Predicting the evolutionary potential of natural tree populations requires the estimation of heritability and genetic correlations among traits on which selection acts, as differences in evolutionary success between species may rely on differences for these genetic parameters. estimates are expected to be more accurate than measures done under controlled conditions which do not reflect the natural environmental variance.

Reproduction, one of the main components of plant fitness, is highly variable in response to environmental cues, but little is known about the genetic determinism underlying reproduction-related traits in forest tree species. There is therefore an urgent need to characterize the genetic architecture of those traits if we are to predict the evolutionary trajectories of forest populations facing rapidly changing environment and mitigate their impacts. Using a full-sib family of pedunculate oak (), we investigated the within population variability of seed production and mean seed mass during four consecutive years. Reproductive traits were highly variable between trees and between years. The high narrow sense heritability and evolvability estimated underline the important genetic effect on the variability in seed production and mean seed mass. Despite a large variability over years, reproductive traits show significant genetic correlation between years. Furthermore, for the first time in forest tree species, quantitative trait loci (QTLs) associated with seed production and mean mass of a seed have been identified. While it is commonly assumed and observed that fitness-traits have low narrow sense heritabilities, our findings show that reproduction-related traits may undergo evolutionary changes under selective pressure and may be determinant for tree adaptation.

Efforts to detect loci under selection in plants have mostly focussed on single species. However, assuming that intraspecific divergence may lead to speciation, comparisons of genetic variation within and among recently diverged taxa can help to locate such genes. In this study, coalescent and outlier detection methods were used to assess nucleotide polymorphism and divergence at 79 nuclear gene fragments (1212 SNPs) in 16 populations (153 individuals) of the closely related, but phenotypically and ecologically distinct, pine taxa , and across their European distributions. Simultaneously, mitochondrial DNA markers, which are maternally inherited in pines and distributed by seeds at short geographic distance, were used to assess genetic relationships of the focal populations and taxa. The majority of nuclear loci showed homogenous patterns of variation between the taxa due to a high number of shared SNPs and haplotypes, similar levels of polymorphism, and low net divergence. However, against this common genetic background and an overall low population structure within taxa at mitochondrial markers, we identified several genes showing signatures of selection, accompanied by significant intra- and interspecific divergence. Our results indicate that loci involved in species divergence may be involved in intraspecific local adaptation.

Rapid human-induced environmental changes like climate warming represent a challenge for forest ecosystems. Due to their biological complexity and the long generation time of their keystone tree species, genetic adaptation in these ecosystems might not be fast enough to keep track with conditions changing at such a fast pace. The study of adaptation to environmental change and its genetic mechanisms is therefore key for ensuring a sustainable support and management of forests. The 4-day conference of the European Research Group EvolTree (https://www.evoltree.eu) on the topic of "Genomics and Adaptation in Forest Ecosystems" brought together over 130 scientists to present and discuss the latest developments and findings in forest evolutionary research. Genomic studies in forest trees have long been hampered by the lack of high-quality genomics resources and affordable genotyping methods. This has dramatically changed in the last few years; the conference impressively showed how such tools are now being applied to study past demography, adaptation and interactions with associated organisms. Moreover, genomic studies are now finally also entering the world of conservation and forest management, for example by measuring the value or cost of interspecific hybridization and introgression, assessing the vulnerability of species and populations to future change, or accurately delineating evolutionary significant units. The newly launched conference series of EvolTree will hopefully play a key role in the exchange and synthesis of such important investigations.

Genetic diversity influences the evolutionary potential of forest trees under changing environmental conditions, thus indirectly the ecosystem services that forests provide. European beech ( L.) is a dominant European forest tree species that increasingly suffers from climate change-related die-back. Here, we conducted a systematic literature review of neutral genetic diversity in European beech and created a meta-data set of expected heterozygosity () from all past studies providing nuclear microsatellite data. We propose a novel approach, based on population genetic theory and a min-max scaling to make past studies comparable. Using a new microsatellite data set with unprecedented geographic coverage and various re-sampling schemes to mimic common sampling biases, we show the potential and limitations of the scaling approach. The scaled meta-dataset reveals the expected trend of decreasing genetic diversity from glacial refugia across the species range and also supports the hypothesis that different lineages met and admixed north of the European mountain ranges. As a result, we present a map of genetic diversity across the range of European beech which could help to identify seed source populations harboring greater diversity and guide sampling strategies for future genome-wide and functional investigations of genetic variation. Our approach illustrates how to combine information from several nuclear microsatellite data sets to describe patterns of genetic diversity extending beyond the geographic scale or mean number of loci used in each individual study, and thus is a proof-of-concept for synthesizing knowledge from existing studies also in other species.

Many quantitative genetic models assume that all genetic variation is additive because of a lack of data with sufficient structure and quality to determine the relative contribution of additive and non-additive variation. Here the fractions of additive () and non-additive () genetic variation were estimated in Sitka spruce for height, bud burst and pilodyn penetration depth. Approximately 1500 offspring were produced in each of three sib families and clonally replicated across three geographically diverse sites. Genotypes from 1525 offspring from all three families were obtained by RADseq, followed by imputation using 1630 loci segregating in all families and mapped using the newly developed linkage map of Sitka spruce. The analyses employed a new approach for estimating and , which combined all available genotypic and phenotypic data with spatial modelling for each trait and site. The consensus estimate for increased with age for height from 0.58 at 2 years to 0.75 at 11 years, with only small overlap in 95% support intervals (). The estimated for bud burst was 0.83 (=[0.78, 0.90]) and 0.84 (=[0.77, 0.92]) for pilodyn depth. Overall, there was no evidence of family heterogeneity for height or bud burst, or site heterogeneity for pilodyn depth, and no evidence of inbreeding depression associated with genomic homozygosity, expected if dominance variance was the major component of non-additive variance. The results offer no support for the development of sublines for crossing within the species. The models give new opportunities to assess more accurately the scale of non-additive variation.

During the process of almond () domestication, essential traits, which gave plants the plasticity for facing unstable environmental conditions, were lost. In general, the domestication process often narrows the natural genetic diversity. Modern selections (i.e., breeding programs) dramatically accelerated this genetic bottleneck trend to a few successful almond cultivars, which are presently the founders of most commercial cultivars worldwide. The concept of utilizing wild species as a source for important traits and for the enrichment of the gene pool was deeply discussed in previous studies. However, in almonds and other species, deliberate utilization of wild species as a genetic resource for breeding programs is quite rare. To address these significant challenges, we generated an interspecific F1 population between the Israeli almond cultivar Um el Fahem (UEF) and a specimen of a local wild almond species, (), originating from the Judea desert. This interspecific F1 population possesses high phenotypic variability, and sixteen segregating traits were phenotyped. Among the segregating traits, we were able to genetically associate six agriculturally important traits, such as leaf chlorophyll content (LCC), flower size, and fruit size. The alleles for Self-Compatibility (SC) and kernel bitterness were previously mapped in almond and were reexamined on the background of the distinctive wild genetic material of . Finally, phenotypic interactions between traits were suggested, such as rootstock perimeter and canopy area that were positively correlated with total yield in the F1 population. This study is a first step towards developing a well-characterized almond interspecies genetic population. The availability of such a genetic tool with detailed phenotypic analysis is crucial to address and explore the profound influence of almond wild species in genetic research and breeding. By using the interspecific population as the infrastructure, we show the advantages and importance of utilizing wild relatives.