Karyotypic study on six populations of species and subspecies of Burnet genera (Sanguisorba ssp.)

The research was carried out to study biodiversity aspects of six small burnet populations, using cytogenetic traits. Root tips were stained; and chromosom morphological traits such as short arm length (SA), long arm length (LA) and total length (TL) were measured using photomicroscope and Micromeasure software. Analysis of variances was performed on chromosomes morphological traits: LA, SA, TL, arm ratio (AR) and centromer index (CI), using unbalanced completely randomized design with at least three replications. Several symmetrical assessment statistics such as: relative length of the shortest chromosome (S%), total form percentage (TF%), A₁, difference of relative length range (DRL), A_2, Levans chromosomal nomenclature method and Stebbins categories (SC) were calculated. Results showed that populations number 10462, 13976 and kangalchal populations were tetraploid (2n=4x=28) while population number 12333 was hexaploid (2n=6x=42), and populations number 13963 and 13296 were octaploid (2n=8x=56). Populations 13296 (octaploid) and 13976 (tetraploid) showed the most asymmetric karyotype between the studied populations base on A₂ and DRL. Populations 13963 (octaploid) and 13976 (tetraploid) showed the most asymmetric karyotype between all of the studied populations base on %TF and A₁. Using principal components analysis, the first three components justified % 99.7 of the total variance. In the first component, SA and TL with the highest coefficients of eigen vectors, were the most important traits. In the second component, LA, AR, CI, %TF and A₁ had the most important role. In the third component, %S, DRL and A₂ were the most important traits. Cluster Analysis classified the population in three clusters when clustering was performed based on karyotypic statistics. Clustering revieled that the octoploid population, 13296 had the most genetic distance with 13976 octaploid papulations. According to the scater plot, base on the first two components, the populations were grouped in three distinct classes, corresponding with the result of cluster analysis.