Genetic diversity of soybean genotypes revealed by agro-morphological and SSR markers
2016
Khatab, I.A. (Kafrelsheikh University (Egypt). Faculty of Agriculture, Department of Genetics) | Morsy, A.R. | Fares, W.M. | Kumamaru, T.
Increasing the diversity of the soybean germplasm base could introduce new genes affecting agronomic traits. In this study, we demonstrated the differences of genetic diversity level among 24 soybean genotypes and adapt an augmented design to screen and select the superior entries among 24 soybean germlasm and to calculate similarity parameters. Likewise, to elucidate the relationships based on molecular markers among new promising lines and introduced genotypes with improved Egyptian commercial cultivars using SSR markers, to use this information in future breeding programs. The results exhibited significant differences among the tested genotypes for all studied characters. This provides evidence for the possibility to carry out a sufficient selection program on the basis of these traits using the studied genotypes. Thirteen out 14 SSR primer pairs amplify polymorphic SSRs from all of these genotypes, a total of 42 alleles were produced. The polymorphic information content (PIC) among genotypes varied from 0.55 (satt001) to 0.88 (satt173) with 2 and 5 alleles respectively. However, Satt005 produced only one monomorphic band. The used SSR primer pairs successfully distinguished most of soybean genotypes, with the exception of a pair of closely related breeding lines from the same cross. The genetic relationships among genotypes based agro-morphological analysis not completely agreed with known pedigrees. However, phylogenetic tree based on SSR confirmed the separation of soybean genotypes into six clusters and were more clearly separated. These results suggest that SSR markers are efficient for measuring genetic diversity and relatedness as well as identifying varieties of soybeans.
Show more [+] Less [-]AGROVOC Keywords
Bibliographic information
This bibliographic record has been provided by Agriculture, Forestry and Fisheries Research Information Technology Center