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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 references 41

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions

            TopHat is a popular spliced aligner for RNA-sequence (RNA-seq) experiments. In this paper, we describe TopHat2, which incorporates many significant enhancements to TopHat. TopHat2 can align reads of various lengths produced by the latest sequencing technologies, while allowing for variable-length indels with respect to the reference genome. In addition to de novo spliced alignment, TopHat2 can align reads across fusion breaks, which can occur after genomic translocations. TopHat2 combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes. TopHat2 is available at http://ccb.jhu.edu/software/tophat.
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              RNA-Seq: a revolutionary tool for transcriptomics.

              RNA-Seq is a recently developed approach to transcriptome profiling that uses deep-sequencing technologies. Studies using this method have already altered our view of the extent and complexity of eukaryotic transcriptomes. RNA-Seq also provides a far more precise measurement of levels of transcripts and their isoforms than other methods. This article describes the RNA-Seq approach, the challenges associated with its application, and the advances made so far in characterizing several eukaryote transcriptomes.
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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
                © 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

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                Pages: 5
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