In order to enhance genetic potential of chickpea materials from the National University of Córdoba Breeding Programme and Germplasm collection (Argentina), a study for a comprehensive understanding of the amount and pattern of genetic variation within and between genotypes was carried out by applying a multivariate analysis form single simple repeats (SSR) and morphological data. Molecular data were also used to determine the discriminating power for genotype identification, and to find the optimal primer combination to ensure unambiguous identification. With the analysis of 15 SSR markers on 53 genotypes, a total of 58 alleles were detected with individual values ranging from one to nine alleles per locus. High values of discriminating power (Dj ⩾ 0.7, PIC ⩾ 0.7), and low values of confusion probability (Cj ⩽ 0.23) were obtained for at least four evaluated markers. The combination of TA113 + TA114 + H1B09 + TA106 primers was effective for discriminating the 53 chickpea genotypes with a cumulative confusion probability value (Ck) of 9.60 × 10−4. Except for some exceptions, individual chickpea genotypes within a cluster in the consensus tree were definitely more closely related with each other by the origin or pedigree. The results confirmed that both multivariate data analysis methods, ordination and clustering, were complementary. In most genotypes, discriminant principal component analysis classification was consistent with the original clusters defined by molecular data. Differences in results from molecular and morphological data indicate that they provide complementary and relevant information for establishing genetic relationships among chickpea materials and a better description and interpretation of the available variability in the germplasm collection.

The aim of the study was to develop the system of polymerase chain reaction (PCR)-based markers for the assessment of genetic diversity and population genetic studies of Gentiana lutea L. as well as to determine the utility of two indices of marker informativeness. The informativeness was determined for 40 PCR primers of different types (random amplified polymorphic DNA, inter simple sequence repeat, inter-retrotransposon amplified polymorphism, resistance gene analog polymorphism and conserved DNA-derived polymorphism markers) by evaluating discriminating power (DL) and resolving power (Rp) in a sample of 30 plants from two populations. Analysis of correlation between the index value and the number of differentiated pairs of genotypes in the given sample revealed that DL is more efficient than Rp; therefore, we selected primers based on the DL value. In total, 12 primers with the largest values of DL were chosen. Analysis of genetic relationship among 86 plants from six populations showed that the number of bands produced by the three of selected primers was sufficient to give average bootstrap support across six key nodes in the dendrogram higher than 85%, while using six of the primers resulted in average bootstrap value exceeding 99%. Thus, a minimal set of three to six selected primers are sufficient for a quick assessment of genetic diversity of G. lutea populations, depending on the sample size and degree of differentiation between populations, while the rest of the primers with DL values above 0.8 may be used for ecogenetic surveys. Preliminary results obtained with selected primers indicate the moderate level of genetic variation within the species and significant differentiation among individual populations.