Diversity analysis of Central Asia and Caucasian lentil (Lens culinaris Medik.) germplasm using SSR fingerprinting

  • Sevda Babayeva
  • Zeynal Akparov
  • Mehraj Abbasov
  • Alamdar Mammadov
  • Mohammad Zaifizadeh
  • Kenneth Street
Short Communication


Diversity analysis was performed among 39 cultivated lentil (Lens culinaris Medik.) accessions of Central Asia and Caucasian origin using five highly polymorphic microsatellite markers. A total of 33 alleles determined ranging from 3 to 8 per locus. Estimated gene diversity value for 33 loci was 0.66. Genetic similarity indices among 39 accessions ranged from 0.24 to 1.0. Cluster analysis using the unweighted pair group method with arithmetic mean method classified accessions into six major groups at 0.5 similarity coefficient. More than half accessions from Tajikistan formed large cluster. On the other hand, a few accessions from each country showed unique genotypes. Overall, most of the accessions, except ones with closely related origin, were distinguished by the present high quality DNA fingerprinting. This molecular diversity information gives important basis for conservation strategy in gene bank and exotic germplasm introduction in breeding programs in Central Asia and Caucasian countries.


DNA fingerprinting Genetic diversity Lens culinaris Medik. Lentil SSRs 



We thank Drs. Durna Aliyeva and Zarifa Suleymanova from Institute of Botany of ANAS for highly skilled technical assistance. Many thanks to ICARDA for providing seeds and its financial support for competition of research work. The authors are grateful to Dr. Kazuhiro Sato, Okayama University for critical reading of the manuscript.


  1. Abo-elwafa A, Murai K, Shimada T (1995) Intra- and inter-specific variations in Lens revealed by RAPD markers. Theor Appl Genet 90:335–340. doi: 10.1007/BF00221974 CrossRefGoogle Scholar
  2. Barulina HI (1930) Lentils of the USSR and other countries. Bull Appl Bot Plant Breed Leningrad Suppl 40:1–319Google Scholar
  3. Datta S, Sourabh B, Kumari J, Kumar Sh (2007) Molecular diversity analysis of lentil genotypes. Pulses newsletter. Indian Institute of Pulses Research, Kanpur. Vol 18(2), 2 ppGoogle Scholar
  4. Dice LR (1945) Measures of the amount of ecologic association between species. Ecology 26:297–302. doi: 10.2307/1932409 CrossRefGoogle Scholar
  5. Ford R, Pang ECK, Taylor PWJ (1997) Diversity analysis and species identification in Lens using PCR generated markers. Euphytica 96:247–255. doi: 10.1023/A:1003097600701 CrossRefGoogle Scholar
  6. Hamwieh A, Udupa SM, Choumane W, Sarker A, Dreyer F, Jung C, Baum M (2005) A genetic linkage map of Lens sp. based on microsatellite and AFLP markers and localization of fusarium vascular wilt resistance. Theor Appl Genet 110:669–677. doi: 10.1007/s00122-004-1892-5 PubMedCrossRefGoogle Scholar
  7. Inder P, Materne M, Taylor PWJ, Ford R (2008) Genotyping elite genotypes within the Australian lentil breeding program with lentil-specific sequenced tagged microsatellite site (STMS) markers. Aust J Agric Res 59:222–225. doi: 10.1071/AR07188 CrossRefGoogle Scholar
  8. Jarvis D, Sthapit B, Sears L (2000) Conserving agricultural biodiversity in situ: a scientific basis for sustainable agriculture. International Plant Genetic Resources Institute, RomeGoogle Scholar
  9. Jin L, Jian-Ping G, Dong-Xu X, Xiao-Yan Z, Jing G, Xu-Xiao Z (2008) Analysis of genetic diversity and population structure in lentil (Lens culinaris Medik.) germplasm by SSR markers. Acta Agron Sin 34(11):1901–1909CrossRefGoogle Scholar
  10. Johansson M, Ellegren H, Andersson L (1992) Cloning and characterization of highly polymorphic porcine microsatellites. J Hered 83:196–198PubMedGoogle Scholar
  11. Joshi RK, Behera L (2006) Identification and differentiation of indigenous non-Basmati aromatic rice genotypes of India using microsatellite markers. Afr J Biotechnol 6(4):348–354Google Scholar
  12. Lelley T, Stachel M, Grausgruber H, Vollmann J (2000) Analysis of relationships between Aegilops tauschii and the D genome of wheat utilizing microsatellites. Genome 43:661–668. doi: 10.1139/gen-43-4-661 PubMedCrossRefGoogle Scholar
  13. Nei M, Li WH (1979) Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc Natl Acad Sci USA 76:5269–5273. doi: 10.1073/pnas.76.10.5269 PubMedCrossRefGoogle Scholar
  14. Rohlf FJ (2000) NTSYS-pc numerical taxonomy and multivariate analysis system, version 2.1. Exeter Publ, New YorkGoogle Scholar
  15. Torres AM, Weeden NF, Martin A (1993) Linkage among isozyme, RFLP and RAPD markers in Vicia faba. Theor Appl Genet 85:937–945. doi: 10.1007/BF00215032 CrossRefGoogle Scholar
  16. Udupa SM, Robertson LD, Weigand F, Baum M, Kahl G (1999) Allelic variation at (TAA)n microsatellite loci in a world collection of chickpea (Cicer arietinum L.) germplasm. Mol Gen Genet 261:354–363. doi: 10.1007/s004380050976 PubMedCrossRefGoogle Scholar
  17. Weir BS (1990) Genetic-data analysis methods for discrete genetic data. Sinauer Assoc Inc., SunderlandGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Sevda Babayeva
    • 1
  • Zeynal Akparov
    • 1
  • Mehraj Abbasov
    • 1
  • Alamdar Mammadov
    • 2
  • Mohammad Zaifizadeh
    • 3
  • Kenneth Street
    • 4
  1. 1.Genetic Resources Institute of ANASBakuAzerbaijan
  2. 2.Institute of Botany of ANASBakuAzerbaijan
  3. 3.Islamic Azad University – Ardabil BranchArdabilIran
  4. 4.ICARDAAleppoSyria

Personalised recommendations