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      Gene expression atlas for the food security crop cassava

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          Summary

          • Cassava ( Manihot esculenta) feeds c. 800 million people world‐wide. Although this crop displays high productivity under drought and poor soil conditions, it is susceptible to disease, postharvest deterioration and the roots contain low nutritional content.

          • Here, we provide molecular identities for 11 cassava tissue/organ types through RNA‐sequencing and develop an open access, web‐based interface for further interrogation of the data.

          • Through this dataset, we consider the physiology of cassava. Specifically, we focus on identification of the transcriptional signatures that define the massive, underground storage roots used as a food source and the favored target tissue for transgene integration and genome editing, friable embryogenic callus ( FEC). Further, we identify promoters able to drive strong expression in multiple tissue/organs.

          • The information gained from this study is of value for both conventional and biotechnological improvement programs.

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          Most cited references35

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            Transcript assembly and abundance estimation from RNA-Seq reveals thousands of new transcripts and switching among isoforms

            High-throughput mRNA sequencing (RNA-Seq) holds the promise of simultaneous transcript discovery and abundance estimation 1-3 . We introduce an algorithm for transcript assembly coupled with a statistical model for RNA-Seq experiments that produces estimates of abundances. Our algorithms are implemented in an open source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed more than 430 million paired 75bp RNA-Seq reads from a mouse myoblast cell line representing a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Analysis of transcript expression over the time series revealed complete switches in the dominant transcription start site (TSS) or splice-isoform in 330 genes, along with more subtle shifts in a further 1,304 genes. These dynamics suggest substantial regulatory flexibility and complexity in this well-studied model of muscle development.
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              TopHat: discovering splice junctions with RNA-Seq

              Motivation: A new protocol for sequencing the messenger RNA in a cell, known as RNA-Seq, generates millions of short sequence fragments in a single run. These fragments, or ‘reads’, can be used to measure levels of gene expression and to identify novel splice variants of genes. However, current software for aligning RNA-Seq data to a genome relies on known splice junctions and cannot identify novel ones. TopHat is an efficient read-mapping algorithm designed to align reads from an RNA-Seq experiment to a reference genome without relying on known splice sites. Results: We mapped the RNA-Seq reads from a recent mammalian RNA-Seq experiment and recovered more than 72% of the splice junctions reported by the annotation-based software from that study, along with nearly 20 000 previously unreported junctions. The TopHat pipeline is much faster than previous systems, mapping nearly 2.2 million reads per CPU hour, which is sufficient to process an entire RNA-Seq experiment in less than a day on a standard desktop computer. We describe several challenges unique to ab initio splice site discovery from RNA-Seq reads that will require further algorithm development. Availability: TopHat is free, open-source software available from http://tophat.cbcb.umd.edu Contact: cole@cs.umd.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                rbart@danforthcenter.org
                Journal
                New Phytol
                New Phytol
                10.1111/(ISSN)1469-8137
                NPH
                The New Phytologist
                John Wiley and Sons Inc. (Hoboken )
                0028-646X
                1469-8137
                24 January 2017
                March 2017
                : 213
                : 4 ( doiID: 10.1111/nph.2017.213.issue-4 )
                : 1632-1641
                Affiliations
                [ 1 ] Donald Danforth Plant Science Center 975 North Warson Road St Louis MO 63132 USA
                [ 2 ] Department of Genetics, Cell Biology & Development and Center for Genome Engineering University of Minnesota Minneapolis MN 55455 USA
                Author notes
                [*] [* ] Author for correspondence:

                Rebecca S. Bart

                Tel: +1 314 587 1696

                Email: rbart@ 123456danforthcenter.org

                Article
                NPH14443 2016-23189
                10.1111/nph.14443
                5516207
                28116755
                bd04867c-0b50-423a-9048-f3f374f11e28
                © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 07 November 2016
                : 18 December 2016
                Page count
                Figures: 5, Tables: 0, Pages: 10, Words: 6387
                Funding
                Funded by: Bill and Melinda Gates Foundation
                Funded by: NCI Cancer Center Support
                Award ID: #P30 CA91842
                Funded by: Siteman Cancer Center
                Funded by: ICTS/CTSA
                Award ID: #UL1 TR000448
                Funded by: National Center for Research Resources (NCRR)
                Funded by: National Institutes of Health (NIH)
                Funded by: NIH Roadmap for Medical Research
                Categories
                Rapid Report
                Research
                Rapid Reports
                Custom metadata
                2.0
                nph14443
                March 2017
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.1.4 mode:remove_FC converted:19.07.2017

                Plant science & Botany
                biotechnology,cassava (manihot esculenta),food security,friable embryogenic callus,gene expression,organized embryogenic structures,rna sequencing

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