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      Population structure and ancestry prediction of Aedes aegypti (Diptera: Culicidae) supports a single African origin of Colombian populations

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          Abstract

          BACKGROUND

          A previous phylogeographic study revealed two Aedes aegypti African-related mitochondrial lineages distributed in Colombian’s cities with different eco-epidemiologic characteristics with regard to dengue virus (DENV). It has been proposed these lineages might indicate independent invasion sources.

          OBJECTIVES

          Assessing to Colombian population structure and to support evidence of its probable source origin.

          METHODS

          We analysed a total of 267 individuals from cities of Bello, Riohacha and Villavicencio, which 241 were related to the West and East African mitochondrial lineages (termed here as WAL and EAL, respectively). Eight polymorphic microsatellite loci were analysed aiming population structure.

          FINDINGS

          Results indicate substantial gene flow among distant and low-connected cities composing a panmictic population with incipient local differentiation of Ae. aegypti is placed in Colombia. Likewise, genetic evidence indicates no significant differences among individuals related to WAL and EAL is placed.

          MAIN CONCLUSIONS

          Minimal genetic differentiation in low-connected Ae. aegypti populations of Colombia, and lack concordance between mitochondrial and nuclear genealogies suggest that Colombian Ae. aegypti shared a common demographic history. Under this scenario, we suggest current Ae. aegypti population structure reflects a single origin instead of contemporary migration, which founding populations have a single source from a mitochondrial polymorphic African ancient.

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          Most cited references57

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          Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

          Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com
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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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              Inference of Population Structure Using Multilocus Genotype Data

              We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.
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                Author and article information

                Journal
                Mem Inst Oswaldo Cruz
                Mem Inst Oswaldo Cruz
                mioc
                Memórias do Instituto Oswaldo Cruz
                Instituto Oswaldo Cruz, Ministério da Saúde
                0074-0276
                1678-8060
                09 July 2021
                2021
                : 116
                : e200441
                Affiliations
                [1 ]Universidad de Antioquia, Grupo de Biología y Control de Enfermedades Infecciosas, Medellin, Colombia
                [2 ]Universidad Pedagógica y Tecnológica de Colombia, Laboratorio de Investigación en Genética Evolutiva, Boyacá, Colombia
                Author notes
                + Corresponding author: amgomezpa@ 123456gmail.com

                YM performed the experiments; YC and AGP designed the experiments, analysed data and wrote the manuscript; OT and AGP were performed the study design, project administration and funding acquisition. All authors read and approved the final manuscript.

                Author information
                http://orcid.org/0000-0002-1069-9199
                Article
                00312
                10.1590/0074-02760200441
                8279122
                34259736
                210e1e38-4e73-4021-aa7d-ff6c5acefb31

                This is an open-access article distributed under the terms of the Creative Commons Attribution License

                History
                : 28 August 2020
                : 07 June 2021
                Page count
                Figures: 2, Tables: 2, References: 52
                Categories
                Original Article

                colombia,genetics,aedes aegypti,population structure,microsatellites

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