Assessing the adaptive potential of European beech populations to temperature and precipitation along a steep environmental gradient in the south-eastern Carpathians.

It is necessary to assess the adaptive potential of European beech populations to climate change. Environmental association analysis is a powerful tool for identifying gene loci that contribute to local adaptation to environmental pressures. Genotypic data were collected from ~100 adult beech trees per stand in five locations in the south-eastern Romanian Carpathians along an altitudinal gradient associated with precipitation and temperature. In total, 53 environmental variables, e.g., temperature and precipitation, were used to perform environmental association analysis using LFMM (latent factor mixed models) to identify Single Nucleotide Polymorphism (SNP) markers associated with these. In addition, the principal components (PC) from a principal components analysis (PCA) performed on all environmental variables were used to perform an environmental association analysis. We identified 446 SNP markers significantly associated with the first PC. These overlapped with the SNP markers significantly associated with most environmental variables. The first PC was correlated with all temperature-based variables at |r| ~0.989 to ~0.997. A high peak on chromosome 2 from ~4.56 to ~16.27 Mb appeared in all results. This region was ~3.47 Mb downstream of a region for local adaptation identified by Lazic et al. (2024). In this peak, 273 markers located in the coding region of 22 genes were found. The two genes, polygalacturonase QRT3-like and NRT1/PTR_FAMILY 5.4-like, may be involved in local adaptation based on our literature review. Polygalacturonase QRT3-like plays a role in pollen development in Arabidopsis. At the corresponding SNP markers, there was a correlation of the minor allele frequency and temperature-based environmental variables.