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      Chloroplot: An Online Program for the Versatile Plotting of Organelle Genomes

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          Abstract

          Understanding the complexity of genomic structures and their unique architecture is linked with the power of visualization tools used to represent these features. Such tools should be able to provide a realistic and scalable version of genomic content. Here, we present an online organelle plotting tool focused on chloroplasts, which were developed to visualize the exclusive structure of these genomes. The distinguished unique features of this program include its ability to represent the Single Short Copy (SSC) regions in reverse complement, which allows the depiction of the codon usage bias index for each gene, along with the possibility of the minor mismatches between inverted repeat (IR) regions and user-specified plotting layers. The versatile color schemes and diverse functionalities of the program are specifically designed to reflect the accurate scalable representation of the plastid genomes. We introduce a Shiny app website for easy use of the program; a more advanced application of the tool is possible by further development and modification of the downloadable source codes provided online. The software and its libraries are completely coded in R, available at https://irscope.shinyapps.io/chloroplot/.

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          Most cited references40

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          MITOS: improved de novo metazoan mitochondrial genome annotation.

          About 2000 completely sequenced mitochondrial genomes are available from the NCBI RefSeq data base together with manually curated annotations of their protein-coding genes, rRNAs, and tRNAs. This annotation information, which has accumulated over two decades, has been obtained with a diverse set of computational tools and annotation strategies. Despite all efforts of manual curation it is still plagued by misassignments of reading directions, erroneous gene names, and missing as well as false positive annotations in particular for the RNA genes. Taken together, this causes substantial problems for fully automatic pipelines that aim to use these data comprehensively for studies of animal phylogenetics and the molecular evolution of mitogenomes. The MITOS pipeline is designed to compute a consistent de novo annotation of the mitogenomic sequences. We show that the results of MITOS match RefSeq and MitoZoa in terms of annotation coverage and quality. At the same time we avoid biases, inconsistencies of nomenclature, and typos originating from manual curation strategies. The MITOS pipeline is accessible online at http://mitos.bioinf.uni-leipzig.de. Copyright © 2012 Elsevier Inc. All rights reserved.
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            GeSeq – versatile and accurate annotation of organelle genomes

            Abstract We have developed the web application GeSeq (https://chlorobox.mpimp-golm.mpg.de/geseq.html) for the rapid and accurate annotation of organellar genome sequences, in particular chloroplast genomes. In contrast to existing tools, GeSeq combines batch processing with a fully customizable reference sequence selection of organellar genome records from NCBI and/or references uploaded by the user. For the annotation of chloroplast genomes, the application additionally provides an integrated database of manually curated reference sequences. GeSeq identifies genes or other feature-encoding regions by BLAT-based homology searches and additionally, by profile HMM searches for protein and rRNA coding genes and two de novo predictors for tRNA genes. These unique features enable the user to conveniently compare the annotations of different state-of-the-art methods, thus supporting high-quality annotations. The main output of GeSeq is a GenBank file that usually requires only little curation and is instantly visualized by OGDRAW. GeSeq also offers a variety of optional additional outputs that facilitate downstream analyzes, for example comparative genomic or phylogenetic studies.
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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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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                25 September 2020
                2020
                : 11
                : 576124
                Affiliations
                [1] 1 Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki , Helsinki, Finland
                [2] 2 Finnish Museum of Natural History (Botany), University of Helsinki , Helsinki, Finland
                [3] 3 Department of Biosciences, Viikki Plant Science Centre, University of Helsinki , Helsinki, Finland
                Author notes

                Edited by: Nunzio D’Agostino, University of Naples Federico II, Italy

                Reviewed by: JianJun Jin, Columbia University, United States; Chang Liu, Chinese Academy of Medical Sciences and Peking Union Medical College, China; Gavin Conant, North Carolina State University, United States; Nicolas Dierckxsens, KU Leuven, Belgium

                *Correspondence: Ali Amiryousefi, ali.amiryousefi@ 123456helsinki.fi

                These authors have contributed equally to this work

                This article was submitted to Computational Genomics, a section of the journal Frontiers in Genetics

                Article
                10.3389/fgene.2020.576124
                7545089
                33101394
                89b8b451-778d-49ef-a8c3-50977a25c9ab
                Copyright © 2020 Zheng, Poczai, Hyvönen, Tang and Amiryousefi.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 25 June 2020
                : 28 August 2020
                Page count
                Figures: 3, Tables: 1, Equations: 0, References: 42, Pages: 8, Words: 5319
                Funding
                Funded by: Academy of Finland 10.13039/501100002341
                Funded by: European Research Council 10.13039/501100000781
                Categories
                Genetics
                Technology and Code

                Genetics
                chloroplast genome,dna barcoding,endosymbiosis,mitochondrial genome,photosynthesis,plastomics,visualization

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