ESTIMATION OF GENETIC DIVERSITY AMONG SOME BREAD WHEAT (Triticum aestivum L.) GENOTYPES USING MOLECULAR MARKERS AND AGRONOMIC TRAITS

Document Type : original papers

Authors

1 (1) Department of Bioinformatics, Genetic Engineering and Biotechnology Research Institute (GEBRI), Sadat City University, Sadat City, P.O. Box, 79, Egypt

2 (2) Department of Crop Science, Faculty of Agriculture, Menoufiya University, Shebin El-Kom, Egypt

3 (3) Department of Biotechnology, Faculty of Agriculture, Al-Azhar University, Cairo, Egypt

4 (4) Department of Plant Biotechnology, Genetic Engineering and Biotechnology Research Institute (GEBRI), Sadat City University, Sadat City, P.O. Box, 79, Egypt

Abstract

ABSTRACT: Genetic diversity was investigated among some bread wheat varieties bynine simple sequence repeat markers and fifteen agronomic traits. The wheat simple sequence repeat markers(SSRs) used determined nine loci located on nine chromosomes and were capable of detecting 41 alleles with an average of 4.56 alleles per locus. The number of alleles per locus ranged from 3 to 7 and the allelicpolymorphism information content (PIC) value ranged from 0.448 for the Xgwm333-7B to 0.857 for the Xgwm626-6B with an average of 0.665. The results revealed that the varieties differed for SSRs markers and agronomic traits.Significant correlation coefficient between gene diversity and the number of polymorphic bands was high, r = 0.852 (P <0.01). The genetic similarity based on agronomic traits ranged from 0.61 to 1.82 washigher than SSR markers which ranged from 0.136 to 0.991.Fifteen agronomic traits were used for morphological analysis. Cluster analysis was conducted based on SSRs and agronomic traitsto group the wheat varieties and construct dendrogram. Three main groups distinguished by SSRs. However, the clusteranalysis based on agronomic traits assignedthe varieties into three different groups. SSR markers showed high level of polymorphism among the varieties examined. The present study indicates that SSR markers and agronomic traits could be successfully used in genetic characterization and diversity in wheat. Also, Information generated from this study can be used to select parents for hybrid development to maximize yield and its components.

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