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Guillot L, Delage L, Viari A, Vandenbrouck Y, Com E, Ritter A, Lavigne R, Marie D, Peterlongo P, Potin P, Pineau C. Peptimapper: proteogenomics workflow for the expert annotation of eukaryotic genomes. BMC Genomics 2019; 20:56. [PMID: 30654742 PMCID: PMC6337836 DOI: 10.1186/s12864-019-5431-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Accepted: 01/03/2019] [Indexed: 01/02/2023] Open
Abstract
Background Accurate structural annotation of genomes is still a challenge, despite the progress made over the past decade. The prediction of gene structure remains difficult, especially for eukaryotic species, and is often erroneous and incomplete. We used a proteogenomics strategy, taking advantage of the combination of proteomics datasets and bioinformatics tools, to identify novel protein coding-genes and splice isoforms, assign correct start sites, and validate predicted exons and genes. Results Our proteogenomics workflow, Peptimapper, was applied to the genome annotation of Ectocarpus sp., a key reference genome for both the brown algal lineage and stramenopiles. We generated proteomics data from various life cycle stages of Ectocarpus sp. strains and sub-cellular fractions using a shotgun approach. First, we directly generated peptide sequence tags (PSTs) from the proteomics data. Second, we mapped PSTs onto the translated genomic sequence. Closely located hits (i.e., PSTs locations on the genome) were then clustered to detect potential coding regions based on parameters optimized for the organism. Third, we evaluated each cluster and compared it to gene predictions from existing conventional genome annotation approaches. Finally, we integrated cluster locations into GFF files to use a genome viewer. We identified two potential novel genes, a ribosomal protein L22 and an aryl sulfotransferase and corrected the gene structure of a dihydrolipoamide acetyltransferase. We experimentally validated the results by RT-PCR and using transcriptomics data. Conclusions Peptimapper is a complementary tool for the expert annotation of genomes. It is suitable for any organism and is distributed through a Docker image available on two public bioinformatics docker repositories: Docker Hub and BioShaDock. This workflow is also accessible through the Galaxy framework and for use by non-computer scientists at https://galaxy.protim.eu. Data are available via ProteomeXchange under identifier PXD010618. Electronic supplementary material The online version of this article (10.1186/s12864-019-5431-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Laetitia Guillot
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35042, Rennes cedex, France.,Protim, Univ Rennes, F-35042, Rennes cedex, France
| | - Ludovic Delage
- Sorbonne Université, UPMC, CNRS, UMR 8227, Integrative Biology of Marine Models, Biological Station, CS 90074, F-29688, Roscoff, France
| | - Alain Viari
- INRIA Grenoble-Rhône-Alpes, F-38330, Montbonnot-Saint-Martin, France
| | - Yves Vandenbrouck
- University Grenoble Alpes, CEA, Inserm, BIG-BGE, 38000, Grenoble, France
| | - Emmanuelle Com
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35042, Rennes cedex, France.,Protim, Univ Rennes, F-35042, Rennes cedex, France
| | - Andrés Ritter
- Sorbonne Université, UPMC, CNRS, UMR 8227, Integrative Biology of Marine Models, Biological Station, CS 90074, F-29688, Roscoff, France.,Present address: Sorbonne Université, CNRS, Institut de Biologie Paris-Seine, Laboratory of Computational and Quantitative Biology, F-75005, Paris, France
| | - Régis Lavigne
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35042, Rennes cedex, France.,Protim, Univ Rennes, F-35042, Rennes cedex, France
| | - Dominique Marie
- Sorbonne Université, UPMC, CNRS, UMR 8227, Integrative Biology of Marine Models, Biological Station, CS 90074, F-29688, Roscoff, France
| | | | - Philippe Potin
- Sorbonne Université, UPMC, CNRS, UMR 8227, Integrative Biology of Marine Models, Biological Station, CS 90074, F-29688, Roscoff, France
| | - Charles Pineau
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35042, Rennes cedex, France. .,Protim, Univ Rennes, F-35042, Rennes cedex, France.
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Sanders WS, Wang N, Bridges SM, Malone BM, Dandass YS, McCarthy FM, Nanduri B, Lawrence ML, Burgess SC. The proteogenomic mapping tool. BMC Bioinformatics 2011; 12:115. [PMID: 21513508 PMCID: PMC3107813 DOI: 10.1186/1471-2105-12-115] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2010] [Accepted: 04/22/2011] [Indexed: 11/25/2022] Open
Abstract
Background High-throughput mass spectrometry (MS) proteomics data is increasingly being used to complement traditional structural genome annotation methods. To keep pace with the high speed of experimental data generation and to aid in structural genome annotation, experimentally observed peptides need to be mapped back to their source genome location quickly and exactly. Previously, the tools to do this have been limited to custom scripts designed by individual research groups to analyze their own data, are generally not widely available, and do not scale well with large eukaryotic genomes. Results The Proteogenomic Mapping Tool includes a Java implementation of the Aho-Corasick string searching algorithm which takes as input standardized file types and rapidly searches experimentally observed peptides against a given genome translated in all 6 reading frames for exact matches. The Java implementation allows the application to scale well with larger eukaryotic genomes while providing cross-platform functionality. Conclusions The Proteogenomic Mapping Tool provides a standalone application for mapping peptides back to their source genome on a number of operating system platforms with standard desktop computer hardware and executes very rapidly for a variety of datasets. Allowing the selection of different genetic codes for different organisms allows researchers to easily customize the tool to their own research interests and is recommended for anyone working to structurally annotate genomes using MS derived proteomics data.
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Affiliation(s)
- William S Sanders
- Department of Computer Science & Engineering, Mississippi State University, MS, USA
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McCarthy FM, Gresham CR, Buza TJ, Chouvarine P, Pillai LR, Kumar R, Ozkan S, Wang H, Manda P, Arick T, Bridges SM, Burgess SC. AgBase: supporting functional modeling in agricultural organisms. Nucleic Acids Res 2010; 39:D497-506. [PMID: 21075795 PMCID: PMC3013706 DOI: 10.1093/nar/gkq1115] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
AgBase (http://www.agbase.msstate.edu/) provides resources to facilitate modeling of functional genomics data and structural and functional annotation of agriculturally important animal, plant, microbe and parasite genomes. The website is redesigned to improve accessibility and ease of use, including improved search capabilities. Expanded capabilities include new dedicated pages for horse, cat, dog, cotton, rice and soybean. We currently provide 590 240 Gene Ontology (GO) annotations to 105 454 gene products in 64 different species, including GO annotations linked to transcripts represented on agricultural microarrays. For many of these arrays, this provides the only functional annotation available. GO annotations are available for download and we provide comprehensive, species-specific GO annotation files for 18 different organisms. The tools available at AgBase have been expanded and several existing tools improved based upon user feedback. One of seven new tools available at AgBase, GOModeler, supports hypothesis testing from functional genomics data. We host several associated databases and provide genome browsers for three agricultural pathogens. Moreover, we provide comprehensive training resources (including worked examples and tutorials) via links to Educational Resources at the AgBase website.
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Affiliation(s)
- Fiona M McCarthy
- Department of Basic Sciences, College of Veterinary Medicine, PO Box 6100, Mississippi State University, MS 39762, USA.
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