Your Steinbrenner-guide for setup and optimisation of qPCR assays

The proper analysis of gene expression, miRNA, lncRNAs as well as the quantification of oligonucleotides requires a thoroughly established qPCR assay. This guide will show you how you achieve a reliable system and help you to understand how various factors influence the sensitivity, specificity, and robustness of the assay.

Parameters for the optimisation of a qPCR assay

Please start with a profound test assay to see if your setup needs modifications. This test should comprise:

  • No Template Control (NTC)
  • NoRT Control (noRT)
  • A dilution series of the template (5-6 step 10-fold serial dilution)
  • Several primer concentrations


  • Melting temperature
  • Amplicon length
  • Primer concentration
  • Homologous regions


  • Amount of template
  • RT Primer – Random / dT?
  • Purity of RT primer

qPCR Setup

  • SYBRGreen vs probe assay?
  • Annealing temperature and -time
  • Extension temperature and -time
  • Microtiter plates – white or transparent?
  • Reaction volume

Designing a test assay

More about ROX

Some qPCR master mixes contain an internal passive reference dye, ROX is the most common one.

Many qPCR cyclers use ROX to normalize the fluorescence signal. By comparing the ROX-signals from each sample (well) with those of the reporter – either TaqMan-probe or SYBRGreen – the software calculates a “normalized” fluorescence (Rn). The advantage of this method is that it reduces the well-to-well variances and minimizes the effects of pipetting errors.

A Tip

  • If possible, activate the ROX-option of your qPCR cycler
  • If you use a master mix with ROX, please check if your cycler requires „Low ROX“, or „High ROX“.

Assay Setup

  • Pipette a 5 step 10-fold dilution series of your cDNA (100%, 10%, 1%, 0.1%, 0.01%)
  • Design a test assay with genes of low and high expression level (reference gene/housekeeping gene). This setup will later show you how your system behaves with different cDNA input.
  • Work with min 3 replicates to minimize pipetting errors and variances.

qPCR master mix protocol

Component 25 μl PCR reaction Final concentration
2x PCR master mix 12,5 µl 1 x
Forward primer (i.e. 5 pmol/µl) variable (i.e. 2 µl) 0.1 – 0.2 µM    
Reverse primer (i.e. 5 pmol/µl) variable (i.e. 2 µl) 0.1 – 0.2 µM    
Template DNA variable 0.1 – 10 ng/reaction
Sterile distilled water adjust to 25 μl final volume

qPCR master mix cycles

Step Time Temperature
Initial denaturation 2-15 minutes1) 92° – 95°C
25 – 35 cycles 2)
Denaturation 2 – 10 seconds 92°C
Annealing 20 seconds 55° – 68°C
Extension variable, depends on

length of PCR product


1) Initial denaturation depends on template amount, for larger amounts longer denaturation is recommended
2) When working with low copy numbers of template up to 10 cycles should be added

Calculation of Efficiency

Cq-value and determination of primer efficiency

The melting curve and the Cq/Ct-values are essential parameters to evaluate a qPCR assay. It is important to know that

1) the Cq/Ct-values decrease with increasing amount of cDNA

2) given an efficiency of 100 %, each 10-fold dilution step of cDNA mathematically results in an increase of the Cq/Ct-value of 3.32 cycles.

3)  in practice an efficiency of exactely 100% will hardly be reached because many independent factors play a role: polymerase, primer design, setup, target sequence, and general PCR conditions.

4) it may happen that the calculation of the efficiency results in a score of more than 100%. This effect is most probably caused by the mathematical method used and does not reflect a problem of the assay.

Most qPCR machines automatically calculate the Cq/Ct-values. If not, please see this list of software and other tools.

How do I calculate the primer efficiency?

Start with a linear regression analysis of the dilution series. First, you plot the Cq-values against the amount of DNA and then you calculate the slope of the linear regression. In our example, it is –3,479.

Now you insert this value into the following formula:

For the example on the right, the result is:

As explained above, this result lies within a very good range. The conclusion is that this qPCR setting shows a very good performance.


It is not necessary to achieve a calculated efficiency of 100%. In real life any assay with an efficiency factor between 90% and 110% will provide results that you can rely on.

cDNA-input Mean Cq-value
100% (10 ng) 18,54
10 % (1 ng) 21,73
1 % (0.1 ng) 25,1
0.1% (0.01 ng) 28,6
0.01% (0.001 ng) 32,5

Fig 1: Calculation of efficiency via linear regression

In-Well qPCR Efficiency

Estimation of the in-well efficiency

The calculation of qPCR in-well efficiency requires a special software tool. They require qPCR raw data (fluorescence raw data), the pre-calculated Cq/Ct values cannot be used for these calculations.

A list of tools for in-well qPCR efficiency calculation is listed here.

Another aspect to evaluate a qPCR assay is the calculation of the PCR efficiency of every single reaction. This procedure allows to calculate the efficiency for different amounts of template and to identify a possible PCR inhibition.

This calculation also requires the raw data of the fluorescence detection, and cannot be performed with the Cq-values.

As shown in fig. 2, the efficiency of the PCR is very similar for all amounts of template tested. This result is excellent and shows that the chosen combination of primer, template and primaQUANT CYBR is almost perfect.

Fig 2: In-well efficiency of primaQUANT CYBR for different amounts of template

Melting Curve

A melting curve is created by measuring the fluorescence whilst continuously raising the temperature. As soon as the temperature exceeds the melting temperature of the amplicon, the amplicon strands separate. This results in a release of the intercalating dye.

A melting curve normally shows a characteristic, relatively narrow peak. The temperature below the highest point of the peak reflects the melting temperature. It mainly depends on the length and sequence of the amplicon and usually increases with its length and with higher GC-pairings. The melting curve provides essential information about the specificity of the reaction and a melting curve analysis is thus mandatory for each run and each sample!

Ideally, a melting curve of a SYBRGreen assay should only show one peak. Fig. 3 shows that our primaQUANT master mix (red curve) works quite nicely and produces only one peak in the melting curves of each dilution However, if your curves look like the blue ones, your setup urgently needs some optimisation. In the worst case you should also consider to try another master mix.

Fig 3: Melting curves of a dilution series with two different master mixes.

Did you know?

  • The melting temperature itself is not an absolute value. Although it should be stable within the same environment, it depends on the polymerase and the buffers used. It is thus quite likely that you will get a slightly different melting temperature/curve if you change the master mix. This is of no concern and should not prevent you from exchanging a given setup or master mix to a better performing one.
  • A single peak in a melting curve does not necessarily represent the desired amplicon. Verify with an agarose gel (1.5 %-2 %, or higher concentrated with small amplicons) if your qPCR product actually has the same size as your target.
  • If the melting curve shows several peaks – within a non-multiplex assay – we recommend to always analyse the length of all amplicons. So you can rule out primer-dimers and will get more information about the possible nature of the unspecific products.

Improving the specificity of your qPCR

Primer concentration

The primer concentration is a critical factor in a qPCR reaction that has always to be optimised. The lower the primer concentration, the fewer primer-dimers and other by-products will occur. In general, it is not necessary to exceed a primer concentration of 200-300 nM per reaction.

For the qPCR assay shown in fig. 3 the optimal primer concentration was 300 nM (forward and reverse).

Fig 4 The effect of different primer concentrations on the fluorescence curve and the Cq-value

Mikeska, T., & Dobrovic, A. (2009). Validation of a primer optimisation matrix to improve the performance of reverse transcription – quantitative real-time PCR assays. BMC Research Notes, 2, 112.

Amplicon length

The robustness and sensitivity as well as the specificity of a qPCR assay also depend on the amplicon length. This is especially true for Taqman/probe assays, whereas an SYBRGreen assay reacts much more stable towards different amplicon lengths as shown in fig 5a/b.

Assay type Optimal amplicon size
TaqMan / Hydrolysis probes 80 – 100 bp
Probes up to 100 bp bp
SYBRGreen / EvaGreen 120 – 200 bp

Effect of amplicon length in probe-assays

Fig 5a: Different amplicon lengths within one assay should be avoided

Mikeska, T., & Dobrovic, A. (2009). Validation of a primer optimisation matrix to improve the performance of reverse transcription – quantitative real-time PCR assays. BMC Research Notes, 2, 112.
Effect of amplicon length in SYBRGreen assay

Fig 5b: Different amplicon lengths within one assay should be avoided

Mikeska, T., & Dobrovic, A. (2009). Validation of a primer optimisation matrix to improve the performance of reverse transcription – quantitative real-time PCR assays. BMC Research Notes, 2, 112.

Annealing temperature

General rule: The higher the annealing temperature, the more specific the reaction.

Usually, the annealing temperature lies in the range of 60°C. Accordingly, the primers should have a melting temperature of  > 60°C. However, it is no problem to increase the annealing temperature, e.g. to 72°C to achieve higher specifity, provided you can then design primers with a melting temperature of more than 72°C.

Your Product Specialist

Jan Winter

Product Manager Genomics

PCR, qPCR, Magnetic Beads & CRISPR/Cas9

+49 (152) 3361 2537