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How to improve qPCR assay design by understanding the impact of primer mismatches?

Jo Vandesompele - Sep 8, 2013

Designing a well working and reliable qPCR assay is a lot of work. Apart from prediction of specificity, the assay should also be screened for possible secondary DNA structures that interfere with efficient amplification (see Figure 1 in D'haene et al., Methods, 2010) and for the presence of single nucleotide polymorphisms (SNPs) that impair amplification of the variant allele.

Schematic representation of the run lay-out for an example screening in a 384-well plate.pngMost researchers realize that the assay must be specific and therefore perform some kind of in silico specificity analysis, often done by performing a BLAST homology search analysis using their predesigned primer sequences, or using Primer-BLAST that combines primer design and BLAST analysis. However, it is not commonly known how many mismatches against a homologous sequence are needed in order for the PCR assay to be specific and thus not amplifying the homologous off-target sequence. In addition, many researchers are not aware of the impact a SNP may have on qPCR assay performance and thus do not screen for this. Also here, there is hardly any published information on the impact of SNPs in function of their number and location in the primer. Evaluation of the presence of known SNPs in the primer sequences can be done with short nucleotide variation BLAST.

This blog highlights an article Steve Lefever in my research group at Ghent University (Lefever et al., Clinical Chemistry, 2010). This study has carefully and systematically measured the impact of primer mismatches on qPCR assay performance. Mismatches can result from either SNPs in the primer annealing region of the target of interest or primer alignment against homologous off-target sequences.

The study clearly indicated that quantitative nucleic acid measurements are affected by the number and positions of mismatches in primer-annealing sites. The top figure shows an example with one mismatch in the forward primer and 2 mismatches in the reverse primer, resulting in an 8 cycle delay compared to the perfect match reaction. The extent of qPCR inhibition is in general negatively correlated with the distance of a mismatch from the primer’s 3' end. Assessing how qPCR reactions behave when both primers harbor mismatches should help in optimizing assay-specificity predictions. The data in Lefever et al. show that 4 mismatches in a single primer block amplification almost completely, whereas 3 mismatches in one of the primers must be combined with at least 2 mismatches in the other primer to achieve the same extent of inhibition. These results suggest that avoiding up to 3 mismatches when evaluating the specificity of a primer during the primer design process can largely prevent the generation of nonspecific assays.

Ideally, primers should be completely SNP free; however, with a mean of 1 SNP per 58 bp in the human genome, or 1 SNP per approximately 20 bp in the exome (based on NCBI's dbSNP release 137), that standard is often impossible. Given the degree of mismatch tolerable during primer design, evaluations of primers designed in silico against the most recent SNP database (including SNPs with minor-allele frequencies of <1%) will greatly increase the probability of designing reliable primer sets. Such evaluations would exclude primers harboring SNPs or mismatches in the last 5 bases at a primer’s 3' end.

The conclusions of the article are based on 10 720 qPCR reactions using more than 1000 primer-template combinations.

Topics: SNP- quality control- primer

Jo Vandesompele

Jo Vandesompele

Jo Vandesompele is co-founder and CSO of Biogazelle. He is also a professor in Functional Cancer Genomics and Applied Bioinformatics at Ghent University, Belgium. Jo obtained a Master of Science in Bioscience Engineering (1997) and a PhD in Medical Genetics (2002). He is author of more than 200 scientific articles in international journals, including some pioneering publications in the domain of qPCR based nucleic acid quantification.

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