Forest trees growing in high altitude conditions offer a convenient model for studying adaptation processes. They are subject to a whole range of adverse factors that are likely to cause local adaptation and related genetic changes. Siberian larch (Larix sibirica Ledeb.), whose distribution covers different altitudes, makes it possible to directly compare lowland with highland populations. This paper presents for the first time the results of studying the genetic differentiation of Siberian larch populations, presumably associated with adaptation to the altitudinal gradient of climatic conditions, based on a joint analysis of altitude and six other bioclimatic variables, together with a large number of genetic markers, single nucleotide polymorphisms (SNPs), obtained from double digest restriction-site-associated DNA sequencing (ddRADseq). In total, 25,143 SNPs were genotyped in 231 trees. In addition, a dataset of 761 supposedly selectively neutral SNPs was assembled by selecting SNPs located outside coding regions in the Siberian larch genome and mapped to different contigs. The analysis using four different methods (PCAdapt, LFMM, BayeScEnv and RDA) revealed 550 outlier SNPs, including 207 SNPs whose variation was significantly correlated with the variation of some of environmental factors and presumably associated with local adaptation, including 67 SNPs that correlated with altitude based on either LFMM or BayeScEnv and 23 SNPs based on both of them. Twenty SNPs were found in the coding regions of genes, and 16 of them represented non-synonymous nucleotide substitutions. They are located in genes involved in the processes of macromolecular cell metabolism and organic biosynthesis associated with reproduction and development, as well as organismal response to stress. Among these 20 SNPs, nine were possibly associated with altitude, but only one of them was identified as associated with altitude by all four methods used in the study, a nonsynonymous SNP in scaffold_31130 in position 28092, a gene encoding a cell membrane protein with uncertain function. Among the studied populations, at least two main groups (clusters), the Altai populations and all others, were significantly genetically different according to the admixture analysis based on any of the three SNP datasets as follows: 761 supposedly selectively neutral SNPs, all 25,143 SNPs and 550 adaptive SNPs. In general, according to the AMOVA results, genetic differentiation between transects or regions or between population samples was relatively low, although statistically significant, based on 761 neutral SNPs (F_ST = 0.036) and all 25,143 SNPs (F_ST = 0.017). Meanwhile, the differentiation based on 550 adaptive SNPs was much higher (F_ST = 0.218). The data showed a relatively weak but highly significant linear correlation between genetic and geographic distances (r = 0.206, p = 0.001).

Dendrogenomics is a new interdisciplinary approach that allows joint analysis of dendrological and genomic data and opens up new ways to study the temporal dynamics of forest treelines, delineate spatial and temporal population structures, decipher individual tree responses to abiotic and biotic stresses, and evaluate the adaptive genetic potential of forest tree populations. These data are needed for the prediction of climate change effects and mitigation of the negative effects. We present here an association analysis of the variation of 27 individual tree traits, including adaptive dendrophenotypes reflecting the individual responses of trees to drought stress, such as the resistance (Rt), recovery (Rc), resilience (Rs), and relative resilience (RRs) indexes measured in 136 Siberian larch trees in 5 populations in the foothills of the Batenevsky Ridge (Kuznetsk Alatau, Republic of Khakassia, Russia), with variation of 9742 SNPs genotyped using ddRADseq in the same trees. The population structure of five closely located Siberian larch populations was relatively weak (F_ST = 0.018). We found that the level of individual heterozygosity positively correlated with the Rc and RR indices for the five studied drought periods and partly with the Rs indices for three drought periods. It seems that higher individual heterozygosity improves the adaptive capabilities of the tree. We also discovered a significant negative relationship between individual heterozygosity and the Rt index in four out of five periods, which means that growth slows down during droughts more in trees with higher individual heterozygosity and is likely associated with energy and internal resource reallocation toward more efficient water and energy usage and optimization of larch growth during drought years. We found 371 SNPs with potentially adaptive variations significantly associated with the variation of adaptive dendrophenotypes based on all three different methods of association analysis. Among them, 26 SNPs were located in genomic regions carrying functional genes: 21 in intergenic regions and 5 in gene-coding regions. Based on the obtained results, it can be assumed that these populations of Siberian larch have relatively high standing adaptive genetic variation and adaptive potential underlying the adaptations of larch to various climatic conditions.

The genetic differentiation of Siberian larch (Larix sibirica Ledeb.) populations along the latitudinal gradient of climatic conditions was studied using high-throughput double digest restriction-site associated DNA sequencing (ddRADseq) data. We studied correlation of five main climatic variables with variation of 47.929 single nucleotide polymorphisms (SNPs). In total, 125 trees were genotyped and studied: 61 trees in four populations along the western geographic transect and 64 trees in four populations along the eastern geographic transect. Twenty-one SNPs with signatures of selection were identified, including nine outlier SNPs whose variation cannot be explained by selectively neutral processes, and 12 SNPs whose variation correlated with the environmental factors. Seven SNPs are located in the introns of mitochondrial genes NAD1, NAD2 and ribosomal protein gene L2, three are located relatively close to the mitochondrial genes encoding NAD2 and ribosomal proteins S7 and S11, one is located at a distance from the nuclear gene encoding a protein homologous to the microtubule-associated futsch-like protein of Arabidopsis thaliana, two in the tentative protein genes of unknown nature and three in contigs containing no genes, and for which no homologous sequences were found in the NCBI GenBank.

A joint analysis of dendrochronological and genomic data was performed to identify genetic mechanisms of adaptation and assess the adaptive genetic potential of Siberian stone pine (Pinus sibirica Du Tour) populations. The data obtained are necessary for predicting the effect of climate change and mitigating its negative consequences. Presented are the results of an association analysis of the variation of 84,853 genetic markers (single nucleotide polymorphisms—SNPs) obtained by double digest restriction-site associated DNA sequencing (ddRADseq) and 110 individual phenotypic traits, including dendrophenotypes based on the dynamics of tree-ring widths (TRWs) of 234 individual trees in six natural populations of Siberian stone pine, which have a history of extreme climatic stresses (e.g., droughts) and outbreaks of defoliators (e.g., pine sawfly [Neodiprion sertifer Geoff.]). The genetic structure of studied populations was relatively weak; samples are poorly differentiated and belong to genetically similar populations. Genotype–dendrophenotype associations were analyzed using three different approaches and corresponding models: General Linear Model (GLM), Bayesian Sparse Linear Mixed Model (BSLMM), and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK), respectively. Thirty SNPs were detected by at least two different approaches, and two SNPs by all three. In addition, three SNPs associated with mean values of recovery dendrophenotype (Rc) averaged across multiple years of climatic stresses were also found by all three methods. The sequences containing these SNPs were annotated using genome annotation of a very closely related species, whitebark pine (P. albicaulis Engelm.). We found that most of the SNPs with supposedly adaptive variation were located in intergenic regions. Three dendrophenotype-associated SNPs were located within the 10 Kbp regions and one in the intron of the genes encoding proteins that play a crucial role in ensuring the integrity of the plant’s genetic information, particularly under environmental stress conditions that can induce DNA damage. In addition, we found a correlation of individual heterozygosity with some dendrophenotypes. Heterosis was observed in most of these statistically significant cases; signs of homeostasis were also detected. Although most of the identified SNPs were not assigned to a particular gene, their high polymorphism and association with adaptive traits likely indicate high adaptive potential that can facilitate adaptation of Siberian stone pine populations to the climatic stresses and climate change.

This study evaluates the vulnerability of Siberian larch (Larix sibirica L.) populations to future climate change using a genomic offset (GO) framework that integrates genome-wide SNP data with environmental variables. We analyzed 488 individuals from 37 populations across climatically diverse regions of Russia, genotyped by sequencing at over 20,000 SNP loci using the ddRADseq method. Gene–environment association (GEA) analyses (BayeScEnv, LFMM2, and RDA) identified candidate adaptive loci linked to six key bioclimatic variables. Based on these loci, GO was estimated using three approaches implemented in RONA–RDA, RDA, and Gradient Forest frameworks under multiple climate models (MIROC6, BCC-CSM2-MR, MRI-ESM2-0), scenarios (SSP2-4.5, SSP3-7.0, SSP5-8.5), and time periods (2041–2060, 2061–2080, and 2081–2100). Results revealed consistent spatial patterns of vulnerability, with northern and high-altitude populations, as well as populations from more continental and moisture-limited regions, exhibiting the highest GO and thus the greatest risk of maladaptation. In contrast, several central and southern populations showed relatively low vulnerability. The importance of temperature stability (isothermality) and precipitation of the driest month as key drivers of adaptive variation was highlighted. Despite differences in SNP datasets, population rankings remained highly consistent, supporting the robustness of predictions. Overall, our findings demonstrate substantial heterogeneity in climate vulnerability across the species range and provide a genomic basis for conservation strategies, including assisted gene exchange and climate-adaptive forest management.