Genetic variation and signatures of natural selection in populations of European beech (Fagus sylvatica L.) along precipitation gradients

Abstract

European beech (Fagus sylvatica L.) is one of the most important forest tree species in Europe, and its genetic adaptation potential to climate change is of great interest. Saplings and adults from 12 European beech populations were sampled along two steep precipitation gradients in Switzerland. All individuals were genotyped at 13 microsatellite markers and 70 SNPs in 24 stress response and phenology related candidate genes. Both SSR and SNP markers had high genetic diversity in the studied populations and low but statistically significant population differentiation. Two approaches were used to discover SNPs with signatures of selection: search for FST SNP outliers and analyses of SNP associations with environmental variables such as temperatures, precipitation and humidity. Three (4.3%) SNPs were consistently identified as outliers in the adults by more than one method, and they were very likely under positive selection. Twenty (28.6%) SNPs in the saplings and 10 (14.3%) SNPs in the adults were associated with environmental variables found by more than one method. In general, there were 22 (31.4%) SNPs in 17 (70.8%) candidate genes in the saplings, and 16 (22.9%) SNPs in 10 (41.6%) candidate genes in the adults, consistently identified by at least two of the five methods used, indicating that they are very likely under selection. Genes with SNPs showing signatures of selection are involved in a wide range of molecular functions, such as oxidoreductases (IDH), hydrolases (CysPro), transferases (XTH), transporters (KT2), chaperones (CP10) and transcription factors (DAG, NAC transcription factor). The obtained data will help us better understand the genetic variation underlying adaptation to environmentally changing conditions in European beech, which is of great importance for the development of scientific guidelines for the sustainable management and conservation of this important species.

Plant Nutritional Status Explains the Modifying Effect of Provenance on the Response of Beech Sapling Root Traits to Differences in Soil Nutrient Supply

“…Beech populations across central Europe have been shown to be genetically closely related in terms of neutral markers, such as microsatellite loci, but to differ in genes related to adaptive traits (e.g., Buiteveld et al, 2007). Nevertheless, genotypic diversity has often been found to be larger within than among populations, also including also adaptive traits (e.g., Cuervo-Alarcon et al, 2018). In contrast to the lack of studies on acclimation to changes in nutrient supply, the ability of beech populations from sites with different climatic conditions to acclimate, in the short term, to increased drought frequency has recently received much attention (Meier and Leuschner, 2008;Cuervo-Alarcon et al, 2018).…”

“…Nevertheless, genotypic diversity has often been found to be larger within than among populations, also including also adaptive traits (e.g., Cuervo-Alarcon et al, 2018). In contrast to the lack of studies on acclimation to changes in nutrient supply, the ability of beech populations from sites with different climatic conditions to acclimate, in the short term, to increased drought frequency has recently received much attention (Meier and Leuschner, 2008;Cuervo-Alarcon et al, 2018). Specifically, Meier and Leuschner (2008) found that while root traits, such as relative fine root growth and turnover, of beech populations from sites differing in precipitation responded generally strongly to drought treatment, the effect of provenance was small.…”

Rapid identification and interpretation of gene–environment associations using the new R.SamBada landscape genomics pipeline

“…samβada is written in C++ with a particular emphasis on high-performance computing (HPC). Since its publication, samβada, as applied alone or in combination with other methods, proved useful to target putative genomic regions underlying local adaptation in a wide variety of species, including domestic animals such as swine and cattle (Cesconeto et al, 2017;Vajana et al, 2018), wild animals such as the freshwater sculpin and European pond turtle (Lucek, Keller, Nolte, & Seehausen, 2018;Pereira, Teixeira, & Velo-Antón, 2018), and many different plant species including the European beech and the cow-tail fir (Cuervo-Alarcon et al, 2018;Shih, Chang, Chung, Chiang, & Hwang, 2018).…”

Genetic Variation Related to High Elevation Adaptation Revealed by Common Garden Experiments in Pinus yunnanensis

“…Despite these caveats, F ST outlier methods have been used in a large number of studies and has brought emblematic allele discoveries at genes involved in adaptation to different environment conditions (Feulner et al, 2015;Wang et al, 2015;Elgvin et al, 2017;Fustier et al, 2017). However, BayeScan has been considered more conservative in identifying outlier SNPs than other methods (Narum and Hess, 2011b;Cuervo-Alarcon et al, 2018;Gros-Balthazard et al, 2019), and its power to detect outliers depends largely on sample size and number of sampled populations (Lotterhos and Whitlock, 2015;Ahrens et al, 2018). Considering that, in this study, only two populations are involved in each comparison, so, we solely used F ST scan to detect outlier SNPs.…”