6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Population genomics meet Lagrangian simulations: Oceanographic patterns and long larval duration ensure connectivity among Paracentrotus lividus populations in the Adriatic and Ionian seas

      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

          Connectivity between populations influences both their dynamics and the genetic structuring of species. In this study, we explored connectivity patterns of a marine species with long‐distance dispersal, the edible common sea urchin Paracentrotus lividus, focusing mainly on the Adriatic–Ionian basins (Central Mediterranean). We applied a multidisciplinary approach integrating population genomics, based on 1,122 single nucleotide polymorphisms ( SNPs) obtained from 2b‐ RAD in 275 samples, with Lagrangian simulations performed with a biophysical model of larval dispersal. We detected genetic homogeneity among eight population samples collected in the focal Adriatic–Ionian area, whereas weak but significant differentiation was found with respect to two samples from the Western Mediterranean (France and Tunisia). This result was not affected by the few putative outlier loci identified in our dataset. Lagrangian simulations found a significant potential for larval exchange among the eight Adriatic–Ionian locations, supporting the hypothesis of connectivity of P. lividus populations in this area. A peculiar pattern emerged from the comparison of our results with those obtained from published P. lividus cytochrome b (cytb) sequences, the latter revealing genetic differentiation in the same geographic area despite a smaller sample size and a lower power to detect differences. The comparison with studies conducted using nuclear markers on other species with similar pelagic larval durations in the same Adriatic–Ionian locations indicates species‐specific differences in genetic connectivity patterns and warns against generalizing single‐species results to the entire community of rocky shore habitats.

          Related collections

          Most cited references70

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

          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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

            NIH Image to ImageJ: 25 years of image analysis.

            For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity.

              We review commonly used population definitions under both the ecological paradigm (which emphasizes demographic cohesion) and the evolutionary paradigm (which emphasizes reproductive cohesion) and find that none are truly operational. We suggest several quantitative criteria that might be used to determine when groups of individuals are different enough to be considered 'populations'. Units for these criteria are migration rate (m) for the ecological paradigm and migrants per generation (Nm) for the evolutionary paradigm. These criteria are then evaluated by applying analytical methods to simulated genetic data for a finite island model. Under the standard parameter set that includes L = 20 High mutation (microsatellite-like) loci and samples of S = 50 individuals from each of n = 4 subpopulations, power to detect departures from panmixia was very high ( approximately 100%; P < 0.001) even with high gene flow (Nm = 25). A new method, comparing the number of correct population assignments with the random expectation, performed as well as a multilocus contingency test and warrants further consideration. Use of Low mutation (allozyme-like) markers reduced power more than did halving S or L. Under the standard parameter set, power to detect restricted gene flow below a certain level X (H(0): Nm < X) can also be high, provided that true Nm < or = 0.5X. Developing the appropriate test criterion, however, requires assumptions about several key parameters that are difficult to estimate in most natural populations. Methods that cluster individuals without using a priori sampling information detected the true number of populations only under conditions of moderate or low gene flow (Nm < or = 5), and power dropped sharply with smaller samples of loci and individuals. A simple algorithm based on a multilocus contingency test of allele frequencies in pairs of samples has high power to detect the true number of populations even with Nm = 25 but requires more rigorous statistical evaluation. The ecological paradigm remains challenging for evaluations using genetic markers, because the transition from demographic dependence to independence occurs in a region of high migration where genetic methods have relatively little power. Some recent theoretical developments and continued advances in computational power provide hope that this situation may change in the future.
                Bookmark

                Author and article information

                Contributors
                lorenzo.zane@unipd.it
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                14 March 2017
                April 2017
                : 7
                : 8 ( doiID: 10.1002/ece3.2017.7.issue-8 )
                : 2463-2479
                Affiliations
                [ 1 ] Department of BiologyUniversity of Padova PadovaItaly
                [ 2 ]Consorzio Nazionale Interuniversitario per le Scienze del Mare (CoNISMa) RomaItaly
                [ 3 ] Dipartimento di Elettronica, Informazione e BioingegneriaPolitecnico di Milano MilanoItaly
                [ 4 ] Department of Biological and Environmental Sciences and TechnologiesUniversity of Salento LecceItaly
                [ 5 ]Institut National Agronomique de Tunisie (INAT) TunisTunisia
                [ 6 ] USR 3278 CNRS‐EPHE CRIOBEUniversité de Perpignan Via Dominitia Perpignan CedexFrance
                [ 7 ] Department for Earth, Environment and Life Sciences (DiSTAV)University of Genoa GenoaItaly
                [ 8 ]University of Zadar ZadarCroatia
                [ 9 ]Institute of Marine Biology Kotor (IBMK) KotorMontenegro
                [ 10 ] Department of Comparative Biomedicine and Food ScienceUniversity of Padova Legnaro PadovaItaly
                Author notes
                [*] [* ] Correspondence

                Lorenzo Zane, Department of Biology, University of Padova, Padova, Italy.

                Email: lorenzo.zane@ 123456unipd.it

                Author information
                http://orcid.org/0000-0002-6963-2132
                Article
                ECE32844
                10.1002/ece3.2844
                5395429
                28428839
                611d899e-c908-424f-9380-1fb65a4e5ed9
                © 2017 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 02 November 2016
                : 20 January 2017
                : 28 January 2017
                Page count
                Figures: 5, Tables: 5, Pages: 17, Words: 14756
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                ece32844
                April 2017
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.0.9 mode:remove_FC converted:18.04.2017

                Evolutionary Biology
                2b‐rad,biophysical models,population genomics,sea urchin,seascape genetics,snps
                Evolutionary Biology
                2b‐rad, biophysical models, population genomics, sea urchin, seascape genetics, snps

                Comments

                Comment on this article