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A bioinformatics approach to identifying Wolbachia infections in arthropods

, 1 , 2 , 1

PeerJ

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Wolbachia, Insects, Bioinformatics, NCBI SRA, Anopheles

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      Abstract

      Wolbachia is the most widespread endosymbiont, infecting >20% of arthropod species, and capable of drastically manipulating the host’s reproductive mechanisms. Conventionally, diagnosis has relied on PCR amplification; however, PCR is not always a reliable diagnostic technique due to primer specificity, strain diversity, degree of infection and/or tissue sampled. Here, we look for evidence of Wolbachia infection across a wide array of arthropod species using a bioinformatic approach to detect the Wolbachia genes ftsZ, wsp, and the groE operon in next-generation sequencing samples available through the NCBI Sequence Read Archive. For samples showing signs of infection, we attempted to assemble entire Wolbachia genomes, and in order to better understand the relationships between hosts and symbionts, phylogenies were constructed using the assembled gene sequences. Out of the 34 species with positively identified infections, eight species of arthropod had not previously been recorded to harbor Wolbachia infection. All putative infections cluster with known representative strains belonging to supergroup A or B, which are known to only infect arthropods. This study presents an efficient bioinformatic approach for post-sequencing diagnosis and analysis of Wolbachia infection in arthropods.

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            Author and article information

            Affiliations
            [1 ]Department of Biological Sciences, State University of New York at Oswego , Oswego, NY, United States of America
            [2 ]Department of Biology, Syracuse University , Syracuse, NY, United States of America
            Contributors
            Journal
            PeerJ
            PeerJ
            peerj
            peerj
            PeerJ
            PeerJ Inc. (San Francisco, USA )
            2167-8359
            3 September 2018
            2018
            : 6
            6126470 5486 10.7717/peerj.5486
            ©2018 Pascar and Chandler

            This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

            Funding
            Funded by: National Science Foundation
            Award ID: NSF DEB-1453298
            Funded by: Indiana University
            Award ID: ABI-1458641
            This work was supported by the National Science Foundation (NSF DEB-1453298 to Christopher Chandler, and ABI-1458641 to Indiana University). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
            Categories
            Bioinformatics
            Entomology
            Evolutionary Studies
            Genomics
            Microbiology

            anopheles, ncbi sra, bioinformatics, insects, wolbachia

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