Theoretical and Applied Genetics

, Volume 111, Issue 5, pp 906–913

Genetic structure and diversity of European flint maize populations determined with SSR analyses of individuals and bulks

  • Jochen C. Reif
  • Sonia Hamrit
  • Martin Heckenberger
  • Wolfgang Schipprack
  • Hans Peter Maurer
  • Martin Bohn
  • Albrecht E. Melchinger
Original Paper


Landraces of maize represent a valuable genetic resource for breeding and genetic studies. Using simple sequence repeat (SSR) markers, we analysed five flint maize populations from Central Europe that had played an important role in the pre-hybrid era in Germany. Our objectives were to (1) investigate the molecular genetic diversity within and among the populations based on the SSR analysis of individuals, (2) compare these results of the SSR analysis based on individuals with those based on bulks, (3) examine genotype frequencies for deviations from Hardy–Weinberg equilibrium (HWE) at individual loci, and (4) test for linkage disequilibrium (LD) between pairs of loci within populations. Thirty individuals and their bulked DNA per population were fingerprinted with 55 SSR markers. Across all populations, 46.7% of the SSR markers deviated significantly from HWE, with an excess of homozygosity in 97% of the cases. This excess of homozygosity can largely be explained by experimental errors during the amplification of SSRs apart from genuine genetic causes. Allele frequencies of the SSR analyses of individuals and bulks were significantly correlated (r=0.85, P< 0.01), suggesting that SSR analysis of bulks is very cost-effective for large-scale molecular characterisation of germplasm collections. No evidence for genome-wide LD among pairs of loci was observed, indicating that the populations are well suited for high resolution association mapping studies.


  1. Dubreuil P, Charcosset A (1998) Genetic diversity within and among maize populations: a comparison between isozyme and RFLP loci. Theor Appl Genet 96:577–587CrossRefGoogle Scholar
  2. Dubreuil P, Rebourg C, Merlino M, Charcosset A (1999) Evaluation of a DNA pooled-sampling strategy for estimating the RFLP diversity of maize populations. Plant Mol Biol Rep 17:123–138CrossRefGoogle Scholar
  3. Falconer DS, TFC Mackay (1996) Introduction to quantitative genetics, 4th edn. Longman Group Ltd, LondonGoogle Scholar
  4. Gauthier P, Gouesnard B, Dallard L, Redaelli R, Rebourg C, Charcosset A, Boyat A (2002) RFLP diversity and relationships among traditional European maize populations. Theor Appl Genet 105:91–99CrossRefPubMedGoogle Scholar
  5. Goodman MM, Stuber CW (1983) Races of maize: VI. Isozyme variation among races of maize in Bolivia. Maydica 28:169–187Google Scholar
  6. Gower JC (1966) Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika 53:325–338Google Scholar
  7. Guo S, Thompson E (1992) Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics 48:361–372PubMedCrossRefGoogle Scholar
  8. Hardy GH (1908) Mendelian proportions in a mixed population. Science 28:49–50PubMedCrossRefGoogle Scholar
  9. Hollander M, Wolfe DA (1973) Nonparametric statistical inference. Wiley, New York, pp 139–146Google Scholar
  10. Ihaka R, Gentleman R (1996) A language for data analysis and graphics. J Comput Graph Stat 53:299–314CrossRefGoogle Scholar
  11. Kahler AL, Hallauer AR, Gardner CO (1986) Allozyme polymorphisms within and among open-pollinated and adapted exotic populations of maize. Theor Appl Genet 72:592–601CrossRefGoogle Scholar
  12. Kimura M, Ohta T (1978) Stepwise mutation model and distribution of allelic frequencies in a finite population. Proc Natl Acad Sci USA 75:2868–2872PubMedCrossRefGoogle Scholar
  13. Labate JA, Lamkey KR, Lee M, Woodman W (2000) Hardy-Weinberg and linkage equilibrium estimates in the BSSS and BSCB1 random mated populations. Maydica 45:243–255Google Scholar
  14. Labate JA, Lamkey KR, Mitchell SH, Kresovich S, Sullivan H, Smith JSC (2003) Molecular and historical aspects of Corn Belt dent diversity. Crop Sci 43:80–91CrossRefGoogle Scholar
  15. Legendre P, Legendre L (1998) Numerical ecology, 2nd edn. Elsevier, AmsterdamGoogle Scholar
  16. Lewis PO, Zaykin D (1999) Genetic data analysis. Computer program for the analysis of allelic data. Version 1.0. Distributed by the authors at ( (verified 1 August 2004). Lewis Labs, Univ. of Connecticut, Storrs, CT
  17. Liu K, Goodman M, Muse S, Smith JS, Buckler E, Doebley J (2003) Genetic structure and diversity among maize inbred lines as inferred from DNA microsatellites. Genetics 165:2117–2128PubMedGoogle Scholar
  18. Lynch M, Walsh B (1997) Genetics and analysis of quantitative traits. Sinauer Assoc, Sunderland, p 413Google Scholar
  19. Matsuoka Y, Mitchell SE, Kresovich S, Goodman M, Doebley J (2002) Microsatellites in Zea—variability, patterns of mutations, and use for evolutionary studies. Theor Appl Genet 104:436–450CrossRefPubMedGoogle Scholar
  20. Maurer HP, Melchinger AE, Frisch M (2004) Plabsoft: software for simulation and data analysis in plant breeding. XVIIth EUCARPIA General Congress 2004, Tulln, AustriaGoogle Scholar
  21. Nei M (1987) Molecular evolutionary genetics. Columbia University Press, New YorkGoogle Scholar
  22. Oettler G, Schnell FW, Utz HF (1976) Die westdeutschen Getreide- und Kartoffelsortimente im Spiegel ihrer Vermehrungsflächen. In: Alleweldt G (ed) Hohenheimer Arbeiten Schriftenreihe der Universität Hohenheim Reihe:Pflanzliche Produktion. Verlag Eugen Ulmer, Stuttgart, GermanyGoogle Scholar
  23. Patefield WM (1981) Algorithm AS159. An efficient method of generating r×c tables with given row and column totals. Appl Stat 30:91–97CrossRefGoogle Scholar
  24. Powell W, Morgante M, Andre C, Hanafey M, Vogel J, Tingey S, Rafalski A (1996) The comparison of RFLP, RAPD, AFLP, and SSR (microsatellite) markers for germplasm analysis. Mol Breed 2:225–238CrossRefGoogle Scholar
  25. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedGoogle Scholar
  26. Rebourg C, Gouesnard B, Charcosset A (2001) Large scale molecular analysis of traditional European maize populations. Relationships with morphological variation. Heredity 86:574–587CrossRefPubMedGoogle Scholar
  27. Rebourg C, Gouesnard B, Welcker C, Dubreuil P, Chastanet M, Charcosset A (2003) Maize introduction into Europe: the history reviewed in the light of molecular data. Theor Appl Genet 106:895–903PubMedGoogle Scholar
  28. Reif JC, Xia XC, Melchinger AE, Warburton ML, Hoisington DA, Beck D, Bohn M, Frisch M (2004) Genetic diversity determined within and among CIMMYT maize populations of tropical, subtropical, and temperate germplasm by SSR markers. Crop Sci 44:326–334CrossRefGoogle Scholar
  29. Reif JC, Hamrit S, Heckenberger M, Schipprack W, Bohn M, Melchinger AE (2005) Trends in genetic diversity among European maize cultivars and their parental components during the past 50 years. Theor Appl Genet (in press)Google Scholar
  30. Remington DL, Thornsberry JM, Matsuoka Y, Wilson LM, Whitt SR, Doebley J, Kresovich S, Goodman MM, Buckler E (2001) Structure of linkage disequilibrium and phenotypic associations in the maize genome. Proc Natl Acad Sci USA 98:11479–11484CrossRefPubMedGoogle Scholar
  31. Revilla P, Vales MI, Malvar RA, Ordas A (1997) Allozyme frequencies, heterozygosity and genetic distances following S1 recurrent selection in two synthetic maize populations. Theor Appl Genet 95:1057–1061CrossRefGoogle Scholar
  32. Saghai-Maroof MA, Soliman KM, Jorgenson R, Allward RW (1984) Ribosomal DNA spacer length polymorphisms in barley: Mendelian inheritance, chromosomal location and population dynamics. Proc Natl Acad Sci USA 81:8014–8018PubMedCrossRefGoogle Scholar
  33. Schnell FW (1992) Maiszüchtung und die Züchtungsforschung in der Bundesrepublik Deutschland. Vorträge Pflanzenzüchtung 22:27–44Google Scholar
  34. Senior ML, Murphy JP, Goodman MM, Stuber CW (1998) Utility of SSRs for determining genetic similarities and relationships in maize using an agarose gel system. Crop Sci 38:1088–1098CrossRefGoogle Scholar
  35. Smith JSC, Chin ECL, Shu H, Smith OS, Wall SJ, Senior ML, Mitchell SE, Kresovich S, Ziegle J (1997) An evaluation of utility of SSR loci as molecular markers in maize (Zea mays L.): comparisons with data from RFLPs and pedigree. Theor Appl Gen 95:163–173CrossRefGoogle Scholar
  36. Snedecor GW, Cochran WG (1980) Statistical methods. Iowa State University Press, AmesGoogle Scholar
  37. Vigouroux Y, Jaqueth JS, Matsuoka Y, Smith OS, Beavis WD (2002) Rate and pattern of mutation at microsatellite loci in maize. Mol Biol Evol 19:1251–1260PubMedGoogle Scholar
  38. Warburton ML, Xianchun X, Crossa J, Franco J, Melchinger AE, Frisch M, Bohn M, Hoisington D (2002) Genetic characterization of CIMMYT inbred maize lines and open pollinated populations using large scale fingerprinting methods. Crop Sci 42:1832–1840CrossRefGoogle Scholar
  39. Weinberg W (1909) Über Vererbungsgesetze beim Menschen. Zeitschrift für induktive Abstammungs- und Vererbungslehre 1:377–393CrossRefGoogle Scholar
  40. Weir BS (1996) Genetic data analysis II, 2nd edn. Sinauer Associates Inc, SunderlandGoogle Scholar
  41. Wright S (1978) Evolution and genetics of populations, Vol. IV. The Univ of Chicago Press, Chicago, IL, p 91Google Scholar

Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • Jochen C. Reif
    • 1
  • Sonia Hamrit
    • 1
  • Martin Heckenberger
    • 1
  • Wolfgang Schipprack
    • 1
  • Hans Peter Maurer
    • 1
  • Martin Bohn
    • 2
  • Albrecht E. Melchinger
    • 1
  1. 1.Institute of Plant Breeding, Seed Science, and Population GeneticsUniversity of HohenheimStuttgartGermany
  2. 2.Crop Science DepartmentUniversity of IllinoisUrbana ChampaignUSA

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