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      Studying bacterial transcriptomes using RNA-seq

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      Current Opinion in Microbiology
      Current Biology

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          Abstract

          Genome-wide studies of bacterial gene expression are shifting from microarray technology to second generation sequencing platforms. RNA-seq has a number of advantages over hybridization-based techniques, such as annotation-independent detection of transcription, improved sensitivity and increased dynamic range. Early studies have uncovered a wealth of novel coding sequences and non-coding RNA, and are revealing a transcriptional landscape that increasingly mirrors that of eukaryotes. Already basic RNA-seq protocols have been improved and adapted to looking at particular aspects of RNA biology, often with an emphasis on non-coding RNAs, and further refinements to current techniques will improve our understanding of gene expression, and genome content, in the future.

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          Most cited references34

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          Fast algorithms for large-scale genome alignment and comparison.

          We describe a suffix-tree algorithm that can align the entire genome sequences of eukaryotic and prokaryotic organisms with minimal use of computer time and memory. The new system, MUMmer 2, runs three times faster while using one-third as much memory as the original MUMmer system. It has been used successfully to align the entire human and mouse genomes to each other, and to align numerous smaller eukaryotic and prokaryotic genomes. A new module permits the alignment of multiple DNA sequence fragments, which has proven valuable in the comparison of incomplete genome sequences. We also describe a method to align more distantly related genomes by detecting protein sequence homology. This extension to MUMmer aligns two genomes after translating the sequence in all six reading frames, extracts all matching protein sequences and then clusters together matches. This method has been applied to both incomplete and complete genome sequences in order to detect regions of conserved synteny, in which multiple proteins from one organism are found in the same order and orientation in another. The system code is being made freely available by the authors.
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            SSAHA: a fast search method for large DNA databases.

            We describe an algorithm, SSAHA (Sequence Search and Alignment by Hashing Algorithm), for performing fast searches on databases containing multiple gigabases of DNA. Sequences in the database are preprocessed by breaking them into consecutive k-tuples of k contiguous bases and then using a hash table to store the position of each occurrence of each k-tuple. Searching for a query sequence in the database is done by obtaining from the hash table the "hits" for each k-tuple in the query sequence and then performing a sort on the results. We discuss the effect of the tuple length k on the search speed, memory usage, and sensitivity of the algorithm and present the results of computational experiments which show that SSAHA can be three to four orders of magnitude faster than BLAST or FASTA, while requiring less memory than suffix tree methods. The SSAHA algorithm is used for high-throughput single nucleotide polymorphism (SNP) detection and very large scale sequence assembly. Also, it provides Web-based sequence search facilities for Ensembl projects.
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              Is Open Access

              Artemis and ACT: viewing, annotating and comparing sequences stored in a relational database

              Motivation: Artemis and Artemis Comparison Tool (ACT) have become mainstream tools for viewing and annotating sequence data, particularly for microbial genomes. Since its first release, Artemis has been continuously developed and supported with additional functionality for editing and analysing sequences based on feedback from an active user community of laboratory biologists and professional annotators. Nevertheless, its utility has been somewhat restricted by its limitation to reading and writing from flat files. Therefore, a new version of Artemis has been developed, which reads from and writes to a relational database schema, and allows users to annotate more complex, often large and fragmented, genome sequences. Results: Artemis and ACT have now been extended to read and write directly to the Generic Model Organism Database (GMOD, http://www.gmod.org) Chado relational database schema. In addition, a Gene Builder tool has been developed to provide structured forms and tables to edit coordinates of gene models and edit functional annotation, based on standard ontologies, controlled vocabularies and free text. Availability: Artemis and ACT are freely available (under a GPL licence) for download (for MacOSX, UNIX and Windows) at the Wellcome Trust Sanger Institute web sites: http://www.sanger.ac.uk/Software/Artemis/ http://www.sanger.ac.uk/Software/ACT/ Contact: artemis@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                Journal
                Curr Opin Microbiol
                Curr. Opin. Microbiol
                Current Opinion in Microbiology
                Current Biology
                1369-5274
                1879-0364
                October 2010
                October 2010
                : 13
                : 5
                : 619-624
                Affiliations
                The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, Cambridgeshire, CB10 1SA, UK
                Article
                COMICR815
                10.1016/j.mib.2010.09.009
                3025319
                20888288
                c98e29b9-afe6-4ce7-8753-9fdd3838f7f1
                © 2010 Elsevier Ltd.

                This document may be redistributed and reused, subject to certain conditions.

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                Microbiology & Virology
                Microbiology & Virology

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