Evaluation of genetic diversity in Agropyron cristatum using ISSR molecular marker

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Research Paper 01/05/2015
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Evaluation of genetic diversity in Agropyron cristatum using ISSR molecular marker

Mandana Moradi, Ezatollah Farshadfar, Hooshmand Safari
J. Bio. Env. Sci.6( 5), 425-432, May 2015.
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Abstract

In order to evaluate genetic diversity, 13 accessions of Agropyron Cristatum were investigated using ISSR molecular markers. The 12 ISSR primers amplified a total of 65 bands of which 60 bands showed polymorphism and 5 bands were monomorphic. Maximum number of bands (8) was related to the primers IS9 and IS13, while minimum bands (4) belonged to the primers IS3 and IS12. The percentage of polymorphic bands (PPB) ranged between 60 and 100. Mean numbers of scored bands (NSB) and polymorphic bands (NPB) per primer were 5.42 and 5, respectively. The PIC values for varied from 0.23 to 0.47 with an average of 0.35. The lowest and the highest PIC indices were recorded for primers IS3 and IS6, respectively. Therefore primer IS6 determined genetic distance much better than other primers so it can be used for the analysis of genetic diversity in agropyron in the future investigations. The primers IS3 with the lowest PIC didn’t have good ability to discriminate genotypes. Cluster analysis based on Dice coefficient of genetic distance classified the accessions into four groups. The first group consisted of genotypes G7 and G13 with average similarity coefficient 0.68. The second group included the accessions 4, G5, G10 and G11 with similarity coefficient 0.71. Genotypes G6, G8 and G9 were located in the third group with similarity coefficient 0.63 The fourth group had the genotypes G1, G2, G3 and G12 with similarity coefficient 0.58, therefore maximum similarity belonged to group 2, while minimum similarity was attributed to group 4. Biplot analysis divided the genotypes into 4 groups which is in accordance with results of cluster analysis. Molecular analysis of variance confirmed significant difference between groupings of accessions based on cluster analysis.

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