DOI: 10.5061/dryad.vhhmgqp4d
title: Data from: The influence of post-glacial migration and hybridization on the gene pool of marginal Quercus pubescens populations in Central Europe

description: Background and Aims In Central Europe, the drought-tolerant downy oak
 (Quercus pubescens) is at the northern edge of its natural distribution
 range, often growing in small and spatially isolated populations. Here, we
 elucidate how the population genetic structure of Central European Q.
 pubescens was shaped by geographic barriers, genetic drift and
 introgression with the closely related sessile oak (Q. petraea). Methods
 27 Q. pubescens populations from the northern margin of Q. pubescens’
 natural distribution range were sampled. Based on 16 nuclear
 microsatellite markers (nSSRs), Bayesian clustering and distance-based
 analyses were performed to determine the intraspecific genetic structure
 and to identify genetic barriers. To identify drivers of introgression
 with Q. petraea, generalised linear models were applied to link levels of
 introgression with environmental conditions. To track post-glacial
 migration routes, the spatial distribution of haplotypes based on 8
 chloroplast microsatellite markers (cpSSRs) was investigated. Key Results
 Based on nSSRs, the study populations of Q. pubescens were divided into a
 western and an eastern genetic cluster. Within these clusters, more
 pronounced genetic substructure was observed in the west, probably due to
 a rugged topography and limited gene flow. Introgression from Q. petraea
 was more prevalent at wetter and north-exposed sites and in the west. The
 identified cpSSR haplotypes followed known migration pathways. Conclusions
 Our results suggest two late-glacial refugia in or near the southwestern
 Alps and the southeastern Alps as potential sources for post-glacial
 migration. Although some genetic exchange is evident in Northern Italy,
 south of the Alps, the two clusters remain distinct at a large scale.
 Landscape features and introgression with Q. petraea shaped the genetic
 substructure at a smaller scale. Our study provides a comprehensive
 overview of the genetic structure of Q. pubescens in Central Europe,
 relevant for conservation.
description: Genotyping of nSSRs and cpSSRs: To determine the length of the
 amplified fragments (alleles) in base pairs (bp), capillary
 electrophoresis was performed using the sequencer SeqStudio Genetic
 Analyzer from Applied Biosystems by Thermo Fisher Scientific. The software
 GeneMapper® Software 6 (Applied Biosystems) was used to perform peak
 scoring. Exported allele lists have been stored as text files. 
 Georeferenced samples: All samples have been georeferenced in the
 field by using a GPS device. All coordinates were stored in decimal degree
 (WGS 84).
description: # Data from: The influence of post-glacial migration and hybridization on
 the gene pool of marginal Quercus pubescens populations in Central Europe
 [https://doi.org/10.5061/dryad.vhhmgqp4d](https://doi.org/10.5061/dryad.vhhmgqp4d) ## Description of the data and file structure Genotyping: All individuals were genotyped with nSSRs (nuclear microsatellite markers), whereas cpSSRs (chloroplast microsatellite markers) were amplified for every second individual of a population. To determine the length of the amplified fragments (alleles) in base pairs (bp), capillary electrophoresis was performed using the sequencer SeqStudio Genetic Analyzer from Applied Biosystems by Thermo Fisher Scientific. The software GeneMapper® Software 6 (Applied Biosystems) was used to perform peak scoring. Georeferencing of individuals: All individuals were georeferenced in the field by using a GPS device. Geographic positions are stored in decimal degree (WGS 84) ### Files and variables #### File: DRYAD\_Dataset\_AoB\_Q\_pubescens\_2024.xlsx **Description:** The datasets consists of genotype lists of nSSRs and cpSSRs for each individual white oak tree used in the analysis. About 16 NSSRs and 8 cpSSRs were used. The reference to each loci is also given. Data about studied populations are also give by the country, population ID used in the study, and the geographic position. ##### Variables * ID of individuals, ID of populations, loci names for nSSRs and cpSSRs including the respective basepair leght of each individual at each locus. * Geographic position: latitude, longitude in decimal degrees (WGS 84) ## Code/software To open the dataset file the free software tool "LibeOffice Calc" can be used. Genotype lists can be copied to any text document editor to be further processed for other software.