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      Parallels between experimental and natural evolution of legume symbionts

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          Abstract

          The emergence of symbiotic interactions has been studied using population genomics in nature and experimental evolution in the laboratory, but the parallels between these processes remain unknown. Here we compare the emergence of rhizobia after the horizontal transfer of a symbiotic plasmid in natural populations of Cupriavidus taiwanensis, over 10 MY ago, with the experimental evolution of symbiotic Ralstonia solanacearum for a few hundred generations. In spite of major differences in terms of time span, environment, genetic background, and phenotypic achievement, both processes resulted in rapid genetic diversification dominated by purifying selection. We observe no adaptation in the plasmid carrying the genes responsible for the ecological transition. Instead, adaptation was associated with positive selection in a set of genes that led to the co-option of the same quorum-sensing system in both processes. Our results provide evidence for similarities in experimental and natural evolutionary transitions and highlight the potential of comparisons between both processes to understand symbiogenesis.

          Abstract

          It is unclear if experimental evolution is a good model for natural processes. Here, Clerissi et al. find parallels between the evolution of symbiosis in rhizobia after horizontal transfer of a plasmid over 10 million years ago and experimentally evolved symbionts.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Codon-substitution models for heterogeneous selection pressure at amino acid sites.

            Comparison of relative fixation rates of synonymous (silent) and nonsynonymous (amino acid-altering) mutations provides a means for understanding the mechanisms of molecular sequence evolution. The nonsynonymous/synonymous rate ratio (omega = d(N)d(S)) is an important indicator of selective pressure at the protein level, with omega = 1 meaning neutral mutations, omega 1 diversifying positive selection. Amino acid sites in a protein are expected to be under different selective pressures and have different underlying omega ratios. We develop models that account for heterogeneous omega ratios among amino acid sites and apply them to phylogenetic analyses of protein-coding DNA sequences. These models are useful for testing for adaptive molecular evolution and identifying amino acid sites under diversifying selection. Ten data sets of genes from nuclear, mitochondrial, and viral genomes are analyzed to estimate the distributions of omega among sites. In all data sets analyzed, the selective pressure indicated by the omega ratio is found to be highly heterogeneous among sites. Previously unsuspected Darwinian selection is detected in several genes in which the average omega ratio across sites is 1. Genes undergoing positive selection include the beta-globin gene from vertebrates, mitochondrial protein-coding genes from hominoids, the hemagglutinin (HA) gene from human influenza virus A, and HIV-1 env, vif, and pol genes. Tests for the presence of positively selected sites and their subsequent identification appear quite robust to the specific distributional form assumed for omega and can be achieved using any of several models we implement. However, we encountered difficulties in estimating the precise distribution of omega among sites from real data sets.
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              ClonalFrameML: Efficient Inference of Recombination in Whole Bacterial Genomes

              Recombination is an important evolutionary force in bacteria, but it remains challenging to reconstruct the imports that occurred in the ancestry of a genomic sample. Here we present ClonalFrameML, which uses maximum likelihood inference to simultaneously detect recombination in bacterial genomes and account for it in phylogenetic reconstruction. ClonalFrameML can analyse hundreds of genomes in a matter of hours, and we demonstrate its usefulness on simulated and real datasets. We find evidence for recombination hotspots associated with mobile elements in Clostridium difficile ST6 and a previously undescribed 310kb chromosomal replacement in Staphylococcus aureus ST582. ClonalFrameML is freely available at http://clonalframeml.googlecode.com/.
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                Author and article information

                Contributors
                Catherine.masson@inra.fr
                erocha@pasteur.fr
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                11 June 2018
                11 June 2018
                2018
                : 9
                : 2264
                Affiliations
                [1 ]ISNI 0000 0001 2353 6535, GRID grid.428999.7, Microbial Evolutionary Genomics, , Institut Pasteur, ; 28 rue Dr. Roux, 75015 Paris, France
                [2 ]ISNI 0000 0001 2112 9282, GRID grid.4444.0, UMR3525, , CNRS, ; 28 rue Dr. Roux, 75015 Paris, France
                [3 ]ISNI 0000 0001 2112 9282, GRID grid.4444.0, LIPM, Université de Toulouse, INRA, , CNRS, ; 31326 Castanet-Tolosan, France
                [4 ]ISNI 0000 0001 2180 5818, GRID grid.8390.2, LABGeM, , Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Université d’Evry, Université Paris-Saclay, ; 2 rue Gaston Crémieux, 91057 Evry, France
                [5 ]ISNI 0000 0001 2164 4508, GRID grid.264260.4, Department of Biological Sciences, , State University of New York, ; 4400 Vestal Parkway East, PO Box 6000, Binghamton, NY 13902 USA
                [6 ]IRD, Cirad, Université de Montpellier, IPME, 911, avenue Agropolis—BP64501, 34394 Montpellier Cedex 5, France
                Author information
                http://orcid.org/0000-0003-3891-672X
                http://orcid.org/0000-0001-7704-822X
                Article
                4778
                10.1038/s41467-018-04778-5
                5995829
                29891837
                bd2798be-5adb-4b66-a8d7-d62fe7455c54
                © The Author(s) 2018

                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/.

                History
                : 18 January 2018
                : 11 May 2018
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001665, Agence Nationale de la Recherche (French National Research Agency);
                Award ID: ANR-12-ADAP-0014-01
                Award ID: ANR-16-CE20-0011-01
                Award ID: ANR-10-INBS-09
                Award ID: ANR-10-LABX-41
                Award Recipient :
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