Abstract
The major malaria mosquito, Anopheles gambiae s.l, is one of the most studied organisms in medical research and also one of the most genetically diverse. When designing polymerase chain reaction (PCR) or hybridisation-based molecular assays, reliable primer and probe design is crucial. However, single nucleotide polymorphisms (SNPs) in primer binding sites can prevent primer binding, leading to null alleles, or bind suboptimally, leading to preferential amplification of specific alleles. Given the extreme genetic diversity of An. gambiae, researchers need to consider this genetic variation when designing primers and probes to avoid amplification problems. In this note, we present a python package, AgamPrimer, which exploits the AG1000G dataset and allows users to rapidly design primers in An. gambiae, whilst summarising genetic variation in the primer binding sites and visualising the position of primer pairs. AgamPrimer allows the design of both genomic DNA and cDNA primers and hybridisation probes. By coupling this python package with Google Colaboratory, AgamPrimer is an open and accessible platform for primer and probe design, hosted in the cloud for free. AgamPrimer is available here https://github.com/sanjaynagi/AgamPrimer and we hope it will be a useful resource for the community to design probe and primer sets that can be reliably deployed across the An. gambiae species range.
Competing Interest Statement
The authors have declared no competing interest.
