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Silver fir (Abies alba Mill.) is a keystone conifer of European montane forest ecosystems that has experienced large fluctuations in population size during during the Quaternary and, more recently, due to land-use change. To forecast the species' future distribution and survival, it is important to investigate the genetic basis of adaptation to environmental change, notably to extreme events. For this purpose, we here provide a first draft genome assembly and annotation of the silver fir genome, established through a community-based initiative. DNA obtained from haploid megagametophyte and diploid needle tissue was used to construct and sequence Illumina paired-end and mate-pair libraries, respectively, to high depth. The assembled A. alba genome sequence accounted for over 37 million scaffolds corresponding to 18.16 Gb, with a scaffold N50 of 14,051 bp. Despite the fragmented nature of the assembly, a total of 50,757 full-length genes were functionally annotated in the nuclear genome. The chloroplast genome was also assembled into a single scaffold (120,908 bp) that shows a high collinearity with both the A. koreana and A. sibirica complete chloroplast genomes. This first genome assembly of silver fir is an important genomic resource that is now publicly available in support of a new generation of research. By genome-enabling this important conifer, this resource will open the gate for new research and more precise genetic monitoring of European silver fir forests.

The effects of selection on an organism's genome are hard to detect on small spatial scales, as gene flow can swamp signatures of local adaptation. Therefore, most genome scans to detect signatures of environmental selection are performed on large spatial scales; however, divergent selection on the local scale (e.g. between contrasting soil conditions) has also been demonstrated, in particular for herbaceous plants.Here, we hypothesised that in topographically complex landscapes, microenvironment variability is strong enough to leave a selective footprint in the genomes of long‐lived organisms. To test this, we investigated paired south‐ versus north‐facing Pinus pinaster stands on the local scale, with trees growing in close vicinity (≤820 m distance between paired south‐ and north‐facing stands), in a Mediterranean mountain area. While trees on north‐facing slopes experience less radiation, trees on south‐facing slopes suffer from especially harsh conditions, particularly during the dry summer season.Two outlier analyses consistently revealed five putatively adaptive loci (out of 4034), in candidate genes two of which encoded non‐synonymous substitutions. Additionally, one locus showed consistent allele frequency differences in all three stand pairs indicating divergent selection despite high gene flow on the local scale. Permutation tests demonstrated that our findings were robust.Functional annotation of these candidate genes revealed biological functions related to abiotic stress response, such as water availability, in other plant species.Synthesis. Our study highlights how divergent selection in heterogeneous microenvironments shapes and maintains the functional genetic variation within populations of long‐lived forest tree species, being the first to focus on adaptive genetic divergence between south‐ and north‐facing slopes within continuous forest stands. This is especially relevant in the current context of climate change, as this variation is at the base of plant population responses to future climate. [ABSTRACT FROM AUTHOR]

In nature conservation, there is keen interest in predicting how populations will respond to environmental changes such as climate change. These predictions can help determine whether a population can be self‐sustaining under future alterations of its habitat or whether it may require human intervention such as protection, restoration, or assisted migration. An increasingly popular approach in this respect is the concept of genomic offset, which combines genomic and environmental data from different time points and/or locations to assess the degree of possible maladaptation to new environmental conditions. Here, we argue that the concept of genomic offset holds great potential, but an exploration of its risks and limitations is needed to use it for recommendations in conservation or assisted migration. After briefly describing the concept, we list important issues to consider (e.g., statistical frameworks, population genetic structure, migration, independent evidence) when using genomic offset or developing these methods further. We conclude that genomic offset is an area of development that still lacks some important features and should be used in combination with other approaches to inform conservation measures. [ABSTRACT FROM AUTHOR]

The ongoing increase in global temperature affects biodiversity, especially in mountain regions where climate change is exacerbated. As sessile, long‐lived organisms, trees are especially challenged in terms of adapting to rapid climate change. Here, we show that low rates of allele frequency shifts in Swiss stone pine (Pinus cembra) occurring near the treeline result in high genomic vulnerability to future climate warming, presumably due to the species' long generation time. Using exome sequencing data from adult and juvenile cohorts in the Swiss Alps, we found an average rate of allele frequency shift of 1.23 × 10−2/generation (i.e. 40 years) at presumably neutral loci, with similar rates for putatively adaptive loci associated with temperature (0.96 × 10−2/generation) and precipitation (0.91 × 10−2/generation). These recent shifts were corroborated by forward‐in‐time simulations at neutral and adaptive loci. Additionally, in juvenile trees at the colonisation front we detected alleles putatively beneficial under a future warmer and drier climate. Notably, the observed past rate of allele frequency shift in temperature‐associated loci was decidedly lower than the estimated average rate of 6.29 × 10−2/generation needed to match a moderate future climate scenario (RCP4.5). Our findings suggest that species with long generation times may have difficulty keeping up with the rapid climate change occurring in high mountain areas and thus are prone to local extinction in their current main elevation range. [ABSTRACT FROM AUTHOR]

It has long been discussed to what extent related species develop similar genetic mechanisms to adapt to similar environments. Most studies documenting such convergence have either used different lineages within species or surveyed only a limited portion of the genome. Here, we investigated whether similar or different sets of orthologous genes were involved in genetic adaptation of natural populations of three related plant species to similar environmental gradients in the Alps. We used whole‐genome pooled population sequencing to study genome‐wide SNP variation in 18 natural populations of three Brassicaceae (Arabis alpina, Arabidopsis halleri, and Cardamine resedifolia) from the Swiss Alps. We first de novo assembled draft reference genomes for all three species. We then ran population and landscape genomic analyses with ~3 million SNPs per species to look for shared genomic signatures of selection and adaptation in response to similar environmental gradients acting on these species. Genes with a signature of convergent adaptation were found at significantly higher numbers than expected by chance. The most closely related species pair showed the highest relative over‐representation of shared adaptation signatures. Moreover, the identified genes of convergent adaptation were enriched for nonsynonymous mutations, suggesting functional relevance of these genes, even though many of the identified candidate genes have hitherto unknown or poorly described functions based on comparison with Arabidopsis thaliana. We conclude that adaptation to heterogeneous Alpine environments in related species is partly driven by convergent evolution, but that most of the genomic signatures of adaptation remain species‐specific. [ABSTRACT FROM AUTHOR]

It is generally accepted that the spatial distribution of neutral genetic diversity within a species' native range mostly depends on effective population size, demographic history, and geographic position. However, it is unclear how genetic diversity at adaptive loci correlates with geographic peripherality or with habitat suitability within the ecological niche. Using exome‐wide genomic data and distribution maps of the Alpine range, we first tested whether geographic peripherality correlates with four measures of population genetic diversity at > 17,000 SNP loci in 24 Alpine populations (480 individuals) of Swiss stone pine (Pinus cembra) from Switzerland. To distinguish between neutral and adaptive SNP sets, we used four approaches (two gene diversity estimates, FST outlier test, and environmental association analysis) that search for signatures of selection. Second, we established ecological niche models for P. cembra in the study range and investigated how habitat suitability correlates with genetic diversity at neutral and adaptive loci. All estimates of neutral genetic diversity decreased with geographic peripherality, but were uncorrelated with habitat suitability. However, heterozygosity (He) at adaptive loci based on Tajima's D declined significantly with increasingly suitable conditions. No other diversity estimates at adaptive loci were correlated with habitat suitability. Our findings suggest that populations at the edge of a species' geographic distribution harbour limited neutral genetic diversity due to demographic properties. Moreover, we argue that populations from suitable habitats went through strong selection processes, are thus well adapted to local conditions, and therefore exhibit reduced genetic diversity at adaptive loci compared to populations at niche margins. [ABSTRACT FROM AUTHOR]

Long generation times have been suggested to hamper rapid genetic adaptation of organisms to changing environmental conditions. We examined if environmental memory of the parental Scots pines (Pinus sylvestris L.) drive offspring survival and growth. We used seeds from trees growing under naturally dry conditions (control), irrigated trees (irrigated from 2003 to 2016), and formerly irrigated trees ("irrigation stop"; irrigated from 2003–2013; control condition since 2014). We performed two experiments, one under controlled greenhouse conditions and one at the experimental field site. In the greenhouse, the offspring from control trees exposed regularly to drought were more tolerant to hot–drought conditions than the offspring from irrigated trees and showed lower mortality even though there was no genetic difference. However, under optimal conditions (high water supply and full sunlight), these offspring showed lower growth and were outperformed by the offspring of the irrigated trees. This different offspring growth, with the offspring of the "irrigation‐stop" trees showing intermediate responses, points to the important role of transgenerational memory for the long‐term acclimation of trees. Such memory effects, however, may be overridden by climatic extremes during germination and early growth stages such as the European 2018 mega‐drought that impacted our field experiment. Environmental conditions (natural dry vs. irrigated) experienced by the mother trees of Pinus sylvestris significantly influenced the offspring's growth and survival, indicating that transgenerational environmental memory can shape trees' acclimation potential over the midterm to the long term. [ABSTRACT FROM AUTHOR]

Background and Aims Hybridization and introgression play an important role in the evolution and diversification of plants. To assess the degree of past and current hybridization, the level of genetic admixture in populations needs to be investigated. Ongoing hybridization and blurred species separation have made it challenging to assign European white oak taxa based on leaf morphology and/or genetic markers and to assess the level of admixture. Therefore, there is a need for powerful markers that differentiate between taxa. Here, we established a condensed set of single-nucleotide polymorphism (SNP) markers to reliably differentiate between the three most common oak species in temperate European forests (Quercus robur , Q. petraea , Q. pubescens) and to assess the degree of admixture in a large set of selected Swiss populations. Methods A training set of 194 presumably pure reference samples from Switzerland and Europe was used to assign 633 test individuals with two different approaches (population genetic-based/Bayesian vs. assumption-free/discriminative classifier) using 58 selected SNPs from coding regions. Admixture was calculated at the individual and population level with the Shannon diversity index based on individual assignment probabilities. Key Results Depending on the approach, 97.5–100 % of training individuals were assigned correctly, and additional analyses showed that the established SNP set could be further reduced while maintaining its discriminatory power. The two assignment approaches showed high overlap (99 %) in assigning training individuals and slightly less overlap in test individuals (84 %). Levels of admixture varied widely among populations. Mixed stands of Q. petraea and Q. pubescens revealed much higher degrees of admixture than mixed stands of the other two taxon pairs, accentuating high levels of gene flow between these two taxa in Switzerland. Conclusions Our set of SNPs warrants reliable taxon discrimination with great potential for further applications. We show that the three European white oak taxa have largely retained their species integrity in Switzerland despite high levels of admixture. [ABSTRACT FROM AUTHOR]

Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco‐evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large‐scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco‐evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions. [ABSTRACT FROM AUTHOR]

Many forest tree species have characteristics that make the study of their evolutionary ecology complex. For example, they are long‐lived and thus have long generation times, and their often large, complex genomes have hampered establishing genomic resources. One way to tackle this challenge is to access multiple complementary data sources and analytical approaches when attempting to infer patterns of adaptive evolution. In the cover article of this issue of Molecular Ecology, Depardieu et al. (2021) combine large amounts of environmental, genomic, dendrochronological, and gene expression data in a common garden to explore the polygenic basis of drought resistance in white spruce (Picea glauca), a long‐lived conifer. They identify candidate genes involved in growth and resistance to extreme drought events and show how multiple data sets may deliver complementary evidence to circumvent the manifold challenges of the research field. [ABSTRACT FROM AUTHOR]

Despite decreasing sequencing costs, whole‐genome sequencing for population‐based genome scans for selection is still prohibitively expensive for organisms with large genomes. Moreover, the repetitive nature of large genomes often represents a challenge in bioinformatic and downstream analyses. Here, we use in‐depth transcriptome sequencing to design probes for exome capture in Swiss stone pine (Pinus cembra), a conifer with an estimated genome size of 29.3 Gbp and no reference genome available. We successfully applied around 55,000 self‐designed probes, targeting 25,000 contigs, to DNA pools of seven populations from the Swiss Alps and identified >160,000 SNPs in around 15,000 contigs. The probes performed equally well in pools of the closely related species Pinus sibirica; in both species, more than 70% of the targeted contigs were sequenced at a depth ≥40× (number of haplotypes in the pool). However, a thorough analysis of individually sequenced P. cembra samples indicated that a majority of the contigs (63%) represented multi‐copy genes. We therefore removed paralogous contigs based on heterozygote excess and deviation from allele balance. Without putatively paralogous contigs, allele frequencies of population pools represented accurate estimates of individually determined allele frequencies. We show that inferences of neutral and adaptive genetic variation may be biased when not accounting for such multi‐copy genes. Without individual genotype data, it would have been nearly impossible to recognize and deal with the problem of multi‐copy contigs. We advocate to put more emphasis on identifying paralogous loci, which will be facilitated by the establishment of additional high‐quality reference genomes. [ABSTRACT FROM AUTHOR]

Over the last decade, the genomic revolution has offered the possibility to generate tremendous amounts of data that contain valuable information on the genetic basis of phenotypic traits, such as those linked to human diseases or those that allow for species to adapt to a changing environment. Most ecologically relevant traits are controlled by a large number of genes with small individual effects on trait variation, but that are connected with one another through complex developmental, metabolic and biochemical networks. As a result, it has recently been suggested that most adaptation events in natural populations are reached via correlated changes at multiple genes at a time, for which the name polygenic adaptation has been coined. The current challenge is to develop methods to extract the relevant information from genomic data to detect the signature of polygenic evolutionary change. The symposium entitled “Detecting the Genomic Signal of Polygenic Adaptation and the Role of Epistasis in Evolution” held in 2017 at the University of Zürich aimed at reviewing our current state of knowledge. In this review, we use the talks of the invited speakers to summarize some of the most recent developments in this field. [ABSTRACT FROM AUTHOR]

Background: Microsatellite markers are widely used for estimating genetic diversity within and differentiation among populations. However, it has rarely been tested whether such estimates are useful proxies for genome-wide patterns of variation and differentiation. Here, we compared microsatellite variation with genome-wide single nucleotide polymorphisms (SNPs) to assess and quantify potential marker-specific biases and derive recommendations for future studies. Overall, we genotyped 180 Arabidopsis halleri individuals from nine populations using 20 microsatellite markers. Twelve of these markers were originally developed for Arabidopsis thaliana (cross-species markers) and eight for A. halleri (species-specific markers). We further characterized 2 million SNPs across the genome with a pooled whole-genome re-sequencing approach (Pool-Seq). Results: Our analyses revealed that estimates of genetic diversity and differentiation derived from cross-species and species-specific microsatellites differed substantially and that expected microsatellite heterozygosity (SSR-He) was not significantly correlated with genome-wide SNP diversity estimates (SNP-He and θWatterson) in A. halleri. Instead, microsatellite allelic richness (Ar) was a better proxy for genome-wide SNP diversity. Estimates of genetic differentiation among populations (FST) based on both marker types were correlated, but microsatellite-based estimates were significantly larger than those from SNPs. Possible causes include the limited number of microsatellite markers used, marker ascertainment bias, as well as the high variance in microsatellite-derived estimates. In contrast, genomewide SNP data provided unbiased estimates of genetic diversity independent of whether genome- or only exome-wide SNPs were used. Further, we inferred that a few thousand random SNPs are sufficient to reliably estimate genome-wide diversity and to distinguish among populations differing in genetic variation. Conclusions: We recommend that future analyses of genetic diversity within and differentiation among populations use randomly selected high-throughput sequencing-based SNP data to draw conclusions on genome-wide diversity patterns. In species comparable to A. halleri, a few thousand SNPs are sufficient to achieve this goal. [ABSTRACT FROM AUTHOR]

Testing how populations are locally adapted and predicting their response to their future environment is of key importance in view of climate change. Landscape genomics is a powerful approach to investigate genes and environmental factors involved in local adaptation. In a pooled amplicon sequencing approach of 94 genes in 71 populations, we tested whether >3500 single nucleotide polymorphisms ( SNPs) in the three most common oak species in Switzerland ( Quercus petraea, Q. pubescens, Q. robur) show an association with abiotic factors related to local topography, historical climate and soil characteristics. In the analysis including all species, the most frequently associated environmental factors were those best describing the habitats of the species. In the species-specific analyses, the most important environmental factors and associated SNPs greatly differed among species. However, we identified one SNP and seven genes that were associated with the same environmental factor across all species. We finally used regressions of allele frequencies of the most strongly associated SNPs along environmental gradients to predict the risk of nonadaptedness ( RONA), which represents the average change in allele frequency at climate-associated loci theoretically required to match future climatic conditions. RONA is considerable for some populations and species (up to 48% in single populations) and strongly differs among species. Given the long generation time of oaks, some of the required allele frequency changes might not be realistic to achieve based on standing genetic variation. Hence, future adaptedness requires gene flow or planting of individuals carrying beneficial alleles from habitats currently matching future climatic conditions. [ABSTRACT FROM AUTHOR]

Landscape genomics is an emerging research field that aims to identify the environmental factors that shape adaptive genetic variation and the gene variants that drive local adaptation. Its development has been facilitated by next-generation sequencing, which allows for screening thousands to millions of single nucleotide polymorphisms in many individuals and populations at reasonable costs. In parallel, data sets describing environmental factors have greatly improved and increasingly become publicly accessible. Accordingly, numerous analytical methods for environmental association studies have been developed. Environmental association analysis identifies genetic variants associated with particular environmental factors and has the potential to uncover adaptive patterns that are not discovered by traditional tests for the detection of outlier loci based on population genetic differentiation. We review methods for conducting environmental association analysis including categorical tests, logistic regressions, matrix correlations, general linear models and mixed effects models. We discuss the advantages and disadvantages of different approaches, provide a list of dedicated software packages and their specific properties, and stress the importance of incorporating neutral genetic structure in the analysis. We also touch on additional important aspects such as sampling design, environmental data preparation, pooled and reduced-representation sequencing, candidate-gene approaches, linearity of allele-environment associations and the combination of environmental association analyses with traditional outlier detection tests. We conclude by summarizing expected future directions in the field, such as the extension of statistical approaches, environmental association analysis for ecological gene annotation, and the need for replication and post hoc validation studies. [ABSTRACT FROM AUTHOR]

Natural genetic variation is essential for the adaptation of organisms to their local environment and to changing environmental conditions. Here, we examine genomewide patterns of nucleotide variation in natural populations of the outcrossing herb Arabidopsis halleri and associations with climatic variation among populations in the Alps. Using a pooled population sequencing (Pool-Seq) approach, we discovered more than two million SNPs in five natural populations and identified highly differentiated genomic regions and SNPs using FST-based analyses. We tested only the most strongly differentiated SNPs for associations with a nonredundant set of environmental factors using partial Mantel tests to identify topo-climatic factors that may underlie the observed footprints of selection. Possible functions of genes showing signatures of selection were identified by Gene Ontology analysis. We found 175 genes to be highly associated with one or more of the five tested topo-climatic factors. Of these, 23.4% had unknown functions. Genetic variation in four candidate genes was strongly associated with site water balance and solar radiation, and functional annotations were congruent with these environmental factors. Our results provide a genomewide perspective on the distribution of adaptive genetic variation in natural plant populations from a highly diverse and heterogeneous alpine environment. [ABSTRACT FROM AUTHOR]

Abstract: Infections by multiple parasite species are common in nature and have important consequences for between-species interactions and coevolutionary dynamics with the host populations. For example, ecological and evolutionary factors underlying the structure of parasite communities determine the range of hosts a parasite can infect and set the basis for both evolution of host defences and parasite virulence, as well as management of diseases. Studies investigating these factors have been facilitated in the recent past by genetic methods, which surmount difficulties of traditional morphological taxonomy in identifying individual parasite species. Here we take a step further and present a novel methodological approach to analyze parasite communities as a whole. We determined the relative frequencies of interspecific SNP alleles by pyrosequencing naturally pooled samples of closely related Diplostomum spp. trematodes infecting eye lenses of freshwater fish. Pyrosequencing allowed us to use naturally pooled community samples (lenses) to increase the sample size and statistical power, without sequencing single parasite specimens. In a case study, we applied this method to analyze the community structure of the eye flukes across fish host species of a freshwater system in Finland. We found that the fish species harboured significantly different parasite communities and that multiple species infections were common. Our study provides an example of how quantitative pyrosequencing can be used to answer evolutionary and ecological questions in natural communities of parasites. [Copyright &y& Elsevier]

Sequencing of pooled samples (Pool-Seq) using next-generation sequencing technologies has become increasingly popular, because it represents a rapid and cost-effective method to determine allele frequencies for single nucleotide polymorphisms (SNPs) in population pools. Validation of allele frequencies determined by Pool-Seq has been attempted using an individual genotyping approach, but these studies tend to use samples from existing model organism databases or DNA stores, and do not validate a realistic setup for sampling natural populations. Here we used pyrosequencing to validate allele frequencies determined by Pool-Seq in three natural populations of Arabidopsis halleri (Brassicaceae). The allele frequency estimates of the pooled population samples (consisting of 20 individual plant DNA samples) were determined after mapping Illumina reads to (i) the publicly available, high-quality reference genome of a closely related species (Arabidopsis thaliana) and (ii) our own de novo draft genome assembly of A. halleri. We then pyrosequenced nine selected SNPs using the same individuals from each population, resulting in a total of 540 samples. Our results show a highly significant and accurate relationship between pooled and individually determined allele frequencies, irrespective of the reference genome used. Allele frequencies differed on average by less than 4%. There was no tendency that either the Pool-Seq or the individual-based approach resulted in higher or lower estimates of allele frequencies. Moreover, the rather high coverage in the mapping to the two reference genomes, ranging from 55 to 284x, had no significant effect on the accuracy of the Pool-Seq. A resampling analysis showed that only very low coverage values (below 10-20x) would substantially reduce the precision of the method. We therefore conclude that a pooled re-sequencing approach is well suited for analyses of genetic variation in natural populations. [ABSTRACT FROM AUTHOR]

Vertebrate hosts often defend themselves against several co-infecting parasite genotypes simultaneously. This has important implications for the ecological dynamics and the evolution of host defence systems and parasite strategies. For example, it can drive the specificity of the adaptive immune system towards high genotype-specificity or cross-reactivity against several parasite genotypes depending on the sequence and probability of re-infections. However, to date, there is very little evidence on these interactions outside mammalian disease literature. In this study we asked whether genotype-specific or cross-reactive responses dominate in the adaptive immune system of a fish host towards a common macroparasite. In other words, we investigated if the infection success of a parasite genotype is influenced by the immunization genotype. We reciprocally immunized and re-exposed rainbow trout (Oncorhynchus mykiss) to a range of genotypes of the trematode eye fluke Diplostomum pseudospathaceum, and measured infection success of the parasite. We found that the infection success of the parasite genotypes in the re-exposure did not depend on the immunization genotype. While immunization reduced average infection success by 31%, the reduction was not larger against the initial immunization genotype. Our results suggest significant cross-reactivity, which may be advantageous for the host in genetically diverse re-exposures and have significant evolutionary implications for parasite strategies. Overall, our study is among the first to demonstrate cross-reactivity of adaptive immunity against genetically diverse macroparasites with complex life cycles. [ABSTRACT FROM AUTHOR]