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      Analysis of the genetic diversity and structure across a wide range of germplasm reveals prominent gene flow in apple at the European level

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          Abstract

          Background

          The amount and structure of genetic diversity in dessert apple germplasm conserved at a European level is mostly unknown, since all diversity studies conducted in Europe until now have been performed on regional or national collections. Here, we applied a common set of 16 SSR markers to genotype more than 2,400 accessions across 14 collections representing three broad European geographic regions (North + East, West and South) with the aim to analyze the extent, distribution and structure of variation in the apple genetic resources in Europe.

          Results

          A Bayesian model-based clustering approach showed that diversity was organized in three groups, although these were only moderately differentiated (F ST = 0.031). A nested Bayesian clustering approach allowed identification of subgroups which revealed internal patterns of substructure within the groups, allowing a finer delineation of the variation into eight subgroups (F ST = 0.044). The first level of stratification revealed an asymmetric division of the germplasm among the three groups, and a clear association was found with the geographical regions of origin of the cultivars. The substructure revealed clear partitioning of genetic groups among countries, but also interesting associations between subgroups and breeding purposes of recent cultivars or particular usage such as cider production. Additional parentage analyses allowed us to identify both putative parents of more than 40 old and/or local cultivars giving interesting insights in the pedigree of some emblematic cultivars.

          Conclusions

          The variation found at group and subgroup levels may reflect a combination of historical processes of migration/selection and adaptive factors to diverse agricultural environments that, together with genetic drift, have resulted in extensive genetic variation but limited population structure. The European dessert apple germplasm represents an important source of genetic diversity with a strong historical and patrimonial value. The present work thus constitutes a decisive step in the field of conservation genetics. Moreover, the obtained data can be used for defining a European apple core collection useful for further identification of genomic regions associated with commercially important horticultural traits in apple through genome-wide association studies.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12870-016-0818-0) contains supplementary material, which is available to authorized users.

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          Most cited references59

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          Estimating the probability of identity among genotypes in natural populations: cautions and guidelines.

          Individual identification using DNA fingerprinting methods is emerging as a critical tool in conservation genetics and molecular ecology. Statistical methods that estimate the probability of sampling identical genotypes using theoretical equations generally assume random associations between alleles within and among loci. These calculations are probably inaccurate for many animal and plant populations due to population substructure. We evaluated the accuracy of a probability of identity (P(ID)) estimation by comparing the observed and expected P(ID), using large nuclear DNA microsatellite data sets from three endangered species: the grey wolf (Canis lupus), the brown bear (Ursus arctos), and the Australian northern hairy-nosed wombat (Lasiorinyus krefftii). The theoretical estimates of P(ID) were consistently lower than the observed P(ID), and can differ by as much as three orders of magnitude. To help researchers and managers avoid potential problems associated with this bias, we introduce an equation for P(ID) between sibs. This equation provides an estimator that can be used as a conservative upper bound for the probability of observing identical multilocus genotypes between two individuals sampled from a population. We suggest computing the actual observed P(ID) when possible and give general guidelines for the number of codominant and dominant marker loci required to achieve a reasonably low P(ID) (e.g. 0.01-0.0001).
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            spagedi: a versatile computer program to analyse spatial genetic structure at the individual or population levels

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              Current trends in microsatellite genotyping.

              Microsatellites have been popular molecular markers ever since their advent in the late eighties. Despite growing competition from new genotyping and sequencing techniques, the use of these versatile and cost-effective markers continues to increase, boosted by successive technical advances. First, methods for multiplexing PCR have considerably improved over the last years, thereby decreasing genotyping costs and increasing throughput. Second, next-generation sequencing technologies allow the identification of large numbers of microsatellite loci at reduced cost in non-model species. As a consequence, more stringent selection of loci is possible, thereby further enhancing multiplex quality and efficiency. However, current practices are lagging behind. By surveying recently published population genetic studies relying on simple sequence repeats, we show that more than half of the studies lack appropriate quality controls and do not make use of multiplex PCR. To make the most of the latest technical developments, we outline the need for a well-established strategy including standardized high-throughput bench protocols and specific bioinformatic tools, from primer design to allele calling. © 2011 Blackwell Publishing Ltd.
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                Author and article information

                Contributors
                charles-eric.durel@angers.inra.fr
                Journal
                BMC Plant Biol
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central (London )
                1471-2229
                8 June 2016
                8 June 2016
                2016
                : 16
                : 130
                Affiliations
                [ ]IRHS, INRA, AGROCAMPUS-Ouest, Université d’Angers, SFR 4207 QUASAV, 42 rue Georges Morel, 49071 Beaucouzé cedex, France
                [ ]Department of Agricultural Sciences, University of Bologna, Viale Giuseppe Fanin 44, 40127 Bologna, Italy
                [ ]Plateforme Gentyane, INRA UMR1095 Genetics, Diversity and Ecophysiology of Cereals, 63100 Clermont-Ferrand, France
                [ ]CRA-W, Centre Wallon de Recherches Agronomiques, Plant Breeding & Biodiversity, Bâtiment Emile Marchal, Rue de Liroux, 4 - 5030 Gembloux, Belgium
                [ ]School of Agriculture, Policy and Development, University of Reading, Whiteknights, Reading, RG6 6AR UK
                [ ]NIAB EMR, East Malling Research, East Malling, Kent, ME19 6BJ United Kingdom
                [ ]Washington State University Tree Fruit Research and Extension Center, 1100 N Western Ave, Wenatchee, WA 98801 USA
                [ ]RBIPH, Research and Breeding Institute of Pomology Holovousy Ltd., 508 01 Horice, Czech Republic
                [ ]Department of Plant Breeding, Balsgård, Fjälkestadsvägen 459, Swedish University of Agricultural Sciences, 291 94 Kristianstad, Sweden
                [ ]Department of Plant Breeding, Swedish University of Agricultural Sciences, Box 101, 230 53 Alnarp, Sweden
                [ ]Public University of Navarre (UPNA), Campus Arrosadia, 31006 Pamplona, Spain
                [ ]Agroscope, Institute for Plant Production Sciences IPS, Schloss 1, P.O. Box, 8820, Wädenswil, Switzerland
                [ ]NCRRIH&V, North Caucasian Regional Research Institute of Horticulture and Viticulture, 39, 40-letiya Pobedy street, Krasnodar, 350901 Russian Federation
                [ ]VNIISPK, The All Russian Research Institute of Fruit Crop Breeding, 302530, p/o Zhilina, Orel district, Russian Federation
                [ ]Kyrgyz National Agrarian University, 68 Mederova Street, 720005, Bishkek Kyrgyzstan
                Article
                818
                10.1186/s12870-016-0818-0
                4898379
                27277533
                108b9b3a-a7bb-4019-87c0-a2d9e0fe8290
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 23 February 2016
                : 23 May 2016
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                Plant science & Botany
                malus x domestica borkh.,genetic resources,population structure,variability,ssr markers,differentiation,parentage analysis

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