PCR-CTPP design based on Particle Swarm Optimization with Fuzzy Adaptive Strategy

PCR-CTPP (Polymerase chain reaction with confronting two-pair primers) is a time- and cost-effective SNP genotyping method. However, the design of feasible PCR-CTPP primer sets is still challenging. In this study, we propose a PSO (particle swarm optimization) with fuzzy adaptive strategy, named FAPSO, to design feasible PCR-CTPP primer sets. Two hundred and eighty-eight SNPs which exclude the deletion/insertion polymorphism (DIP) and multi-nucleotide polymorphism (MNP) in SLC6A4 gene were tested in silicon by the proposed method. The results shown the proposed method provides more feasible PCR-CTPP primers than a GA (genetic algorithm)-based and a native PSO-based method. In conclusion, the FAPSO-based method is useful to assist the biologists and researchers to design feasible PCR-CTPP primer sets.