Identification and characterization of microsatellite markers for population genetic studies of Panstrongylus megistus (Burmeister, 1835) (Triatominae: Reduviidae)

BackgroundPanstrongylus megistus is the most important vector of Chagas disease in Brazil. Studies show that the principal factor hindering the control of triatomines is reinfestation of houses previously treated with insecticides. Studies at the microgeographic level are therefore necessary to better understand these events. However, an efficient molecular marker is not yet available for carrying out such analyses in this species. The aim of the present study was to identify and characterize microsatellite loci for future population genetic studies of P. megistus.Methods This study work consisted of five stages: (i) sequencing of genomic DNA; (ii) assembly and selection of contigs containing microsatellites; (iii) validation of amplification and evaluation of polymorphic loci; (iv) standardization of the polymorphic loci; and (v) verification of cross-amplification with other triatomine species.ResultsSequencing of males and females generated 7,908,463 contigs with a total length of 2,043,422,613 bp. A total of 2,043,690 regions with microsatellites in 1,441,091 contigs were obtained, with mononucleotide repeats being the most abundant class. From a panel of 96 loci it was possible to visualize polymorphisms in 64.55% of the loci. Of the 20 loci genotyped, the number of alleles varied from two to nine with an average of 4.9. Cross-amplification with other species of triatomines was observed in 13 of the loci.ConclusionsDue to the high number of alleles encountered, polymorphism and the capacity to amplify from geographically distant populations, the microsatellites described here show promise for utilization in population genetic studies of P. megistus.

Automated summary

This study identified and characterized microsatellite loci for future population genetic studies of P. megistus, showing high polymorphism and the potential for amplification across different geographic populations.