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      Inter- and intra-specific pan-genomes of Borrelia burgdorferi sensu lato: genome stability and adaptive radiation

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          Abstract

          Background

          Lyme disease is caused by spirochete bacteria from the Borrelia burgdorferi sensu lato ( B. burgdorferi s.l.) species complex. To reconstruct the evolution of B. burgdorferi s.l. and identify the genomic basis of its human virulence, we compared the genomes of 23 B. burgdorferi s.l. isolates from Europe and the United States, including B. burgdorferi sensu stricto ( B. burgdorferi s.s., 14 isolates), B. afzelii (2), B. garinii (2), B. “ bavariensis” (1), B. spielmanii (1), B. valaisiana (1), B. bissettii (1), and B. “ finlandensis” (1).

          Results

          Robust B. burgdorferi s.s. and B. burgdorferi s.l. phylogenies were obtained using genome-wide single-nucleotide polymorphisms, despite recombination. Phylogeny-based pan-genome analysis showed that the rate of gene acquisition was higher between species than within species, suggesting adaptive speciation. Strong positive natural selection drives the sequence evolution of lipoproteins, including chromosomally-encoded genes 0102 and 0404, cp26-encoded ospC and b08, and lp54-encoded dbpA, a07, a22, a33, a53, a65. Computer simulations predicted rapid adaptive radiation of genomic groups as population size increases.

          Conclusions

          Intra- and inter-specific pan-genome sizes of B. burgdorferi s.l. expand linearly with phylogenetic diversity. Yet gene-acquisition rates in B. burgdorferi s.l. are among the lowest in bacterial pathogens, resulting in high genome stability and few lineage-specific genes. Genome adaptation of B. burgdorferi s.l. is driven predominantly by copy-number and sequence variations of lipoprotein genes. New genomic groups are likely to emerge if the current trend of B. burgdorferi s.l. population expansion continues.

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          Most cited references104

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

          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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            The Bioperl toolkit: Perl modules for the life sciences.

            The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.
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              A codon-based model of nucleotide substitution for protein-coding DNA sequences.

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              A codon-based model for the evolution of protein-coding DNA sequences is presented for use in phylogenetic estimation. A Markov process is used to describe substitutions between codons. Transition/transversion rate bias and codon usage bias are allowed in the model, and selective restraints at the protein level are accommodated using physicochemical distances between the amino acids coded for by the codons. Analyses of two data sets suggest that the new codon-based model can provide a better fit to data than can nucleotide-based models and can produce more reliable estimates of certain biologically important measures such as the transition/transversion rate ratio and the synonymous/nonsynonymous substitution rate ratio.
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                Author and article information

                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2013
                10 October 2013
                : 14
                : 693
                Affiliations
                [1 ]Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
                [2 ]Department of Pathology, Division of Microbiology and Immunology, University of Utah Medical School, Salt Lake City, Utah 84112, USA
                [3 ]Department of Medicine, Health Science Center, Stony Brook University, Stony Brook, New York 11794, USA
                [4 ]Department of Biological Sciences, Hunter College of the City University of New York, New York, New York 10065, USA
                [5 ]Biology Department, Brookhaven National Laboratory, Upton, New York 11793, USA
                [6 ]Department of Medicine, University of Medicine and Dentistry of New Jersey, New Jersey Medical School, Newark, New Jersey 07103, USA
                Article
                1471-2164-14-693
                10.1186/1471-2164-14-693
                3833655
                24112474
                4a45cb6d-cda5-4623-81ad-b2266cf681f9
                Copyright © 2013 Mongodin 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.

                History
                : 28 May 2013
                : 26 September 2013
                Categories
                Research Article

                Genetics
                borrelia burgdorferi,lyme borreliosis,pan-genome,single-nucleotide polymorphisms,phylogenetic tree,genome evolution simulation

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