SSR marker-based molecular characterization and genetic diversity analysis of aromatic landreces of rice (Oryza sativa L.)

Article info: Received: 29 June 2012 In revised form: 18 July 2012 Accepted: 24 July 2012 ABSTRACT Molecular characterization of the genotypes gives precise information about the extent of genetic diversity which helps in the development of an appropriate breeding program. In the present study, a total of 24 SSR markers were used across 12 elite aromatic rice genotypes for their characterization and discrimination. Among these 24 markers 9 microsatellite markers were showed polymorphism. The number of alleles per locus ranged from 2 alleles (RM510, RM244, and RM277) to 6 alleles (RM 163), with an average of 3.33 alleles across 9 loci obtained in the study. The polymorphic information content values ranged from 0.14 (RM510) to 0.71 (RM163) in all 9 loci with an average of 0.48. RM163 was found the best marker for the identification of 12 genotypes as revealed by PIC values. The frequency of most common allele at each locus ranged from 41% (RM163, RM590, and RM413) to 91% (RM510). The pairwise genetic dissimilarity co-efficient indicated that the highest genetic distance was obtained between Basmati PNR 346 and Deepa; Basmati PNR 346 and Patnai-23; Dolargura and Sugandha; Bhogganijia and Sugandha; and finally between Dolargura and Chinikani (88.89%). Opchaya, Basmati PNR 346 and Sugandha had close similarity among them but showed wide dissimilarity with other genotypes. Being grouped into distant clusters Dolargura and Opchaya could be utilized as potential parents for the improvement of fine grain aromatic rice varieties. Genotypes Deepa and Patnai-23 (having zero dissimilarity) might have possessed somewhat similar genetic background and more markers are needed to discriminate them. The microsatellite marker based molecular fingerprinting could serve as a sound basis in the identification of genetically distant accessions as well as in the duplicate sorting of the morphologically close accessions.