Molecular identification and phylogenetic analysis of Anopheles mosquitoes from malaria endemic-areas of Limpopo Province, South Africa

Abstract Background The transmission of malaria is primarily driven by female Anopheles mosquitoes. In Limpopo Province, South Africa, malaria control is closely linked to vector surveillance programmes, where accurate characterisation of mosquitoes plays a key role in guiding intervention measures. However, mosquito identification is based on visible morphological traits, which is error-prone, specifically in damaged specimens, cryptic species, or limited taxonomic expertise. This study therefore aimed to investigate the use of 18 S rDNA-based molecular identification as a complementary approach to morphological methods for identifying mosquitoes collected from malaria-affected villages in Limpopo Province. Methodology Forty-two (42) mosquito samples used in this study were morphologically identified using standard taxonomic keys. Molecular characterization was conducted through amplifying and sequencing a fragment of the 18 S ribosomal DNA (rDNA) gene. The resulting sequences were analysed through BLAST searches, multiple sequence alignment, and maximum likelihood phylogenetic analysis was used to assess species identity and genetic relationships. Results Four (4) Anopheles species types, including An. gambiae , An. funestus , An. maculipalpis , and An. squamosus , were identified by BLAST. Molecular identification assigned 27 of 42 specimens to species different from their morphological identification. This difference likely reflects the limitations of morphological identification as well as the conserved nature of the 18 S rDNA marker, which may reduce species-level resolution. Six specimen sequences were excluded from the phylogenetic analysis due to poor sequence quality. Maximum likelihood phylogenetic reconstruction using the 36 mosquito samples, six other mosquito reference sequences from GenBank, and one outgroup sequence showed that all our specimens clustered around related sequences of their respective species, supported by strong bootstrap values, highlighting consistent genetic grouping. Overall, intraspecific genetic divergence based on the 18 S rDNA marker was low. Conclusion This pilot study demonstrates that molecular identification using the 18 S rDNA marker can effectively support traditional morphological identification of Anopheles mosquitoes in Limpopo Province. Although 18 S rDNA reliably confirmed genus-level identification and general species grouping, its conserved nature limited its ability to resolve closely related species with certainty. Therefore, combining morphological methods with additional variable molecular markers would increase the precision of mosquito identification, strengthen mosquito vector monitoring, and support programmes targeting malaria transmission in South Africa.