Exploiting extension bias in polymerase chain reaction to improve primer specificity in ensembles of nearly identical DNA templates

• Published in: Environmental microbiology 2014-05, Vol.16 (5), p.1354-1365
• Main Authors: Wright, Erik S, Yilmaz, L. Safak, Ram, Sri, Gasser, Jeremy M, Harrington, Gregory W, Noguera, Daniel R
• Format: Article
• Language: English
• Subjects: alleles; Animal, plant and microbial ecology; Archaea - genetics; Bacteria - classification; Bacteria - genetics; Base Pair Mismatch; Base Sequence; Biological and medical sciences; Deoxyribonucleic acid; DNA; DNA - chemistry; DNA Primers - chemistry; DNA-Directed DNA Polymerase - metabolism; Fundamental and applied biological sciences. Psychology; General aspects; Genes; hybridization; Microbial ecology; microbiology; Polymerase chain reaction; Polymerase Chain Reaction - methods; ribosomal RNA; RNA, Ribosomal, 16S - genetics; synergism; Templates, Genetic
• ISSN: 1462-2912; 1462-2920
• DOI: 10.1111/1462-2920.12259

We describe a semi‐empirical framework that combines thermodynamic models of primer hybridization with experimentally determined elongation biases introduced by 3′‐end mismatches for improving polymerase chain reaction (PCR)‐based sequence discrimination. The framework enables rational and automatic design of primers for optimal targeting of one or more sequences in ensembles of nearly identical DNA templates. In situations where optimal targeting is not feasible, the framework accurately predicts non‐target sequences that are difficult to distinguish with PCR alone. Based on the synergistic effects of disparate sources of PCR bias, we used our framework to robustly distinguish between two alleles that differ by a single base pair. To demonstrate the applicability to environmental microbiology, we designed primers specific to all recognized archaeal and bacterial genera in the Ribosomal Database Project, and have made these primers available online. We applied these primers experimentally to obtain genus‐specific amplification of 16S rRNA genes representing minor constituents of an environmental DNA sample. Our results demonstrate that inherent PCR biases can be reliably employed in an automatic fashion to maximize sequence discrimination and accurately identify potential cross‐amplifications. We have made our framework accessible online as a programme for designing primers targeting one group of sequences in a set with many other sequences (http://DECIPHER.cee.wisc.edu).