Quantitative PCR is a widely applied method for measuring gene expression. It is also used for confirming sequencing data and detecting high-sensitivity targets.
Nevertheless, the accuracy of your qPCR data depends heavily on primer design. Many people overlook this aspect. But even minor design defects can lead to false results.
Learning about the best practices and what may go wrong can help a lot with the performance of your assays.
The Basics: Length, GC Content, and Specificity
Length
In qPCR, you only need simple and balanced primers. 18–25 nucleotides long is ideal. This length will provide sufficient specificity without compromising binding efficiency.
GC Content
This one should be in the range of 40–60%. This content will maintain a stable binding while preventing a very high melting temperature.
Specificity
In qPCR, specificity is non-negotiable. The primers are required to amplify the target of interest. This is preferably spanning exon-exon junctions when using cDNA to prevent amplification of genomic DNA.
You can run in silico specificity checks on relevant databases. It helps to catch off-target binding before it becomes an expensive lab problem.
The Temperature and Design of Amplicons Are Important
The melting temperatures (Tm) of all primers should be similar. They should typically be within 1 to 2 C of each other. This is necessary so that annealing is synchronized during the cycle. Most of the qPCR assays are most effective at a Tm of 58–62 C.
Another important parameter is the amplicon size. In the case of qPCR, short is an advantage: the range of 70–200 base pairs is usually recommended. Short amplicons can be amplified more easily and can be more readily subjected to rapid cycling and precise quantification. This is advantageous when dealing with partially degraded RNA samples.
The Importance of Preventing Secondary Structures and Dimers
Unwanted primer interactions have been one of the most frequent causes of poor qPCR performance. Consider things like hairpins, self-dimers, and cross-dimers. They are all capable of competing with target binding. This reduces the effectiveness and raises the background signal.
At this point, you can use an analysis software to perform a primer dimer check. You can also use it to test secondary structure formation and determine the thermodynamic stability before ordering oligos. Such tools can offer predictive information that is hard to detect. Consequently, this can save you several iterations of redesign and optimization.
Avoid These Frequent Errors That Lead to the Invalidation of qPCR Results
- Designing primers using sequence complementarity without regard to the dynamics of the reaction.
- Using primers originally developed to run on a conventional PCR. They might not be ideally matched to the sensitivity and efficiency of qPCR.
- Overlooking reaction conditions, e.g., Mg 2 + concentration, or annealing temperature. This may mask primer-related problems.
- Failure to experimentally validate primers. Even carefully designed primers must be tested for efficiency, preferably 90–110%. They should also be evaluated through melt curve analysis to verify single and specific products.
The Takeaway
An effective qPCR primer design only requires you to get the basics right, plus smart analytical software. Take the time to design, analyze, and test your primers correctly. You will establish the basis of reliable, reproducible, and meaningful qPCR data.