How to evaluate your qPCR and RT-qPCR results 

Science Hub

In this blogpost the qPCR and RT-qPCR methods are described, their usefulness and power as well as their sensitivity and vulnerability. In addition, it is explained how qPCR evaluation  is accomplished by applying the “MIQE” guidelines and NEB´s “dots in boxes” quality scoring methods.  The Luna product portfolio from NEB has been developed in accordance with these methods. Based on this, they are best-in-class product, when compared to other commercially available qPCR products. 

The following topics are covered: 

  • Usefulness and power of qPCR and RT-qPCR 
  • Sensitivity and vulnerability of qPCR and RT-qPCR reaction 
  • The “MIQE guidelines” 
  • NEB´s “dots in boxes” quality scoring method 
  • Development of best-in-class products NEB Luna products  


Usefulness and power of qPCR and RT-qPCR  

qPCR (quantitative polymerase chain reaction) and RT-qPCR (Reverse Transcriptase-qPCR) are extremely precise and powerful methods for quantitative detection of even sparse amounts of specific target DNA and RNA, respectively. The combined speed, sensitivity, and specificity of these methods are making them today’s benchmark technologies for detecting specific nucleic acid sequences in research, diagnostic, forensic and biotechnology to name a few. Since the sample material may be of various sources e.g., blood, urine, sewage, seawater but also extracts from solid samples of body tissues, soil, wood, and others the range of applications is very widespread. 

The quantification of specific target RNA (via cDNA) or DNA sequences is accomplished by real-time measurement of fluorescence emitted during PCR replication. The fluorescence is correlated to the numbers of target RNA/DNA sequences, and the instrument is set to detect when the fluorescence signal reaches a predetermined threshold. Since the target RNA/DNA sequences are duplicated in each PCR amplification round, the number of replications needed to reach the preset detection point depends on the original number of target sequences in the sample. Thus, there is an exponential relationship between the original number of target RNA/DNA target sequences in the sample, and the number of cycles (quantification cycles) needed to reach the detection point Ct (cycle threshold). This exponential relationship is what makes the methodology extremely powerful.  

Sensitivity and vulnerability of qPCR and RT-qPCR reaction 

The power of the qPCR and RT-qPCR reactions make the techniques very sensitive but also vulnerable. Small variations in number of target RNA/DNA molecules have substantial consequences for the number of cycles measured to reach the detection point. In addition, the efficiency of the amplification process may be influenced by many factors e.g., inhibitors of the PCR reaction. 

The specificity of the reaction, meaning the detection of the target sequences rather than other sequences depends on the primers selected. This must be evaluated carefully when setting up a new method by determining e.g.: 1. Homology to other sequences in the samples analyzed, 2. Tendency of secondary structures of the amplicons and 3. The melting temperature (Tm) and tendency of primer-dimer formation of the primers.  

In the RT-qPCR reaction, the reverse transcription reaction adds a further level of risk for uncertainty, complicating the interpretation of the results. 1. RNA is extremely susceptible to degradation and must be handled carefully during storage and handling and 2. Possible DNA contamination should be excluded by incorporating a no–reverse transcription control. 

The “MIQE guidelines”  

The “Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines” are a set of protocols for conducting and reporting qPCR experiments and data, as devised by Bustin et al. in 2009. (Bustin, S.A. et al. (2009) Clin Chem. 55, 611-22 and Trombley Hall, A. et al. (2013) PLoS One 8(9):e73845).  

* The MIQE guidelines describe only qPCR and not RT-qPCR, as they are related only to the amplification of DNA and not the reverse transcriptase reaction. 

The aim of these guidelines was to simplify the review of experimental details, data analysis and reporting methods in order to increase the reliability of results, ensure the integrity of the scientific literature and promote consistency. 

By providing all relevant experimental conditions and assay characteristics in a streamlined, consistent format and experimental transparency with full disclosure of all reagents, sequences, and analysis methods, other investigators are enabled to reproduce results and reviewers can easily assess the validity of the protocols used and results obtained.  

General implementation of these guidelines has been an important requisite for the maturing of qPCR into a robust, accurate and reliable nucleic acid quantification technology.  

NEB's “dots in boxes” qPCR quality scoring method

NEB has further built on the MIQE qPCR guidelines by developing their qPCR quality scoring method named “Dot in boxes”. This method allows many targets and conditions to be compared in a single graph. The output is a dot plot, capturing the key features of a successful, high-quality qPCR experiment in a single point.  

In each qPCR experiment, triplicate reactions are set up throughout a five-log concentration range of the target DNA sequence (Figure 2: “Amplification plot” - bottom-left). Three NTC (no template control) reactions are also included, making a total of 18 reactions per condition or target. The PCR efficiency in percent is calculated (Figure 2: “Standard curve” - top-left) and plotted against ΔCq (Figure 2: “qPCR performance dot plot” - center), which is the difference between the average Cq (quantification cycle) of the NTC and the lowest input. The ΔCq parameter captures both detection of the lowest input and non-template amplification. Acceptable performance criteria are defined as an efficiency of 90-110% and a ΔCq of ≥ 3 (green box in “qPCR performance dot plot”). 

Other performance criteria are evaluated by using a 5-point Quality Score (Figure 2: “Quality score” top-right). Included factors are: 

  1. Linearity of amplification, as indicated by the R2 standard curve  
  2. Reproducibility, as indicated by the consistency of triplicate Cq values for each input concentration  
  3. Fluorescence consistency, as indicated by similar endpoint fluorescence (RFUmax) 
  4. Curve steepness  
  5. Sigmoid curve shape 

The Quality Score is represented by the size and fill of the plotted dot, where a solid dot within the box demonstrates an experiment that passes all performance criteria. An example of this analysis is displayed to the right.

Development of best-in-class products NEB Luna products   

NEB established the “dots in boxes” analysis method in parallel with development of their Luna products for qPCR and RT-qPCR. The aim was to establish a quick and efficient evaluation of product performances. 

Therefore, all Luna products have been developed with focus on the “Dots in boxes” scoring method, by rigorous testing to ensure acquiring the best-in-class products in all critical parameters and for all targets. As a result, the Luna product portfolio offers exceptional performance in terms of efficiency, linearity, specificity, sensitivity, accuracy, and reproducibility across a wide range of targets, including templates of varied length, GC-content, and abundance. 

A comprehensive market-wide evaluation of commercially available qPCR products displayed below demonstrates that NEB’s Luna Universal qPCR Master Mix outperformed all other reagents tested (Figure 3A & 3B).   


Figure on the left:

Figure 3A (left). Evaluation of commercially available qPCR products demonstrates robustness and specificity of Luna. Panels of qPCR/RT-qPCR targets varying in abundance, length, and %GC were used to evaluate the performance of a variety of commercial reagents. The bar graph summarizes % of targets that met acceptable performance criteria of 90 – 110% Efficiency, ΔCq ≥ 3 and Quality Score > 3 (indicated by green box on dot plot and line on Quality Score key) from individual experiments, evaluated as described above. Each target panel was run by 2 users and according to manufacturer's protocols. 

Figure 3B (right). A set of 24 targets demonstrates the most sensitive quantitation from the Luna Cell Ready One-Step RT-qPCR Kit compared to the commercially available cell lysis One-Step RT-qPCR kits. Approximately 2,500 A549 cells were lysed in 50 µl Luna Cell Ready lysis reactions (NEB #E3032) using standard reaction conditions or with commercially available kits from Bio-Rad (SingleShot SYBR Green One-Step Kit, #172-5095), Qiagen (FastLane Cell SYBR Green Kit, #216213) and Thermo Fisher (Cells-to-CT 1-Step PowerSYBR Green Kit, A25600) following manufacturer-recommended protocols. Two biological replicates were processed for each kit. 24 genes of interest were then quantitated using the One-Step RT-qPCR module from each kit with 1 μl of cell lysate as input (equal to 50 cells in a 20 µl RT-qPCR reaction), with duplicate reactions for each biological sample. Average Cqs are shown for NEB (closed orange circles), BioRad (open squares), Qiagen (open triangles) and Thermo Fisher (crosses). To standardize results, 12% of total fluorescence was set as a threshold. The Luna Cell Ready One-Step RT-qPCR kit shows the earliest Cq for 23/24 genes across variable expression levels, with an average of 2.3 Cq faster than Bio-Rad, 3.8 Cq faster than Qiagen and 3.6 Cq faster than Thermo Fisher.


Want to know more? Reach out to Pia!

Pia Ojala

Product Specialist

+358 20 7410 274

Pia Ojala