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      Pseudomonas Genome Database: improved comparative analysis and population genomics capability for Pseudomonas genomes

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          Abstract

          Pseudomonas is a metabolically-diverse genus of bacteria known for its flexibility and leading free living to pathogenic lifestyles in a wide range of hosts. The Pseudomonas Genome Database ( http://www.pseudomonas.com) integrates completely-sequenced Pseudomonas genome sequences and their annotations with genome-scale, high-precision computational predictions and manually curated annotation updates. The latest release implements an ability to view sequence polymorphisms in P. aeruginosa PAO1 versus other reference strains, incomplete genomes and single gene sequences. This aids analysis of phenotypic variation between closely related isolates and strains, as well as wider population genomics and evolutionary studies. The wide range of tools for comparing Pseudomonas annotations and sequences now includes a strain-specific access point for viewing high precision computational predictions including updated, more accurate, protein subcellular localization and genomic island predictions. Views link to genome-scale experimental data as well as comparative genomics analyses that incorporate robust genera-geared methods for predicting and clustering orthologs. These analyses can be exploited for identifying putative essential and core Pseudomonas genes or identifying large-scale evolutionary events. The Pseudomonas Genome Database aims to provide a continually updated, high quality source of genome annotations, specifically tailored for Pseudomonas researchers, but using an approach that may be implemented for other genera-level research communities.

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          Most cited references28

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          The generic genome browser: a building block for a model organism system database.

          The Generic Model Organism System Database Project (GMOD) seeks to develop reusable software components for model organism system databases. In this paper we describe the Generic Genome Browser (GBrowse), a Web-based application for displaying genomic annotations and other features. For the end user, features of the browser include the ability to scroll and zoom through arbitrary regions of a genome, to enter a region of the genome by searching for a landmark or performing a full text search of all features, and the ability to enable and disable tracks and change their relative order and appearance. The user can upload private annotations to view them in the context of the public ones, and publish those annotations to the community. For the data provider, features of the browser software include reliance on readily available open source components, simple installation, flexible configuration, and easy integration with other components of a model organism system Web site. GBrowse is freely available under an open source license. The software, its documentation, and support are available at http://www.gmod.org.
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            NCBI GEO: archive for high-throughput functional genomic data

            The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest public repository for high-throughput gene expression data. Additionally, GEO hosts other categories of high-throughput functional genomic data, including those that examine genome copy number variations, chromatin structure, methylation status and transcription factor binding. These data are generated by the research community using high-throughput technologies like microarrays and, more recently, next-generation sequencing. The database has a flexible infrastructure that can capture fully annotated raw and processed data, enabling compliance with major community-derived scientific reporting standards such as ‘Minimum Information About a Microarray Experiment’ (MIAME). In addition to serving as a centralized data storage hub, GEO offers many tools and features that allow users to effectively explore, analyze and download expression data from both gene-centric and experiment-centric perspectives. This article summarizes the GEO repository structure, content and operating procedures, as well as recently introduced data mining features. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.
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              An ordered, nonredundant library of Pseudomonas aeruginosa strain PA14 transposon insertion mutants.

              Random transposon insertion libraries have proven invaluable in studying bacterial genomes. Libraries that approach saturation must be large, with multiple insertions per gene, making comprehensive genome-wide scanning difficult. To facilitate genome-scale study of the opportunistic human pathogen Pseudomonas aeruginosa strain PA14, we constructed a nonredundant library of PA14 transposon mutants (the PA14NR Set) in which nonessential PA14 genes are represented by a single transposon insertion chosen from a comprehensive library of insertion mutants. The parental library of PA14 transposon insertion mutants was generated by using MAR2xT7, a transposon compatible with transposon-site hybridization and based on mariner. The transposon-site hybridization genetic footprinting feature broadens the utility of the library by allowing pooled MAR2xT7 mutants to be individually tracked under different experimental conditions. A public, internet-accessible database (the PA14 Transposon Insertion Mutant Database, http://ausubellab.mgh.harvard.edu/cgi-bin/pa14/home.cgi) was developed to facilitate construction, distribution, and use of the PA14NR Set. The usefulness of the PA14NR Set in genome-wide scanning for phenotypic mutants was validated in a screen for attachment to abiotic surfaces. Comparison of the genes disrupted in the PA14 transposon insertion library with an independently constructed insertion library in P. aeruginosa strain PAO1 provides an estimate of the number of P. aeruginosa essential genes.
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                Author and article information

                Journal
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                January 2011
                January 2011
                6 October 2010
                6 October 2010
                : 39
                : Database issue , Database issue
                : D596-D600
                Affiliations
                1Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC V5A 1S6 and 2Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
                Author notes
                *To whom correspondence should be addressed. Tel: +778 782 5646; Fax: +778 782 5583; Email: brinkman@ 123456sfu.ca
                Article
                gkq869
                10.1093/nar/gkq869
                3013766
                20929876
                af387f57-e80f-435a-bfb6-2fd2060479e3
                © The Author(s) 2010. 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), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 25 August 2010
                : 15 September 2010
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                Genetics
                Genetics

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