5
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Genomic Evidence for Sequestration of Influenza A Virus Lineages in Sea Duck Host Species

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Wild birds are considered the natural reservoir of influenza A viruses (IAVs) making them critical for IAV surveillance efforts. While sea ducks have played a role in novel IAV emergence events that threatened food security and public health, very few surveillance samples have been collected from sea duck hosts. From 2014–2018, we conducted surveillance focused in the Mississippi flyway, USA at locations where sea duck harvest has been relatively successful compared to our other sampling locations. Our surveillance yielded 1662 samples from sea ducks, from which we recovered 77 IAV isolates. Our analyses identified persistence of sea duck specific IAV lineages across multiple years. We also recovered sea duck origin IAVs containing an H4 gene highly divergent from the majority of North American H4-HA with clade node age of over 65 years. Identification of IAVs with long branch lengths is indicative of substantial genomic change consistent with persistence without detection by surveillance efforts. Sea ducks play a role in the movement and long-term persistence of IAVs and are likely harboring more undetected IAV diversity. Sea ducks should be a point of emphasis for future North American wild bird IAV surveillance efforts.

          Related collections

          Most cited references41

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

            Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments

              Background We recently described FastTree, a tool for inferring phylogenies for alignments with up to hundreds of thousands of sequences. Here, we describe improvements to FastTree that improve its accuracy without sacrificing scalability. Methodology/Principal Findings Where FastTree 1 used nearest-neighbor interchanges (NNIs) and the minimum-evolution criterion to improve the tree, FastTree 2 adds minimum-evolution subtree-pruning-regrafting (SPRs) and maximum-likelihood NNIs. FastTree 2 uses heuristics to restrict the search for better trees and estimates a rate of evolution for each site (the “CAT” approximation). Nevertheless, for both simulated and genuine alignments, FastTree 2 is slightly more accurate than a standard implementation of maximum-likelihood NNIs (PhyML 3 with default settings). Although FastTree 2 is not quite as accurate as methods that use maximum-likelihood SPRs, most of the splits that disagree are poorly supported, and for large alignments, FastTree 2 is 100–1,000 times faster. FastTree 2 inferred a topology and likelihood-based local support values for 237,882 distinct 16S ribosomal RNAs on a desktop computer in 22 hours and 5.8 gigabytes of memory. Conclusions/Significance FastTree 2 allows the inference of maximum-likelihood phylogenies for huge alignments. FastTree 2 is freely available at http://www.microbesonline.org/fasttree.
                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Viruses
                Viruses
                viruses
                Viruses
                MDPI
                1999-4915
                24 January 2021
                February 2021
                : 13
                : 2
                : 172
                Affiliations
                [1 ]Department of Veterinary Preventive Medicine, College of Veterinary Medicine, The Ohio State University, Columbus, OH 43210, USA; mcbride.338@ 123456osu.edu (D.S.M.); lauterbach.7@ 123456osu.edu (S.E.L.); nolting.4@ 123456osu.edu (J.M.N.)
                [2 ]Programme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore; yaotli@ 123456u.duke.nus.edu (Y.-T.L.); gavin.smith@ 123456duke-nus.edu.sg (G.J.D.S.); yvonne.su@ 123456duke-nus.edu.sg (Y.C.F.S.)
                [3 ]Diagnostic Virology Laboratory, National Veterinary Services Laboratories, APHIS, USDA, 1920 Dayton Avenue, Ames, IA 50010, USA; mary.l.killian@ 123456usda.gov
                Author notes
                [* ]Correspondence: bowman.214@ 123456osu.edu ; Tel.: +1-(614)-292-6923; Fax: +1-(614)-292-4142
                Author information
                https://orcid.org/0000-0002-7408-3959
                https://orcid.org/0000-0001-5031-468X
                https://orcid.org/0000-0002-2705-4805
                https://orcid.org/0000-0002-0738-8453
                Article
                viruses-13-00172
                10.3390/v13020172
                7911388
                33498851
                c9756eec-1e7e-4aca-a180-01f4f1cfc908
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 31 December 2020
                : 21 January 2021
                Categories
                Article

                Microbiology & Virology
                influenza a virus,ducks,birds,genomics,prevalence,united states,great lakes region
                Microbiology & Virology
                influenza a virus, ducks, birds, genomics, prevalence, united states, great lakes region

                Comments

                Comment on this article