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      Tracking the return of Aedes aegypti to Brazil, the major vector of the dengue, chikungunya and Zika viruses

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          Abstract

          Background

          Aedes aegypti, commonly known as “the yellow fever mosquito”, is of great medical concern today primarily as the major vector of dengue, chikungunya and Zika viruses, although yellow fever remains a serious health concern in some regions. The history of Ae. aegypti in Brazil is of particular interest because the country was subjected to a well-documented eradication program during 1940s-1950s. After cessation of the campaign, the mosquito quickly re-established in the early 1970s with several dengue outbreaks reported during the last 30 years. Brazil can be considered the country suffering the most from the yellow fever mosquito, given the high number of dengue, chikungunya and Zika cases reported in the country, after having once been declared “free of Ae. aegypti”.

          Methodology/Principal findings

          We used 12 microsatellite markers to infer the genetic structure of Brazilian Ae. aegypti populations, genetic variability, genetic affinities with neighboring geographic areas, and the timing of their arrival and spread. This enabled us to reconstruct their recent history and evaluate whether the reappearance in Brazil was the result of re-invasion from neighboring non-eradicated areas or re-emergence from local refugia surviving the eradication program. Our results indicate a genetic break separating the northern and southern Brazilian Ae. aegypti populations, with further genetic differentiation within each cluster, especially in southern Brazil.

          Conclusions/Significance

          Based on our results, re-invasions from non-eradicated regions are the most likely scenario for the reappearance of Ae. aegypti in Brazil. While populations in the northern cluster are likely to have descended from Venezuela populations as early as the 1970s, southern populations seem to have derived more recently from northern Brazilian areas. Possible entry points are also revealed within both southern and northern clusters that could inform strategies to control and monitor this important arbovirus vector.

          Author summary

          Aedes aegypti (“yellow fever mosquito”) is of great medical concern because it is the primary vector of important viruses causing dengue fever, chikungunya and Zika, as well as increasingly transmitting yellow fever once again. Due to the Zika outbreak, which started in Brazil in 2015 and rapidly spread with million cases reported in Central/South America and the Caribbean, this mosquito has attained special notoriety. Brazil is by far the most affected country not only by Zika, but also by dengue and chikungunya. Interestingly, in 1950s Brazil had been declared “free of Ae. aegypti” after a well-documented eradication program. However, during the last 45 years Ae. aegypti reappeared in Brazil causing several dengue outbreaks, with millions of reported cases. Here, we used genetic data to study the reappearance of Ae. aegypti in Brazil after the putative eradication event. Our results support re-invasion; mosquitoes from the non-eradicated areas in Venezuela invaded North Brazil, later expanding their distribution southwards. We also identify specific locations in Brazil, as possible entry points. This knowledge can inform strategies to control the spread of the vector and of the diseases it transmits.

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          Most cited references48

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          Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power.

          Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (DLR) appeared to be an effective way to predict whether F0 immigrants could be identified for a particular pair of populations using a given set of markers.
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            Detecting immigration by using multilocus genotypes.

            Immigration is an important force shaping the social structure, evolution, and genetics of populations. A statistical method is presented that uses multilocus genotypes to identify individuals who are immigrants, or have recent immigrant ancestry. The method is appropriate for use with allozymes, microsatellites, or restriction fragment length polymorphisms (RFLPs) and assumes linkage equilibrium among loci. Potential applications include studies of dispersal among natural populations of animals and plants, human evolutionary studies, and typing zoo animals of unknown origin (for use in captive breeding programs). The method is illustrated by analyzing RFLP genotypes in samples of humans from Australian, Japanese, New Guinean, and Senegalese populations. The test has power to detect immigrant ancestors, for these data, up to two generations in the past even though the overall differentiation of allele frequencies among populations is low.
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              Isolation by distance, web service

              Background The population genetic pattern known as "isolation by distance" results from spatially limited gene flow and is a commonly observed phenomenon in natural populations. However, few software programs exist for estimating the degree of isolation by distance among populations, and they tend not to be user-friendly. Results We have created Isolation by Distance Web Service (IBDWS) a user-friendly web interface for determining patterns of isolation by distance. Using this site, population geneticists can perform a variety of powerful statistical tests including Mantel tests, Reduced Major Axis (RMA) regression analysis, as well as calculate F ST between all pairs of populations and perform basic summary statistics (e.g., heterozygosity). All statistical results, including publication-quality scatter plots in Postscript format, are returned rapidly to the user and can be easily downloaded. Conclusion IBDWS population genetics analysis software is hosted at and documentation is available at . The source code has been made available on Source Forge at .
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Negl Trop Dis
                PLoS Negl Trop Dis
                plos
                plosntds
                PLoS Neglected Tropical Diseases
                Public Library of Science (San Francisco, CA USA )
                1935-2727
                1935-2735
                25 July 2017
                July 2017
                : 11
                : 7
                : e0005653
                Affiliations
                [1 ] Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, United States of America
                [2 ] Laboratório de Biologia Computacional e Sistemas, IOC–Fiocruz, Rio de Janeiro, Brazil
                [3 ] Laboratório de Fisiologia e Controle de Artrópodes Vetores, IOC-FIOCRUZ, Rio de Janeiro, Brazil
                University of Texas Medical Branch, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                • Conceptualization: JRP.

                • Formal analysis: PK JRP AC.

                • Investigation: RS AGS.

                • Resources: AJM RS BE.

                • Writing – original draft: PK AC JRP.

                • Writing – review & editing: PK AGS BE AJM RS AC JRP.

                Author information
                http://orcid.org/0000-0002-8007-5330
                Article
                PNTD-D-17-00121
                10.1371/journal.pntd.0005653
                5526527
                28742801
                af94dd12-6a16-48a9-b7d8-0f2cc8bde5e0
                © 2017 Kotsakiozi 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
                : 26 January 2017
                : 19 May 2017
                Page count
                Figures: 4, Tables: 1, Pages: 20
                Funding
                PK was supported by the Bodossaki Foundation in Greece. RS and AJM were supported by grants from the Brazilian Health ministry (CNPq and Fiocruz) and the Rio de Janeiro state research foundation (Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro -FAPERJ) and the National Institute of Science and Technology - Molecular Entomology (INCT-EM). Financial support was provided by NIAID RO1 AI101112 and UO1 AI115595 awarded to JRP. The funders had no role in the 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
                Evolutionary Biology
                Population Genetics
                Biology and Life Sciences
                Genetics
                Population Genetics
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Medicine and Health Sciences
                Infectious Diseases
                Disease Vectors
                Insect Vectors
                Mosquitoes
                Aedes Aegypti
                Biology and Life Sciences
                Species Interactions
                Disease Vectors
                Insect Vectors
                Mosquitoes
                Aedes Aegypti
                Biology and Life Sciences
                Organisms
                Animals
                Invertebrates
                Arthropoda
                Insects
                Mosquitoes
                Aedes Aegypti
                People and places
                Geographical locations
                South America
                Venezuela
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                Evolutionary Biology
                Population Genetics
                Gene Flow
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                Genetics
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                Biology and Life Sciences
                Population Biology
                Population Genetics
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                North America
                Caribbean
                Biology and Life Sciences
                Genetics
                Genetic Loci
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                North America
                Caribbean
                Dominica
                Custom metadata
                All relevant data are within the paper and its Supporting Information files. In addition, the data contained in S1 Appendix will be available on VectorBase.org as of October 2017.

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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