Genetic diversity of kaffir sorghum accessions from the VIR collection in kafirin-encoding loci

Background . Sorghum is a universal, highly drought-resistant crop, widely cultivated throughout the world. Sorghum grain has a valuable biochemical composition and is utilized in both food and feed production. Due to the unique structure of endosperm storage proteins, kafirins, adding sorghum flour to dough is promising for producing dietetic nutrition components. Employing polymorphic DNA markers to study the diversity of kaffir sorghum accessions from the VIR collection as potential donors of biological and morphological traits in their grain is relevant for the development of sterile lines and sterility maintainers. Materials and methods . Sixteen kaffir sorghum accessions were phenotyped according to morphological features and kafirin electrophoretic banding patterns in their grain, and genotyped using PCR markers specific for kafirin-encoding genes. The phenotype of mature grains was assessed by seed coat color as well as by the thickness ratio between the vitreous and farinaceous endosperm layers on grain cuts. Proteins were fractionated by polyacrylamide gel electrophoresis. The SSR markers linked to the genes for β - and γ -kafirins, and the STS marker of the coding region of the δ -kafirin gene were used in the PCR analysis. Results and conclusions . The studied accessions differed in grain color and endosperm structure. Three accessions demonstrated a significant thickness of the vitreous layer, while the others had a farinaceous or partially vitreous endosperm. No differences were found among the accessions in the kafirin electrophoretic banding patterns. Meanwhile, the accessions manifested highly polymorphic fragments amplified with primers flanking microsatellite sequences linked to the β - and γ -kafirin genes. Two different versions of the STS marker were detected after amplification with the primers specific to the δ -kafirincoding gene region. The studied accessions were differentiated using the principal coordinates analysis (PCoA).