Understanding the dynamics and mechanisms of local adaptation in natural populations provides the basis for predicting responses to environmental changes, including those associated to global climate change. European beech (Fagus sylvatica L.) is one of the most economically and ecologically important deciduous trees in Europe. Nevertheless, little is known about its genomic adaptive diversity and adaptive potential. Genetic differentiation in beech sites associated with environmental adaptation was assessed by genotyping 1384 single nucleotide polymorphisms (SNPs) in candidate genes. The study included 153 beech individuals from 12 populations located in Italy, Slovenia, and Croatia, with diverse bio-geoclimatic conditions. PCA-based and the Fst-based method of differentiation (PCAdapt and LEA) and two different Environmental Association Analysis approaches (Latent Factor Mixed Model and Samβada) were used to identify loci with significant correlations with bioclimatic indicators. The results obtained in this study allowed us to identify signature of regional and local environment adaptation. Specific patterns of local adaptation were observed for each studied population. We identified allelic variants associated with the response to precipitation fluctuations and drought periods during the growing season. Particularly interesting is the observation of differences in the presence and effect of allelic variants among different sites, likely due to adaptation to the local environment and the different silvicultural history of each observed population.

Genome-wide SNP association analysis reveals the genomic signature of local adaptation in natural populations of European beech (Fagus sylvatica L.) / Cesare Garosi, Cristina Vettori, Lorenzo Arcidiaco, Marko Bajc, Hojka Kraigher, Marjana Westergren, Davide Travaglini, Rok Damjanić, Kristina Sever, Andrej Breznikar, Andreja Gregoric, Miran Lanšćak, Mladen Ivankovic, Sanja Bogunović, Donatella Paffetti. - In: TREES, FORESTS AND PEOPLE. - ISSN 2666-7193. - ELETTRONICO. - 21:(2025), pp. 100981.1-100981.12. [10.1016/j.tfp.2025.100981]

Genome-wide SNP association analysis reveals the genomic signature of local adaptation in natural populations of European beech (Fagus sylvatica L.)

Cesare Garosi;Cristina Vettori
;
Davide Travaglini;Donatella Paffetti
2025

Abstract

Understanding the dynamics and mechanisms of local adaptation in natural populations provides the basis for predicting responses to environmental changes, including those associated to global climate change. European beech (Fagus sylvatica L.) is one of the most economically and ecologically important deciduous trees in Europe. Nevertheless, little is known about its genomic adaptive diversity and adaptive potential. Genetic differentiation in beech sites associated with environmental adaptation was assessed by genotyping 1384 single nucleotide polymorphisms (SNPs) in candidate genes. The study included 153 beech individuals from 12 populations located in Italy, Slovenia, and Croatia, with diverse bio-geoclimatic conditions. PCA-based and the Fst-based method of differentiation (PCAdapt and LEA) and two different Environmental Association Analysis approaches (Latent Factor Mixed Model and Samβada) were used to identify loci with significant correlations with bioclimatic indicators. The results obtained in this study allowed us to identify signature of regional and local environment adaptation. Specific patterns of local adaptation were observed for each studied population. We identified allelic variants associated with the response to precipitation fluctuations and drought periods during the growing season. Particularly interesting is the observation of differences in the presence and effect of allelic variants among different sites, likely due to adaptation to the local environment and the different silvicultural history of each observed population.
2025
21
1
12
Cesare Garosi, Cristina Vettori, Lorenzo Arcidiaco, Marko Bajc, Hojka Kraigher, Marjana Westergren, Davide Travaglini, Rok Damjanić, Kristina Sever, A...espandi
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1432732
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