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      Evolutionary Insights from a Genetically Divergent Hantavirus Harbored by the European Common Mole ( Talpa europaea)

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          Abstract

          Background

          The discovery of genetically distinct hantaviruses in shrews (Order Soricomorpha, Family Soricidae) from widely separated geographic regions challenges the hypothesis that rodents (Order Rodentia, Family Muridae and Cricetidae) are the primordial reservoir hosts of hantaviruses and also predicts that other soricomorphs harbor hantaviruses. Recently, novel hantavirus genomes have been detected in moles of the Family Talpidae, including the Japanese shrew mole ( Urotrichus talpoides) and American shrew mole ( Neurotrichus gibbsii). We present new insights into the evolutionary history of hantaviruses gained from a highly divergent hantavirus, designated Nova virus (NVAV), identified in the European common mole ( Talpa europaea) captured in Hungary.

          Methodology/Principal Findings

          Pair-wise alignment and comparison of the full-length S- and L-genomic segments indicated moderately low sequence similarity of 54–65% and 46–63% at the nucleotide and amino acid levels, respectively, between NVAV and representative rodent- and soricid-borne hantaviruses. Despite the high degree of sequence divergence, the predicted secondary structure of the NVAV nucleocapsid protein exhibited the characteristic coiled-coil domains at the amino-terminal end, and the L-segment motifs, typically found in hantaviruses, were well conserved. Phylogenetic analyses, using maximum-likelihood and Bayesian methods, showed that NVAV formed a distinct clade that was evolutionarily distant from all other hantaviruses.

          Conclusions

          Newly identified hantaviruses harbored by shrews and moles support long-standing virus-host relationships and suggest that ancestral soricomorphs, rather than rodents, may have been the early or original mammalian hosts.

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          Most cited references53

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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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              Prediction of protein secondary structure at better than 70% accuracy.

              We have trained a two-layered feed-forward neural network on a non-redundant data base of 130 protein chains to predict the secondary structure of water-soluble proteins. A new key aspect is the use of evolutionary information in the form of multiple sequence alignments that are used as input in place of single sequences. The inclusion of protein family information in this form increases the prediction accuracy by six to eight percentage points. A combination of three levels of networks results in an overall three-state accuracy of 70.8% for globular proteins (sustained performance). If four membrane protein chains are included in the evaluation, the overall accuracy drops to 70.2%. The prediction is well balanced between alpha-helix, beta-strand and loop: 65% of the observed strand residues are predicted correctly. The accuracy in predicting the content of three secondary structure types is comparable to that of circular dichroism spectroscopy. The performance accuracy is verified by a sevenfold cross-validation test, and an additional test on 26 recently solved proteins. Of particular practical importance is the definition of a position-specific reliability index. For half of the residues predicted with a high level of reliability the overall accuracy increases to better than 82%. A further strength of the method is the more realistic prediction of segment length. The protein family prediction method is available for testing by academic researchers via an electronic mail server.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2009
                7 July 2009
                : 4
                : 7
                : e6149
                Affiliations
                [1 ]Pacific Center for Emerging Infectious Diseases Research, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, United States of America
                [2 ]Department of Microbiology, College of Medicine, Institute for Viral Diseases and Bank for Pathogenic Viruses, Korea University, Seoul, Korea
                [3 ]Infectious Disease Surveillance Center, National Institute of Infectious Diseases, Tokyo, Japan
                [4 ]Department of Biology and Museum of Southwestern Biology, University of New Mexico, Albuquerque, New Mexico, United States of America
                [5 ]Pacific Biosciences Research Center, University of Hawaii at Manoa, Honolulu, Hawaii, United States of America
                Institute of Molecular and Cell Biology, Singapore
                Author notes

                Conceived and designed the experiments: HJK SB RY. Performed the experiments: HJK LS. Analyzed the data: HJK SB GM JAC RY. Contributed reagents/materials/analysis tools: HJK SB SA AGH GM JWS JAC. Wrote the paper: HJK SB GM JAC RY.

                Article
                09-PONE-RA-09542R1
                10.1371/journal.pone.0006149
                2702001
                19582155
                b4883601-a782-48cc-a5ae-053c7564bada
                Kang 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
                : 1 April 2009
                : 4 June 2009
                Page count
                Pages: 12
                Categories
                Research Article
                Virology/Emerging Viral Diseases
                Virology/Virus Evolution and Symbiosis
                Infectious Diseases/Viral Infections

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                Uncategorized

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