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      Expanded host and geographic range of tadpole associations with the Severe Perkinsea Infection group

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          Abstract

          Severe Perkinsea infection is an emerging disease of amphibians, specifically tadpoles. Disease presentation correlates with liver infections of a subclade of Perkinsea (Alveolata) protists, named Pathogenic Perkinsea Clade (PPC). Tadpole mortality events associated with PPC infections have been reported across North America, from Alaska to Florida. Here, we investigate the geographic and host range of PPC associations in seemingly healthy tadpoles sampled from Panama, a biogeographic provenance critically affected by amphibian decline. To complement this work, we also investigate a mortality event among Hyla arborea tadpoles in captive-bred UK specimens. PPC SSU rDNA was detected in 10 of 81 Panama tadpoles tested, and H. arborea tadpoles from the UK. Phylogenies of the Perkinsea SSU rDNA sequences demonstrate they are highly similar to PPC sequences sampled from mortality events in the USA, and phylogenetic analysis of tadpole mitochondrial SSU rDNA demonstrates, for the first time, PPC associations in diverse hylids. These data provide further understanding of the biogeography and host range of this putative pathogenic group, factors likely to be important for conservation planning.

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          Most cited references34

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          IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

          Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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            ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

            Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.
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              SeaView version 4: A multiplatform graphical user interface for sequence alignment and phylogenetic tree building.

              We present SeaView version 4, a multiplatform program designed to facilitate multiple alignment and phylogenetic tree building from molecular sequence data through the use of a graphical user interface. SeaView version 4 combines all the functions of the widely used programs SeaView (in its previous versions) and Phylo_win, and expands them by adding network access to sequence databases, alignment with arbitrary algorithm, maximum-likelihood tree building with PhyML, and display, printing, and copy-to-clipboard of rooted or unrooted, binary or multifurcating phylogenetic trees. In relation to the wide present offer of tools and algorithms for phylogenetic analyses, SeaView is especially useful for teaching and for occasional users of such software. SeaView is freely available at http://pbil.univ-lyon1.fr/software/seaview.
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                Author and article information

                Contributors
                Journal
                Biol Lett
                RSBL
                roybiolett
                Biology Letters
                The Royal Society
                1744-9561
                1744-957X
                June 16, 2021
                June 2021
                June 16, 2021
                : 17
                : 6
                : 20210166
                Affiliations
                [ 1 ]Living Systems Institute and Biosciences, University of Exeter, , Exeter, Devon EX4 4QD, UK
                [ 2 ]Institute of Parasitology, Biology Centre, Czech Academy of Sciences, , 370 05 České Budějovice, Czech Republic
                [ 3 ]Department of Zoology, University of Oxford, , Oxford OX1 3SZ, UK
                [ 4 ]Smithsonian Tropical Research Institute, , Panamá, Republic of Panama
                [ 5 ]Sistema Nacional de Investigación, SENACYT, , Panamá, Republic of Panama
                [ 6 ]Smithsonian National Zoo and Conservation Biology Institute, , Washington D.C., USA
                [ 7 ]Faculty of Sciences, University of South Bohemia, , 370 05 České Budějovice, Czech Republic
                [ 8 ]CNRS, Université of Brest, IRD, Ifremer, LEMAR, , Plouzané, France
                Author notes

                Electronic supplementary material is available online at https://doi.org/10.6084/m9.figshare.c.5448491.

                Author information
                http://orcid.org/0000-0002-1904-8843
                http://orcid.org/0000-0003-3669-7463
                http://orcid.org/0000-0002-9692-0973
                Article
                rsbl20210166
                10.1098/rsbl.2021.0166
                8205526
                34129800
                56e1bcf4-1476-4413-85eb-543b2a9a7929
                © 2021 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : March 25, 2020
                : May 24, 2021
                Funding
                Funded by: Office of the Royal Society, http://dx.doi.org/10.13039/501100008134;
                Award ID: CHG\R1\170042
                Award ID: UF130382
                Funded by: H2020 European Research Council, http://dx.doi.org/10.13039/100010663;
                Award ID: J.L. is supported by the grant ERC CZ LL1601 and t
                Funded by: ERD Funds of the Czech Ministry of Education;
                Award ID: 16_019/0000759
                Funded by: Agence Nationale de la Recherche, http://dx.doi.org/10.13039/501100001665;
                Award ID: ANR-16_ACHN_0003
                Funded by: H2020 Marie Skłodowska-Curie Actions, http://dx.doi.org/10.13039/100010665;
                Award ID: ITN project SINGEK (http://www.singek.eu/; agreeme
                Funded by: French Nationalprogram EC2CO;
                Award ID: Ecosphère Continentale et côtière - N°13046
                Funded by: Institute of Parasitology, BC CAS;
                Award ID: RVO 60077344
                Categories
                1001
                60
                87
                Conservation Biology
                Research Articles

                Life sciences
                frog disease,amphibian conservation,alveolate parasites
                Life sciences
                frog disease, amphibian conservation, alveolate parasites

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