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      East African cassava mosaic-like viruses from Africa to Indian ocean islands: molecular diversity, evolutionary history and geographical dissemination of a bipartite begomovirus

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          Abstract

          Background

          Cassava (Manihot esculenta) is a major food source for over 200 million sub-Saharan Africans. Unfortunately, its cultivation is severely hampered by cassava mosaic disease (CMD). Caused by a complex of bipartite cassava mosaic geminiviruses (CMG) species (Family: Geminivirideae; Genus: Begomovirus) CMD has been widely described throughout Africa and it is apparent that CMG's are expanding their geographical distribution. Determining where and when CMG movements have occurred could help curtail its spread and reveal the ecological and anthropic factors associated with similar viral invasions. We applied Bayesian phylogeographic inference and recombination analyses to available and newly described CMG sequences to reconstruct a plausible history of CMG diversification and migration between Africa and South West Indian Ocean (SWIO) islands.

          Results

          The isolation and analysis of 114 DNA-A and 41 DNA-B sequences demonstrated the presence of three CMG species circulating in the Comoros and Seychelles archipelagos (East African cassava mosaic virus, EACMV; East African cassava mosaic Kenya virus, EACMKV; and East African cassava mosaic Cameroon virus, EACMCV). Phylogeographic analyses suggest that CMG’s presence on these SWIO islands is probably the result of at least four independent introduction events from mainland Africa occurring between 1988 and 2009. Amongst the islands of the Comoros archipelago, two major migration pathways were inferred: One from Grande Comore to Mohéli and the second from Mayotte to Anjouan. While only two recombination events characteristic of SWIO islands isolates were identified, numerous re-assortments events were detected between EACMV and EACMKV, which seem to almost freely interchange their genome components.

          Conclusions

          Rapid and extensive virus spread within the SWIO islands was demonstrated for three CMG complex species. Strong evolutionary or ecological interaction between CMG species may explain both their propensity to exchange components and the absence of recombination with non-CMG begomoviruses. Our results suggest an important role of anthropic factors in CMGs spread as the principal axes of viral migration correspond with major routes of human movement and commercial trade. Finer-scale temporal analyses of CMGs to precisely scale the relative contributions of human and insect transmission to their movement dynamics will require further extensive sampling in the SWIO region.

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          Most cited references34

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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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            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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              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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                Author and article information

                Journal
                BMC Evol Biol
                BMC Evol. Biol
                BMC Evolutionary Biology
                BioMed Central
                1471-2148
                2012
                27 November 2012
                : 12
                : 228
                Affiliations
                [1 ]CIRAD, UMR PVBMT, Pôle de Protection des Plantes, 7 Chemin de l’IRAT, Saint-Pierre, Ile de La Réunion, 97410, France
                [2 ]Université de La Réunion, UMR PVBMT, Pôle de Protection des Plantes, 7 Chemin de l’IRAT, Saint-Pierre, Ile de La Réunion, 97410, France
                [3 ]Service de Protection des Végétaux - Direction de l’Agriculture et de la Forêt, B.P 103, Mamoudzou, Mayotte, 97600, France
                [4 ]Institut National de Recherche pour l’Agriculture, la Pêche et l’Environnement, BP289, Moroni, Grande Comore, Union des Comores
                [5 ]South African National Bioinformatics Institute, University of the Western Cape, Cape Town, South Africa
                [6 ]School of Biological Sciences, University of Canterbury, Private Bag 4800, Christchurch, New Zealand
                [7 ]Biomolecular interaction centre, University of Canterbury, Private Bag 4800, Christchurch, New Zealand
                [8 ]Electron Microscope Unit, University of Cape Town, Rondebosch, 7701, Cape Town, South Africa
                [9 ]Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Observatory 7925, Cape Town, South Africa
                Article
                1471-2148-12-228
                10.1186/1471-2148-12-228
                3560262
                23186303
                3969716b-9d91-4bab-a014-4eb0f0fd730d
                Copyright ©2012 De Bruyn et al.; 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
                : 1 August 2012
                : 15 November 2012
                Categories
                Research Article

                Evolutionary Biology
                cassava,recombination,phylogeography,dissemination,africa,begomoviruses
                Evolutionary Biology
                cassava, recombination, phylogeography, dissemination, africa, begomoviruses

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