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      Divergent regional evolutionary histories of a devastating global amphibian pathogen

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          Abstract

          Emerging infectious diseases are a pressing threat to global biological diversity. Increased incidence and severity of novel pathogens underscores the need for methodological advances to understand pathogen emergence and spread. Here, we use genetic epidemiology to test, and challenge, key hypotheses about a devastating zoonotic disease impacting amphibians globally. Using an amplicon-based sequencing method and non-invasive samples we retrospectively explore the history of the fungal pathogen Batrachochytrium dendrobatidis ( Bd) in two emblematic amphibian systems: the Sierra Nevada of California and Central Panama. The hypothesis in both regions is the hypervirulent Global Panzootic Lineage of Bd ( BdGPL) was recently introduced and spread rapidly in a wave-like pattern. Our data challenge this hypothesis by demonstrating similar epizootic signatures can have radically different underlying evolutionary histories. In Central Panama, our genetic data confirm a recent and rapid pathogen spread. However, BdGPL in the Sierra Nevada has remarkable spatial structuring, high genetic diversity and a relatively older history inferred from time-dated phylogenies. Thus, this deadly pathogen lineage may have a longer history in some regions than assumed, providing insights into its origin and spread. Overall, our results highlight the importance of integrating observed wildlife die-offs with genetic data to more accurately reconstruct pathogen outbreaks.

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          Most cited references64

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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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            Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7

            Abstract Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more. Tracer is open-source and available at http://beast.community/tracer.
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              adegenet: a R package for the multivariate analysis of genetic markers.

              The package adegenet for the R software is dedicated to the multivariate analysis of genetic markers. It extends the ade4 package of multivariate methods by implementing formal classes and functions to manipulate and analyse genetic markers. Data can be imported from common population genetics software and exported to other software and R packages. adegenet also implements standard population genetics tools along with more original approaches for spatial genetics and hybridization. Stable version is available from CRAN: http://cran.r-project.org/mirrors.html. Development version is available from adegenet website: http://adegenet.r-forge.r-project.org/. Both versions can be installed directly from R. adegenet is distributed under the GNU General Public Licence (v.2).
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing-original draftRole: Writing-review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing-original draftRole: Writing-review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: VisualizationRole: Writing-original draftRole: Writing-review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: SupervisionRole: Writing-original draftRole: Writing-review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: SupervisionRole: Writing-original draftRole: Writing-review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: VisualizationRole: Writing-original draftRole: Writing-review & editing
                Journal
                Proc Biol Sci
                Proc Biol Sci
                RSPB
                royprsb
                Proceedings of the Royal Society B: Biological Sciences
                The Royal Society
                0962-8452
                1471-2954
                June 30, 2021
                June 23, 2021
                June 23, 2021
                : 288
                : 1953
                : 20210782
                Affiliations
                [ 1 ]Department of Environmental Science, Policy, and Management, University of California Berkeley, , Berkeley, CA, USA
                [ 2 ]Museum of Vertebrate Zoology, University of California Berkeley, , Berkeley, CA, USA
                [ 3 ]Center for Conservation Genomics, Smithsonian Conservation Biology Institute, National Zoological Park, , Washington, DC, USA
                [ 4 ]Sierra Nevada Aquatic Research Laboratory, University of California, , Mammoth Lakes, CA, USA
                [ 5 ]Earth Research Institute, University of California, , Santa Barbara, CA, USA
                [ 6 ]Department of Ecology, Evolution, and Marine Biology, University of California, , Santa Barbara, CA, USA
                [ 7 ]Department of Biology, University of Nevada, , Reno, NV, USA
                [ 8 ]Department of Biological Sciences, University of Pittsburgh, , Pittsburgh, PA, USA
                Author notes

                Electronic supplementary material is available online at https://doi.org/10.6084/m9.figshare.c.5459508.

                Author information
                http://orcid.org/0000-0002-1329-8702
                Article
                rspb20210782
                10.1098/rspb.2021.0782
                8220259
                34157877
                7c3abc1f-9144-4e16-b4d4-d7f967f3b156
                © 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
                : April 6, 2021
                : May 28, 2021
                Funding
                Funded by: Division of Environmental Biology, http://dx.doi.org/10.13039/100000155;
                Award ID: 1457695
                Award ID: 1551488
                Award ID: 1557190
                Award ID: 166311
                Funded by: National Park Service, http://dx.doi.org/10.13039/100007516;
                Funded by: DOD SERDP;
                Categories
                1001
                60
                70
                198
                Global Change and Conservation
                Research Articles
                Custom metadata
                June 30, 2021

                Life sciences
                wildlife disease,batrachochytrium dendrobatidis,genetic epidemiology,population genetics,amphibians

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