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      Molecular Evolution and Spatial Transmission of Severe Fever with Thrombocytopenia Syndrome Virus Based on Complete Genome Sequences

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          Abstract

          Severe fever with thrombocytopenia syndrome virus (SFTSV) was a novel tick-borne bunyavirus that caused hemorrhagic fever with a high fatality rate in East Asia. In this study we analyzed the complete genome sequences of 122 SFTSV strains to determine the phylogeny, evolution and reassortment of the virus. We revealed that the evolutionary rate of three genome segments were different, with highest in the S segment and lowest in the L segment. The SFTSV strains were phylogenetically classified into 5 lineages (A, B, C, D and E) with each genome segment. SFTSV strains from China were classified in all 5 lineages, strains from South Korea were classified into 3 lineages (A, D, and E), and all strains from Japan were classified in only linage E. Using the average evolutionary rate of the three genome segments, we found that the extant SFTSV originated 20–87 years ago in the Dabie Mountain area in central China. The viruses were then transmitted to other areas of China, Japan and South Korea. We also found that six SFTSV strains were reassortants. Selection pressure analysis suggested that SFTSV was under purifying selection according to the four genes (RNA-dependent RNA polymerase, glycoprotein, nucleocapsid protein, non-structural protein), and two sites (37, 1033) of glycoproteins were identified as being under strong positive selection. We concluded that SFTSV originated in central China and spread to other places recently and the virus was under purifying selection with high frequency of reassortment.

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          Most cited references33

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          Host species barriers to influenza virus infections.

          Most emerging infectious diseases in humans originate from animal reservoirs; to contain and eradicate these diseases we need to understand how and why some pathogens become capable of crossing host species barriers. Influenza virus illustrates the interaction of factors that limit the transmission and subsequent establishment of an infection in a novel host species. Influenza species barriers can be categorized into virus-host interactions occurring within individuals and host-host interactions, either within or between species, that affect transmission between individuals. Viral evolution can help surmount species barriers, principally by affecting virus-host interactions; however, evolving the capability for sustained transmission in a new host species represents a major adaptive challenge because the number of mutations required is often large.
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            Using Time-Structured Data to Estimate Evolutionary Rates of Double-Stranded DNA Viruses

            Abstract Double-stranded (ds) DNA viruses are often described as evolving through long-term codivergent associations with their hosts, a pattern that is expected to be associated with low rates of nucleotide substitution. However, the hypothesis of codivergence between dsDNA viruses and their hosts has rarely been rigorously tested, even though the vast majority of nucleotide substitution rate estimates for dsDNA viruses are based upon this assumption. It is therefore important to estimate the evolutionary rates of dsDNA viruses independent of the assumption of host-virus codivergence. Here, we explore the use of temporally structured sequence data within a Bayesian framework to estimate the evolutionary rates for seven human dsDNA viruses, including variola virus (VARV) (the causative agent of smallpox) and herpes simplex virus-1. Our analyses reveal that although the VARV genome is likely to evolve at a rate of approximately 1 × 10−5 substitutions/site/year and hence approaching that of many RNA viruses, the evolutionary rates of many other dsDNA viruses remain problematic to estimate. Synthetic data sets were constructed to inform our interpretation of the substitution rates estimated for these dsDNA viruses and the analysis of these demonstrated that given a sequence data set of appropriate length and sampling depth, it is possible to use time-structured analyses to estimate the substitution rates of many dsDNA viruses independently from the assumption of host-virus codivergence. Finally, the discovery that some dsDNA viruses may evolve at rates approaching those of RNA viruses has important implications for our understanding of the long-term evolutionary history and emergence potential of this major group of viruses.
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              Temporal and spatial analysis of the 2014–2015 Ebola virus outbreak in West Africa

              Analysis of 179 new Ebola virus sequences from patient samples collected in Guinea between March 2014 and January 2015 shows how different lineages evolved and spread in West Africa. Supplementary information The online version of this article (doi:10.1038/nature14594) contains supplementary material, which is available to authorized users. Miles Carroll and colleagues report describe the genetic evolution of Ebola virus circulating in West Africa, based on 179 new virus sequences from patient samples collected in Guinea between March 2014 and January 2015. Their analysis shows how different lineages evolved and spread in West Africa between Sierra Leone, Guinea and Liberia. Supplementary information The online version of this article (doi:10.1038/nature14594) contains supplementary material, which is available to authorized users. West Africa is currently witnessing the most extensive Ebola virus (EBOV) outbreak so far recorded 1 , 2 , 3 . Until now, there have been 27,013 reported cases and 11,134 deaths. The origin of the virus is thought to have been a zoonotic transmission from a bat to a two-year-old boy in December 2013 (ref. 2 ). From this index case the virus was spread by human-to-human contact throughout Guinea, Sierra Leone and Liberia. However, the origin of the particular virus in each country and time of transmission is not known and currently relies on epidemiological analysis, which may be unreliable owing to the difficulties of obtaining patient information. Here we trace the genetic evolution of EBOV in the current outbreak that has resulted in multiple lineages. Deep sequencing of 179 patient samples processed by the European Mobile Laboratory, the first diagnostics unit to be deployed to the epicentre of the outbreak in Guinea, reveals an epidemiological and evolutionary history of the epidemic from March 2014 to January 2015. Analysis of EBOV genome evolution has also benefited from a similar sequencing effort of patient samples from Sierra Leone. Our results confirm that the EBOV from Guinea moved into Sierra Leone, most likely in April or early May. The viruses of the Guinea/Sierra Leone lineage mixed around June/July 2014. Viral sequences covering August, September and October 2014 indicate that this lineage evolved independently within Guinea. These data can be used in conjunction with epidemiological information to test retrospectively the effectiveness of control measures, and provides an unprecedented window into the evolution of an ongoing viral haemorrhagic fever outbreak. Supplementary information The online version of this article (doi:10.1038/nature14594) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                21 March 2016
                2016
                : 11
                : 3
                : e0151677
                Affiliations
                [1 ]School of Public Health, Shandong University, Jinan, Shandong Province, China
                [2 ]Department of Pathology, University of Texas Medical Branch, Galveston, Texas, United States of America
                University of Minnesota College of Veterinary Medicine, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: XJY LZ JWL. Performed the experiments: JWL. Analyzed the data: JWL XJY. Contributed reagents/materials/analysis tools: LML MML YS XS. Wrote the paper: JWL XJY.

                Article
                PONE-D-15-50437
                10.1371/journal.pone.0151677
                4801363
                26999664
                d734c9f6-a5b0-439a-b252-b05201b5e454
                © 2016 Liu et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 November 2015
                : 2 March 2016
                Page count
                Figures: 3, Tables: 2, Pages: 13
                Funding
                This work was supported by a grant from Shandong Province Science and Technology Development Program (2014GSF121004) and a grant from the National Nature Science Foundation of China (31570167).
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