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Breeding patterns and cultivated beets origins by genetic diversity and linkage disequilibrium analyses

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Genetic diversity in worldwide population of beets is strongly affected by the domestication history, and the comparison of linkage disequilibrium in worldwide and elite populations highlights strong selection pressure.

Abstract

Genetic relationships and linkage disequilibrium (LD) were evaluated in a set of 2035 worldwide beet accessions and in another of 1338 elite sugar beet lines, using 320 and 769 single nucleotide polymorphisms, respectively. The structures of the populations were analyzed using four different approaches. Within the worldwide population, three of the methods gave a very coherent picture of the population structure. Fodder beet and sugar beet accessions were grouped together, separated from garden beets and sea beets, reflecting well the origins of beet domestication. The structure of the elite panel, however, was less stable between clustering methods, which was probably because of the high level of genetic mixing in breeding programs. For the linkage disequilibrium analysis, the usual measure (r 2) was used, and compared with others that correct for population structure and relatedness (r 2 S , r 2 V , r 2 VS ). The LD as measured by r 2 persisted beyond 10 cM within the elite panel and fell below 0.1 after less than 2 cM in the worldwide population, for almost all chromosomes. With correction for relatedness, LD decreased under 0.1 by 1 cM for almost all chromosomes in both populations, except for chromosomes 3 and 9 within the elite panel. In these regions, the larger extent of LD could be explained by strong selection pressure.

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References

  • Adetunji I, Willems G, Tschoep H, Bürkholz A, Barnes S, Boer M, Malosetti M, Horemans S, van Eeuwijk F (2014) Genetic diversity and linkage disequilibrium analysis in elite sugar beet breeding lines and wild beet accessions. Theor Appl Genet 127(3):559–571

    Article  CAS  PubMed  Google Scholar 

  • Barzen E, Mechelke W, Ritter E, Seitzer JF, Salamini F (1992) RFLP markers for sugar beet breeding—chromosomal linkage maps and location of major genes for rhizomania resistance, monogermy and hypocotyl color. Plant J 2:601–611

    Article  CAS  Google Scholar 

  • Biancardi E, Lewellen RT, De Biaggi M, Erichsen AW, Stevanato P (2002) The origin of rhizomania resistance in sugar beet. Euphytica 127:383–397

    Article  CAS  Google Scholar 

  • Biancardi E, Skaracis GN, Steinrücken G, De Biaggi M, Panella L, Lewellen RT, Campbell LG, Yu MH, Stevanato P, McGrath LG (2005) Objectives of sugar beet breeding. In: Biancardi E, Campbell LG, Skaracis GN, De Biaggi M (eds) Genetics and breeding of sugar beet. Science Publishers Inc, Enfield, pp 53–168

    Google Scholar 

  • Blondel VD, Guillaume J-L, Lambiotte R, Lefebvre E (2008) Fast unfolding of communities in large networks. J Stat Mech: Theory Exp 10:P10008

    Article  Google Scholar 

  • Bosemark NO (1979) Genetic poverty of the sugar beet in Europe. In: Proceedings of the conference broadening genetic base of crops. Pudoc, Wageningen, the Netherlands, pp. 29–35

  • Bosemark NO (1989) Prospects for beet breeding and use of genetic resources. In: Report of the international workshop beta genetic resources. International board for plant genetic resources. Rome, Italy, pp. 89–97

  • Bosemark N (1993) Genetics and breeding. In: Cooke DA, Scott RK (eds) The sugar beet crop. Chapman and Hall, London, pp 67–119

    Chapter  Google Scholar 

  • Bosemark NO (2006) Genetics and breeding. In: Draycott AP (ed) Sugar beet. Blackwell Publishing Ltd, Oxford, pp 50–88

    Chapter  Google Scholar 

  • Boudry P, Wieber R, Saumitou-Laprade P, Pillen K, van Dijk H, Jung C (1994) Identification of RFLP markers closely linked to the bolting gene B and their significance for the study of the annual habit in beets (Beta vulgaris L.). Theor App Genet 88:852–858

    Article  CAS  Google Scholar 

  • Butterfass T (1964) Die Chloroplastenzahlen in verschiedenartigen Zellen trisomer Zuckerrüben (Beta vulgaris). Z Bot 52:46–77

    Google Scholar 

  • Büttner B, Abou-Elwafa SE, Zhang W, Jung C, Müller AE (2010) A survey of EMS-induced biennial Beta vulgaris mutants reveals a novel bolting locus which is unlinked to the bolting gene B. Theor Appl Genet 121(6):1117–1131

    Article  PubMed  Google Scholar 

  • Cai D, Kleine M, Kifle S, Harloff HJ, Sandal NN, Marcker KA, Klein-Lankhorst RM, Salentijn EM, Lange W, Stiekema WJ, Wyss U, Grundler FM (1997) Positional cloning of a gene for nematode resistance in sugar beet. Sciences 275(5301):832–834

    Article  CAS  Google Scholar 

  • Clauset A, Newman ME, Moore C (2004) Finding community structure in very large networks Phys. Rev E 70:066111

    Google Scholar 

  • Cooke DA, Scott RK (1993) The sugar beet crop. Chapman and Hall Publishers, London, p 675

    Book  Google Scholar 

  • Csardi G, Nepusz T (2006) The igraph software package for complex network research. Int J Compl Syst 1695, http://igraph.org

  • Earl DA, vonHoldt BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4(2):359–361

    Article  Google Scholar 

  • Engelhardt BE, Stephens M (2010) Analysis of population structure: a unifying framework and novel methods based on sparse factor analysis. PLoS Genet 6:e1001117

    Article  PubMed Central  PubMed  Google Scholar 

  • Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620

    Article  CAS  PubMed  Google Scholar 

  • Fischer HE (1989) Origin of the ‘Weisse Schlesische Rübe’ (white Silesian beet) and resynthesis of sugar beet. Euphytica 41:75–80

    Article  Google Scholar 

  • Flint-Garcia SA, Thornsberry JM, Buckler ES IV (2003) Structure of linkage disequilibrium in plants. Annu Rev Plant Biol 54:357–374

    Article  CAS  PubMed  Google Scholar 

  • Gaut BS, Long AD (2003) The lowdown on linkage disequilibrium. Plant Cell 15:1502–1506

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Gill NT, Vear KC (1958) Agricultural botany. Duckworth, London

    Google Scholar 

  • Gupta PK, Rustgi S, Kulwal PL (2005) Linkage disequilibrium and association studies in higher plants: present status and future prospects. Plant Mol Biol 57:461–485

    Article  CAS  PubMed  Google Scholar 

  • Hedrick PW (1987) Gametic disequilibrium measures: proceed with caution. Genetics 117:331–341

    PubMed Central  CAS  PubMed  Google Scholar 

  • Hill WG, Weir BS (1988) Variances and covariances of squared linkage disequilibria in finite populations. Theor Popul Biol 33:54–78

    Article  CAS  PubMed  Google Scholar 

  • Jäger S, Hemmrich G, Franke A, Dohm JC, Minoche AE, Himmelbauer H, Capistrano GGG, Harloff HJ, Jung C (2012) Re-sequencing and hybrid assembly strategy of two nematode resistant Beta vulgaris translocation lines. In: Plant and animal genome XX, 14–18 Jan 2012, San Diego

  • Josse J, Husson H, Pagès J (2011) Multiple imputation in PCA. Adv Data Anal Classif 5(3):231–246

    Article  Google Scholar 

  • Jung C, Herrmann RG, Eibl C, Kleine M (1994) Molecular analysis of a translocation in sugar beet carrying a gene for nematode resistance from Beta Procumbens. J Sugar Beet Res 41:27–42

    Article  Google Scholar 

  • Kim S, Plagnol V, Hu TT, Toomajian C, Clark RM, Ossowski S, Ecker JR, Weigel D, Nordborg M (2007) Recombination and linkage disequilibrium in Arabidopsis thaliana. Nat Genet 39:1151–1155

    Article  CAS  PubMed  Google Scholar 

  • Kraft T, Hansen M, Nilsson N-O (2000) Linkage disequilibrium and fingerprinting in sugar beet. Theor Appl Genet 101:323–326

    Article  Google Scholar 

  • Lewellen RT (1988) Selection for resistance to rhizomania in sugar beet. In: Proceedings of the 5th international congress plant pathology. Kyoto, Japan, p. 455

  • Lewellen RT, Whitney ED (1993) Registration of germplasm lines developed from composite crosses of sugarbeet x Beta maritima. Crop Sci 33:882–883

    Article  Google Scholar 

  • Li J, Schulz B, Stich B (2010) Population structure and genetic diversity in elite sugar beet germplasm investigated with SSR markers. Euphytica 175:35–42

    Article  CAS  Google Scholar 

  • Li J, Luhmann A-K, Weizleder K, Stich B (2011) Genome-wide distribution of genetic diversity and linkage disequilibrium in elite sugar beet germplasm. BMC Genom 12:484

    Article  CAS  Google Scholar 

  • Mangin B, Siberchicot A, Nicolas S, Doligez A, This P, Cierco-Ayrolles C (2012) Novel measures of linkage disequilibrium that correct the bias due to population structure and relatedness. Heredity 108:285–291

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • McDonald JH (2014) Handbook of biological statistics, 3rd edn. Sparky House Publishing, Baltimore

    Google Scholar 

  • McGrath JM, Saccomani M, Stevanato P, Biancardi E (2007) Beet. In: Kole C (ed) Genome mapping and molecular breeding in plants, vol 5. Springer, Heidelberg, pp 191–207

  • McGrann GRD, Grimmer M, Mutasa-Göttgens EF, Stevens M (2009) Progress towards the understanding and control of sugar beet rhizomania disease. Mol Plant Pathol 10:129–141

    Article  CAS  PubMed  Google Scholar 

  • Mezmouk S, Dubreuil P, Bosio M, Décousset L, Charcosset A, Praud S, Mangin B (2011) Effect of population structure corrections on the results of association mapping tests in complex maize diversity panels. Theor Appl Genet 122:1149–1160

    Article  PubMed Central  PubMed  Google Scholar 

  • Newman MEJ (2006) Finding community structure in networks using the eigenvectors of matrices. Phys Rev E 74:036104

    Article  CAS  Google Scholar 

  • Owen FV (1945) Cytoplasmically inherited male-sterility in sugar beets. J Agric Res 71:423–440

    Google Scholar 

  • Patterson N, Price AL, Reich D (2006) Population structure and eigenanalysis. Plos Genet 2:e190

    Article  PubMed Central  PubMed  Google Scholar 

  • Pons P, Latapy M (2006) Computing communities in large networks using random walks. J Graph Algorithm Appl 10(2):191–218

    Article  Google Scholar 

  • Pritchard JK, Przeworski M (2001) Linkage disequilibrium in humans: models and data. Am J Hum Genet 69(1):1–14

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959

    PubMed Central  CAS  PubMed  Google Scholar 

  • R Core Team (2014) R: a language and environment for statistical computing. R foundation for statistical computing. Vienna, Austria. http://www.R-project.org

  • Raghavan UN, Albert R, Kumara S (2007) Near linear time algorithm to detect community structures in large-scale networks. Phys Rev E 76:036106

    Article  Google Scholar 

  • Rosvall M, Axelsson D, Bergstrom CT (2009) The map equation. Eur Phys J Spec Top 178(1):13–23

    Article  Google Scholar 

  • Scheet P, Stephens M (2006) A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase. Am J Hum Genet 78:629–644

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Scholten OE, Jansen RC, Keiser LCP, de Block TSM, Lange W (1996) Major genes for resistance to beet necrotic yellow vein virus (BNYVV) in Beta vulgaris. Euphytica 91:331–339

    Article  Google Scholar 

  • Scholten OE, de Block TSM, Klein-Lankhorst R, Lange W (1999) Inheritance of resistance to beet necrotic yellow vein virus in Beta vulgaris conferred by a second gene for resistance. Theor Appl Genet 99:740–746

    Article  CAS  PubMed  Google Scholar 

  • Schondelmaier J, Jung C (1997) Chromosomal assignment of the nine linkage groups of sugar beet (Beta vulgaris L.) using primary trisomics. Theor Appl Genet 95:590–596

    Article  Google Scholar 

  • Tracy CA, Widom H (1994) Level-spacing distributions and the Airy kernel. Commun Math Phys 159:151–174

    Article  Google Scholar 

  • Yu J, Buckler ES (2006) Genetic association mapping and genome organization of maize. Curr Opin Biotechnol 17:155–160

    Article  CAS  PubMed  Google Scholar 

  • Yu JM, Pressoir G, Briggs WH, Bi IV, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES (2005) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208

    Article  PubMed  Google Scholar 

  • Zhu C, Gore M, Buckler ES, Yu J (2008) Status and prospects of association mapping in plants. Plant Genome 1(1):5–20

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This research was carried out with the financial support of the French national research agency (ANR) within the AKER program which is part of the “Programme d’Investissements d’Avenir”. AKER is a French research initiative for a sustainable beet improvement with innovative breeding strategies based on allelic variation mining and novel -omic tools. We thank Dr Steve Barnes, SESVanderHave, for his critical review of the manuscript. We thank two anonymous referees who helped us to greatly improve our discussion.

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Correspondence to Ellen Goudemand.

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Communicated by M. Frisch.

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Mangin, B., Sandron, F., Henry, K. et al. Breeding patterns and cultivated beets origins by genetic diversity and linkage disequilibrium analyses. Theor Appl Genet 128, 2255–2271 (2015). https://doi.org/10.1007/s00122-015-2582-1

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