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      PGAP: pan-genomes analysis pipeline

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          Abstract

          Summary: With the rapid development of DNA sequencing technology, increasing bacteria genome data enable the biologists to dig the evolutionary and genetic information of prokaryotic species from pan-genome sight. Therefore, the high-efficiency pipelines for pan-genome analysis are mostly needed. We have developed a new pan-genome analysis pipeline (PGAP), which can perform five analytic functions with only one command, including cluster analysis of functional genes, pan-genome profile analysis, genetic variation analysis of functional genes, species evolution analysis and function enrichment analysis of gene clusters. PGAP's performance has been evaluated on 11 Streptococcus pyogenes strains.

          Availability:PGAP is developed with Perl script on the Linux Platform and the package is freely available from http://pgap.sf.net.

          Contact: junyu@ 123456big.ac.cn ; xiaojingfa@ 123456big.ac.cn

          Supplementary information: Supplementary data are available at Bioinformatics online.

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          Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial "pan-genome".

          H Tettelin, V Masignani, M. J. Cieslewicz … (2005)
          The development of efficient and inexpensive genome sequencing methods has revolutionized the study of human bacterial pathogens and improved vaccine design. Unfortunately, the sequence of a single genome does not reflect how genetic variability drives pathogenesis within a bacterial species and also limits genome-wide screens for vaccine candidates or for antimicrobial targets. We have generated the genomic sequence of six strains representing the five major disease-causing serotypes of Streptococcus agalactiae, the main cause of neonatal infection in humans. Analysis of these genomes and those available in databases showed that the S. agalactiae species can be described by a pan-genome consisting of a core genome shared by all isolates, accounting for approximately 80% of any single genome, plus a dispensable genome consisting of partially shared and strain-specific genes. Mathematical extrapolation of the data suggests that the gene reservoir available for inclusion in the S. agalactiae pan-genome is vast and that unique genes will continue to be identified even after sequencing hundreds of genomes.
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            Whole-genome random sequencing and assembly of Haemophilus influenzae Rd.

            E Kirkness, C Bult, A Kerlavage … (1995)
            An approach for genome analysis based on sequencing and assembly of unselected pieces of DNA from the whole chromosome has been applied to obtain the complete nucleotide sequence (1,830,137 base pairs) of the genome from the bacterium Haemophilus influenzae Rd. This approach eliminates the need for initial mapping efforts and is therefore applicable to the vast array of microbial species for which genome maps are unavailable. The H. influenzae Rd genome sequence (Genome Sequence DataBase accession number L42023) represents the only complete genome sequence from a free-living organism.
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              Bacterial pathogenomics.

              Mark J. Pallen, Brendan W. Wren (2007)
              Genomes from all of the crucial bacterial pathogens of humans, plants and animals have now been sequenced, as have genomes from many of the important commensal, symbiotic and environmental microorganisms. Analysis of these sequences has revealed the forces that shape pathogen evolution and has brought to light unexpected aspects of pathogen biology. The finding that horizontal gene transfer and genome decay have key roles in the evolution of bacterial pathogens was particularly surprising. It has also become evident that even the definitions for 'pathogen' and 'virulence factor' need to be re-evaluated.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Bioinformatics
                Journal ID (publisher-id): bioinformatics
                Journal ID (hwp): bioinfo
                Title: Bioinformatics
                Publisher: Oxford University Press
                ISSN (Print): 1367-4803
                ISSN (Electronic): 1367-4811
                Publication date (Print): 1 February 2012
                Publication date (Electronic): 29 November 2011
                Publication date PMC-release: 29 November 2011
                Volume: 28
                Issue: 3
                Pages: 416-418
                Affiliations
                1CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029 and 2Graduate University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
                Author notes
                * To whom correspondence should be addressed.

                Associate Editor: John Quackenbush

                Article
                Publisher ID: btr655
                DOI: 10.1093/bioinformatics/btr655
                PMC ID: 3268234
                PubMed ID: 22130594
                SO-VID: 0c71e298-a6cf-4669-ad86-2bb345088acc
                Copyright © © The Author(s) 2011. Published by Oxford University Press.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 1 September 2011
                Date revision received : 4 November 2011
                Date accepted : 23 November 2011
                Page count
                Pages: 3
                Categories
                Subject: Applications Note
                Subject: Genome Analysis

                ScienceOpen disciplines: Bioinformatics & Computational biology
                Data availability:
                ScienceOpen disciplines: Bioinformatics & Computational biology

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