Why bother with PCR primer efficiencies?
Every time you receive a new set of primers, especially when using SYBR Green chemistry during quantitative polymerase chain reaction (qPCR), you should always run a standard curve to calculate the efficiency of your PCR primers.
The reason we bother calculating PCR primer efficiencies is to be able to correctly analyse the results. For the calculation of gene expression, such as the delta-delta Ct method, it is assumed that the PCR primer efficiencies are comparable for the gene of interest and for the housekeeping gene. Therefore, dissimilar PCR primer efficiencies within your experiment can impact your final result.
A video tutorial on qPCR primer efficiency calculation can be found in our Mastering qPCR course.
>>Use code 20QPCR to get 20% off<<
What is the correct PCR primer efficiency value?
Obviously, a perfect primer set will have a primer efficiency of 100%. In other words, for every PCR cycle, the number of copies of the PCR product will double in size during the logarithmic phase of the PCR reaction.
To get a 100% primer efficiency for all of your primer sets is highly unlikely. Therefore, it is recommended that all the primer sets used in your experiment lie between 90 – 110% efficient. If so, they are deemed comparable.
How to perform a standard curve
So you have designed and received your new primers. Now what? Well, the first thing you will need is a template to use for standard curve generation. Ideally, this should be from the same source as what will be used during your experiment. So, if you have generated complementary DNA (cDNA) from RNA extracted from a cell culture experiment, for example, then use one of these samples as your template.
To create a standard curve, it is recommended to start with the undiluted cDNA sample as your first point. From this, you need to create a serial dilution series. A 1:10 dilution is commonly used to create a standard curve with at least 5-points. If you can include more points in your standard curve, then this would be better. So long as the standard curve covers the Ct values of your experimental samples then this is fine.
Here is an example of a 1:10 serial dilution standard curve containing 5 points:
Perform a qPCR reaction using your standard curve containing the recommended reagents and concentrations for the qPCR master mix of your choice, as a starting point. Make sure to perform each sample in duplicate at the very least, or even better, triplicate. Also, don’t forget to include no template controls (NTCs), i.e. PCR-grade water instead of the sample, on your plate to identify any contamination.
How to calculate primer efficiencies
Some qPCR machines will be able to calculate this for you, but I prefer to export my raw results and calculate the PCR primer efficiencies manually.
Here is how to calculate a primer efficiency using Microsoft Excel. The Excel formula used in each section is highlighted in grey.
1. Calculate your average Ct values from each of your replicates/triplicates
The first step is to average the technical replicate Ct values.
The function in Excel is found below, where the Ct1 and Ct2 values represent the cells for each technical replicate.
The starting quantity is based on your dilutions. So, for example, I like to call the first value ‘1‘ since this is the stock, undiluted cDNA. Then do 1:10 dilutions of this value.
Then, the log value of these should be determined. Simply use the LOG function in Excel to do this.
To quickly calculate the slope of the line, use the SLOPE function in Excel. Specifically, it is the slope between the log values just created and the average Ct values.
=SLOPE(Average Ct value range, log quantity range)
Alternatively, you can plot the log values against the average Ct values as a scatter plot. To do this, first, create a scatter plot between the average Ct values and the log values. Then select ‘Add Chart Element > Trendline > More Trendline Options …’. From here, select the ‘Display Equation on chart’ option to view the regression equation. The slope value will be the value at the start (just before the x). In this example, the slope is -3.359.
Primer efficiency values are presented as a percentage. To calculate primer efficiency values, use the following equation.
=(10^(-1/The Slope Value)-1)*100
This will give you a primer efficiency score as a percentage. Hopefully, this is between 90 – 110%. By using the above dataset, the efficiency comes to 98%.
If your standard curve and primer efficiency is not within the desired range, don’t worry. There are a few things you can do to improve your PCR primers efficiencies, such as adjusting the primer concentrations and the annealing temperature of your reaction. If you are really struggling after that, then I suggest designing new primers.
PCR primer efficiency calculator
If you prefer, I have created a PCR primer efficiency online calculator. To use this, simply enter the slope of the line, as determined above, and the calculator will return the primer efficiency value and the amplification factor (E).
Free PCR primer efficiency Microsoft Excel template
Are you still struggling to calculate your PCR primer efficiencies? Well, I have made an Excel worksheet to hopefully help you out.
All you have to do is to fill in the Ct values from your replicates and the dilution factor used when making the standard curve, e.g. 10, and the sheet will (hopefully) work out the rest for you. This will also work out the slope, R2 value and the PCR primer efficiency value as a percentage.
Click here to download the template.