RAPD analysis of genetic diversity in natural populations of Aegilops geniculata Roth and Triticum durum Desf from Tunisia

Aegilops geniculata Roth (Poaceae) is a potential source of genetic variation for wheat improvement. In order to distinguish and evaluate different genetic of Aegilops and Triticum using RAPD markers, thirteen Aegilops geniculata populations and three durum wheat varieties (Triticum durum Desf.) were collected from different regions of Tunisia (North and central). Aegilops geniculata Roth populations (Goussa, Djebel Abderahmen, Tabarka, Djebel Ressas), (Bizerte, Zaghouan), (Mekna, Ain Zana), (Djebel Oust, Souk jemaa, Sbeitla), (Djebel Serj, Nefza) constitute different groups. Complement gene locus were amplified by nineteen RAPD primers witch produced 212 bands, that 182 bands (about 86%) were polymorphic. The results revealed that genetic diversity within populations was relatively high. Nei’s genetic diversity (H) and Shannon’s index (I) were 0.324, 0.484 respectively. Global AMOVA showed that genetic variation within populations accounted 80% occurring (ΦPT =0.205 p<0.05). The total genetic diversity (Ht) and the within population genetic diversity (Hs) were 0.3195 and 0.1516 respectively, Total gene diversity was attributable mostly to diversity within population, indicating that the groups of populations were likely to differ genetically. Genetic differentiation was low in the two closely related species. The amount of gene flow (Nm) among groups of populations was also low. Despite the relatively restricted geographical range covered by the investigation, studied groups of populations exhibited a pronounced genetic divergence at different hierarchical levels. Therefore, dendrogram based on Nei’s genetic distance indicated segregation of Aegilops geniculata groups of populations and Triticum durum into two main clear pattern clusters. All this results proved that RAPD markers could be a powerful tool for investigating genetic variation and for detecting genetic structuring of populations at different hierarchical levels according to the segregation by distance model.