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      A simple, fast, and accurate method of phylogenomic inference

      research-article
      1 , ,   1 , 2 , 3
      Genome Biology
      BioMed Central

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          Abstract

          An automated pipeline for phylogenomic analysis (AMPHORA) is presented that overcomes existing limits to large-scale protein phylogenetic inference.

          Abstract

          The explosive growth of genomic data provides an opportunity to make increased use of protein markers for phylogenetic inference. We have developed an automated pipeline for phylogenomic analysis (AMPHORA) that overcomes the existing bottlenecks limiting large-scale protein phylogenetic inference. We demonstrated its high throughput capabilities and high quality results by constructing a genome tree of 578 bacterial species and by assigning phylotypes to 18,607 protein markers identified in metagenomic data collected from the Sargasso Sea.

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          Most cited references31

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          Profile hidden Markov models.

          S. Eddy (1998)
          The recent literature on profile hidden Markov model (profile HMM) methods and software is reviewed. Profile HMMs turn a multiple sequence alignment into a position-specific scoring system suitable for searching databases for remotely homologous sequences. Profile HMM analyses complement standard pairwise comparison methods for large-scale sequence analysis. Several software implementations and two large libraries of profile HMMs of common protein domains are available. HMM methods performed comparably to threading methods in the CASP2 structure prediction exercise.
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            The Ribosomal Database Project (RDP-II): sequences and tools for high-throughput rRNA analysis

            The Ribosomal Database Project (RDP-II) provides the research community with aligned and annotated rRNA gene sequences, along with analysis services and a phylogenetically consistent taxonomic framework for these data. Updated monthly, these services are made available through the RDP-II website (http://rdp.cme.msu.edu/). RDP-II release 9.21 (August 2004) contains 101 632 bacterial small subunit rRNA gene sequences in aligned and annotated format. High-throughput tools for initial taxonomic placement, identification of related sequences, probe and primer testing, data navigation and subalignment download are provided. The RDP-II email address for questions or comments is rdpstaff@msu.edu.
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              SAR11 clade dominates ocean surface bacterioplankton communities.

              The most abundant class of bacterial ribosomal RNA genes detected in seawater DNA by gene cloning belongs to SAR11-an alpha-proteobacterial clade. Other than indications of their prevalence in seawater, little is known about these organisms. Here we report quantitative measurements of the cellular abundance of the SAR11 clade in northwestern Sargasso Sea waters to 3,000 m and in Oregon coastal surface waters. On average, the SAR11 clade accounts for a third of the cells present in surface waters and nearly a fifth of the cells present in the mesopelagic zone. In some regions, members of the SAR11 clade represent as much as 50% of the total surface microbial community and 25% of the subeuphotic microbial community. By extrapolation, we estimate that globally there are 2.4 x 10(28) SAR11 cells in the oceans, half of which are located in the euphotic zone. Although the biogeochemical role of the SAR11 clade remains uncertain, these data support the conclusion that this microbial group is among the most successful organisms on Earth.
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                Author and article information

                Journal
                Genome Biol
                Genome Biology
                BioMed Central
                1465-6906
                1465-6914
                2008
                13 October 2008
                : 9
                : 10
                : R151
                Affiliations
                [1 ]Genome Center, University of California, One Shields Avenue, Davis, CA 95616, USA
                [2 ]Section of Evolution and Ecology, College of Biological Sciences, University of California, One Shields Avenue, Davis, CA 95616, USA
                [3 ]Department of Medical Microbiology and Immunology, School of Medicine, University of California, One Shields Avenue, Davis, CA 95616, USA
                Article
                gb-2008-9-10-r151
                10.1186/gb-2008-9-10-r151
                2760878
                18851752
                2bf564bf-cc2e-4a80-b7cf-d687c110eb27
                Copyright © 2008 Wu and Eisen; 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
                : 12 August 2008
                : 26 September 2008
                : 13 October 2008
                Categories
                Method

                Genetics
                Genetics

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