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      Candidate pathogenicity islands in the genome of ‘ Candidatus Rickettsiella isopodorum’, an intracellular bacterium infecting terrestrial isopod crustaceans

      research-article
      1 , 2 , 1 ,
      PeerJ
      PeerJ Inc.
      Rickettsiella, Genomic islands, Trachelipus rathkei, mcf2

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          Abstract

          The bacterial genus Rickettsiellabelongs to the order Legionellales in the Gammaproteobacteria, and consists of several described species and pathotypes, most of which are considered to be intracellular pathogens infecting arthropods. Two members of this genus, R. grylliand R. isopodorum, are known to infect terrestrial isopod crustaceans. In this study, we assembled a draft genomic sequence for R. isopodorum, and performed a comparative genomic analysis with R. grylli. We found evidence for several candidate genomic island regions in R. isopodorum, none of which appear in the previously available R. grylli genome sequence .Furthermore, one of these genomic island candidates in R. isopodorum contained a gene that encodes a cytotoxin partially homologous to those found in Photorhabdus luminescensand Xenorhabdus nematophilus (Enterobacteriaceae), suggesting that horizontal gene transfer may have played a role in the evolution of pathogenicity in Rickettsiella. These results lay the groundwork for future studies on the mechanisms underlying pathogenesis in R. isopodorum, and this system may provide a good model for studying the evolution of host-microbe interactions in nature.

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          Most cited references43

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          Reconstructing mitochondrial genomes directly from genomic next-generation sequencing reads—a baiting and iterative mapping approach

          We present an in silico approach for the reconstruction of complete mitochondrial genomes of non-model organisms directly from next-generation sequencing (NGS) data—mitochondrial baiting and iterative mapping (MITObim). The method is straightforward even if only (i) distantly related mitochondrial genomes or (ii) mitochondrial barcode sequences are available as starting-reference sequences or seeds, respectively. We demonstrate the efficiency of the approach in case studies using real NGS data sets of the two monogenean ectoparasites species Gyrodactylus thymalli and Gyrodactylus derjavinoides including their respective teleost hosts European grayling (Thymallus thymallus) and Rainbow trout (Oncorhynchus mykiss). MITObim appeared superior to existing tools in terms of accuracy, runtime and memory requirements and fully automatically recovered mitochondrial genomes exceeding 99.5% accuracy from total genomic DNA derived NGS data sets in <24 h using a standard desktop computer. The approach overcomes the limitations of traditional strategies for obtaining mitochondrial genomes for species with little or no mitochondrial sequence information at hand and represents a fast and highly efficient in silico alternative to laborious conventional strategies relying on initial long-range PCR. We furthermore demonstrate the applicability of MITObim for metagenomic/pooled data sets using simulated data. MITObim is an easy to use tool even for biologists with modest bioinformatics experience. The software is made available as open source pipeline under the MIT license at https://github.com/chrishah/MITObim.
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            Toward an online repository of Standard Operating Procedures (SOPs) for (meta)genomic annotation.

            The methodologies used to generate genome and metagenome annotations are diverse and vary between groups and laboratories. Descriptions of the annotation process are helpful in interpreting genome annotation data. Some groups have produced Standard Operating Procedures (SOPs) that describe the annotation process, but standards are lacking for structure and content of these descriptions. In addition, there is no central repository to store and disseminate procedures and protocols for genome annotation. We highlight the importance of SOPs for genome annotation and endorse an online repository of SOPs.
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              REAPR: a universal tool for genome assembly evaluation

              Methods to reliably assess the accuracy of genome sequence data are lacking. Currently completeness is only described qualitatively and mis-assemblies are overlooked. Here we present REAPR, a tool that precisely identifies errors in genome assemblies without the need for a reference sequence. We have validated REAPR on complete genomes or de novo assemblies from bacteria, malaria and Caenorhabditis elegans, and demonstrate that 86% and 82% of the human and mouse reference genomes are error-free, respectively. When applied to an ongoing genome project, REAPR provides corrected assembly statistics allowing the quantitative comparison of multiple assemblies. REAPR is available at http://www.sanger.ac.uk/resources/software/reapr/.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                21 December 2016
                2016
                : 4
                : e2806
                Affiliations
                [1 ]Department of Biological Sciences, State University of New York at Oswego , Oswego, NY, United States
                [2 ]Department of Biological Sciences, State University of New York at Buffalo , Buffalo, NY, United States
                Article
                2806
                10.7717/peerj.2806
                5181103
                61d14435-004e-4da7-8caf-1d612b241dbc
                ©2016 Wang 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.

                History
                : 5 August 2016
                : 20 November 2016
                Funding
                Funded by: Rice Creek Associates
                Funded by: SUNY Oswego Scholarly & Creative Activities Committee
                Funded by: NSF
                Award ID: DEB-1453298
                This work was supported by a Rice Creek Associates Small Grant to CHC, a SUNY Oswego Scholarly and Creative Activities Committee grant to YW, and NSF DEB-1453298 to CHC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Evolutionary Studies
                Genomics
                Microbiology

                rickettsiella,genomic islands,trachelipus rathkei,mcf2
                rickettsiella, genomic islands, trachelipus rathkei, mcf2

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