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      Nanopore sequencing improves the draft genome of the human pathogenic amoeba Naegleria fowleri

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          Abstract

          Naegleria fowleri is an environmental protist found in soil and warm freshwater sources worldwide and is known for its ability to infect humans and causing a rapid and mostly fatal primary amoebic meningoencephalitis. When contaminated water enters the nose, the facultative parasite follows the olfactory nerve and enters the brain by crossing the cribriform plate where it causes tissue damage and haemorrhagic necrosis. Although N. fowleri has been studied for several years, the mechanisms of pathogenicity are still poorly understood. Furthermore, there is a lack of knowledge on the genomic level and the current reference assembly is limited in contiguity. To improve the draft genome and to investigate pathogenicity factors, we sequenced the genome of N. fowleri using Oxford Nanopore Technology (ONT). Assembly and polishing of the long reads resulted in a high-quality draft genome whose N50 is 18 times higher than the previously published genome. The prediction of potentially secreted proteins revealed a large proportion of enzymes with a hydrolysing function, which could play an important role during the pathogenesis and account for the destructive nature of primary amoebic meningoencephalitis. The improved genome provides the basis for further investigation unravelling the biology and the pathogenic potential of N. fowleri.

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          Most cited references36

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          Rfam: an RNA family database.

          Rfam is a collection of multiple sequence alignments and covariance models representing non-coding RNA families. Rfam is available on the web in the UK at http://www.sanger.ac.uk/Software/Rfam/ and in the US at http://rfam.wustl.edu/. These websites allow the user to search a query sequence against a library of covariance models, and view multiple sequence alignments and family annotation. The database can also be downloaded in flatfile form and searched locally using the INFERNAL package (http://infernal.wustl.edu/). The first release of Rfam (1.0) contains 25 families, which annotate over 50 000 non-coding RNA genes in the taxonomic divisions of the EMBL nucleotide database.
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            OrthoVenn: a web server for genome wide comparison and annotation of orthologous clusters across multiple species

            Genome wide analysis of orthologous clusters is an important component of comparative genomics studies. Identifying the overlap among orthologous clusters can enable us to elucidate the function and evolution of proteins across multiple species. Here, we report a web platform named OrthoVenn that is useful for genome wide comparisons and visualization of orthologous clusters. OrthoVenn provides coverage of vertebrates, metazoa, protists, fungi, plants and bacteria for the comparison of orthologous clusters and also supports uploading of customized protein sequences from user-defined species. An interactive Venn diagram, summary counts, and functional summaries of the disjunction and intersection of clusters shared between species are displayed as part of the OrthoVenn result. OrthoVenn also includes in-depth views of the clusters using various sequence analysis tools. Furthermore, OrthoVenn identifies orthologous clusters of single copy genes and allows for a customized search of clusters of specific genes through key words or BLAST. OrthoVenn is an efficient and user-friendly web server freely accessible at http://probes.pw.usda.gov/OrthoVenn or http://aegilops.wheat.ucdavis.edu/OrthoVenn.
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              TEclass--a tool for automated classification of unknown eukaryotic transposable elements.

              The large number of sequenced genomes required the development of software that reconstructs the consensus sequences of transposons and other repetitive elements. However, the available tools usually focus on the accurate identification of raw repeats and provide no information about the taxonomic position of the reconstructed consensi. TEclass is a tool to classify unknown transposable elements into their four main functional categories, which reflect their mode of transposition: DNA transposons, long terminal repeats (LTRs), long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs). TEclass uses machine learning support vector machine (SVM) for classification based on oligomer frequencies. It achieves 90-97% accuracy in the classification of novel DNA and LTR repeats, and 75% for LINEs and SINEs. http://www.compgen.uni-muenster.de/teclass, stand alone program upon request.
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                Author and article information

                Contributors
                matthias.wittwer@babs.admin.ch
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                5 November 2019
                5 November 2019
                2019
                : 9
                : 16040
                Affiliations
                [1 ]ISNI 0000 0001 0726 5157, GRID grid.5734.5, Interfaculty Bioinformatics Unit and Swiss Institute of Bioinformatics, , University of Bern, ; Bern, Switzerland
                [2 ]Spiez Laboratory, Federal Office for Civil Protection, Austrasse, Spiez Switzerland
                [3 ]ISNI 0000 0001 0726 5157, GRID grid.5734.5, Graduate School for Cellular and Biomedical Sciences, , University of Bern, ; Bern, Switzerland
                Author information
                http://orcid.org/0000-0003-4354-2419
                Article
                52572
                10.1038/s41598-019-52572-0
                6831594
                31690847
                93277d41-ebcf-4b9a-a490-71fc12ff5a9a
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 July 2019
                : 12 October 2019
                Funding
                Funded by: Swiss Federal Office for Civil Protection (project number 353005702)
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                next-generation sequencing,parasite genomics
                Uncategorized
                next-generation sequencing, parasite genomics

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