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      SNP discovery and genetic mapping using genotyping by sequencing of whole genome genomic DNA from a pea RIL population

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          Abstract

          Background

          Progress in genetics and breeding in pea still suffers from the limited availability of molecular resources. SNP markers that can be identified through affordable sequencing processes, without the need for prior genome reduction or a reference genome to assemble sequencing data would allow the discovery and genetic mapping of thousands of molecular markers. Such an approach could significantly speed up genetic studies and marker assisted breeding for non-model species.

          Results

          A total of 419,024 SNPs were discovered using HiSeq whole genome sequencing of four pea lines, followed by direct identification of SNP markers without assembly using the discoSnp tool. Subsequent filtering led to the identification of 131,850 highly designable SNPs, polymorphic between at least two of the four pea lines.

          A subset of 64,754 SNPs was called and genotyped by short read sequencing on a subpopulation of 48 RILs from the cross ‘Baccara’ x ‘PI180693’. This data was used to construct a WGGBS-derived pea genetic map comprising 64,263 markers. This map is collinear with previous pea consensus maps and therefore with the Medicago truncatula genome. Sequencing of four additional pea lines showed that 33 % to 64 % of the mapped SNPs, depending on the pairs of lines considered, are polymorphic and can therefore be useful in other crosses.

          The subsequent genotyping of a subset of 1000 SNPs, chosen for their mapping positions using a KASP™ assay, showed that almost all generated SNPs are highly designable and that most (95 %) deliver highly qualitative genotyping results. Using rather low sequencing coverages in SNP discovery and in SNP inferring did not hinder the identification of hundreds of thousands of high quality SNPs.

          Conclusions

          The development and optimization of appropriate tools in SNP discovery and genetic mapping have allowed us to make available a massive new genomic resource in pea. It will be useful for both fine mapping within chosen QTL confidence intervals and marker assisted breeding for important traits in pea improvement.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-016-2447-2) contains supplementary material, which is available to authorized users.

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          Most cited references6

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          Single nucleotide polymorphism genotyping using Kompetitive Allele Specific PCR (KASP): overview of the technology and its application in crop improvement

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            CARHTA GENE: multipopulation integrated genetic and radiation hybrid mapping.

            CAR(H)(T)A GENE: is an integrated genetic and radiation hybrid (RH) mapping tool which can deal with multiple populations, including mixtures of genetic and RH data. CAR(H)(T)A GENE: performs multipoint maximum likelihood estimations with accelerated expectation-maximization algorithms for some pedigrees and has sophisticated algorithms for marker ordering. Dedicated heuristics for framework mapping are also included. CAR(H)(T)A GENE: can be used as a C++ library, through a shell command and a graphical interface. The XML output for companion tools is integrated. The program is available free of charge from www.inra.fr/bia/T/CarthaGene for Linux, Windows and Solaris machines (with Open Source). tschiex@toulouse.inra.fr.
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              Mapping with RAD (restriction-site associated DNA) markers to rapidly identify QTL for stem rust resistance in Lolium perenne.

              A mapping population was created to detect quantitative trait loci (QTL) for resistance to stem rust caused by Puccinia graminis subsp. graminicola in Lolium perenne. A susceptible and a resistant plant were crossed to produce a pseudo-testcross population of 193 F(1) individuals. Markers were produced by the restriction-site associated DNA (RAD) process, which uses massively parallel and multiplexed sequencing of reduced-representation libraries. Additional simple sequence repeat (SSR) and sequence-tagged site (STS) markers were combined with the RAD markers to produce maps for the female (738 cM) and male (721 cM) parents. Stem rust phenotypes (number of pustules per plant) were determined in replicated greenhouse trials by inoculation with a field-collected, genetically heterogeneous population of urediniospores. The F(1) progeny displayed continuous distribution of phenotypes and transgressive segregation. We detected three resistance QTL. The most prominent QTL (qLpPg1) is located near 41 cM on linkage group (LG) 7 with a 2-LOD interval of 8 cM, and accounts for 30-38% of the stem rust phenotypic variance. QTL were detected also on LG1 (qLpPg2) and LG6 (qLpPg3), each accounting for approximately 10% of phenotypic variance. Alleles of loci closely linked to these QTL originated from the resistant parent for qLpPg1 and from both parents for qLpPg2 and qLpPg3. Observed quantitative nature of the resistance may be due to partial-resistance effects against all pathogen genotypes, or qualitative effects completely preventing infection by only some genotypes in the genetically mixed inoculum. RAD markers facilitated rapid construction of new genetic maps in this outcrossing species and will enable development of sequence-based markers linked to stem rust resistance in L. perenne.
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                Author and article information

                Contributors
                gilles.boutet@rennes.inra.fr
                susete.ac@gmail.com
                matthieu.falque@moulon.inra.fr
                pierre.peterlongo@inria.fr
                emeline.lhuillier@udear.cnrs.fr
                olivier.bouchez@toulouse.inra.fr
                clement.lavaud@rennes.inra.fr
                marie-laure.pilet@rennes.inra.fr
                nathalie.riviere@biogemma.com
                alain.baranger@rennes.inra.fr
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                18 February 2016
                18 February 2016
                2016
                : 17
                : 121
                Affiliations
                [ ]INRA, UMR 1349 IGEPP, BP35327, Le Rheu Cedex, 35653 France
                [ ]INRA, UMR Génétique Quantitative et Evolution – Le Moulon, INRA - Univ Paris-Sud - CNRS - AgroParisTech, Ferme du Moulon, 91190 Gif-sur-Yvette, France
                [ ]INRIA Rennes - Bretagne Atlantique/IRISA, EPI GenScale, Rennes, 35042 France
                [ ]GeT-PlaGe, Genotoul, INRA Auzeville F31326, Castanet-tolosan, France
                [ ]Biogemma, route d’Ennezat, CS90126, Chappes, 63720 France
                [ ]INRA, UMR1388 INRA/ENVT/ENSAT GenPhySE, INRA Auzeville F31326, Castanet-tolosan, France
                [ ]PISOM, UMT INRA/CETIOM, BP35327, Le Rheu Cedex, 35653 France
                Article
                2447
                10.1186/s12864-016-2447-2
                4758021
                26892170
                e05204e6-fdbe-4fb6-bf5b-817f16192fd2
                © Boutet et al. 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
                : 22 September 2015
                : 8 February 2016
                Funding
                Funded by: French National FASO (Fonds d'Action Stratégique des Oléoprotéagineux)
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                Genetics
                aphanomyces euteiches,pisum sativum,next generation sequencing,marker assisted selection,qtl

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