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      Genome skimming is a low-cost and robust strategy to assemble complete mitochondrial genomes from ethanol preserved specimens in biodiversity studies

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          Abstract

          Global loss of biodiversity is an ongoing process that concerns both local and global authorities. Studies of biodiversity mainly involve traditional methods using morphological characters and molecular protocols. However, conventional methods are a time consuming and resource demanding task. The development of high-throughput sequencing (HTS) techniques has reshaped the way we explore biodiversity and opened a path to new questions and novel empirical approaches. With the emergence of HTS, sequencing the complete mitochondrial genome became more accessible, and the number of genome sequences published has increased exponentially during the last decades. Despite the current state of knowledge about the potential of mitogenomics in phylogenetics, this is still a relatively under-explored area for a multitude of taxonomic groups, especially for those without commercial relevance, non-models organisms and with preserved DNA. Here we take the first step to assemble and annotate the genomes from HTS data using a new protocol of genome skimming which will offer an opportunity to extend the field of mitogenomics to under-studied organisms. We extracted genomic DNA from specimens preserved in ethanol. We used Nextera XT DNA to prepare indexed paired-end libraries since it is a powerful tool for working with diverse samples, requiring a low amount of input DNA. We sequenced the samples in two different Illumina platform (MiSeq or NextSeq 550). We trimmed raw reads, filtered and had their quality tested accordingly. We performed the assembly using a baiting and iterative mapping strategy, and the annotated the putative mitochondrion through a semi-automatic procedure. We applied the contiguity index to access the completeness of each new mitogenome. Our results reveal the efficiency of the proposed method to recover the whole mitogenomes of preserved DNA from non-model organisms even if there are gene rearrangement in the specimens. Our findings suggest the potential of combining the adequate platform and library to the genome skimming as an innovative approach, which opens a new range of possibilities of its use to obtain molecular data from organisms with different levels of preservation.

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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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            Applications of next generation sequencing in molecular ecology of non-model organisms.

            As most biologists are probably aware, technological advances in molecular biology during the last few years have opened up possibilities to rapidly generate large-scale sequencing data from non-model organisms at a reasonable cost. In an era when virtually any study organism can 'go genomic', it is worthwhile to review how this may impact molecular ecology. The first studies to put the next generation sequencing (NGS) to the test in ecologically well-characterized species without previous genome information were published in 2007 and the beginning of 2008. Since then several studies have followed in their footsteps, and a large number are undoubtedly under way. This review focuses on how NGS has been, and can be, applied to ecological, population genetic and conservation genetic studies of non-model species, in which there is no (or very limited) genomic resources. Our aim is to draw attention to the various possibilities that are opening up using the new technologies, but we also highlight some of the pitfalls and drawbacks with these methods. We will try to provide a snapshot of the current state of the art for this rapidly advancing and expanding field of research and give some likely directions for future developments.
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              GenBank

              GenBank® is a comprehensive database that contains publicly available nucleotide sequences for more than 300 000 organisms named at the genus level or lower, obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and accession numbers are assigned by GenBank® staff upon receipt. Daily data exchange with the European Molecular Biology Laboratory Nucleotide Sequence Database in Europe and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through the National Center for Biotechnology Information (NCBI) Entrez retrieval system, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI Homepage: www.ncbi.nlm.nih.gov.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                13 September 2019
                2019
                : 7
                : e7543
                Affiliations
                [1 ]Department of Zoology, Institute of Biosciences, University of São Paulo , São Paulo, São Paulo, Brazil
                [2 ]Department of Bioinformatics and Genomics / College of Computing and Informatics, University of North Carolina at Charlotte , Charlotte, NC, United States of America
                Article
                7543
                10.7717/peerj.7543
                6746217
                31565556
                5d937b02-4fab-460f-a6b7-9e6ded07bc07
                ©2019 Trevisan et al.

                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
                : 14 January 2019
                : 24 July 2019
                Funding
                Funded by: Fundação de Amparo à Pesquisa do Estado de São Paulo
                Funded by: FAPESP
                Award ID: #2013/04585-3
                Award ID: #2016/20792-7
                Award ID: #2017/11063-4
                Award ID: #2018/03534-0
                This work was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo, FAPESP grants #2013/04585-3, #2016/20792-7, #2017/11063-4 and #2018/03534-0. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Biodiversity
                Evolutionary Studies
                Parasitology
                Zoology
                Histology

                mitochondrial genome,automated assembly,automated annotation,poorly preserved samples,high-coverage genome,diptera,cestoda

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