Best practices for genetic and genomic data archiving.

Genetic and genomic data are collected for a vast array of scientific and applied purposes. Despite mandates for public archiving, data are typically used only by the generating authors. The reuse of genetic and genomic datasets remains uncommon because it is difficult, if not impossible, due to non-standard archiving practices and lack of contextual metadata. But as the new field of macrogenetics is demonstrating, if genetic data and their metadata were more accessible and FAIR (findable, accessible, interoperable and reusable) compliant, they could be reused for many additional purposes. We discuss the main challenges with existing genetic and genomic data archives, and suggest best practices for archiving genetic and genomic data. Recognizing that this is a longstanding issue due to little formal data management training within the fields of ecology and evolution, we highlight steps that research institutions and publishers could take to improve data archiving.

Re-thinking the environment in landscape genomics.

Detecting the extrinsic selective pressures shaping genomic variation is critical for a better understanding of adaptation and for forecasting evolutionary responses of natural populations to changing environmental conditions. With increasing availability of geo-referenced environmental data, landscape genomics provides unprecedented insights into how genomic variation and underlying gene functions affect traits potentially under selection. Yet, the robustness of genotype-environment associations used in landscape genomics remains tempered due to various limitations, including the characteristics of environmental data used, sampling designs employed, and statistical frameworks applied. Here, we argue that using complementary or new environmental data sources and well-informed sampling designs may help improve the detection of selective pressures underlying patterns of local adaptation in various organisms and environments.

The mitochondrial genome sequence of Abies alba Mill. reveals a high structural and combinatorial variation.

BACKGROUND: Plant mitogenomes vary widely in size and genomic architecture. Although hundreds of plant mitogenomes of angiosperm species have already been sequence-characterized, only a few mitogenomes are available from gymnosperms. Silver fir (Abies alba) is an economically important gymnosperm species that is widely distributed in Europe and occupies a large range of environmental conditions. Reference sequences of the nuclear and chloroplast genome of A. alba are available, however, the mitogenome has not yet been assembled and studied. RESULTS: Here, we used paired-end Illumina short reads generated from a single haploid megagametophyte in combination with PacBio long reads from high molecular weight DNA of needles to assemble the first mitogenome sequence of A. alba. Assembly and scaffolding resulted in 11 mitogenome scaffolds, with the largest scaffold being 0.25 Mbp long. Two of the scaffolds displayed a potential circular structure supported by PCR. The total size of the A. alba mitogenome was estimated at 1.43 Mbp, similar to the size (1.33 Mbp) of a draft assembly of the Abies firma mitogenome. In total, 53 distinct genes of known function were annotated in the A. alba mitogenome, comprising 41 protein-coding genes, nine tRNA, and three rRNA genes. The proportion of highly repetitive elements (REs) was 0.168. The mitogenome seems to have a complex and dynamic structure featured by high combinatorial variation, which was specifically confirmed by PCR for the contig with the highest mapping coverage. Comparative analysis of all sequenced mitogenomes of gymnosperms revealed a moderate, but significant positive correlation between mitogenome size and proportion of REs. CONCLUSIONS: The A. alba mitogenome provides a basis for new comparative studies and will allow to answer important structural, phylogenetic and other evolutionary questions. Future long-read sequencing with higher coverage of the A. alba mitogenome will be the key to further resolve its physical structure. The observed positive correlation between mitogenome size and proportion of REs will be further validated once available mitogenomes of gymnosperms would become more numerous. To test whether a higher proportion of REs in a mitogenome leads to an increased recombination and higher structural complexity and variability is a prospective avenue for future research.

Genomics and adaptation in forest ecosystems.

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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11295-022-01542-1.

Tackling the challenges of evolutionary forest research with multidata approaches.

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.

Prospects and limitations of genomic offset in conservation management.

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.

Post-glacial re-colonization and natural selection have shaped growth responses of silver fir across Europe.

Warmer climate and more frequent extreme droughts will pose major threats to forest ecosystems. Past demography processes due to post-glacial recolonization and adaptation to local environmental conditions are among the main contributors to genetic differentiation processes among provenances. Assessing the intra-specific variability of tree growth responses to such changes is crucial to explore a species' potential to cope with climate warming. We combined growth-related traits derived from tree-ring width series with neutral genetic information of 18 European provenances of silver fir (Abies alba Mill.) growing in two common garden experiments in Switzerland. Analyses based on neutral single nucleotide polymorphisms revealed that the studied provenances grouped into three longitudinal clusters. These three genetic clusters showed differences in growth traits (height and DBH), with the provenances from the eastern cluster exhibiting the highest growth. The Pyrenees cluster showed significantly lower recovery and resilience to the extreme drought of 2003 as well as lower values of growth autocorrelation. QST-FST and correlation analyses with climate of provenance origin suggest that the differences among provenances found in some traits result from natural selection. Our study suggests that the last post-glacial re-colonization and natural selection are the major drivers explaining the intra-specific variability in growth of silver fir across Europe. These findings highlight the importance of combining dendroecology and genetic analyses on fitness-related traits to assess the potential of a species to cope with global environmental change and provide insights to support assisted gene flow to ensure the persistence of the species in European forests.

Genomic vulnerability to rapid climate warming in a tree species with a long generation time.

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.

Genomic signatures of convergent adaptation to Alpine environments in three Brassicaceae species.

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.

Disentangling the effects of geographic peripherality and habitat suitability on neutral and adaptive genetic variation in Swiss stone pine.

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.

Author Correction: The GenTree Dendroecological Collection, tree-ring and wood density data from seven tree species across Europe.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Evolutionary genomics can improve prediction of species' responses to climate change.

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.

Memory of environmental conditions across generations affects the acclimation potential of scots pine.

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.

A species-discriminatory single-nucleotide polymorphism set reveals maintenance of species integrity in hybridizing European white oaks (Quercus spp.) despite high levels of admixture.

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.

The GenTree Dendroecological Collection, tree-ring and wood density data from seven tree species across Europe.

The dataset presented here was collected by the GenTree project (EU-Horizon 2020), which aims to improve the use of forest genetic resources across Europe by better understanding how trees adapt to their local environment. This dataset of individual tree-core characteristics including ring-width series and whole-core wood density was collected for seven ecologically and economically important European tree species: silver birch (Betula pendula), European beech (Fagus sylvatica), Norway spruce (Picea abies), European black poplar (Populus nigra), maritime pine (Pinus pinaster), Scots pine (Pinus sylvestris), and sessile oak (Quercus petraea). Tree-ring width measurements were obtained from 3600 trees in 142 populations and whole-core wood density was measured for 3098 trees in 125 populations. This dataset covers most of the geographical and climatic range occupied by the selected species. The potential use of it will be highly valuable for assessing ecological and evolutionary responses to environmental conditions as well as for model development and parameterization, to predict adaptability under climate change scenarios.

A Reference Genome Sequence for the European Silver Fir (Abies alba Mill.): A Community-Generated Genomic Resource.

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.

Using transcriptome sequencing and pooled exome capture to study local adaptation in the giga-genome of Pinus cembra.

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.

Transmembrane transport and stress response genes play an important role in adaptation of Arabidopsis halleri to metalliferous soils.

When plants adapt to local environments, strong signatures of selection are expected in the genome, particularly in high-stress environments such as trace metal element enriched (metalliferous) soils. Using Arabidopsis halleri, a model species for metal homeostasis and adaptation to extreme environments, we identifid genes, gene variants, and pathways that are associated with soil properties and may thus contribute to adaptation to high concentrations of trace metal elements. We analysed whole-genome Pool-seq data from two metallicolous (from metalliferous soils) and two non-metallicolous populations (in total 119 individuals) and associated allele frequencies of the identified single-nucleotide polymorphisms (SNPs) with soil variables measured on site. Additionally, we accounted for polygenic adaptation by searching for gene pathways showing enrichment of signatures of selection. Out of >2.5 million SNPs, we identified 57 SNPs in 19 genes that were significantly associated with soil variables and are members of three enriched pathways. At least three of these candidate genes and pathways are involved in transmembrane transport and/or associated with responses to various stresses such as oxidative stress. We conclude that both allocation and detoxification processes play a crucial role in A. halleri for coping with these unfavourable conditions.

Detecting the genomic signal of polygenic adaptation and the role of epistasis in evolution.

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.