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      Unraveling chloroplast transcriptomes with ChloroSeq, an organelle RNA-Seq bioinformatics pipeline

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          Abstract

          Online sequence repositories are teeming with RNA sequencing (RNA-Seq) data from a wide range of eukaryotes. Although most of these data sets contain large numbers of organelle-derived reads, researchers tend to ignore these data, focusing instead on the nuclear-derived transcripts. Consequently, GenBank contains massive amounts of organelle RNA-Seq data that are just waiting to be downloaded and analyzed. Recently, a team of scientists designed an open-source bioinformatics program called ChloroSeq, which systemically analyzes an organelle transcriptome using RNA-Seq. The ChloroSeq pipeline uses RNA-Seq alignment data to deliver detailed analyses of organelle transcriptomes, which can be fed into statistical software for further analysis and for generating graphical representations of the data. In addition to providing data on expression levels via coverage statistics, ChloroSeq can examine splicing efficiency and RNA editing profiles. Ultimately, ChloroSeq provides a well-needed avenue for researchers of all stripes to start exploring organelle transcription and could be a key step toward a more thorough understanding of organelle gene expression.

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          Most cited references33

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          OrganellarGenomeDRAW—a suite of tools for generating physical maps of plastid and mitochondrial genomes and visualizing expression data sets

          Mitochondria and plastids (chloroplasts) are cell organelles of endosymbiotic origin that possess their own genetic information. Most organellar DNAs map as circular double-stranded genomes. Across the eukaryotic kingdom, organellar genomes display great size variation, ranging from ∼15 to 20 kb (the size of the mitochondrial genome in most animals) to >10 Mb (the size of the mitochondrial genome in some lineages of flowering plants). We have developed OrganellarGenomeDraw (OGDRAW), a suite of software tools that enable users to create high-quality visual representations of both circular and linear annotated genome sequences provided as GenBank files or accession numbers. Although all types of DNA sequences are accepted as input, the software has been specifically optimized to properly depict features of organellar genomes. A recent extension facilitates the plotting of quantitative gene expression data, such as transcript or protein abundance data, directly onto the genome map. OGDRAW has already become widely used and is available as a free web tool (http://ogdraw.mpimp-golm.mpg.de/). The core processing components can be downloaded as a Perl module, thus also allowing for convenient integration into custom processing pipelines.
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            Insights into the evolution of mitochondrial genome size from complete sequences of Citrullus lanatus and Cucurbita pepo (Cucurbitaceae).

            The mitochondrial genomes of seed plants are unusually large and vary in size by at least an order of magnitude. Much of this variation occurs within a single family, the Cucurbitaceae, whose genomes range from an estimated 390 to 2,900 kb in size. We sequenced the mitochondrial genomes of Citrullus lanatus (watermelon: 379,236 nt) and Cucurbita pepo (zucchini: 982,833 nt)--the two smallest characterized cucurbit mitochondrial genomes--and determined their RNA editing content. The relatively compact Citrullus mitochondrial genome actually contains more and longer genes and introns, longer segmental duplications, and more discernibly nuclear-derived DNA. The large size of the Cucurbita mitochondrial genome reflects the accumulation of unprecedented amounts of both chloroplast sequences (>113 kb) and short repeated sequences (>370 kb). A low mutation rate has been hypothesized to underlie increases in both genome size and RNA editing frequency in plant mitochondria. However, despite its much larger genome, Cucurbita has a significantly higher synonymous substitution rate (and presumably mutation rate) than Citrullus but comparable levels of RNA editing. The evolution of mutation rate, genome size, and RNA editing are apparently decoupled in Cucurbitaceae, reflecting either simple stochastic variation or governance by different factors.
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              Coordination of gene expression between organellar and nuclear genomes.

              Following the acquisition of chloroplasts and mitochondria by eukaryotic cells during endosymbiotic evolution, most of the genes in these organelles were either lost or transferred to the nucleus. Encoding organelle-destined proteins in the nucleus allows for host control of the organelle. In return, organelles send signals to the nucleus to coordinate nuclear and organellar activities. In photosynthetic eukaryotes, additional interactions exist between mitochondria and chloroplasts. Here we review recent advances in elucidating the intracellular signalling pathways that coordinate gene expression between organelles and the nucleus, with a focus on photosynthetic plants.
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                Author and article information

                Journal
                Brief Bioinform
                Brief. Bioinformatics
                bib
                Briefings in Bioinformatics
                Oxford University Press
                1467-5463
                1477-4054
                November 2017
                26 September 2016
                26 September 2016
                : 18
                : 6
                : 1012-1016
                Affiliations
                Department of Biology, University of Western Ontario, London, Ontario, Canada
                Author notes
                Corresponding author: David Roy Smith, Department of Biology, University of Western Ontario, London, Ontario N6A 5B7, Canada. Tel.: (519) 661 2111, ext; 86482; E-mail: dsmit242@ 123456uwo.ca
                Article
                bbw088
                10.1093/bib/bbw088
                5862312
                27677960
                dbf55fd0-2959-4e80-a489-2af83afa4385
                © The Author 2016. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 21 July 2016
                : 24 August 2016
                Page count
                Pages: 5
                Categories
                Software Review

                Bioinformatics & Computational biology
                chloroplast transcription,organelle transcriptomics,plastid rna,rna editing,rna-seq

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