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      Genetic variability and evolutionary dynamics of viruses of the family Closteroviridae

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          Abstract

          RNA viruses have a great potential for genetic variation, rapid evolution and adaptation. Characterization of the genetic variation of viral populations provides relevant information on the processes involved in virus evolution and epidemiology and it is crucial for designing reliable diagnostic tools and developing efficient and durable disease control strategies. Here we performed an updated analysis of sequences available in Genbank and reviewed present knowledge on the genetic variability and evolutionary processes of viruses of the family Closteroviridae. Several factors have shaped the genetic structure and diversity of closteroviruses. (I) A strong negative selection seems to be responsible for the high genetic stability in space and time for some viruses. (2) Long distance migration, probably by human transport of infected propagative plant material, have caused that genetically similar virus isolates are found in distant geographical regions. (3) Recombination between divergent sequence variants have generated new genotypes and plays an important role for the evolution of some viruses of the family Closteroviridae. (4) Interaction between virus strains or between different viruses in mixed infections may alter accumulation of certain strains. (5) Host change or virus transmission by insect vectors induced changes in the viral population structure due to positive selection of sequence variants with higher fitness for host-virus or vector-virus interaction (adaptation) or by genetic drift due to random selection of sequence variants during the population bottleneck associated to the transmission process.

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          Analyzing the mosaic structure of genes.

          Some genes in prokaryotes consist of a mosaic of regions derived from different ancestors by horizontal gene transfer. A method is described for demonstrating the statistical significance of such mosaic structure and for locating the crossover points separating different regions.
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            A modified bootscan algorithm for automated identification of recombinant sequences and recombination breakpoints.

            We have developed a modified BOOTSCAN algorithm that may be used to screen nucleotide sequence alignments for evidence of recombination without prior identification of nonrecombinant reference sequences. The algorithm is fast and includes a Bonferroni corrected statistical test of recombination to circumvent the multiple testing problems encountered when using the BOOTSCAN method to explore alignments for evidence of recombination. Using both simulated and real datasets we demonstrate that the modified algorithm is more powerful than other phylogenetic recombination detection methods and performs almost as well as one of the best substitution distribution recombination detection methods.
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              An exact nonparametric method for inferring mosaic structure in sequence triplets.

              Statistical tests for detecting mosaic structure or recombination among nucleotide sequences usually rely on identifying a pattern or a signal that would be unlikely to appear under clonal reproduction. Dozens of such tests have been described, but many are hampered by long running times, confounding of selection and recombination, and/or inability to isolate the mosaic-producing event. We introduce a test that is exact, nonparametric, rapidly computable, free of the infinite-sites assumption, able to distinguish between recombination and variation in mutation/fixation rates, and able to identify the breakpoints and sequences involved in the mosaic-producing event. Our test considers three sequences at a time: two parent sequences that may have recombined, with one or two breakpoints, to form the third sequence (the child sequence). Excess similarity of the child sequence to a candidate recombinant of the parents is a sign of recombination; we take the maximum value of this excess similarity as our test statistic Delta(m,n,b). We present a method for rapidly calculating the distribution of Delta(m,n,b) and demonstrate that it has comparable power to and a much improved running time over previous methods, especially in detecting recombination in large data sets.
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                Author and article information

                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                26 June 2013
                2013
                : 4
                : 151
                Affiliations
                Instituto Valenciano de Investigaciones Agrarias Moncada, Valencia, Spain
                Author notes

                Edited by: Ricardo Flores, Instituto de Biología Molecular y Celular de Plantas, Spain

                Reviewed by: Scott J. Harper, University of Florida, USA; Ioannis E. Tzanetakis, University of Arkansas, USA

                *Correspondence: Luis Rubio, Instituto Valenciano de Investigaciones Agrarias, Ctra. Moncada-Naquera Km 5, 46113 Moncada, Valencia, Spain e-mail: lrubio@ 123456ivia.es

                This article was submitted to Frontiers in Virology, a specialty of Frontiers in Microbiology.

                Article
                10.3389/fmicb.2013.00151
                3693128
                23805130
                02389afd-5726-467b-bf86-480664fdab06
                Copyright © 2013 Rubio, Guerri and Moreno.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

                History
                : 15 February 2013
                : 29 May 2013
                Page count
                Figures: 1, Tables: 2, Equations: 0, References: 174, Pages: 15, Words: 13239
                Categories
                Microbiology
                Original Research Article

                Microbiology & Virology
                closterovirus,crinivirus,ampelovirus,recombination,selection,phylogeny,gene flow
                Microbiology & Virology
                closterovirus, crinivirus, ampelovirus, recombination, selection, phylogeny, gene flow

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