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Phylogeography, colonization and population history of the Midas cichlid species complex (Amphilophus spp.) in the Nicaraguan crater lakes

1 , 2 , , 1

BMC Evolutionary Biology

BioMed Central

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      Abstract

      Background

      Elucidation of the mechanisms driving speciation requires detailed knowledge about the phylogenetic relationships and phylogeography of the incipient species within their entire ranges as well as their colonization history. The Midas cichlid species complex Amphilophus spp. has been proven to be a powerful model system for the study of ecological specialization, sexual selection and the mechanisms of sympatric speciation. Here we present a comprehensive and integrative phylogeographic analysis of the complete Midas Cichlid species complex in Nicaragua (> 2000 individuals) covering the entire distributional range, using two types of molecular markers (the mitochondrial DNA control region and 15 microsatellites). We investigated the majority of known lake populations of this species complex and reconstructed their colonization history in order to distinguish between alternative speciation scenarios.

      Results

      We found that the large lakes contain older and more diverse Midas Cichlid populations, while all crater lakes hold younger and genetically less variable species assemblages. The large lakes appear to have repeatedly acted as source populations for all crater lakes, and our data indicate that faunal exchange among crater lakes is extremely unlikely. Despite their very recent (often only a few thousand years old) and common origin from the two large Nicaraguan lakes, all crater lake Midas Cichlid radiations underwent independent, but parallel, evolution, and comprise distinct genetic units. Indeed several of these crater lakes contain multiple genetically distinct incipient species that most likely arose through sympatric speciation. Several crater lake radiations can be traced back to a single ancestral line, but some appear to have more than one founding lineage. The timing of the colonization(s) of each crater lake differs, although most of them occurred more (probably much more) recently than 20,000 years ago.

      Conclusion

      The genetic differentiation of the crater lake populations is directly related to the number of founding lineages, but independent of the timing of colonization. Interestingly, levels of phenotypic differentiation, and speciation events, appeared independent of both factors.

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      Most cited references 76

      • Record: found
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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/ approximately pritch/home. html.
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          • Record: found
          • Abstract: not found
          • Article: not found

          Estimating F-Statistics for the Analysis of Population Structure

           B Weir,  C. Cockerham (1984)
            Bookmark

            Author and article information

            Affiliations
            [1 ]Lehrstuhl für Zoologie und Evolutionsbiologie, Department of Biology, University of Konstanz, Universitätsstrasse 10, 78457 Konstanz, Germany
            [2 ]Museo Nacional de Ciencias Naturales CSIC, José Gutiérrez Abascal 2, 28006 Madrid, Spain
            Contributors
            Journal
            BMC Evol Biol
            BMC Evolutionary Biology
            BioMed Central
            1471-2148
            2010
            26 October 2010
            : 10
            : 326
            3087546
            1471-2148-10-326
            20977752
            10.1186/1471-2148-10-326
            Copyright ©2010 Barluenga and Meyer; licensee BioMed Central Ltd.

            This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

            Categories
            Research Article

            Evolutionary Biology

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