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      Genetic diversity and population structure of Leishmania (Viannia) braziliensis in the Peruvian jungle

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          Abstract

          Background

          Human cutaneous leishmaniasis caused by Leishmania (Viannia) braziliensis is highly prevalent in the Peruvian jungle, where it affects military forces deployed to fight against drug trafficking and civilian people that migrate from the highland to the lowland jungle for economic activities such as mining, agriculture, construction, and chestnut harvest.

          We explored the genetic diversity and population structure of 124 L. (V. ) braziliensis isolates collected from the highland (Junín, Cusco, and Ayacucho) and lowland Peruvian jungle (Loreto, Ucayali, and Madre de Dios). All samples were genotyped using Multilocus Microsatellite Typing (MLMT) of ten highly polymorphic markers.

          Principal findings

          High polymorphism and genetic diversity were found in Peruvian isolates of L. (V. ) braziliensis. Most markers are not in Hardy-Weinberg equilibrium; this deviation is most likely caused by local inbreeding, as shown by the positive F IS values. Linkage Disequilibrium in subpopulations was not strong, suggesting the reproduction was not strictly clonal. Likewise, for the first time, two genetic clusters of this parasite were determined, distributed in both areas of the Peruvian jungle, which suggested a possible recent colonization event of the highland jungle from the lowland jungle.

          Conclusions

          L. (V. ) braziliensis exhibits considerable genetic diversity with two different clusters in the Peruvian jungle. Migration analysis suggested a colonization event between geographical areas of distribution. Although no human migration was observed at the time of sampling, earlier displacement of humans, reservoirs, or vectors could have been responsible for the parasite spread in both regions.

          Author summary

          L. (V. ) braziliensis is widespread in the Peruvian jungle region. In this region, the departments of Cusco and Madre de Dios account for a large number of patients that get infected while working in the virgin forest. For the first time, we described ample genetic diversity among Peruvian L. (V. ) braziliensis isolates with new alleles that were not previously reported in South America. In addition, two different genetic clusters or subpopulations of L. (V. ) braziliensis in the Amazon Rainforest of Peru were described. This finding reveals the important distribution of parasite populations and suggests a possible colonization event between ecoregions of the highland and lowland Peruvian jungle independently of recent human migration.

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          Most cited references64

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          Detecting the number of clusters of individuals using the software structure: a simulation study

          The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.
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            Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows.

            We present here a new version of the Arlequin program available under three different forms: a Windows graphical version (Winarl35), a console version of Arlequin (arlecore), and a specific console version to compute summary statistics (arlsumstat). The command-line versions run under both Linux and Windows. The main innovations of the new version include enhanced outputs in XML format, the possibility to embed graphics displaying computation results directly into output files, and the implementation of a new method to detect loci under selection from genome scans. Command-line versions are designed to handle large series of files, and arlsumstat can be used to generate summary statistics from simulated data sets within an Approximate Bayesian Computation framework. © 2010 Blackwell Publishing Ltd.
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              STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: ResourcesRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Negl Trop Dis
                PLoS Negl Trop Dis
                plos
                PLoS Neglected Tropical Diseases
                Public Library of Science (San Francisco, CA USA )
                1935-2727
                1935-2735
                23 May 2022
                May 2022
                : 16
                : 5
                : e0010374
                Affiliations
                [1 ] Department of Parasitology, U.S. Naval Medical Research Unit 6, Lima, Peru
                [2 ] Facultad de Ciencias Biológicas, Universidad Nacional Mayor de San Marcos, Lima, Peru
                [3 ] Unidad de Biotecnología Molecular, Universidad Peruana Cayetano Heredia, Lima, Peru
                [4 ] Department of Scientific Computing, Florida State University, Tallahassee, Florida, United States of America
                Charité University Medicine Berlin, GERMANY
                Author notes

                The authors have declared that no competing interests exist.

                [¤]

                Current address: Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium

                Author information
                https://orcid.org/0000-0002-3379-4869
                https://orcid.org/0000-0003-0033-6770
                https://orcid.org/0000-0002-4193-8017
                https://orcid.org/0000-0003-0947-5451
                https://orcid.org/0000-0003-2159-5667
                Article
                PNTD-D-20-02125
                10.1371/journal.pntd.0010374
                9126394
                35605021
                5e86fc26-9c06-4cb2-884f-b07e258e209b

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 5 December 2020
                : 30 March 2022
                Page count
                Figures: 2, Tables: 6, Pages: 18
                Funding
                Funded by: Armed Forces Health Surveillance Division
                Award ID: PROMIS ID P00106_18_N6_04 for FY2018
                Funded by: U.S. National Science Foundation
                Award ID: DBI 1564822
                Award Recipient :
                This work was supported by an award from the Armed Forces Health Surveillance Branch (AFHSB) and its Global Emerging Infections Surveillance and Response (GEIS) Section, PROMIS ID P00106_18_N6_04 for FY2018. PB was partly supported by grant DBI 1564822 from the US National Science Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                People and places
                Geographical locations
                South America
                Brazil
                Biology and Life Sciences
                Ecology
                Ecosystems
                Jungles
                Ecology and Environmental Sciences
                Ecology
                Ecosystems
                Jungles
                Ecology and Environmental Sciences
                Terrestrial Environments
                Jungles
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                Evolutionary Biology
                Population Genetics
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                Genetics
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                Population Biology
                Population Genetics
                People and places
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                South America
                Peru
                Biology and Life Sciences
                Genetics
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                Microsatellite Loci
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                Genetic Loci
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                Biogeography
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                All relevant data are within the manuscript and its Supporting Information files.

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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