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ModuleOrganizer: detecting modules in families of transposable elements

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      Abstract

      Background

      Most known eukaryotic genomes contain mobile copied elements called transposable elements. In some species, these elements account for the majority of the genome sequence. They have been subject to many mutations and other genomic events (copies, deletions, captures) during transposition. The identification of these transformations remains a difficult issue. The study of families of transposable elements is generally founded on a multiple alignment of their sequences, a critical step that is adapted to transposons containing mostly localized nucleotide mutations. Many transposons that have lost their protein-coding capacity have undergone more complex rearrangements, needing the development of more complex methods in order to characterize the architecture of sequence variations.

      Results

      In this study, we introduce the concept of a transposable element module, a flexible motif present in at least two sequences of a family of transposable elements and built on a succession of maximal repeats. The paper proposes an assembly method working on a set of exact maximal repeats of a set of sequences to create such modules. It results in a graphical view of sequences segmented into modules, a representation that allows a flexible analysis of the transformations that have occurred between them. We have chosen as a demonstration data set in depth analysis of the transposable element Foldback in Drosophila melanogaster. Comparison with multiple alignment methods shows that our method is more sensitive for highly variable sequences. The study of this family and the two other families AtREP21 and SIDER2 reveals new copies of very different sizes and various combinations of modules which show the potential of our method.

      Conclusions

      ModuleOrganizer is available on the Genouest bioinformatics center at http://moduleorganizer.genouest.org

      Related collections

      Most cited references 38

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      Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

      The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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        Repbase Update, a database of eukaryotic repetitive elements.

        Repbase Update is a comprehensive database of repetitive elements from diverse eukaryotic organisms. Currently, it contains over 3600 annotated sequences representing different families and subfamilies of repeats, many of which are unreported anywhere else. Each sequence is accompanied by a short description and references to the original contributors. Repbase Update includes Repbase Reports, an electronic journal publishing newly discovered transposable elements, and the Transposon Pub, a web-based browser of selected chromosomal maps of transposable elements. Sequences from Repbase Update are used to screen and annotate repetitive elements using programs such as Censor and RepeatMasker. Repbase Update is available on the worldwide web at http://www.girinst.org/Repbase_Update.html.
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          Hierarchical Grouping to Optimize an Objective Function

           Joe Ward (1963)
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            Author and article information

            Affiliations
            [1 ]IBISC, Tour Evry 2, 523, place des terrasses del'agora, 91000 Evry, France
            [2 ]INP-ENSAT, Avenue de l'agrobiopole 31326 Castanet tolosan, France
            [3 ]IRISA-INRIA, Campus de Beaulieu, bât 12, 35042 Rennes cedex, France
            Contributors
            Journal
            BMC Bioinformatics
            BMC Bioinformatics
            BioMed Central
            1471-2105
            2010
            22 September 2010
            : 11
            : 474
            2955051
            1471-2105-11-474
            20860790
            10.1186/1471-2105-11-474
            Copyright ©2010 Tempel et al; licensee BioMed Central Ltd.

            This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

            Categories
            Research Article

            Bioinformatics & Computational biology

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