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      Modularized Evolution in Archaeal Methanogens Phylogenetic Forest

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          Abstract

          Methanogens are methane-producing archaea that plays a key role in the global carbon cycle. To date, the evolutionary history of methanogens and closely related nonmethanogen species remains unresolved among studies conducted upon different genetic markers, attributing to horizontal gene transfers (HGTs). With an effort to decipher both congruent and conflicting evolutionary events, reconstruction of coevolved gene clusters and hierarchical structure in the archaeal methanogen phylogenetic forest, comprehensive evolution, and network analyses were performed upon 3,694 gene families from 41 methanogens and 33 closely related archaea. Our results show that 1) greater than 50% of genes are in topological dissonance with others; 2) the prevalent interorder HGTs, even for core genes, in methanogen genomes led to their scrambled phylogenetic relationships; 3) most methanogenesis-related genes have experienced at least one HGT; 4) greater than 20% of the genes in methanogen genomes were transferred horizontally from other archaea, with genes involved in cell-wall synthesis and defense system having been transferred most frequently; 5) the coevolution network contains seven statistically robust modules, wherein the central module has the highest average node strength and comprises a majority of the core genes; 6) different coevolutionary module genes boomed in different time and evolutionary lineage, constructing diversified pan-genome structures; 7) the modularized evolution is also closely related to the vertical evolution signals and the HGT rate of the genes. Overall, this study presented a modularized phylogenetic forest that describes a combination of complicated vertical and nonvertical evolutionary processes for methanogenic archaeal species.

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            A decade after the beginning of the genomic era, the question of how genomics can describe a bacterial species has not been fully addressed. Experimental data have shown that in some species new genes are discovered even after sequencing the genomes of several strains. Mathematical modeling predicts that new genes will be discovered even after sequencing hundreds of genomes per species. Therefore, a bacterial species can be described by its pan-genome, which is composed of a "core genome" containing genes present in all strains, and a "dispensable genome" containing genes present in two or more strains and genes unique to single strains. Given that the number of unique genes is vast, the pan-genome of a bacterial species might be orders of magnitude larger than any single genome.
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              The All-Species Living Tree project: a 16S rRNA-based phylogenetic tree of all sequenced type strains.

              The signing authors together with the journal Systematic and Applied Microbiology (SAM) have started an ambitious project that has been conceived to provide a useful tool especially for the scientific microbial taxonomist community. The aim of what we have called "The All-Species Living Tree" is to reconstruct a single 16S rRNA tree harboring all sequenced type strains of the hitherto classified species of Archaea and Bacteria. This tree is to be regularly updated by adding the species with validly published names that appear monthly in the Validation and Notification lists of the International Journal of Systematic and Evolutionary Microbiology. For this purpose, the SAM executive editors, together with the responsible teams of the ARB, SILVA, and LPSN projects (www.arb-home.de, www.arb-silva.de, and www.bacterio.cict.fr, respectively), have prepared a 16S rRNA database containing over 6700 sequences, each of which represents a single type strain of a classified species up to 31 December 2007. The selection of sequences had to be undertaken manually due to a high error rate in the names and information fields provided for the publicly deposited entries. In addition, from among the often occurring multiple entries for a single type strain, the best-quality sequence was selected for the project. The living tree database that SAM now provides contains corrected entries and the best-quality sequences with a manually checked alignment. The tree reconstruction has been performed by using the maximum likelihood algorithm RAxML. The tree provided in the first release is a result of the calculation of a single dataset containing 9975 single entries, 6728 corresponding to type strain gene sequences, as well as 3247 additional high-fquality sequences to give robustness to the reconstruction. Trees are dynamic structures that change on the basis of the quality and availability of the data used for their calculation. Therefore, the addition of new type strain sequences in further subsequent releases may help to resolve certain branching orders that appear ambiguous in this first release. On the web sites: www.elsevier.de/syapm and www.arb-silva.de/living-tree, the All-Species Living Tree team will release a regularly updated database compatible with the ARB software environment containing the whole 16S rRNA dataset used to reconstruct "The All-Species Living Tree". As a result, the latest reconstructed phylogeny will be provided. In addition to the ARB file, a readable multi-FASTA universal sequence editor file with the complete alignment will be provided for those not using ARB. There is also a complete set of supplementary tables and figures illustrating the selection procedure and its outcome. It is expected that the All-Species Living Tree will help to improve future classification efforts by simplifying the selection of the correct type strain sequences. For queries, information updates, remarks on the dataset or tree reconstructions shown, a contact email address has been created (living-tree@arb-silva.de). This provides an entry point for anyone from the scientific community to provide additional input for the construction and improvement of the first tree compiling all sequenced type strains of all prokaryotic species for which names had been validly published.
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                Author and article information

                Journal
                Genome Biol Evol
                Genome Biol Evol
                gbe
                gbe
                Genome Biology and Evolution
                Oxford University Press
                1759-6653
                December 2014
                09 December 2014
                09 December 2014
                : 6
                : 12
                : 3344-3359
                Affiliations
                1School of Biological Sciences, Faculty of Science, The University of Hong Kong, China
                2Center for Marine Environmental Studies, Ehime University, Japan
                3Bioinformatics Center, Nanjing Agricultural University, People's Republic of China
                4Present address: Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON, Canada
                Author notes
                *Corresponding author: E-mail: fcleung@ 123456hkucc.hku.hk .

                These authors contributed equally to this work.

                Associate editor: Bill Martin

                Article
                evu259
                10.1093/gbe/evu259
                4986457
                25502908
                7090c3fc-5e5c-4e25-a16a-d2acd3c9479a
                © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 17 November 2014
                Page count
                Pages: 16
                Categories
                Research Article

                Genetics
                network analysis,co-evolution network,hgt,lgt,phylogenetic forest,modularized evolution
                Genetics
                network analysis, co-evolution network, hgt, lgt, phylogenetic forest, modularized evolution

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