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      Extensive gene content variation in the Brachypodium distachyon pan-genome correlates with population structure

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          Abstract

          While prokaryotic pan-genomes have been shown to contain many more genes than any individual organism, the prevalence and functional significance of differentially present genes in eukaryotes remains poorly understood. Whole-genome de novo assembly and annotation of 54 lines of the grass Brachypodium distachyon yield a pan-genome containing nearly twice the number of genes found in any individual genome. Genes present in all lines are enriched for essential biological functions, while genes present in only some lines are enriched for conditionally beneficial functions (e.g., defense and development), display faster evolutionary rates, lie closer to transposable elements and are less likely to be syntenic with orthologous genes in other grasses. Our data suggest that differentially present genes contribute substantially to phenotypic variation within a eukaryote species, these genes have a major influence in population genetics, and transposable elements play a key role in pan-genome evolution.

          Abstract

          The role of differential gene content in the evolution and function of eukaryotic genomes remains poorly explored. Here the authors assemble and annotate the Brachypodium distachyon pan-genome consisting of 54 diverse lines and reveal the differential present genes as a major driver of phenotypic variation.

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          Whole-genome sequencing of multiple Arabidopsis thaliana populations.

          The plant Arabidopsis thaliana occurs naturally in many different habitats throughout Eurasia. As a foundation for identifying genetic variation contributing to adaptation to diverse environments, a 1001 Genomes Project to sequence geographically diverse A. thaliana strains has been initiated. Here we present the first phase of this project, based on population-scale sequencing of 80 strains drawn from eight regions throughout the species' native range. We describe the majority of common small-scale polymorphisms as well as many larger insertions and deletions in the A. thaliana pan-genome, their effects on gene function, and the patterns of local and global linkage among these variants. The action of processes other than spontaneous mutation is identified by comparing the spectrum of mutations that have accumulated since A. thaliana diverged from its closest relative 10 million years ago with the spectrum observed in the laboratory. Recent species-wide selective sweeps are rare, and potentially deleterious mutations are more common in marginal populations.
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            Inconsistency of phylogenetic estimates from concatenated data under coalescence.

            Although multiple gene sequences are becoming increasingly available for molecular phylogenetic inference, the analysis of such data has largely relied on inference methods designed for single genes. One of the common approaches to analyzing data from multiple genes is concatenation of the individual gene data to form a single supergene to which traditional phylogenetic inference procedures - e.g., maximum parsimony (MP) or maximum likelihood (ML) - are applied. Recent empirical studies have demonstrated that concatenation of sequences from multiple genes prior to phylogenetic analysis often results in inference of a single, well-supported phylogeny. Theoretical work, however, has shown that the coalescent can produce substantial variation in single-gene histories. Using simulation, we combine these ideas to examine the performance of the concatenation approach under conditions in which the coalescent produces a high level of discord among individual gene trees and show that it leads to statistically inconsistent estimation in this setting. Furthermore, use of the bootstrap to measure support for the inferred phylogeny can result in moderate to strong support for an incorrect tree under these conditions. These results highlight the importance of incorporating variation in gene histories into multilocus phylogenetics.
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              Genomics of bacteria and archaea: the emerging dynamic view of the prokaryotic world

              The first bacterial genome was sequenced in 1995, and the first archaeal genome in 1996. Soon after these breakthroughs, an exponential rate of genome sequencing was established, with a doubling time of approximately 20 months for bacteria and approximately 34 months for archaea. Comparative analysis of the hundreds of sequenced bacterial and dozens of archaeal genomes leads to several generalizations on the principles of genome organization and evolution. A crucial finding that enables functional characterization of the sequenced genomes and evolutionary reconstruction is that the majority of archaeal and bacterial genes have conserved orthologs in other, often, distant organisms. However, comparative genomics also shows that horizontal gene transfer (HGT) is a dominant force of prokaryotic evolution, along with the loss of genetic material resulting in genome contraction. A crucial component of the prokaryotic world is the mobilome, the enormous collection of viruses, plasmids and other selfish elements, which are in constant exchange with more stable chromosomes and serve as HGT vehicles. Thus, the prokaryotic genome space is a tightly connected, although compartmentalized, network, a novel notion that undermines the ‘Tree of Life’ model of evolution and requires a new conceptual framework and tools for the study of prokaryotic evolution.
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                Author and article information

                Contributors
                jpvogel@lbl.gov
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                19 December 2017
                19 December 2017
                2017
                : 8
                : 2184
                Affiliations
                [1 ]ISNI 0000 0004 0449 479X, GRID grid.451309.a, DOE Joint Genome Institute, ; Walnut Creek, CA 94598 USA
                [2 ]ISNI 0000 0001 1017 9305, GRID grid.466637.6, Estación Experimental de Aula Dei-CSIC, ; 50059 Zaragoza, Spain
                [3 ]ISNI 0000 0004 1762 9673, GRID grid.450869.6, Fundación ARAID, ; 50018 Zaragoza, Spain
                [4 ]Grupo de Bioquímica, Biofísica y Biología Computacional (BIFI, UNIZAR), Unidad Asociada al CSIC, 500018 Zaragoza, Spain
                [5 ]ISNI 0000 0001 0701 8607, GRID grid.28803.31, University of Wisconsin, ; Madison, WI 53706 USA
                [6 ]ISNI 0000 0004 0520 2998, GRID grid.454753.4, United States Department of Energy Great Lakes Bioenergy Research Center, ; Madison, WI 53726 USA
                [7 ]ISNI 000000041936754X, GRID grid.38142.3c, Harvard University, ; Cambridge, MA 02138 USA
                [8 ]ISNI 0000 0001 2181 7878, GRID grid.47840.3f, University California, Berkeley, ; Berkeley, CA 94720 USA
                [9 ]ISNI 0000 0004 1937 0650, GRID grid.7400.3, University of Zürich, ; Zürich, CH-8006 Switzerland
                [10 ]ISNI 0000 0001 2184 9220, GRID grid.266683.f, University of Massachusetts Amherst, Institute for Applied Life Sciences, ; Amherst, MA 01003 USA
                [11 ]ISNI 0000 0001 0668 7884, GRID grid.5596.f, University of Leuven, KU Leuven, ; Leuven, 3000 Belgium
                [12 ]ISNI 0000 0001 2156 6108, GRID grid.41891.35, Montana State University, ; Bozeman, MT 59717 USA
                [13 ]ISNI 0000 0004 1936 9924, GRID grid.89336.37, University of Texas Austin, ; Austin, TX 78705 USA
                [14 ]ISNI 0000000121682483, GRID grid.8186.7, Aberystwyth University, ; Aberystwyth, SY23 3FL UK
                [15 ]ISNI 0000000419368657, GRID grid.17635.36, University of Minnesota, ; St. Paul, MN 55108 USA
                [16 ]Universidad de Zaragoza-Escuela Politécnica Superior de Huesca, 22071 Huesca, Spain
                [17 ]ISNI 0000 0001 2341 2786, GRID grid.116068.8, Present Address: Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, ; Cambridge, MA 02139 USA
                Author information
                http://orcid.org/0000-0002-5462-907X
                http://orcid.org/0000-0002-6772-6987
                http://orcid.org/0000-0001-9511-6441
                http://orcid.org/0000-0002-4757-5069
                http://orcid.org/0000-0002-9692-4499
                http://orcid.org/0000-0002-2556-2478
                http://orcid.org/0000-0003-3068-5402
                http://orcid.org/0000-0002-0378-6374
                http://orcid.org/0000-0001-6287-2697
                http://orcid.org/0000-0002-0961-9817
                http://orcid.org/0000-0003-2636-661X
                http://orcid.org/0000-0001-7793-5259
                http://orcid.org/0000-0003-1786-2689
                Article
                2292
                10.1038/s41467-017-02292-8
                5736591
                28232747
                7c7c67bc-b650-4cb9-beca-3b007507ea2a
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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                : 28 November 2016
                : 17 November 2017
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