47
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Phylogeography of Sardinian Cave Salamanders (Genus Hydromantes) Is Mainly Determined by Geomorphology

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Detecting the factors that determine the interruption of gene flow between populations is key to understanding how speciation occurs. In this context, caves are an excellent system for studying processes of colonization, differentiation and speciation, since they represent discrete geographical units often with known geological histories. Here, we asked whether discontinuous calcareous areas and cave systems represent major barriers to gene flow within and among the five species of Sardinian cave salamanders (genus Hydromantes) and whether intraspecific genetic structure parallels geographic distance within and among caves. We generated mitochondrial cytochrome b gene sequences from 184 individuals representing 48 populations, and used a Bayesian phylogeographic approach to infer possible areas of cladogenesis for these species and reconstruct historical and current dispersal routes among distinct populations. Our results show deep genetic divergence within and among all Sardinian cave salamander species, which can mostly be attributed to the effects of mountains and discontinuities in major calcareous areas and cave systems acting as barriers to gene flow. While these salamander species can also occur outside caves, our results indicate that there is a very poor dispersal of these species between separate cave systems.

          Related collections

          Most cited references123

          • Record: found
          • Abstract: found
          • Article: not found

          MRBAYES: Bayesian inference of phylogenetic trees.

          The program MRBAYES performs Bayesian inference of phylogeny using a variant of Markov chain Monte Carlo. MRBAYES, including the source code, documentation, sample data files, and an executable, is available at http://brahms.biology.rochester.edu/software.html.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            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 .
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A simulated annealing approach to define the genetic structure of populations.

              We present a new approach for defining groups of populations that are geographically homogeneous and maximally differentiated from each other. As a by-product, it also leads to the identification of genetic barriers between these groups. The method is based on a simulated annealing procedure that aims to maximize the proportion of total genetic variance due to differences between groups of populations (spatial analysis of molecular variance; samova). Monte Carlo simulations were used to study the performance of our approach and, for comparison, the behaviour of the Monmonier algorithm, a procedure commonly used to identify zones of sharp genetic changes in a geographical area. Simulations showed that the samova algorithm indeed finds maximally differentiated groups, which do not always correspond to the simulated group structure in the presence of isolation by distance, especially when data from a single locus are available. In this case, the Monmonier algorithm seems slightly better at finding predefined genetic barriers, but can often lead to the definition of groups of populations not differentiated genetically. The samova algorithm was then applied to a set of European roe deer populations examined for their mitochondrial DNA (mtDNA) HVRI diversity. The inferred genetic structure seemed to confirm the hypothesis that some Italian populations were recently reintroduced from a Balkanic stock, as well as the differentiation of groups of populations possibly due to the postglacial recolonization of Europe or the action of a specific barrier to gene flow.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                12 March 2012
                : 7
                : 3
                : e32332
                Affiliations
                [1 ]Institut des Sciences de l'Evolution, CNRS-UMR n° 5554, CC 064, Université Montpellier II, Montpellier, France
                [2 ]Centro de Investigação em Biodiversidade e Recursos Genéticos Campus Agrário de Vairão, Vairão, Portugal
                [3 ]Gruppo Speleologico Sassarese, Sassari, Italy
                [4 ]Department of Biogeography, Trier University, Trier, Germany
                University of Arkanas, United States of America
                Author notes

                Conceived and designed the experiments: YC AvdM MM MV. Performed the experiments: AvdM AH. Analyzed the data: YC AvdM JL. Contributed reagents/materials/analysis tools: MV. Wrote the paper: YC. Did field work: YC AvdM MM MV. Fine-tuned the manuscript: YC AH.

                Article
                PONE-D-11-19243
                10.1371/journal.pone.0032332
                3299655
                22427830
                f4836c95-8043-47a8-ada4-face4e5c68ca
                Chiari 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
                : 29 September 2011
                : 25 January 2012
                Page count
                Pages: 15
                Categories
                Research Article
                Biology
                Evolutionary Biology
                Evolutionary Processes
                Evolutionary Systematics
                Population Genetics
                Zoology

                Uncategorized
                Uncategorized

                Comments

                Comment on this article