target DNA in grey, amplified sequence in yellow (heavy weight line), PCR blocker in orange and primers in yellow (fine line).

Light-upon-extension (LUX) probes¹⁵ – Again, one of the primers with LUX-based assays also acts as the probe, however, unlike Scorpions, no quencher is present. The LUX primer has a reporter on one end and adopts a hairpin structure that itself quenches the fluorophore signal. When the primer binds its target, it becomes linearized, unquenching the reporter and producing a fluorescent signal (Figure 10).

Figure 10: Diagram showing how LUX probes function. The fluorescent reporter (R) is shown in green, target DNA in grey, amplified sequence in dark yellow and primers in pale yellow.

QZyme probes¹⁶ – A substrate is incorporated in QZyme assays that contains a reporter and quencher maintained in close proximity. One of the primers incorporates the antisense sequence of a catalytic DNA region able to cleave the substrate. Once amplified, this region then cleaves the substrate, separating the quencher from the fluorophore and producing a fluorescent signal (Figure 11).

Figure 11: Diagram showing how QZyme probes function. The fluorescent reporter (R) is shown in green and the quencher (Q) in purple, target DNA in grey, amplified sequence in dark yellow and primers in pale yellow with the complimentary catalytic region in pink and yellow.

Locked nucleic acid (LocNA) probes¹⁷ – LocNAs are modified nucleotides that contain a methylene bridge, restricting the structure’s flexibility (Figure 12). Incorporating LocNAs within probe sequences can improve specificity and facilitate the use of shorter qPCR probes, helpful in challenging sequences.

Figure 12: A locked nucleic acid monomer. Modified bases contain a methylene bridge bond (red) between the 2′ oxygen and the 4′ carbon of the pentose ring.

qPCR controls

It is important to include appropriate controls^{18, 19} within the experimental set-ups to enable interpretation of the results and the identification of potential issues. These include a no template control (NTC), negative control and positive control.

The NTC should contain all the reagents of the other wells but use PCR grade water in place of a sample. These wells should show no amplification, otherwise it is indicative of DNA/RNA contamination of one or more reagents, or the equipment used to set up the experiment.

Negative controls contain DNA/RNA that lacks the region targeted by the primers and probe. Ideally this would be the same as the sample in every other way, so a strain/individual of the same species lacking the gene of interest (naturally or through genetic manipulation) would be optimal. As the name suggests, the negative control should show no amplification. Depending on how good the assay is, it may be possible to get non-target amplification which should be differentiable from the melt curve data in dye-based assays. If this occurs in assays to be used routinely, selecting an alternative target sequence may be desirable.

The positive control²⁰ should contain the target sequence and be known to amplify successfully (in the case of an established assay) as this is the signal to which unknowns will be compared. If the assay is in development, having confirmatory data that this is a positive sample from other techniques (such as conventional PCR, next-generation sequencing (NGS) or culture) can help to confirm the results obtained. If a positive control fails to amplify, then results from that run should be considered void as it indicates a problem with the assay.

Where assays aim to measure relative quantitation rather than absolute quantitation, as is the case in some transcriptional studies, an endogenous control²¹ is required that should be measured in all wells. For this, a gene is chosen that should be transcribed at a constant, abundant level across all samples in all conditions, such as a housekeeping gene. This is then used to normalize data on transcription of the genes of interest to correct for factors like variation in the amount of starting material and reaction efficiency.

qPCR analysis – Ct value, qPCR melt curve and qPCR standard curve

There are a number of terms that are important to know in understanding qPCR output.

Baseline: The background fluorescence signal, normally determined in the early cycles prior to detectable increases in fluorescence.

Rn (normalized reporter): The fluorescence emission intensity of the fluorescent reporter divided by the fluorescence emission intensity of the passive reference dye.

Rn-: The Rn value of an un-reacted sample, obtained from early cycles or an NTC.

Rn+: The Rn value of a well containing all reaction components, including the template.

ΔRn: The magnitude of the signal generated for a well by the qPCR experiment.

                                                    ΔRn = (Rn+) – (Rn-)

Threshold: The threshold (often seen as a horizontal line on an amplification plot) is the average standard deviation of Rn for the early cycles, multiplied by an adjustable factor often determined by the machine’s software. It represents a statistically significant point above the calculated baseline and should be set in the region associated with an exponential increase in the amount of PCR product.

Ct (threshold cycle): This is the cycle number at which the fluorescence generated by a well crosses the threshold when sufficient amplicons have accumulated. This is also sometimes called the quantification cycle (Cq), crossing point (Cp) or take-off point (TOP).

Many software packages will set the necessary analysis parameters for you; however, it is helpful to understand their meaning, how adjustments may affect results and learn to identify potential problems.

The output obtained from a qPCR experiment will depend in part on the type of analysis that was run, but for all an amplification plot should be obtained. This shows the magnitude of the fluorescent signal (ΔRn) generated on the y-axis plotted over the course of amplification cycles on the x-axis for each well (Figure 13). Where replicates of the same sample are included, they should be as close together as possible. Variations between replicates indicates likely experimental error and repetition may be required. Equally, it is important that no amplification is observed in the NTC or negative control and a good positive signal is seen in the positive control well(s). The earlier the cycle number at which the amplification line crosses the threshold, the higher the target copy number in that well.

Figure 13: Example qPCR amplification plot, this example shows a set of standards run in duplicate. The white line indicates the threshold.

If the aim of the experiment is to determine if a target is present or not and quantification is not necessary, then standards are not included. Many qPCR packages include software that will automatically call such results positive or negative.

When quantification is required, there are two main options, absolute quantitation or relative quantitation. For absolute quantitation,²² standards are included to enable determination of the target copy number in an unknown sample. Standards use DNA of the same species used for the unknowns (often the same as the positive control) and should cover a wide range of concentrations across the full capabilities of the assay (its dynamic range), often in 10-fold serial dilutions, e.g., 1 x 10¹, 1 x 10², 1 x 10³, 1 x 10⁴, 1 x 10⁵, 1 x 10⁶ and 1 x 10⁷ DNA genome copies per well. Quantification of samples that fall outside of this range will be less reliable and it is therefore advisable to adjust unknown sample dilutions to bring them into this range and repeat the test. From this, unknown sample quantities can be extrapolated. The number of DNA copies per µl can be calculated for standards provided the user knows the concentration of the stock DNA sample being used to make the standards and the size of the genome in base pairs. Once this has been determined, appropriate dilutions can be made.

The log of the starting quantity (SQ) is plotted against the Ct value for each of the standard wells and a line of best fit drawn through the data points (Figure 14). The slope indicates the efficiency (E) of the assay and should be 100% (i.e., for each cycle the amount of product doubles).

                                                              E = -1+10^(-1/slope)

Assays should aim for an efficiency between 90 and 110% which corresponds to a slope of -3.58 to -3.10. The R² value is the coefficient of correlation obtained for the standard curve, indicating how good one value is at predicting the other and should be as close to 1 as possible, at least > 0.99.

Figure 14: Example of a qPCR standard curve.

For relative quantitation, normalization known as ΔΔCt is used. Here, the Ct values for each well for the housekeeping gene(s) selected are compared to the Ct values of the gene(s) of interest. These normalized values are then compared between controls and unknown samples. With this method, no standards are required, reducing reagent use. However, greater work is required during development, and it is important to note that this method assumes the amplification efficiencies for all targets are close to 100% and within 5% of each other.

As mentioned previously, melt curve analysis can be used to check the identity of qPCR products, particularly helpful for dye-based amplification. Positive control wells (in a well-designed assay) should give a nice clean peak indicating the melting temperature of the qPCR product (Figure 15). If peaks other than these are observed for some wells, it indicates the presence of non-target products and can mean that quantification in these wells is unreliable. Equally, the absence of the target peak would indicate the absence of the target amplicon, suggesting the well is negative.

Figure 15: Example of qPCR melt curve analysis. Dissociation temperatures are indicated on the x-axis. The change in fluorescence is indicated on the right y-axis (dashed line); at low temperatures the DNA is in double strand form, and it has 100% fluorescence, reducing as the temperature increases and the DNA dissociates. The left y-axis shows Rn, with peaks corresponding to the melting temperatures of the qPCR product(s).

qPCR vs PCR

For both qPCR and PCR, the amplification process occurs in pretty much the same way. However, there are notable differences.

• With traditional PCR, sometimes also called end-point PCR, the products are evaluated at the end of the amplification process, typically by agarose gel electrophoresis. With qPCR, measurements are taken at the end of each amplification cycle using fluorescent reporters. Thus, the actual amplification process itself is tracked rather than just the final product.
• The inclusion of standards of known target copy number enables the copy number of the unknown sample to be determined in qPCR which is not possible with PCR. qPCR may therefore be preferable to PCR where quantification is required.
• The limits of detection for qPCR are typically below those achievable by agarose gel electrophoresis (qPCR is more sensitive than PCR) so it may be desirable to use qPCR where target copy numbers may be low.
• The inclusion of probes in some qPCR methods can make the technique more specific than PCR.
• Amplicons in qPCR are generally smaller than those for PCR (80–150 bp compared to 200–1000 bp or more).
• Unlike PCR, the products of which are often used in downstream experiments such as genetic engineering or sequencing, qPCR products are rarely used for any further purpose.

qPCR vs dPCR

Digital PCR (dPCR)²³ amplifies target regions of DNA or cDNA in much the same way as qPCR, using primers and a probe. However, it differs from qPCR in the way the sample and reactions are handled and how the target is measured. The reaction mix is partitioned into many wells prior to amplification so that each acts as a separate reaction, with each well containing one or no copies of the target. The method relies on the assumption that sample partitioning will follow a Poisson distribution. Following amplification, wells are scored as positive (fluorescent), or negative (not fluorescent) and absolute quantitation is then calculated across all wells that originated from the same initial sample (Figure 16).

As wells are scored positive or negative, the amplification process itself is not tracked like qPCR, but instead fluorescence is measured at the end of amplification. Also in contrast to qPCR, dPCR doesn’t incorporate standards as quantification is absolute, saving time and money and removing the reliance on calibration curves. Applications of dPCR include NGS library quantification, pathogen detection and gene transcription studies, and the technique has been shown to have high sensitivity and accuracy. Rare event detection²⁴ in clinical studies is one area in particular where dPCR has found favor over qPCR thanks to its superior sensitivity.  

Figure 16: Workflow for a dPCR experiment and result interpretation.

What are the purposes of qPCR testing?

qPCR has found numerous applications across many fields of the life sciences including diagnostics, genomics, environmental and food analysis. Let’s consider some of the common uses.

• Transcriptional studies – While qPCR uses DNA or cDNA as its template, the incorporation of RT means that qPCR is an incredibly useful quantitative tool in studying gene transcription.²⁵ This can tell researchers about the genes that are turned on or off in health or disease,²⁶ indicate if a treatment or the administration of certain substances has an impact on an organism at the transcriptional level, identify differences across a population or indicate the knock-on impacts of genetic manipulation. Where multiplexing is used, many transcripts can be analyzed in one reaction.
• Diagnostics – qPCR has a well-established place in both infectious disease diagnostics of humans, animals and plants and in the detection of genetic markers, such as mutations. In infectious disease,¹⁸ such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and streptococcal infections,²⁷ specific, conserved regions of the pathogen are targeted. Where there is considerable population variation, it is important to target regions that show low mutation rates and that are present in all or most strains to avoid false negatives. The use of multiple targets within the same organism, which can be multiplexed, can aid the reduction of false negatives. Quantitative data can be helpful in estimating the pathogenic load, potentially informing treatment or management decisions, and if followed over time can sometimes indicate what stage of infection the patient is at (increasing or decreasing titers). qPCR can even be used on environmental samples, such as wastewater, to help epidemiologists monitor and predict the spread of disease. For congenital diseases, such as Huntington’s disease,²⁸ qPCR can be used to determine if an individual has genetic marker(s) associated with the disease or disease-associated risk factors. This has applications in individuals and in prenatal and preimplantation testing.²⁹ This may be a mutation such a single nucleotide polymorphism (SNP), deletion or insertion, including duplications and changes in the number of microsatellite repeats. This type of genotyping may also have purposes aside from genetic disease diagnostics including applications in selective breeding. Genetic markers may also be detected that can indicate how likely a patient is to respond to certain drugs or therapies, informing treatment options. In cancer diagnosis, qPCR can be used to look for the altered gene transcriptional patterns that are markers of neoplastic change.³⁰
• NGS library quantification – NGS is now a commonly used tool in diagnostics, epidemiology, fundamental research, microbiome studies and environmental analysis to name but a few. However, for successful sequencing, the libraries prepared from samples must be quantified to ensure an optimal amount is loaded onto the sequencing platform.³¹ The use of primers designed to the adapter sequences that flank NGS fragments allows scientists to determine what they have in their sample independent of the sample’s sequence or chosen fragment size and make this calculation accordingly.
• Contaminant detection/authenticity determination – qPCR can be used for the detection of contaminants that have genetic sequences, be that a bacterium, virus, parasite or even another animal species. This is particularly pertinent in food safety settings and in environmental analysis. The determination of authenticity and detection of food fraud may also employ the same principle in determining the species or subspecies of genomes within a sample, as seen in the case of the 2013 horsemeat scandal.

References

1. Ishino S, Ishino Y. DNA polymerases as useful reagents for biotechnology – the history of developmental research in the field. Front. Microbiol. 2014;5:465. doi:10.3389/fmicb.2014.00465

2. Adams G. A beginner’s guide to RT-PCR, qPCR and RT-qPCR. Biochem. 2020;42(3):48-53. doi:10.1042/BIO20200034

3. Udvardi MK, Czechowski T, Scheible WR. Eleven golden rules of quantitative RT-PCR. Plant Cell. 2008;20(7):1736-1737. doi:10.1105/tpc.108.061143

4. Liu Z, Bingga G, Zhang C, et al. Application of duplex fluorescence melting curve analysis (FMCA) to identify canine parvovirus type 2 variants. Front. Microbiol. 2019;10:419. doi:10.3389/fmicb.2019.00419

5. Huang Q, Liu Z, Liao Y, Chen X, Zhang Y, Li Q. Multiplex fluorescence melting curve analysis for mutation detection with dual-labeled, self-quenched probes. PLoS One. 2011;6(4):e19206. doi:10.1371/journal.pone.0019206

6. Karsai A, Müller S, Platz S, Hauser MT. Evaluation of a homemade SYBR® Green I reaction mixture for real-time PCR quantification of gene expression. Biotechniques. 2002;32(4):790-796. doi:10.2144/02324st05

7. Jansson L, Koliana M, Sidstedt M, Hedman J. Blending DNA binding dyes to improve detection in real-time PCR. Biotechnol Rep (Amst). 2017;14:34-37. doi:10.1016/j.btre.2017.02.002

8. Marmiroli N, Maestri E. Chapter 6 - Polymerase chain reaction (PCR). In: Picó Y, ed. Food Toxicants Analysis. Elsevier; 2007:147-187. doi:10.1016/B978-044452843-8/50007-9

9. Nagy A, Vitásková E, Černíková L, et al. Evaluation of TaqMan qPCR system integrating two identically labelled hydrolysis probes in single assay. Sci Rep. 2017;7(1):41392. doi:10.1038/srep41392

10. Wang K, Tang Z, Yang CJ, et al. Molecular engineering of DNA: Molecular beacons. Angew Chem Int Ed Engl. 2009;48(5):856-870. doi:10.1002/anie.200800370

11. Didenko VV. DNA probes using fluorescence resonance energy transfer (FRET): Designs and applications. Biotechniques. 2001;31(5):1106-1121. doi:10.2144/01315rv02

12. Kutyavin IV, Afonina IA, Mills A, et al. 3′-Minor groove binder-DNA probes increase sequence specificity at PCR extension temperatures. Nucleic Acids Res. 2000;28(2):655-661. doi:10.1093/nar/28.2.655

13. Giancola S, McKhann HI, Bérard A, et al. Utilization of the three high-throughput SNP genotyping methods, the GOOD assay, Amplifluor and TaqMan, in diploid and polyploid plants. Theor Appl Genet. 2006;112(6):1115-1124. doi:10.1007/s00122-006-0213-6

14. Thelwell N, Millington S, Solinas A, Booth J, Brown T. Mode of action and application of Scorpion primers to mutation detection. Nucleic Acids Res. 2000;28(19):3752-3761. doi: 10.1093/nar/28.19.3752

15. Kalvatchev ZN, Tsekov ID, Slavov SN, Draganov PI. Effective light-upon-extension real-time PCR primer systems for rapid detection of human viruses. Lab. Med. 2010;41(3):150-155. doi:10.1309/LMLY7BG3D1OJNKHO

16. Ruijter JM, Lorenz P, Tuomi JM, Hecker M, van den Hoff MJB. Fluorescent-increase kinetics of different fluorescent reporters used for qPCR depend on monitoring chemistry, targeted sequence, type of DNA input and PCR efficiency. Microchim Acta. 2014;181(13):1689-1696. doi:10.1007/s00604-013-1155-8

17. Tolstrup N, Nielsen PS, Kolberg JG, Frankel AM, Vissing H, Kauppinen S. OligoDesign: optimal design of LNA (locked nucleic acid) oligonucleotide capture probes for gene expression profiling. Nucleic Acids Res. 2003;31(13):3758-3762. doi:10.1093/nar/gkg580

18. Kralik P, Ricchi M. A basic guide to real time PCR in microbial diagnostics: Definitions, parameters, and everything. Front. Microbiol. 2017;8:108. doi:10.3389/fmicb.2017.00108

19. Taylor SC, Nadeau K, Abbasi M, Lachance C, Nguyen M, Fenrich J. The ultimate qPCR experiment: Producing publication quality, reproducible data the first time. Trends Biotechnol. 2019;37(7):761-774. doi:10.1016/j.tibtech.2018.12.002

20. Lion T. Current recommendations for positive controls in RT-PCR assays. Leukemia. 2001;15(7):1033-1037. doi:10.1038/sj.leu.2402133

21. Gomes AÉI, Stuchi LP, Siqueira NMG, et al. Selection and validation of reference genes for gene expression studies in Klebsiella pneumoniae using reverse transcription quantitative real-time PCR. Sci Rep. 2018;8(1):9001. doi:10.1038/s41598-018-27420-2

22. Brankatschk R, Bodenhausen N, Zeyer J, Bürgmann H. Simple absolute quantification method correcting for quantitative PCR efficiency variations for microbial community samples. Appl Environ Microbiol. 2012;78(12):4481-4489. doi:10.1128/AEM.07878-11

23. Mao X, Liu C, Tong H, Chen Y, Liu K. Principles of digital PCR and its applications in current obstetrical and gynecological diseases. Am J Transl Res. 2019;11(12):7209-7222. PMCID:PMC6943456

24. Taylor SC, Laperriere G, Germain H. Droplet digital PCR versus qPCR for gene expression analysis with low abundant targets: from variable nonsense to publication quality data. Sci Rep. 2017;7(1):2409. doi:10.1038/s41598-017-02217-x

25. DeCoste NJ, Gadkar VJ, Filion M. Relative and absolute quantitative real-time PCR-based quantifications of hcnC and phlD gene transcripts in natural soil spiked with Pseudomonas sp. strain LBUM300. Appl. Environ.l Microbiol. 2011;77(1):41-47. doi:10.1128/AEM.01387-10

26. Sanders R, Mason DJ, Foy CA, Huggett JF. Considerations for accurate gene expression measurement by reverse transcription quantitative PCR when analysing clinical samples. Anal Bioanal Chem. 2014;406(26):6471-6483. doi:10.1007/s00216-014-7857-x

27. Webb K, Barker C, Harrison T, et al. Detection of Streptococcus equi subspecies equi using a triplex qPCR assay. Vet. 2013;195(3):300-304. doi:10.1016/j.tvjl.2012.07.007

28. Mahjoubi F, Montazeri M, Zare-Kahrizi S, Nafisi S. Employing real time PCR for the diagnosis of Huntington disease. Zahedan J Res Med Sci. 2013; 15(7): 26-30. Corpus ID:33493

29. Traeger-Synodinos J. Real-time PCR for prenatal and preimplantation genetic diagnosis of monogenic diseases. Mol Aspects Med. 2006;27(2-3):176-191. doi:10.1016/j.mam.2005.12.004

30. Andergassen U, Zebisch M, Kölbl AC, et al. Real-time qPCR-based detection of circulating tumor cells from blood samples of adjuvant breast cancer patients: A preliminary study. Breast Care (Basel). 2016;11(3):194-198. doi:10.1159/000447041

31. Robin JD, Ludlow AT, LaRanger R, Wright WE, Shay JW. Comparison of DNA quantification methods for next generation sequencing. Sci Rep. 2016;6(1):24067. doi:10.1038/srep24067