Genetic Distance of Sesame (Sesamum indicum L.) Cultivars and Varieties from Northwestern Ethiopia using Inter Simple Sequence Repeat Markers

Authors

  • Admas Alemu
    adth14@gmail.com
    Faculty of Natural and Computational Sciences, Biology Department, Debre Tabor University, Ethiopia, Ethiopia
  • Yohannes Petros College of Natural and Computational Sciences, Biology Department, Haramaya University, Ethiopia, Ethiopia
  • Kassahun Tesfaye Institute of Biotechnology, Addis Ababa University, Ethiopia, Ethiopia
January 1, 2013

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Understanding the genetic diversity of cultivated crops is critical to design breeding methods for improvement. The sesame (Sesamum indicum L) crops cultivated in the major growing areas of Ethiopia are different and expected to be genetically diverse. However, little research was conducted to determine the genetic diversity of Ethiopian sesame landraces. Therefore, six farmers’ cultivars and varieties of sesame from the north-western Ethiopia each consisting of ten individual samples were analyzed using four inter simple sequence repeat (ISSR) markers with the aim of assessing the genetic diversity among and within the cultivars and varieties. Sesame sample leaves were collected from the study area in 2011 main cropping season and dried by in a silica gel for DNA extraction and the samples were moved to the genetics laboratory of Addis Ababa University for further laboratory investigation. The four ISSR primers yielded 37 amplification products of which 36 bands (97.30%) exhibited polymorphism. The maximum similarity was observed between the cultivar Bounje collected from Humera and Besh Besh taken from Metema followed by Gojjam Azene from Humera and Besh Besh from Metema. The least similarity was observed between Hir Hir collected from west Armacheho and Gojjam Azene from Humera. The result of the analysis of molecular variance (AMOVA) revealed a slightly higher percentage of genetic variation among the cultivars and varieties (54.37%) than individuals within each cultivar and variety populations (45.63%). The unweighted pair-group method with arithmetic averages (UPGMA) cluster analysis grouped most of the studied samples to their population. The result confirmed the presence of high genetic diversity in the study area that deserves formulation of breeding strategy for improving the productivity of the crop in the country.

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