Detecting interspecific and geographic differentiation patterns in two interfertile oak species ( Quercus petraea (Matt.) Liebl. and Q. robur L.) using small sets of microsatellite markers

Abstract

Genetic analysis was carried out in order to provide insights into differentiation among populations of two interfertile oak species, Quercus petraea and Quercus robur. Gene flow between the two species, local adaptation and speciation processes in general, may leave differential molecular signatures across the genome. Three interspecific pairs of natural populations from three ecologically different regions, one in central Europe (SW Germany) and two in the Balkan Peninsula (Greece and Bulgaria) were sampled. Grouping of highly informative SSR loci was made according to the component of variation they express—interspecific or provenance specific. ‘Species’ and ‘provenance discriminant’ loci were characterized based on F STs. Locus specific F STs were tested for deviation from the neutral expectation both within and between species. Data were then treated separately in a Bayesian analysis of genetic structure. By using three ‘species discriminant’ loci, high membership probability to inferred species groups was achieved. On the other hand, analysis of genetic structure based on five ‘provenance discriminant’ loci was correlated with geographic region and revealed shared genetic variation between neighbouring Q. petraea and Q. robur. Small sets of highly variable nuclear SSRs were sufficient to discriminate, either between species or between provenances. Thus, an effective tool is provided for molecular identification of both species and provenances. Furthermore, data suggest that a combination of gene flow and natural selection forms these diversity patterns. ‘Species discriminant’ loci might represent genome regions affected by directional selection, which maintains species identity. ‘Provenance specific’ loci might represent genome regions with high interspecific gene flow and common adaptive patterns to local environmental factors.