Genetic Resources and Crop Evolution

, Volume 53, Issue 8, pp 1579–1588 | Cite as

Genetic Diversity Among Traditional Ethiopian Highland Maize Accessions Assessed by Simple Sequence Repeat (SSR) Markers

  • Yoseph Beyene
  • Anna-Maria Botha
  • Alexander A. Myburg


Over the past three centuries, maize has become adapted to complex environmental conditions in the highlands of Ethiopia. We analyzed 62 traditional Ethiopian highland maize accessions, using 20 simple sequence repeat (SSR) markers and 15 morphological traits, to assess genetic diversity and relationships among these accessions and to assess the level of correlation between phenotypic and genetic distances. The accessions varied significantly for all of the measured morphological traits. The average number of alleles per locus was 4.9. Pair-wise genetic dissimilarity coefficients ranged from 0.27 to 0.63 with a mean of 0.49. Ward minimum variance cluster analysis showed that accessions collected from the Northern agroecology were distinct from the Western and Southern agroecologies. However, there was no differentiation between the Western and Southern accessions. This suggested gene flow between these regions. The relationship between morphological and SSR-based distances was significant and positive (r = 0.43, p = 0.001). The high genetic diversity observed among these set of accessions, suggests ample opportunity for the development of improved varieties for different agroecologies of Ethiopia. From conservation perspective, sampling many accessions from all agroecologies would be an effective way of capturing genetic variation for future collections and conservation.


Clustering Ethiopia Genetic diversity Highland maize SSR Zea mays 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. J.F. Barbosa-Neto, C.M. Hernandez, L.S. O’ Donoughue and M.E. Sorrells, Precision of genetic relationship estimates based on molecular markers. Euphytica 98 (1997) 59-67CrossRefGoogle Scholar
  2. Beyene Y., Botha A.M. and Myburg A.A. 2005. Phenotypic diversity for morphological and agronomic traits in traditional Ethiopian highland maize accessions. S. Afr. J. Plant and Soil 22: 100–105.Google Scholar
  3. T.P. Bogyo, E. Porceddu and P. Perrino, Analysis of sampling strategies for collecting genetic material. Econ. Bot. 34 (1990) 11-86Google Scholar
  4. Agricultural Sample Survey 2000/2001 on Area Production of Major Crops, Private Peasant Holdings ‘Meher’ Season. Addis Ababa, Ethiopia: Statistical Bulletins 190 (2001).Google Scholar
  5. Research Strategy Plan for Maize. Ethiopia: Addis Ababa (2000).Google Scholar
  6. P. Dubreuile, P. Dufour, E. Krejet, M. Causse, D. de Vienne, A. Gallais and A. Charcosset, Organization of RFLP diversity among inbred lines of maize representing the most significant heterotic groups. Crop Sci. 36 (1996) 790-799CrossRefGoogle Scholar
  7. J. Felsenstein, PHYLIP (Phylogeny Inference Package) Version 3.5c. Distributed by the Author. SeattleWashington: Department of Genetics, University of Washington (1993).Google Scholar
  8. H. Jerry, Number Cruncher Statistical Systems (NCSS). KaysvilleUtah: Statistical software (2000).Google Scholar
  9. H.P. Hafnagel, Agriculture in Ethiopia. Rome: FAO (1961).Google Scholar
  10. Z.E. Henandez, Maize and man in the greater Southwest. Econ. Bot. 39 (1985) 416-430Google Scholar
  11. N. Mantel, The detection of disease clustering and a generalized regression approach. Cancer Res. 27 (1967) 209-220PubMedGoogle Scholar
  12. Y. Matsuoka, S.E. Mitchell, S. Kresovich, M. Goodman and J. Dobeley, Microsatellite in Zea – variability, patterns of mutations and use for evolutionary studies. Theor. Appl. Genet. 104 (2002) 436-450PubMedCrossRefGoogle Scholar
  13. R.W. Michelmore, I. Paran and R.V. Kessli, Identification of markers linked to disease resistance genes by bulked segregant analysis: a rapid method to detect markers in specific genomic regions using segregant populations. Proc. Natl. Acad. Sci. USA 88 (1991) 9828-9832PubMedCrossRefGoogle Scholar
  14. A.A. Myburg, D.L. Remington, D.M. O’ Malley, R.R. Sederoff and R.W. Whetten, High-throughput AFLP analysis using infrared dye-labelled primers and an automated DNA sequencer. BioTechniques 30 (2001) 348-357PubMedGoogle Scholar
  15. NMSA (National Meteorology Service Agency). 2000. Monthly Weather ReportFebr. 1980 to Dec. 2000. Addis AbabaEthiopia.Google Scholar
  16. M. Nie and W.H. Li, Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc. Natl. Acad. Sci. USA 76 (1979) 5269-5273CrossRefGoogle Scholar
  17. L.R. Pinto, M.L.C. Vieira, C.L.P. de Souza and A.P. de Souza, Genetic diversity assessed by microsatellites in tropical maize populations submitted to a high-intensity reciprocal recurrent selection. Euphytica 134 (2003) 277-286CrossRefGoogle Scholar
  18. C. Rebourg, B. Gouesnard and A. Charcosset, Large scale molecular analysis of traditional European maize populations. Relationships with morphological variation. Heredity 86 (2001) 574-587PubMedCrossRefGoogle Scholar
  19. L. Roldan-Ruiz, F.A. Van Eeuwijk, T.J. Gilliland, P. Dubreuil, C. Dillmann, J. Lallemand, M. Loose De and C.P. Baril, A comparative study of molecular and morphological methods of describing relationships between perennial ryegrass (Lolium perenne L.) varieties. Theor. Appl. Genet. 103 (2001) 1138-1150CrossRefGoogle Scholar
  20. M.A. Saghai-Maroof, R.M. Biyashev, G.P. Yang, Q. Zhang and R.W. Allard, Extraordinarily polymorphic microsatellite DNA in barely: species diversity, chromosomal locations and population dynamics. Proc. Natl. Acad. Sci. USA 91 (1994) 5466-5470PubMedCrossRefGoogle Scholar
  21. M.L. Senior and M. Heun, Mapping maize microsatellites and polymerase chain reaction conformation of the targeted repeats using a CT primer. Genome 36 (1993) 884-889PubMedGoogle Scholar
  22. M.L. Senior, J.P. Murphy, M.M. Goodman and C.W. Stuber, Utility of SSRs for determining genetic similarities and relationships in maize using an agarose gel system. Crop Sci. 38 (1998) 1088-1098CrossRefGoogle Scholar
  23. J.S.C. Smith and O.S. Smith, Fingerprinting crop varieties. Adv. Agron. 47 (1992) 85-140CrossRefGoogle Scholar
  24. S Twumasi-Afriyie, Z Habatmu, Z Kassa, Y Bayisa and T Sewagegn, Development and improvement of highland maize in Ethiopia. 2nd National Maize Workshop of Ethiopia. Ethiopia: Addis Ababa (2001).Google Scholar
  25. M.L. Warburton, X. Zianchun, J. Crossa, J. Franco, A.E. Melchinger, M. Frisch, M. Bohn and D. Hoisington, Genetic characterization of CIMMYT inbred maize lines and open pollinated populations using large scale fingerprinting methods. Crop Sci. 42 (2002) 1832-1840CrossRefGoogle Scholar
  26. J.H. Ward, Hierarchical grouping to optimize an objective function. Am. Stat. Assoc. J. 56 (1963) 236-244CrossRefGoogle Scholar

Copyright information

© Springer 2006

Authors and Affiliations

  • Yoseph Beyene
    • 1
  • Anna-Maria Botha
    • 1
  • Alexander A. Myburg
    • 1
  1. 1.Department of Genetics, Forestry and Agricultural Biotechnology Institute (FABI)University of PretoriaPretoriaSouth Africa

Personalised recommendations