Molecular characterisation and similarity relationships among iranian basil (Ocimum basilicum L.) accessions using inter simple sequence repeat markers

Authors

  • Mohammad Aghaei Urmia University
  • Reza Darvishzadeh Urmia University
  • Abbas Hassani Urmia University

Keywords:

Basil, Cluster analysis, Molecular markers, Plant genetic diversity

Abstract

The study of genetic relationships is a prerequisite for plant breeding activities as well as for conservation of genetic resources. In the present study, genetic diversity among 50 Iranian basil (Ocimum basilicum L.) accessions was determined using inter simple sequence repeat (ISSR) markers. Thirty-eight alleles were generated at 12 ISSR loci. The number of alleles per locus ranged from 1 to 5 with an average of 3.17. The maximum number of alleles was observed at the A7, 818, 825 and 849 loci, and their size ranged from 300 to 2500 bp. A similarity matrix based on Jaccard’s coefficient for all 50 basil accessions gave values from 1.00-0.60. The maximum similarity (1.00) was observed between the “Urmia” and “Shahr-e-Rey II” accessions as well as between the “Urmia” and “Qazvin II” accessions. The lowest similarity (0.60) was observed between the “Tuyserkan I” and “Gom II” accessions. The unweighted pair- group method using arithmetique average UPGMA clustering algorithm classified the studied accessions into three distinct groups. All of the basil accessions, with the exception of “Babol III”, “Ahvaz II”, “Yazd II” and “Ardebil I”, were placed in groups I and II. Leaf colour was a specific characteristic that influenced the clustering of Iranian basil accessions. Because of this relationship, the results of the principal coordinate analysis (PCoA) approximately corresponded to those obtained through cluster analysis. Our results revealed that the geographical distribution of genotypes could not be used as a basis for crossing parents to obtain high heterosis, and therefore, it must be carried out by genetic studies.

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Published

2011-12-07

Issue

Section

Crop Science