Assessment of genetic diversity and determination of population structure lentil genotypes Using SSR Markers

Document Type : Research Paper


1 Department of Plant Sciences and Biotechnology, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University, G.C. Tehran, Iran

2 Professor of Plant Biotechnology, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University. Tehran, Iran.

3 Assistant Professor, Department Cell and Molecular Biology, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University, G.C, Tehran, Iran.

4 Assistant professor, Department of Genetics and National Plant Gene Bank, Seed and Plant Improvement Institute, Agricultural Research Education and Extension. Organization (AREEO), Karaj, Iran. Email:

5 Assistant professor, Department of Agronomy & Plant Breeding, College of Agriculture Islamic Azad University, Sanandaj Branch Sanandaj Iran


Lentil (Lens culinaris) is the third most important grain legume in the world after chickpea (Cicer arietinum L.) and pea (Pisum sativum L.).  Therefore, the aim of this research was (1) to determine the genetic diversity and structure of molecular variation of genotypes and (2) to identify relationships among genotype for conservation, management, and utilization of these genotypes in crop breeding programs.
Materials and methods
Total genomic DNA was extracted from leaves of each genotype following a CTAB protocol.  After DNA extraction, DNA samples were amplified using polymerase chain reaction (PCR).  Evaluation of the genetic diversity of 90 lentil genotypes was performed using 30 SSR markers.
 A total of 145 polymorphic alleles were produced with an average of 4.06 alleles per locus. The highest number of alleles produced belonged to SSR 80 primer with eight alleles and the lowest number of alleles belonged to SSR96 primer with three alleles.  Polymorphic information content (PIC) for the markers ranged between 0.35 to 0.83 with an average of 0.63.  Maximum and minimum PIC have belonged for SSR80 and SSR28, respectively.  Shannon index value was variable from 1.94 (for the SSR80) to 0.829 (for the SSR48). The expected heterozygosity was observed in genotypes ranged from 0.845 (SSR80) to 0.422 (SSR48). The mean of this index obtained with 0.643.  Clustering analysis was performed using Neihbour-Joining algorithm and population structure analysis was performed using Bayesian method.  The best number of sub-populations was identified as three.  Genotypes were identified within the different sub-populations that most of genotypes in sub-populations were not separated based on their geographic origins.
Results of this study revealed that SSR marker has highly potential for evaluation. This marker could separate all of genotypes very well.


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