The Ural Mountains and the West Eurasian Taiga forests are one of the most important centers of genetic diversity for Larix sibirica Ledeb. Forest fragmentation negatively impacts forest ecosystems, especially due to the impact of their intensive use on the effects of climate change. For the preservation and rational use of forest genetic resources, it is necessary to carefully investigate the genetic diversity of the main forest-forming plant species. The Larix genus species are among the most widespread woody plants in the world. The Siberian larch (Larix sibirica, Pinaceae) is found in the forest, forest-tundra, tundra (Southern part), and forest-steppe zones of the North, Northeast, and partly East of the European part of Russia and in Western and Eastern Siberia; in the Urals, the Siberian larch is distributed fragmentarily. In this study, eight pairs of simple sequence repeat (SSR) primers were used to analyse the genetic diversity and population structure of 15 Siberian larch populations in the Urals. Natural populations in the Urals exhibit indicators of genetic diversity comparable to those of Siberia populations (expected heterozygosity, He = 0.623; expected number of alleles, Ne = 4017; observed heterozygosity, Ho = 0.461). Genetic structure analysis revealed that the examined populations are relatively highly differentiated (Fst = 0.089). Using various algorithms for determining the spatial genetic structure, the examined populations formed three groups according to geographical location. The data obtained are required for the development of species conservation and restoration programs, which are especially important in the Middle Urals, which is the region with strong forest fragmentation.

The sustainable use and conservation of forest resources must be carried out with a detailed study of the main forest-forming plant species. Coniferous forests form the basis of boreal forest ecosystems and are of great economic importance. Representatives of forest-forming boreal coniferous species are species of the genus Pinus, including Siberian pine (Pinus sibirica Du Tour) and Scots pine (Pinus sylvestris L.), which are valuable and widely used woody plant species. The purpose of this research was to conduct an extended study of genetic diversity, genetic structure, and differentiation of P. sibirica and P. sylvestris populations under the conditions of their habitat in the Middle and Northern Urals. We studied twelve populations of two Pinus species using the inter-simple sequence repeat (ISSR)-based DNA polymorphism detection PCR method. Populations are characterized by relatively high levels of genetic diversity (P. sylvestris: H_e = 0.163; n_e = 1.270; I = 0.249; P. sibirica: H_e = 0.148; n_e = 1.248; I = 0.225). Analysis of the intrapopulation genetic structure reveals that the studied populations are highly differentiated (P. sylvestris: G_ST = 0.362; P. sibirica: G_ST = 0.460). The interpopulation component comprised 36% and 46% of the total genetic diversity for P. sylvestris and P. sibirica, respectively. Using various algorithms to determine the spatial genetic structure, it was determined that P. sylvestris populations form two groups according to their location at a certain altitude above sea level. P. sibirica populations form two clusters, with an additional subdivision of the two populations into subclusters identified. The data obtained during the study may be useful for further research as well as for conservation management planning and related forestry practices aimed at preserving the genetic resources of valuable forest plant species.

Researched 3 Scots pine populations (Pinus sylvestris L., Pinaceae) and 3 populations of western species of Siberian larch (Larix sibirica Ledeb., Pinaceae) in Perm krai for genetic diversity within species detecting. 114 ISSR–PCR P. sylvestris markers and 116 ISSR–PCR L. sibirica markers were amplified. The rate of polymorphic loci expected heterozygosity and number of rare ISSR–PCR markers were identified. Researched species are characterized by high genetic diversity. The rate of polymorphic loci is higher in P. sylvestris; expected heterozygosity and the number of effective alleles is higher in L. sibirica. Each species has populations with high and low genetic diversity parameters. The rare alleles were identified in every of 6 researched populations, but the number ranges from 6 to 13 in P. sylvestris populations and from 3 to 10 in L. sibirica populations. Genetic structure of researched populations analysis show that the interpopulation component of genetic diversity accounts for 30.28% in P. sylvestris and 30.92% in L. sibirica; most of the genetic diversity of P. sylvestris (69, 72%) and L. sibirica (69.08%) is concentrated within populations. Generic markers were found for the genus Pinus and Larix, and species markers for P. sylvestris and L. sibirica. Identification polymorphic markers or their combinations typical for the studied populations of two studied species. The molecular genetic formulas and barcodes of the studied populations are composed. Data on the intraspecific genetic diversity of populations of woody plants of the Perm krai will allow to recommend measures of their conservation, as well as to carry out molecular genetic identification of both natural populations and wood from these populations, which is important for determining the legality of its harvesting.

Establishing sustainable plantations with genetic diversity equivalent to that of natural populations is vital for successful reforestation efforts. In this study, we present an innovative approach for selecting populations suitable for reforestation, taking into account their genetic uniqueness using Inter Simple Sequence Repeats (ISSR) markers. Our investigation focused on six populations of Picea obovata Ledeb and six populations of Larix sibirica Ledeb, collected from the Northern and Middle Urals. We found that the indicators of genetic diversity were significantly higher in L. sibirica compared to P. obovata, while the number of rare alleles was greater in Siberian spruce (R = 19). Among the P. obovata populations, the Cherdyn’s forestry exhibited notably high genetic diversity, and for L. sibirica, the Gainy’s forestry stood out in this regard. Moreover, the genetic subdivision of the six P. obovata populations (G_ST = 0.331) was higher than that of the six L. sibirica populations (G_ST = 0.177). To ensure optimal seed selection considering the genetic originality coefficient (GOC) and population differentiation, we recommend utilizing the P. obovata population from Gainy’s forestry with a GOC of 0.554 and the L. sibirica population from Cherdyn’s forestry with a GOC of 0.372. These populations harbor typical alleles characteristic of the research region, making them ideal candidates for seed selection. Furthermore, the specific alleles identified can serve as valuable markers for determining the geographic origin of P. obovata and L. sibirica wood, aiding in efforts to trace the sources of these species in forestry and trade practices.

Based on the analysis of the polymorphism of two types of microsatellite markers (ISSR and SSR), the state of gene pools of the fifteen of Siberian larch populations from three regions of the Urals: Northern, Middle and Southern was estimated. The parameters of genetic diversity were revealed, its structure was established at the intrapopulation level. To assess the uniqueness of the gene pool, we used the coefficient of genetic originality (KGO), the analysis of which revealed populations with typical and region-specific gene pools. It was established that the studied samples are generally characterized by a high level of genetic diversity. It was found that the gene pools of samples from the South Urals are characterized by the greatest specificity, the lowest values of KGO, i. e. more typical gene pools, are noted in the North Urals samples of L. sibirica, the average values of KGO are from the samples of the Middle Urals. Also, 3 unique alleles were found in the ZIL, BND, and KCH samples, in the rest, no unique markers were detected. For a comprehensive assessment of the state of the gene pools of populations, all established indicators of genetic diversity have been transferred to the scale for assessing the status of gene pools developed on the example of the studied L. sibirica populations. Based on data on genetic diversity obtained using two types of molecular markers, it was found that the gene pools of ten studied L. sibirica populations are in satisfactory condition, and five have signs of gene pool degradation. Based on the results of the study, recommendations are made on the conservation of L. sibirica genetic resources in the Urals.

Background/Objectives: The spruces of the Picea abies–P. obovata complex have a total range that is the most extensive in the world flora of woody conifers. Hybridization between the nominative species has led to the formation of a wide introgression zone, which probably increases the adaptive potential of the entire species complex. This study aimed to search the genes associated with drought resistance, develop primers for the informative loci of these genes, identify and analyze SNPs, and establish the parameters of nucleotide diversity in the studied populations. Methods: The objects of this study were eight natural populations of the spruce complex in the Urals. Nucleotide sequences related to drought resistance spruce genes with pronounced single-nucleotide substitutions were selected, based on which 16 pairs of primers to their loci were developed and tested. Results: Based on the developed primers, six pairs of primers were chosen to identify SNPs and assess the nucleotide diversity of the studied populations. All selected loci were highly polymorphic (6 to 27 SNPs per locus). It was found that the Pic01 locus is the most variable (Hd = 0.947; π = 0.011) and selectively neutral, and the Pic06 locus is the most conservative (Hd = 0.516; π = 0.002) and has the most significant adaptive value. Conclusions: The nucleotide diversity data for the studied populations reveal similar values among the populations and are consistent with the literature data. The discovered SNPs can be used to identify adaptive genetic changes in spruce populations, which is essential for predicting the effects of climate change.