А. С. Истомина Oil flax is an agricultural crop whose oil is a valuable source of polyunsaturated fatty acids. Currently, the issue of molecular genetic certification of agricultural plants in the Russian Federation, including flax, is of high importance. Existing methodologies have several drawbacks, necessitating the search for new highly informative DNA markers. The aims of the study were in silico and experimental verification of microsatellite (SSR) markers from published sources, assessment of their polymorphism and informativeness for selecting candidates to be included in a DNA marker panel for multiplex PCR and for developing genetic passports for flax varieties, as well as determination of intravarietal polymorphism in flax varieties to assess the feasibility of their reliable certification and subsequent identification. To select optimal microsatellite (SSR) markers, a bioinformatic analysis of over 1,300 nucleotide microsatellite sequences from published sources was performed. The selection criteria included: a 3–6 nucleotide motif, in silico amplification specificity, and primer annealing temperature. As a result of preliminary screening, 63 markers were selected. Experimental testing on seven oil flax varieties bred at V.S. Pustovoit All-Russian Research Institute of Oil Crops allowed the identification of 27 promising loci. Further validation on an extended panel of 23 varieties showed that most markers exhibited moderate or low discriminatory potential (PIC values ranging from 0.08 to 0.46). The exception was four highly polymorphic SSR loci: KY326304, KY326942, KY326968, and Lu2332 (PIC > 0.5), which are recommended for inclusion in the final marker panel for genetic passport development. Analysis of intravarietal polymorphism, examined on small samples using 27 markers, revealed its low level (mean values: Na = 1.27; Ne = 1.19; I = 0.15) confirming the feasibility of molecular genetic identification of flax varieties. To develop a complete certification methodology, further research is required to design new informative SSR markers using modern bioinformatic approaches and genomic library data analysis.
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