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      Sequence-based identification of Anopheles species in eastern Ethiopia

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          The recent finding of a typically non-African Anopheles species in eastern Ethiopia emphasizes the need for detailed species identification and characterization for effective malaria vector surveillance. Molecular approaches increase the accuracy and interoperability of vector surveillance data. To develop effective molecular assays for Anopheles identification, it is important to evaluate different genetic loci for the ability to characterize species and population level variation. Here the utility of the internal transcribed spacer 2 (ITS2) and cytochrome oxidase I (COI) loci for detection of Anopheles species from understudied regions of eastern Ethiopia was investigated.


          Adult mosquitoes were collected from the Harewe locality (east) and Meki (east central) Ethiopia. PCR and Sanger sequencing were performed for portions of the ITS2 and COI loci. Both NCBI’s Basic Local Alignment Search tool (BLAST) and phylogenetic analysis using a maximum-likelihood approach were performed to identify species of Anopheles specimens.


          Two species from the east Ethiopian collection, Anopheles arabiensis and Anopheles pretoriensis were identified. Analyses of ITS2 locus resulted in delineation of both species. In contrast, analysis of COI locus could not be used to delineate An. arabiensis from other taxa in Anopheles gambiae complex, but could distinguish An. pretoriensis sequences from sister taxa.


          The lack of clarity from COI sequence analysis highlights potential challenges of species identification within species complexes. These results provide supporting data for the development of molecular assays for delineation of Anopheles in east Ethiopia.

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          The online version of this article (10.1186/s12936-019-2768-0) contains supplementary material, which is available to authorized users.

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          Most cited references 19

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          A cocktail polymerase chain reaction assay to identify members of the Anopheles funestus (Diptera: Culicidae) group.

          Anopheles funestus Giles is a major malaria vector in Africa belonging to a group of species with morphologically similar characteristics. Morphological identification of members of the A. funestus group is difficult because of overlap of distinguishing characteristics in adult or immature stages as well as the necessity to rear isofemale lines to examine larval and egg characters. A rapid rDNA polymerase chain reaction (PCR) method has been developed to accurately identify five members of the A. funestus group. This PCR is based on species-specific primers in the ITS2 region on the rDNA to identify A. funestus (approximately 505bp), Anopheles vaneedeni Gillies and Coetzee (approximately 587bp), Anopheles rivulorum Leeson (approximately 411bp), Anopheles leesoni Evans (approximately 146bp), and Anopheles parensis Gillies (approximately 252bp).
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            Mosquito genomics. Extensive introgression in a malaria vector species complex revealed by phylogenomics.

            Introgressive hybridization is now recognized as a widespread phenomenon, but its role in evolution remains contested. Here, we use newly available reference genome assemblies to investigate phylogenetic relationships and introgression in a medically important group of Afrotropical mosquito sibling species. We have identified the correct species branching order to resolve a contentious phylogeny and show that lineages leading to the principal vectors of human malaria were among the first to split. Pervasive autosomal introgression between these malaria vectors means that only a small fraction of the genome, mainly on the X chromosome, has not crossed species boundaries. Our results suggest that traits enhancing vectorial capacity may be gained through interspecific gene flow, including between nonsister species.
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              Is Open Access

              Unexpected diversity of Anopheles species in Eastern Zambia: implications for evaluating vector behavior and interventions using molecular tools

              The understanding of malaria vector species in association with their bionomic traits is vital for targeting malaria interventions and measuring effectiveness. Many entomological studies rely on morphological identification of mosquitoes, limiting recognition to visually distinct species/species groups. Anopheles species assignments based on ribosomal DNA ITS2 and mitochondrial DNA COI were compared to morphological identifications from Luangwa and Nyimba districts in Zambia. The comparison of morphological and molecular identifications determined that interpretations of species compositions, insecticide resistance assays, host preference studies, trap efficacy, and Plasmodium infections were incorrect when using morphological identification alone. Morphological identifications recognized eight Anopheles species while 18 distinct sequence groups or species were identified from molecular analyses. Of these 18, seven could not be identified through comparison to published sequences. Twelve of 18 molecularly identified species (including unidentifiable species and species not thought to be vectors) were found by PCR to carry Plasmodium sporozoites - compared to four of eight morphological species. Up to 15% of morphologically identified Anopheles funestus mosquitoes in insecticide resistance tests were found to be other species molecularly. The comprehension of primary and secondary malaria vectors and bionomic characteristics that impact malaria transmission and intervention effectiveness are fundamental in achieving malaria elimination.

                Author and article information

                Malar J
                Malar. J
                Malaria Journal
                BioMed Central (London )
                16 April 2019
                16 April 2019
                : 18
                [1 ]ISNI 0000 0001 2111 2894, GRID grid.252890.4, Department of Biology, , Baylor University, ; Waco, TX USA
                [2 ]GRID grid.449426.9, Department of Biology, , Jigjiga University, ; Jigjiga, Ethiopia
                [3 ]ISNI 0000 0000 8598 2218, GRID grid.266859.6, Department of Bioinformatics and Genomics, , University of North Carolina at Charlotte, ; Charlotte, NC USA
                © The Author(s) 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Funded by: FundRef http://dx.doi.org/10.13039/100011070, Research Opportunities Initiative, University of North Carolina;
                Funded by: UNC Charlotte Multicultural Postdoctoral Fellowship from Academic Affairs
                Funded by: FundRef http://dx.doi.org/10.13039/100007492, Baylor University;
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                © The Author(s) 2019


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