Projection of current and future distribution of adaptive genetic units in an alpine ungulate.

Climate projections predict major changes in alpine environments by the end of the 21st century. To avoid climate-induced maladaptation and extinction, many animal populations will either need to move to more suitable habitats or adapt in situ to novel conditions. Since populations of a species exhibit genetic variation related to local adaptation, it is important to incorporate this variation into predictive models to help assess the ability of the species to survive climate change. Here, we evaluate how the adaptive genetic variation of a mountain ungulate-the Northern chamois (Rupicapra rupicapra)-could be impacted by future global warming. Based on genotype-environment association analyses of 429 chamois using a ddRAD sequencing approach, we identified genetic variation associated with climatic gradients across the European Alps. We then delineated adaptive genetic units and projected the optimal distribution of these adaptive groups in the future. Our results suggest the presence of local adaptation to climate in Northern chamois with similar genetic adaptive responses in geographically distant but climatically similar populations. Furthermore, our results predict that future climatic changes will modify the Northern chamois adaptive landscape considerably, with various degrees of maladaptation risk.

From common gardens to candidate genes: exploring local adaptation to climate in red spruce.

Local adaptation to climate is common in plant species and has been studied in a range of contexts, from improving crop yields to predicting population maladaptation to future conditions. The genomic era has brought new tools to study this process, which was historically explored through common garden experiments. In this study, we combine genomic methods and common gardens to investigate local adaptation in red spruce and identify environmental gradients and loci involved in climate adaptation. We first use climate transfer functions to estimate the impact of climate change on seedling performance in three common gardens. We then explore the use of multivariate gene-environment association methods to identify genes underlying climate adaptation, with particular attention to the implications of conducting genome scans with and without correction for neutral population structure. This integrative approach uncovered phenotypic evidence of local adaptation to climate and identified a set of putatively adaptive genes, some of which are involved in three main adaptive pathways found in other temperate and boreal coniferous species: drought tolerance, cold hardiness, and phenology. These putatively adaptive genes segregated into two 'modules' associated with different environmental gradients. This study nicely exemplifies the multivariate dimension of adaptation to climate in trees.

Double-digest RAD-sequencing: do pre- and post-sequencing protocol parameters impact biological results?

Next-generation sequencing technologies have opened a new era of research in population genetics. Following these new sequencing opportunities, the use of restriction enzyme-based genotyping techniques, such as restriction site-associated DNA sequencing (RAD-seq) or double-digest RAD-sequencing (ddRAD-seq), has dramatically increased in the last decade. From DNA sampling to SNP calling, the laboratory and bioinformatic parameters of enzyme-based techniques have been investigated in the literature. However, the impact of those parameters on downstream analyses and biological results remains less documented. In this study, we investigated the effects of sevral pre- and post-sequencing settings on ddRAD-seq results for two biological systems: a complex of butterfly species (Coenonympha sp.) and several populations of common beech (Fagus sylvatica). Our results suggest that pre-sequencing parameters (i.e., DNA quantity, number of PCR cycles during library preparation) have a significant impact on the number of recovered reads and SNPs, on the number of unique alleles and on individual heterozygosity. In the same way, we found that post-sequencing settings (i.e., clustering and minimum coverage thresholds) influenced loci reconstruction (e.g., number of loci, mean coverage) and SNP calling (e.g., number of SNPs; heterozygosity) but had only a marginal impact on downstream analyses (e.g., measure of genetic differentiation, estimation of individual admixture, and demographic inferences). In addition, replication analyses confirmed the reproducibility of the ddRAD-seq procedure. Overall, this study assesses the degree of sensitivity of ddRAD-seq data to pre- and post-sequencing protocols, and illustrates its robustness when studying population genetics.

Climate-associated genetic variation in Fagus sylvatica and potential responses to climate change in the French Alps.

Local adaptation patterns have been found in many plants and animals, highlighting the genetic heterogeneity of species along their range of distribution. In the next decades, global warming is predicted to induce a change in the selective pressures that drive this adaptive variation, forcing a reshuffling of the underlying adaptive allele distributions. For species with low dispersion capacity and long generation time such as trees, the rapidity of the change could impede the migration of beneficial alleles and lower their capacity to track the changing environment. Identifying the main selective pressures driving the adaptive genetic variation is thus necessary when investigating species capacity to respond to global warming. In this study, we investigate the adaptive landscape of Fagus sylvatica along a gradient of populations in the French Alps. Using a double-digest restriction-site-associated DNA (ddRAD) sequencing approach, we identified 7,000 SNPs from 570 individuals across 36 different sites. A redundancy analysis (RDA)-derived method allowed us to identify several SNPs that were strongly associated with climatic gradients; moreover, we defined the primary selective gradients along the natural populations of F. sylvatica in the Alps. Strong effects of elevation and humidity, which contrast north-western and south-eastern site, were found and were believed to be important drivers of genetic adaptation. Finally, simulations of future genetic landscapes that used these findings allowed identifying populations at risk for F. sylvatica in the Alps, which could be helpful for future management plans.

Unravelling the invasion history of the Asian tiger mosquito in Europe.

Multiple introductions are key features for the establishment and persistence of introduced species. However, little is known about the contribution of genetic admixture to the invasive potential of populations. To address this issue, we studied the recent invasion of the Asian tiger mosquito (Aedes albopictus) in Europe. Combining genome-wide single nucleotide polymorphisms and historical knowledge using an approximate Bayesian computation framework, we reconstruct the colonization routes and establish the demographic dynamics of invasion. The colonization of Europe involved at least three independent introductions in Albania, North Italy and Central Italy that subsequently acted as dispersal centres throughout Europe. We show that the topology of human transportation networks shaped demographic histories with North Italy and Central Italy being the main dispersal centres in Europe. Introduction modalities conditioned the levels of genetic diversity in invading populations, and genetically diverse and admixed populations promoted more secondary introductions and have spread farther than single-source invasions. This genomic study provides further crucial insights into a general understanding of the role of genetic diversity promoted by modern trade in driving biological invasions.

Hybridization promotes speciation in Coenonympha butterflies.

Hybridization has become a central element in theories of animal evolution during the last decade. New methods in population genomics and statistical model testing now allow the disentangling of the complexity that hybridization brings into key evolutionary processes such as local adaptation, colonization of new environments, species diversification and extinction. We evaluated the consequences of hybridization in a complex of three alpine butterflies in the genus Coenonympha, by combining morphological, genetic and ecological analyses. A series of approximate Bayesian computation procedures based on a large SNP data set strongly suggest that the Darwin's Heath (Coenonympha darwiniana) originated through hybridization between the Pearly Heath (Coenonympha arcania) and the Alpine Heath (Coenonympha gardetta) with different parental contributions. As a result of hybridization, the Darwin's Heath presents an intermediate morphology between the parental species, while its climatic niche seems more similar to the Alpine Heath. Our results also reveal a substantial genetic and morphologic differentiation between the two geographically disjoint Darwin's Heath lineages leading us to propose the splitting of this taxon into two different species.

Bringing genomics to the field: An integrative approach to seed sourcing for forest restoration.

Premise: Global anthropogenic change threatens the health and productivity of forest ecosystems. Assisted migration and reforestation are tools to help mitigate these impacts. However, questions remain about how to approach sourcing seeds to ensure high establishment and future adaptability. Methods: Using exome-capture sequencing, we demonstrate a computational approach to finding the best n-sets from a candidate list of seed sources that collectively achieve high genetic diversity (GD) and minimal genetic load (GL), while also increasing evolvability in quantitative traits. The benefits of this three-part strategy (diversity-load-evolvability) are to increase near-term establishment success while also boosting evolutionary potential to respond to future stressors. Members of The Nature Conservancy and the Central Appalachian Spruce Restoration Initiative planted 58,000 seedlings across 255 acres. A subset of seedlings was monitored for establishment success and variation in growth. Results: The results show gains in GD relative to GL and increases in quantitative genetic variation in seedling growth for pooled vs. single-source restoration. No single "super source" was observed across planting sites; rather, monitoring results demonstrate that pooling of multiple sources helps achieve higher GD:GL and evolvability. Discussion: Our study shows the potential for integrating genomics into local-scale restoration and the importance of building partnerships between academic researchers and applied conservation managers.

Chromosome-Level Assembly and Annotation of the Pearly Heath Coenonympha arcania Butterfly Genome.

We present the first chromosome-level genome assembly and annotation of the pearly heath Coenonympha arcania, generated with a PacBio HiFi sequencing approach and complemented with Hi-C data. We additionally compare synteny, gene, and repeat content between C. arcania and other Lepidopteran genomes. This reference genome will enable future population genomics studies with Coenonympha butterflies, a species-rich genus that encompasses some of the most highly endangered butterfly taxa in Europe.

Discovery of cryptic plant diversity on the rooftops of the Alps.

High elevation temperate mountains have long been considered species poor owing to high extinction or low speciation rates during the Pleistocene. We performed a phylogenetic and population genomic investigation of an emblematic high-elevation plant clade (Androsace sect. Aretia, 31 currently recognized species), based on plant surveys conducted during alpinism expeditions. We inferred that this clade originated in the Miocene and continued diversifying through Pleistocene glaciations, and discovered three novel species of Androsace dwelling on different bedrock types on the rooftops of the Alps. This highlights that temperate high mountains have been cradles of plant diversity even during the Pleistocene, with in-situ speciation driven by the combined action of geography and geology. Our findings have an unexpected historical relevance: H.-B. de Saussure likely observed one of these species during his 1788 expedition to the Mont Blanc and we describe it here, over two hundred years after its first sighting.

Genetic, morphological and ecological variation across a sharp hybrid zone between two alpine butterfly species.

Identifying the mechanisms involved in the formation and maintenance of species is a central question in evolutionary biology, and distinguishing the selective drivers of populations' divergence from demographic processes is of particular interest to better understand the speciation process. Hybrid zones are recognized to provide ideal places to investigate the genetic architecture of speciation and to identify the mechanisms allowing diverging species to maintain their integrity in the face of gene flow. Here, we studied two alpine butterfly species, Coenonympha macromma and C. gardetta, which can be found flying together and hybridizing in narrow contact zones in the southern French Alps. We characterized the genomic composition of individuals, their morphology and their local habitat requirements, within and around a hybrid zone. Genetic diversity analysis at 794 SNPs revealed that all individuals within the hybrid zone were highly admixed, which was not the case outside the hybrid zone. Cline analysis showed that, despite ongoing hybridization, 56 out of 122 loci differentially fixed or nearly so between the two species were impermeable to introgression across the sharp hybrid zone (9 km wide). We also found concordance in cline position and width among genetic, morphological and environmental variation, suggesting a coupling of different reproductive barriers. Habitat characteristics such as the presence of trees and shrubs and the start of the growing season were strongly associated with the genetic variation, and we found evidence of divergence at genetic markers associated with morphology and physiology, putatively involved in visual or environmental reproductive isolation. We discuss the various behavioural and ecological factors that might interplay to maintain current levels of divergence and gene flow between this species pair.

Whole-exome sequencing reveals a long-term decline in effective population size of red spruce (Picea rubens).

Understanding the factors influencing the current distribution of genetic diversity across a species range is one of the main questions of evolutionary biology, especially given the increasing threat to biodiversity posed by climate change. Historical demographic processes such as population expansion or bottlenecks and decline are known to exert a predominant influence on past and current levels of genetic diversity, and revealing this demo-genetic history can have immediate conservation implications. We used a whole-exome capture sequencing approach to analyze polymorphism across the gene space of red spruce (Picea rubens Sarg.), an endemic and emblematic tree species of eastern North America high-elevation forests that are facing the combined threat of global warming and increasing human activities. We sampled a total of 340 individuals, including populations from the current core of the range in northeastern USA and southeastern Canada and from the southern portions of its range along the Appalachian Mountains, where populations occur as highly fragmented mountaintop "sky islands." Exome capture baits were designed from the closely relative white spruce (P. glauca Voss) transcriptome, and sequencing successfully captured most regions on or near our target genes, resulting in the generation of a new and expansive genomic resource for studying standing genetic variation in red spruce applicable to its conservation. Our results, based on over 2 million exome-derived variants, indicate that red spruce is structured into three distinct ancestry groups that occupy different geographic regions of its highly fragmented range. Moreover, these groups show small Ne , with a temporal history of sustained population decline that has been ongoing for thousands (or even hundreds of thousands) of years. These results demonstrate the broad potential of genomic studies for revealing details of the demographic history that can inform management and conservation efforts of nonmodel species with active restoration programs, such as red spruce.

Speciation with gene flow: Evidence from a complex of alpine butterflies (Coenonympha, Satyridae).

Until complete reproductive isolation is achieved, the extent of differentiation between two diverging lineages is the result of a dynamic equilibrium between genetic isolation and mixing. This is especially true for hybrid taxa, for which the degree of isolation in regard to their parental species is decisive in their capacity to rise as a new and stable entity. In this work, we explored the past and current patterns of hybridization and divergence within a complex of closely related butterflies in the genus Coenonympha in which two alpine species, C. darwiniana and C. macromma, have been shown to result from hybridization between the also alpine C. gardetta and the lowland C. arcania. By testing alternative scenarios of divergence among species, we show that gene flow has been uninterrupted throughout the speciation process, although leading to different degrees of current genetic isolation between species in contact zones depending on the pair considered. Nonetheless, at broader geographic scale, analyses reveal a clear genetic differentiation between hybrid lineages and their parental species, pointing out to an advanced stage of the hybrid speciation process. Finally, the positive correlation observed between ecological divergence and genetic isolation among these butterflies suggests a potential role for ecological drivers during their speciation processes.

Evaluation of redundancy analysis to identify signatures of local adaptation.

Ordination is a common tool in ecology that aims at representing complex biological information in a reduced space. In landscape genetics, ordination methods such as principal component analysis (PCA) have been used to detect adaptive variation based on genomic data. Taking advantage of environmental data in addition to genotype data, redundancy analysis (RDA) is another ordination approach that is useful to detect adaptive variation. This study aims at proposing a test statistic based on RDA to search for loci under selection. We compare redundancy analysis to pcadapt, which is a nonconstrained ordination method, and to a latent factor mixed model (LFMM), which is a univariate genotype-environment association method. Individual-based simulations identify evolutionary scenarios where RDA genome scans have a greater statistical power than genome scans based on PCA. By constraining the analysis with environmental variables, RDA performs better than PCA in identifying adaptive variation when selection gradients are weakly correlated with population structure. In addition, we show that if RDA and LFMM have a similar power to identify genetic markers associated with environmental variables, the RDA-based procedure has the advantage to identify the main selective gradients as a combination of environmental variables. To give a concrete illustration of RDA in population genomics, we apply this method to the detection of outliers and selective gradients on an SNP data set of Populus trichocarpa (Geraldes et al., ). The RDA-based approach identifies the main selective gradient contrasting southern and coastal populations to northern and continental populations in the north-western American coast.