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      Phylo SI: a new genome-wide approach for prokaryotic phylogeny

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      1 , 1 , 2 , 3 , 1 , *
      Nucleic Acids Research
      Oxford University Press

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          Abstract

          The evolutionary history of all life forms is usually represented as a vertical tree-like process. In prokaryotes, however, the vertical signal is partly obscured by the massive influence of horizontal gene transfer (HGT). The HGT creates widespread discordance between evolutionary histories of different genes as genomes become mosaics of gene histories. Thus, the Tree of Life (TOL) has been questioned as an appropriate representation of the evolution of prokaryotes. Nevertheless a common hypothesis is that prokaryotic evolution is primarily tree-like, and a routine effort is made to place new isolates in their appropriate location in the TOL. Moreover, it appears desirable to exploit non–tree-like evolutionary processes for the task of microbial classification. In this work, we present a novel technique that builds on the straightforward observation that gene order conservation (‘synteny’) decreases in time as a result of gene mobility. This is particularly true in prokaryotes, mainly due to HGT. Using a ‘synteny index’ (SI) that measures the average synteny between a pair of genomes, we developed the phylogenetic reconstruction tool ‘Phylo SI’. Phylo SI offers several attractive properties such as easy bootstrapping, high sensitivity in cases where phylogenetic signal is weak and computational efficiency. Phylo SI was tested both on simulated data and on two bacterial data sets and compared with two well-established phylogenetic methods. Phylo SI is particularly efficient on short evolutionary distances where synteny footprints remain detectable, whereas the nucleotide substitution signal is too weak for reliable sequence-based phylogenetic reconstruction. The method is publicly available at http://research.haifa.ac.il/ssagi/software/PhyloSI.zip.

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          Most cited references63

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          Comparison of phylogenetic trees

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            Distinguishing homologous from analogous proteins.

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              Construction of phylogenetic trees.

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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
                February 2014
                15 November 2013
                15 November 2013
                : 42
                : 4
                : 2391-2404
                Affiliations
                1Department of Evolutionary & Environmental Biology, University of Haifa, Haifa 31905 Israel, 2Department of Molecular Microbiology and Biotechnology Tel Aviv University, Tel Aviv 69978, Israel and 3National Evolutionary Synthesis Center, 2024 W. Main Street A200, Durham, NC 27705, USA
                Author notes
                *To whom correspondence should be addressed. Tel: +972 4 8288774; Fax: +972 4 8288763; Email: ssagi@ 123456research.haifa.ac.il

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.

                Article
                gkt1138
                10.1093/nar/gkt1138
                3936750
                24243847
                e7e915d2-80c2-4482-a701-b571adf5a5fd
                © The Author(s) 2013. Published by Oxford University Press.

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

                History
                : 16 August 2013
                : 14 October 2013
                : 24 October 2013
                Page count
                Pages: 14
                Categories
                Genomics

                Genetics
                Genetics

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