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      TriTrypDB: a functional genomic resource for the Trypanosomatidae

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      1 , 2 , 1 , 3 , 3 , 4 , 1 , 3 , 3 , 3 , 5 , 6 , 7 , 3 , 3 , * , 2 , 1 , * , 1 , 3 , 3 , 2 , 8 , 9 , 3 , 1 , 9 , 5 , 5 , 6 , 10 , 3 , 2 , 5 , 3 , 5 , 1 , 11 , 2 , 5 , 12 , 2 , 3 , 5 , 2 , 1 , 3 , 1 , 2
      Nucleic Acids Research
      Oxford University Press

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          Abstract

          TriTrypDB ( http://tritrypdb.org) is an integrated database providing access to genome-scale datasets for kinetoplastid parasites, and supporting a variety of complex queries driven by research and development needs. TriTrypDB is a collaborative project, utilizing the GUS/WDK computational infrastructure developed by the Eukaryotic Pathogen Bioinformatics Resource Center (EuPathDB.org) to integrate genome annotation and analyses from GeneDB and elsewhere with a wide variety of functional genomics datasets made available by members of the global research community, often pre-publication. Currently, TriTrypDB integrates datasets from Leishmania braziliensis, L. infantum, L. major, L. tarentolae, Trypanosoma brucei and T. cruzi. Users may examine individual genes or chromosomal spans in their genomic context, including syntenic alignments with other kinetoplastid organisms. Data within TriTrypDB can be interrogated utilizing a sophisticated search strategy system that enables a user to construct complex queries combining multiple data types. All search strategies are stored, allowing future access and integrated searches. ‘User Comments’ may be added to any gene page, enhancing available annotation; such comments become immediately searchable via the text search, and are forwarded to curators for incorporation into the reference annotation when appropriate.

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          Most cited references15

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          The genome of the African trypanosome Trypanosoma brucei.

          African trypanosomes cause human sleeping sickness and livestock trypanosomiasis in sub-Saharan Africa. We present the sequence and analysis of the 11 megabase-sized chromosomes of Trypanosoma brucei. The 26-megabase genome contains 9068 predicted genes, including approximately 900 pseudogenes and approximately 1700 T. brucei-specific genes. Large subtelomeric arrays contain an archive of 806 variant surface glycoprotein (VSG) genes used by the parasite to evade the mammalian immune system. Most VSG genes are pseudogenes, which may be used to generate expressed mosaic genes by ectopic recombination. Comparisons of the cytoskeleton and endocytic trafficking systems with those of humans and other eukaryotic organisms reveal major differences. A comparison of metabolic pathways encoded by the genomes of T. brucei, T. cruzi, and Leishmania major reveals the least overall metabolic capability in T. brucei and the greatest in L. major. Horizontal transfer of genes of bacterial origin has contributed to some of the metabolic differences in these parasites, and a number of novel potential drug targets have been identified.
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            The genome sequence of Trypanosoma cruzi, etiologic agent of Chagas disease.

            Whole-genome sequencing of the protozoan pathogen Trypanosoma cruzi revealed that the diploid genome contains a predicted 22,570 proteins encoded by genes, of which 12,570 represent allelic pairs. Over 50% of the genome consists of repeated sequences, such as retrotransposons and genes for large families of surface molecules, which include trans-sialidases, mucins, gp63s, and a large novel family (>1300 copies) of mucin-associated surface protein (MASP) genes. Analyses of the T. cruzi, T. brucei, and Leishmania major (Tritryp) genomes imply differences from other eukaryotes in DNA repair and initiation of replication and reflect their unusual mitochondrial DNA. Although the Tritryp lack several classes of signaling molecules, their kinomes contain a large and diverse set of protein kinases and phosphatases; their size and diversity imply previously unknown interactions and regulatory processes, which may be targets for intervention.
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              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

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                January 2010
                20 October 2009
                20 October 2009
                : 38
                : Database issue , Database issue
                : D457-D462
                Affiliations
                1Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, 2Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA 30602, 3Penn Center for Bioinformatics, University of Pennsylvania, Philadelphia, PA 19104 USA, 4Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK, 5Seattle Biomedical Research Institute, Seattle, WA 98109, 6Department of Global Health, University of Washington, Seattle, WA 98195, 7Center for Applied Genetic Technologies, 8Department of Genetics, 9Department of Computer Science, University of Georgia, Athens, GA 30602, 10Department of Medical Education and Biomedical Informatics, University of Washington, Seattle, WA 98195, 11Department of Biology, University of Pennsylvania, Philadelphia, PA 19104 USA and 12Centre for Immunology and Infection, Department of Biology, University of York, Heslington, York YO10 5YW, UK
                Author notes
                *To whom correspondence should be addressed. Tel: +1 215 746 7019; Fax: +1 215 573 3111; Email: oharb@ 123456pcbi.upenn.edu Correspondence may also be addressed to Christiane Hertz-Fowler. Tel: +44 (0)1223 834244; Fax: +44 (0)1223 494919; Email: chf@ 123456sanger.ac.uk
                Article
                gkp851
                10.1093/nar/gkp851
                2808979
                19843604
                ec382888-f244-4600-9215-cfa1a373d409
                © The Author(s) 2009. 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/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 15 August 2009
                : 23 September 2009
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                Genetics
                Genetics

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