تفکیک ژنتیکی لاین های جدید و امید بخش چقندرقند در واکنش به نماتد سیستی Heterodera schachtii

Sugar beet (Beta vulgaris L.) is one of the most important and strategic crops that one of it’s limiting growth factor is sugar beet cyst nematode, Heterodera schachtii Schmidt. One of the control measure to this disease, H. schachtii is the use of resistant cultivars. This study was performed to evaluate the genetic diversity of 30 resistant and susceptible sugar beet genotypes to cyst nematode using SSR molecular marker. Sugar beet line used were obtained from Isfahan Agricultural Research Center (received from the sugar beet research institute, Karaj, Iran), which are the output of the five forms of cross-breeding and hybrid, pollen breeding, cross-breeding, brothers and sisters, and selected commercial varieties. After sowing in a greenhouse, about a month, fresh and young leaves were collected for DNA extraction. DNA extraction was performed based on the modified CTAB extraction method, and the quantity and quality of DNA extracted were determined by spectrophotometric methods and agarose gel electrophoresis. Propagation of genomic fragments was performed using 7 pairs of SSR-specific primers. Then, the data matrix was evaluated on 69 samples based on Power marker v 3.25 and NTSYS ver 2.02 software, for Jaccard's similarity coefficients and simple matching and Dies based on UPGMA, UPGMC and COMPLETE clustering methods. Also, using the cluster analysis and dendrogram analysis, the matrix of cophenetic correlation coefficients was estimated. Then, with the NTSYS software, the correlation between this matrix and the initial similarity matrix was calculated. Data analysis was carried out to group the masses using Jaccard's similarity coefficient and UPGMA algorithm. The main components were analyzed using NTSYS software to investigate the distribution of markers at the plant gene level. In total, 91 polybags were produced, accounting for 59% of the total 155 bands produced. The average number of polygon bands was 13 bands for each pairs of initials and 3.03 for each genotype. The UDAo15 and UDA013 primer pairs revealed the highest polymorphic index content (PIC) and marker index (MI). Cluster analysis using NTSYS software, with UPGMA method and based on Jacard’s similarity matrix divided the genotypes into 4 major clusters. The dendrogram was consistent with the clustering result of Principal Component Analysis (PCoA). The highest genetic similarity of 91 percent was observed between the lines 45 and 51, that both were offspring of a half sib-family, half-brother half-sister crossing. The results suggested that SSR marker is a reliable tool for revealing high levels of polymorphism among the sugar beet genotypes.