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      Population structure and genetic diversity characterization of a sunflower association mapping population using SSR and SNP markers

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          Abstract

          Background

          Argentina has a long tradition of sunflower breeding, and its germplasm is a valuable genetic resource worldwide. However, knowledge of the genetic constitution and variability levels of the Argentinean germplasm is still scarce, rendering the global map of cultivated sunflower diversity incomplete. In this study, 42 microsatellite loci and 384 single nucleotide polymorphisms (SNPs) were used to characterize the first association mapping population used for quantitative trait loci mapping in sunflower, along with a selection of allied open-pollinated and composite populations from the germplasm bank of the National Institute of Agricultural Technology of Argentina. The ability of different kinds of markers to assess genetic diversity and population structure was also evaluated.

          Results

          The analysis of polymorphism in the set of sunflower accessions studied here showed that both the microsatellites and SNP markers were informative for germplasm characterization, although to different extents. In general, the estimates of genetic variability were moderate. The average genetic diversity, as quantified by the expected heterozygosity, was 0.52 for SSR loci and 0.29 for SNPs. Within SSR markers, those derived from non-coding regions were able to capture higher levels of diversity than EST-SSR. A significant correlation was found between SSR and SNP- based genetic distances among accessions. Bayesian and multivariate methods were used to infer population structure. Evidence for the existence of three different genetic groups was found consistently across data sets ( i.e., SSR, SNP and SSR + SNP), with the maintainer/restorer status being the most prevalent characteristic associated with group delimitation.

          Conclusion

          The present study constitutes the first report comparing the performance of SSR and SNP markers for population genetics analysis in cultivated sunflower. We show that the SSR and SNP panels examined here, either used separately or in conjunction, allowed consistent estimations of genetic diversity and population structure in sunflower breeding materials. The generated knowledge about the levels of diversity and population structure of sunflower germplasm is an important contribution to this crop breeding and conservation.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12870-014-0360-x) contains supplementary material, which is available to authorized users.

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          Most cited references48

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          Estimation of average heterozygosity and genetic distance from a small number of individuals.

          M Nei (1978)
          The magnitudes of the systematic biases involved in sample heterozygosity and sample genetic distances are evaluated, and formulae for obtaining unbiased estimates of average heterozygosity and genetic distance are developed. It is also shown that the number of individuals to be used for estimating average heterozygosity can be very small if a large number of loci are studied and the average heterozygosity is low. The number of individuals to be used for estimating genetic distance can also be very small if the genetic distance is large and the average heterozygosity of the two species compared is low.
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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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              Numerical Ecology

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                Author and article information

                Contributors
                cfilippi@cnia.inta.gov.ar
                naguirre@cnia.inta.gov.ar
                grivas@cnia.inta.gov.ar
                jzubrzycki@cnia.inta.gov.ar
                apuebla@cnia.inta.gov.ar
                cordes.diego@inta.gob.ar
                mvmoreno@manfredi.inta.gov.ar
                cfusari@cnia.inta.gov.ar
                alvarez.daniel@inta.gob.ar
                rheinz@cnia.inta.gov.ar
                ehopp@cnia.inta.gov.ar
                npaniego@cnia.inta.gov.ar
                lia.veronica@inta.gob.ar
                Journal
                BMC Plant Biol
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central (London )
                1471-2229
                13 February 2015
                13 February 2015
                2015
                : 15
                : 52
                Affiliations
                [ ]Instituto de Biotecnología, Centro de Investigaciones en Ciencias Veterinarias y Agronómicas (CICVyA), Instituto Nacional de Tecnología Agropecuaria (INTA), Nicolás Repetto y Los Reseros s/n (1686), Hurlingham, Buenos Aires Argentina
                [ ]Consejo Nacional de Investigaciones Científicas y Técnicas–CONICET, Saavedra 15, C1083ACA Ciudad Autónoma de Buenos Aires, Argentina
                [ ]Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabellón 2, Ciudad Universitaria (1428), Buenos Aires, Argentina
                [ ]Estación Experimental Agropecuaria Manfredi, Ruta Nac. nro. 9 km 636 (5988), Manfredi, Córdoba (INTA) Argentina
                [ ]Currently at System Regulation Group, Metabolic Networks Department, Max Planck Institute of Molecular Plant Physiology, Am Mühlemberg 1, D-14476 Potsdam-Golm, Germany
                Article
                360
                10.1186/s12870-014-0360-x
                4351844
                39b5ebf5-0e19-4cb5-95d1-979d83a6eda0
                © Filippi et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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
                : 27 March 2014
                : 27 November 2014
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Plant science & Botany
                sunflower breeding,genetic resources,snp,ssr,association mapping
                Plant science & Botany
                sunflower breeding, genetic resources, snp, ssr, association mapping

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