International Workshop Advances in Plant Biotechnology for Crop Improvement INAT, 18-20 April 2016 Assessment of genetic diversity for subsequent improvement of confection sunflower in Tunisia Khoufi Sahari1*, Ben Jeddi Fayçal1,Brunel Dominique2 1 Laboratoire des Sciences Horticoles, Institut National Agronomique de Tunisie, 43, avenue Charles Nicolle 1082 Tunis-Mahrajène Tunisie. *: [email protected] 2 US Etude du Polymorphisme des Génomes Végétaux, INRA, CEA/IG/Centre National de Génotypage, Université Paris Saclay, 2 rue Gaston Crémieux, 91057 Evry Cedex, France. Introduction Sunflower (Helianthus annuus L.) is cultivated and consumed in Tunisia mainly as confectionery seeds, which correspond to cultivars with particular phenotypic characteristics (seed size, 100 seed weight, color…). We focused on studying the genetic variation among a collection of 59 populations of cultivated sunflower in Tunisia, combining SSR and SNP as molecular markers in order to start a new plant breeding program. Materials and methods Fig. 1: Sites of sampled populations of sunflower (Helianthus annuus L.) used in this study, circled population represent the core collection. Plant material: 59 sunflower populations (Fig. 1) and 7 reference varieties * (SF012, SF193, SF085, SF332, SF092, SF109 Var Turk). DNA extraction: Total genomic DNA was extracted using DNeasy 96 Plant Kit (QIAGEN, Valencia, CA). DNA sequencing: was conducted with Illumina Sequencing Systems. Bioinformatic analysis: were conducted with CLC Genomics Workbench (v7). SSR assay: 56 Primers *covering 17 linkage groups. Statisticle analysis: Factorial Correspondence Analysis (FCA) was conducted using XLSTAT software (V1.06). SNP assay: EFE, EXECUTER1, AVP1, CG068, P5CS2, LPT3a and LPT3b genes*. Core collections: was performed with MSTRAT software version v4 (Gouesnard et al., 2001). *: reference varieties, SSR markers and genes are provided by the laboratory of Plant-Microbe Interactions (LIPM) INRA Toulouse. Results and Discussion A total of 194 alleles were observed for thirty microsatellite loci (3-10 alleles per locus) and 54 haplotypes corresponding to 117 SNPs identified by NGS sequencing of seven candidate genes (416 haplotypes per gene). No relation was found between genetic and geographical distance within Tunisian populations (r = 0.08; p = 0.18), which suggests seed exchanges between farmers, or agricultural institutes. Factorial correspondence analysis (FCA) highlighted some genetic originality of the Tunisian material compared to six reference varieties from different countries (Fig. 2). Fig. 2: Distribution of reference varieties and Tunisian populations of sunflower according to factors 1 and 2 of FCA based on SSR (a) and SNP (b) markers. MSTRAT generated a core collection: [Hat28 (Slougia), Hat15 (Dougga), Hat40 (Oued Zarga), Hat20 (Ksar Mezouar), Hat25 (Ain Chelou), Hat43 (Sejane), Hat11 (Tounga), and Hat65 (Oued Beja), capturing 90 % of molecular allelic content of the 59 populations (Fig. 3). Conclusion This study highlighted the genetic originality of the Tunisian material compared to reference varieties. No geographical structure was noted, however 8 populations were sorted out by SNP and SSR markers representing a core collection for future improvement of sunflower. Acknowledgements: We thank Nicolas Pouilly, Aurélie Bérard for laboratory assistance, Fig. 3: Comparison of the effectiveness in sampling genetic diversity between the M strategy (top curve) and the random strategy (bottom curve), according to the number of populations of the core collection. Molecular data (SSR and SNP) are the “active variables. Patrick,Vincourt, Stéphane Muños for data analysis and Brigitte Gouesnard for MSTRAT analysis and discussions. Funding for this study was provided by the laboratory of Plant-Microbe Interactions (LIPM) and US_EPGV (Etude du Polymorphisme des Génomes Végétaux) of the French National Institute for Agricultural Research (INRA). References Gouesnard, B., Bataillon, T.M., Decoux, G., Rozale, C., Schoen, D.J. and David, J.L., 2001. MSTRAT: An algorithm for building germplasm core collections by maximizing allelic or phenotypic richness. Journal of heredity 92: 93-94.
