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      Asymmetric Reproductive Barriers and Gene Flow Promote the Rise of a Stable Hybrid Zone in the Mediterranean High Mountain

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          Abstract

          Hybrid zones have the potential to shed light on evolutionary processes driving adaptation and speciation. Secondary contact hybrid zones are particularly powerful natural systems for studying the interaction between divergent genomes to understand the mode and rate at which reproductive isolation accumulates during speciation. We have studied a total of 720 plants belonging to five populations from two Erysimum (Brassicaceae) species presenting a contact zone in the Sierra Nevada mountains (SE Spain). The plants were phenotyped in 2007 and 2017, and most of them were genotyped the first year using 10 microsatellite markers. Plants coming from natural populations were grown in a common garden to evaluate the reproductive barriers between both species by means of controlled crosses. All the plants used for the field and greenhouse study were characterized by measuring traits related to plant size and flower size. We estimated the genetic molecular variances, the genetic differentiation, and the genetic structure by means of the F-statistic and Bayesian inference. We also estimated the amount of recent gene flow between populations. We found a narrow unimodal hybrid zone where the hybrid genotypes appear to have been maintained by significant levels of a unidirectional gene flow coming from parental populations and from weak reproductive isolation between them. Hybrid plants exhibited intermediate or vigorous phenotypes depending on the analyzed trait. The phenotypic differences between the hybrid and the parental plants were highly coherent between the field and controlled cross experiments and through time. The highly coherent results obtained by combining field, experimental, and genetic data demonstrate the existence of a stable and narrow unimodal hybrid zone between Erysimum mediohispanicum and Erysimum nevadense at the high elevation of the Sierra Nevada mountains.

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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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            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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              Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows.

              We present here a new version of the Arlequin program available under three different forms: a Windows graphical version (Winarl35), a console version of Arlequin (arlecore), and a specific console version to compute summary statistics (arlsumstat). The command-line versions run under both Linux and Windows. The main innovations of the new version include enhanced outputs in XML format, the possibility to embed graphics displaying computation results directly into output files, and the implementation of a new method to detect loci under selection from genome scans. Command-line versions are designed to handle large series of files, and arlsumstat can be used to generate summary statistics from simulated data sets within an Approximate Bayesian Computation framework. © 2010 Blackwell Publishing Ltd.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                25 August 2021
                2021
                : 12
                : 687094
                Affiliations
                [1] 1Departamento de Genética, Facultad de Ciencias, Campus Fuentenueva, Universidad de Granada , Granada, Spain
                [2] 2Laboratório Associado, Plant Biology, Research Centre in Biodiversity and Genetic Resources, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade Do Porto, Campus Agrário de Vairão , Fornelo e Vairão, Portugal
                [3] 3Research Unit Modeling Nature, Universidad de Granada , Granada, Spain
                [4] 4Departamento de Ecología Funcional y Evolutiva, Estación Experimental de Zonas Áridas, Consejo Superior de Investigaciones Científicas , Almeria, Spain
                Author notes

                Edited by: Andrew A. Crowl, Duke University, United States

                Reviewed by: Adrian Christopher Brennan, Durham University, United Kingdom; Santiago Martín-Bravo, Universidad Pablo de Olavide, Spain

                *Correspondence: Mohamed Abdelaziz mabdelazizm@ 123456ugr.es

                This article was submitted to Plant Systematics and Evolution, a section of the journal Frontiers in Plant Science

                †These authors have contributed equally to this work and share first authorship

                Article
                10.3389/fpls.2021.687094
                8424041
                34512685
                b7b23b86-c93c-4fa5-a587-26ce632fb28c
                Copyright © 2021 Abdelaziz, Muñoz-Pajares, Berbel, García-Muñoz, Gómez and Perfectti.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 28 March 2021
                : 15 July 2021
                Page count
                Figures: 3, Tables: 6, Equations: 2, References: 102, Pages: 14, Words: 10856
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                hybridization,erysimum mediohispanicum,erysimum nevadense,sierra nevada,phenotype,reproductive isolation

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