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Biological invasions carry substantial practical and scientific importance, and represent natural evolutionary experiments on contemporary timescales. Here, we investigated genomic diversity and environmental adaptation of the crop pest Drosophila suzukii using whole-genome sequencing data and environmental metadata for 29 population samples from its native and invasive range. Through a multifaceted analysis of this population genomic data, we increase our understanding of the D. suzukii genome, its diversity and its evolution, and we identify an appropriate genotype-environment association pipeline for our data set. Using this approach, we detect genetic signals of local adaptation associated with nine distinct environmental factors related to altitude, wind speed, precipitation, temperature, and human land use. We uncover unique functional signatures for each environmental variable, such as the prevalence of cuticular genes associated with annual precipitation. We also infer biological commonalities in the adaptation to diverse selective pressures, particularly in terms of the apparent contribution of nervous system evolution to enriched processes (ranging from neuron development to circadian behavior) and to top genes associated with all nine environmental variables. Our findings therefore depict a finer-scale adaptive landscape underlying the rapid invasion success of this agronomically important species.

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Crop wild relatives (CWR) provide a valuable resource for improving crops. They possess desirable traits that confer resilience to various environmental stresses. To fully utilize crop wild relatives in breeding and conservation programs, it is important to understand the genetic basis of their adaptation. Landscape genomics associates environments with genomic variation and allows for examining the genetic basis of adaptation. Our study examined the differences in allele frequency of 15,416 single nucleotide polymorphisms (SNPs) generated through genotyping by sequencing approach among 153 accessions of 15 wild eggplant relatives and two cultivated species from Africa, the principal hotspot of these wild relatives. We also explored the correlation between these variations and the bioclimatic and soil conditions at their collection sites, providing a comprehensive understanding of the genetic signals of environmental adaptation in African wild eggplant. Redundancy analysis (RDA) results showed that the environmental variation explained 6% while the geographical distances among the collection sites explained 15% of the genomic variation in the eggplant wild relative populations when controlling for population structure. Our findings indicate that even though environmental factors are not the main driver of selection in eggplant wild relatives, it is influential in shaping the genomic variation over time. The selected environmental variables and candidate SNPs effectively revealed grouping patterns according to the environmental characteristics of sampling sites. Using four genotype-environment association methods, we detected 396 candidate SNPs (2.5% of the initial SNPs) associated with eight environmental factors. Some of these SNPs signal genes involved in pathways that help adapt to environmental stresses such as drought, heat, cold, salinity, pests, and diseases. These candidate SNPs will be useful for marker-assisted improvement and characterizing the germplasm of this crop for developing climate-resilient eggplant varieties. The study provides a model for applying landscape genomics to other crops' wild relatives.

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Species that repeatedly evolve phenotypic clines across environmental gradients have been highlighted as ideal systems for characterizing the genomic basis of local environmental adaptation. However, few studies have assessed the importance of observed phenotypic clines for local adaptation: conspicuous traits that vary clinally may not necessarily be the most critical in determining local fitness. The present study was designed to fill this gap, using a plant species characterized by repeatedly evolved adaptive phenotypic clines. White clover is naturally polymorphic for its chemical defence cyanogenesis (HCN release with tissue damage); climate-associated cyanogenesis clines have evolved throughout its native and introduced range worldwide. We performed landscape genomic analyses on 415 wild genotypes from 43 locations spanning much of the North American species range to assess the relative importance of cyanogenesis loci vs. other genomic factors in local climatic adaptation. We find clear evidence of local adaptation, with temperature-related climatic variables best describing genome-wide differentiation between sampling locations. The same climatic variables are also strongly correlated with cyanogenesis frequencies and gene copy number variations (CNVs) at cyanogenesis loci. However, landscape genomic analyses indicate no significant contribution of cyanogenesis loci to local adaptation. Instead, several genomic regions containing promising candidate genes for plant response to seasonal cues are identified - some of which are shared with previously identified QTLs for locally adaptive fitness traits in North American white clover. Our findings suggest that local adaptation in white clover is likely determined primarily by genes controlling the timing of growth and flowering in response to local seasonal cues. More generally, this work suggests that caution is warranted when considering the importance of conspicuous phenotypic clines as primary determinants of local adaptation.

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Biodiversity conservation requires conserving evolutionary potential-the capacity for wild populations to adapt. Understanding genetic diversity and evolutionary dynamics is critical for informing conservation decisions that enhance adaptability and persistence under environmental change. We review how emerging landscape genomic methods provide plant conservation programs with insights into evolutionary dynamics, including local adaptation and its environmental drivers. Landscape genomic approaches that explore relationships between genomic variation and environments complement rather than replace established population genomic and common garden approaches for assessing adaptive phenotypic variation, population structure, gene flow, and demography. Collectively, these approaches inform conservation actions, including genetic rescue, maladaptation prediction, and assisted gene flow. The greatest on-the-ground impacts from such studies will be realized when conservation practitioners are actively engaged in research and monitoring. Understanding the evolutionary dynamics shaping the genetic diversity of wild plant populations will inform plant conservation decisions that enhance the adaptability and persistence of species in an uncertain future.

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Patterns of pathogen prevalence are, at least partially, the result of coevolutionary host-pathogen interactions. Thus, exploring the distribution of host genetic variation in relation to infection by a pathogen within and across populations can provide important insights into mechanisms of host defence and adaptation. Here, we use a landscape genomics approach (Bayenv) in conjunction with genome-wide data (ddRADseq) to test for associations between avian malaria (Plasmodium) prevalence and host genetic variation across 13 populations of the island endemic Berthelot's pipit (Anthus berthelotii). Considerable and consistent spatial heterogeneity in malaria prevalence was observed among populations over a period of 15 years. The prevalence of malaria infection was also strongly positively correlated with pox (Avipoxvirus) prevalence. Multiple host loci showed significant associations with malaria prevalence after controlling for genome-wide neutral genetic structure. These sites were located near to or within genes linked to metabolism, stress response, transcriptional regulation, complement activity and the inflammatory response, many previously implicated in vertebrate responses to malarial infection. Our findings identify diverse genes - not just limited to the immune system - that may be involved in host protection against malaria and suggest that spatially variable pathogen pressure may be an important evolutionary driver of genetic divergence among wild animal populations, such as Berthelot's pipit. Furthermore, our data indicate that spatio-temporal variation in multiple different pathogens (e.g. malaria and pox in this case) may have to be studied together to develop a more holistic understanding of host pathogen-mediated evolution.

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BACKGROUND: Local adaptation is a key evolutionary process that enhances the growth of plants in their native habitat compared to non-native habitats, resulting in patterns of adaptive genetic variation across the entire geographic range of the species. The study of population adaptation to local environments and predicting their response to future climate change is important because of climate change. RESULTS: Here, we explored the genetic diversity of candidate genes associated with bud burst in pedunculate oak individuals sampled from 6 populations in Poland. Single nucleotide polymorphism (SNP) diversity was assessed in 720 candidate genes using the sequence capture technique, yielding 18,799 SNPs. Using landscape genomic approaches, we identified 8 FST outliers and 781 unique SNPs in 389 genes associated with geography, climate, and phenotypic variables (individual/family spring and autumn phenology, family diameter at breast height (DBH), height, and survival) that are potentially involved in local adaptation. Then, using a nonlinear multivariate model, Gradient Forests, we identified vulnerable areas of the pedunculate oak distribution in Poland that are at risk from climate change. CONCLUSIONS: The model revealed that pedunculate oak populations in the eastern part of the analyzed geographical region are the most sensitive to climate change. Our results might offer an initial evaluation of a potential management strategy for preserving the genetic diversity of pedunculate oak.

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Adaptive divergence in response to environmental clines are expected to be common in species occupying heterogeneous environments. Despite numerous advances in techniques appropriate for non-model species, gene-environment association studies in elasmobranchs are still scarce. The bronze whaler or copper shark (Carcharhinus brachyurus) is a large coastal shark with a wide distribution and one of the most exploited elasmobranchs in southern Africa. Here, we assessed the distribution of neutral and adaptive genomic diversity in C. brachyurus across a highly heterogeneous environment in southern Africa based on genome-wide SNPs obtained through a restriction site-associated DNA method (3RAD). A combination of differentiation-based genome-scan (outflank) and genotype-environment analyses (redundancy analysis, latent factor mixed models) identified a total of 234 differentiation-based outlier and candidate SNPs associated with bioclimatic variables. Analysis of 26,299 putatively neutral SNPs revealed moderate and evenly distributed levels of genomic diversity across sites from the east coast of South Africa to Angola. Multivariate and clustering analyses demonstrated a high degree of gene flow with no significant population structuring among or within ocean basins. In contrast, the putatively adaptive SNPs demonstrated the presence of two clusters and deep divergence between Angola and all other individuals from Namibia and South Africa. These results provide evidence for adaptive divergence in response to a heterogeneous seascape in a large, mobile shark despite high levels of gene flow. These results are expected to inform management strategies and policy at the national and regional level for conservation of C. brachyurus populations.

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Aquaculture of the lumpfish (Cyclopterus lumpus L.) has become a large, lucrative industry owing to the escalating demand for "cleaner fish" to minimise sea lice infestations in Atlantic salmon mariculture farms. We used over 10K genome-wide single nucleotide polymorphisms (SNPs) to investigate the spatial patterns of genomic variation in the lumpfish along the coast of Norway and across the North Atlantic. Moreover, we applied three genome scans for outliers and two genotype-environment association tests to assess the signatures and patterns of local adaptation under extensive gene flow. With our 'global' sampling regime, we found two major genetic groups of lumpfish, i.e., the western and eastern Atlantic. Regionally in Norway, we found marginal evidence of population structure, where the population genomic analysis revealed a small portion of individuals with a different genetic ancestry. Nevertheless, we found strong support for local adaption under high gene flow in the Norwegian lumpfish and identified over 380 high-confidence environment-associated loci linked to gene sets with a key role in biological processes associated with environmental pressures and embryonic development. Our results bridge population genetic/genomics studies with seascape genomics studies and will facilitate genome-enabled monitoring of the genetic impacts of escapees and allow for genetic-informed broodstock selection and management in Norway.

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Geoscientists and ecologists alike must confront the impact of climate change on ecosystems and the services they provide. In the marine realm, major changes are projected in net primary and export production, with significant repercussions on food security, carbon storage, and climate system feedbacks. However, these projections do not include the potential for rapid linear evolution to facilitate adaptation to environmental change. Climate genomics confronts this challenge by assessing the vulnerability of ecosystem services to climate change. Because DNA is the primary biological repository of detectable environmentally selected mutations (showing evidence of change before impacts arise in morphological or metabolic patterns), genomics provides a window into selection in response to climate change, while also recording neutral processes deriving from stochastic mechanisms (Lowe et al., Trends in Ecology & Evolution, 2017; 32:141-152). Due to the revolution afforded by sequencing technology developments, genomics can now meet ecologists and climate scientists in a cross-disciplinary space fertile for collaborations. Collaboration between geoscientists, ecologists, and geneticists must be reinforced in order to combine modeling and genomics approaches at every scale to improve our understanding and the management of ecosystems under climate change. To this end, we present advances in climate genomics from plankton to larger vertebrates, stressing the interactions between modeling and genomics, and identifying future work needed to develop and expand the field of climate genomics.

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Biological invasions carry substantial practical and scientific importance, and represent natural evolutionary experiments on contemporary timescales. Here, we investigated genomic diversity and environmental adaptation of the crop pest Drosophila suzukii using whole-genome sequencing data and environmental metadata for 29 population samples from its native and invasive range. Through a multifaceted analysis of this population genomic data, we increase our understanding of the D. suzukii genome, its diversity and its evolution, and we identify an appropriate genotype-environment association pipeline for our data set. Using this approach, we detect genetic signals of local adaptation associated with nine distinct environmental factors related to altitude, wind speed, precipitation, temperature, and human land use. We uncover unique functional signatures for each environmental variable, such as a prevalence of cuticular genes associated with annual precipitation. We also infer biological commonalities in the adaptation to diverse selective pressures, particularly in terms of the apparent contribution of nervous system evolution to enriched processes (ranging from neuron development to circadian behavior) and to top genes associated with all nine environmental variables. Our findings therefore depict a finer-scale adaptive landscape underlying the rapid invasion success of this agronomically important species.

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BACKGROUND AND AIMS: Understanding adaptive genetic variation and whether it can keep pace with predicted future climate change is critical in assessing the genetic vulnerability of species and developing conservation management strategies. The lack of information on adaptive genetic variation in relict species carrying abundant genetic resources hinders the assessment of genetic vulnerability. Using a landscape genomics approach, this study aimed to determine how adaptive genetic variation shapes population divergence and to predict the adaptive potential of Pterocarya macroptera (a vulnerable relict species in China) under future climate scenarios. METHODS: We applied restriction site-associated DNA sequencing (RAD-seq) to obtain 8244 single-nucleotide polymorphisms (SNPs) from 160 individuals across 28 populations. We examined the pattern of genetic diversity and divergence, and then identified outliers by genetic differentiation (FST) and genotype-environment association (GEA) methods. We further dissected the effect of geographical/environmental gradients on genetic variation. Finally, we predicted genetic vulnerability and adaptive risk under future climate scenarios. KEY RESULTS: We identified three genetic lineages within P. macroptera: the Qinling-Daba-Tianmu Mountains (QDT), Western Sichuan (WS) and Northwest Yunnan (NWY) lineages, which showed significant signals of isolation by distance (IBD) and isolation by environment (IBE). IBD and IBE explained 3.7-5.7 and 8.6-12.8 % of the genetic structure, respectively. The identified GEA SNP-related genes were involved in chemical defence and gene regulation and may exhibit higher genetic variation to adapt to the environment. Gradient forest analysis revealed that the genetic variation was mainly shaped by temperature-related variables, indicating its adaptation to local thermal environments. A limited adaptive potential was suggested by the high levels of genetic vulnerability in marginal populations. CONCLUSIONS: Environmental gradient mainly shaped the population differentiation of P. macroptera. Marginal populations may be at high risk of extinction, and thus proactive management measures, such as assisted gene flow, are required to ensure the survival of these populations.

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Wide-ranging species are seldom considered conservation priorities, yet they have the potential to harbour genetically deeply differentiated units across environments or ecological barriers, including some that warrant taxonomic recognition. Documenting such cryptic genetic diversity is especially important for wide-ranging species that are in decline, as they may comprise a set of even more endangered lineages or species with small distributions. However, studies of wide-ranging species, particularly when they cross political borders, are extremely challenging. One approach to overcoming these challenges is to conduct detailed local analyses in combination with less detailed, range-wide studies. We used this approach with the red-footed tortoise (Chelonoidis carbonarius), a threatened species likely to contain cryptic diversity given its vast range and the distinctive ecoregions that it inhabits. Previous single-gene molecular studies indicated the presence of at least five lineages, two of which occur in different ecoregions separated by the Andes within Colombia. We used a comprehensive genomic analysis to test the hypothesis of cryptic diversity within the single jurisdiction of Colombia. We used a combination of restriction-site-associated DNA sequencing and environmental niche modelling to provide three independent lines of evidence that support the presence of important cryptic diversity that may deserve taxonomic recognition: allopatric reproductive isolation, local adaptation and ecological divergence. We also provide a fine-scale genetic map with the distribution of conservation units in Colombia. As we complete ongoing range-wide analyses and make taxonomic adjustments, we recommend that the two lineages in Colombia be treated as separate units for conservation purposes.

Las especies con distribuciones amplias rara vez son consideradas prioridades de conservación, sin embargo, tienen el potencial de albergar unidades genéticamente diferenciadas que en algunos casos justifican reconocimiento taxonómico. Documentar dicha diversidad genética críptica es especialmente importante para las especies de rangos amplios que ya están en peligro de extinción, pues pueden comprender un conjunto de linajes o especies aún más amenazadas y con distribuciones más pequeñas. Sin embargo, los estudios de especies de rangos amplios, particularmente cuando cruzan fronteras políticas, son extremadamente desafiantes. Un enfoque para superar estos desafíos es realizar análisis locales detallados en combinación con estudios en todo el rango de distribución menos detallados. Nosotros usamos este enfoque con la tortuga de patas rojas (Chelonoidis carbonarius), una especie amenazada que probablemente contiene diversidad genética críptica dada su amplia distribución y las distintas ecorregiones en las que habita. Estudios moleculares previos de un solo gen indicaron la presencia de al menos cinco linajes, dos de los cuales ocurren en diferentes ecorregiones separadas por los Andes en Colombia. En este estudio utilizamos una combinación de secuenciación de ADN asociada a sitios de restricción (RADseq) y modelamiento de nicho ecológico para proporcionar tres líneas independientes de evidencia que respaldan la presencia de diversidad críptica importante que puede merecer reconocimiento taxonómico: aislamiento reproductivo alopátrico, adaptación local y divergencia ecológica. También proporcionamos un mapa genético a escala fina con la distribución de unidades de conservación en Colombia. Mientras completamos análisis genómicos en todo el rango de distribución y hacemos ajustes taxonómicos, recomendamos que los dos linajes en Colombia se traten como unidades independientes para fines de conservación.

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As the global climate crisis continues, predictions concerning how wild populations will respond to changing climate conditions are informed by an understanding of how populations have responded and/or adapted to climate variables in the past. Changes in the local biotic and abiotic environment can drive differences in phenology, physiology, morphology and demography between populations leading to local adaptation, yet the molecular basis of adaptive evolution in wild non-model organisms is poorly understood. We leverage comparisons between two lineages of Calochortus venustus occurring along parallel transects that allow us to identify loci under selection and measure clinal variation in allele frequencies as evidence of population-specific responses to selection along climatic gradients. We identify targets of selection by distinguishing loci that are outliers to population structure and by using genotype-environment associations across transects to detect loci under selection from each of nine climatic variables. Despite gene flow between individuals of different floral phenotypes and between populations, we find evidence of ecological specialization at the molecular level, including genes associated with key plant functions linked to plant adaptation to California's Mediterranean climate. Single-nucleotide polymorphisms (SNPs) present in both transects show similar trends in allelic similarity across latitudes indicating parallel adaptation to northern climates. Comparisons between eastern and western populations across latitudes indicate divergent genetic evolution between transects, suggesting local adaptation to either coastal or inland habitats. Our study is among the first to show repeated allelic variation across climatic clines in a non-model organism.

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Ectomycorrhizal (ECM) fungi serve key functions in forest ecosystems by supplying water and nutrients to tree hosts, yet mutualistic plant-fungi interactions are jeopardised by environmental alterations. Here, we discuss the great potential and current limitations of landscape genomics in investigating signatures of local adaptation in natural populations of ECM fungi.

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Climate change is altering species ranges, and relative abundances within ranges, as populations become differentially adapted and vulnerable to the climates they face. Understanding present species ranges, whether species harbour and exchange adaptive variants, and how variants are distributed across landscapes undergoing rapid change, is therefore crucial to predicting responses to future climates and informing conservation strategies. Such insights are nonetheless lacking for most species of conservation concern. We assess genomic patterns of neutral variation, climate adaptation and climate vulnerability (offsets in predicted distributions of putatively adaptive variants across present and future landscapes) for sister foundation species, the marine tubeworms Galeolaria caespitosa and Galeolaria gemineoa, in a sentinel region for climate change impacts. We find that species are genetically isolated despite uncovering sympatry in their ranges, show parallel and nonparallel signals of thermal adaptation on spatial scales smaller than gene flow across their ranges, and are predicted to face different risks of maladaptation under future temperatures across their ranges. Our findings have implications for understanding local adaptation in the face of gene flow, and generate spatially explicit predictions for climatic disruption of adaptation and species distributions in coastal ecosystems that could guide experimental validation and conservation planning.

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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.

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Aquatic ectotherms are predicted to harbour genomic signals of local adaptation resulting from selective pressures driven by the strong influence of climate conditions on body temperature. We investigated local adaptation in redband trout (Oncorhynchus mykiss gairdneri) using genome scans for 547 samples from 11 populations across a wide range of habitats and thermal gradients in the interior Columbia River. We estimated allele frequencies for millions of single nucleotide polymorphism loci (SNPs) across populations using low-coverage whole genome resequencing, and used population structure outlier analyses to identify genomic regions under divergent selection between populations. Twelve genomic regions showed signatures of local adaptation, including two regions associated with genes known to influence migration and developmental timing in salmonids (GREB1L, ROCK1, SIX6). Genotype-environment association analyses indicated that diurnal temperature variation was a strong driver of local adaptation, with signatures of selection driven primarily by divergence of two populations in the northern extreme of the subspecies range. We also found evidence for adaptive differences between high-elevation desert vs. montane habitats at a smaller geographical scale. Finally, we estimated vulnerability of redband trout to future climate change using ecological niche modelling and genetic offset analyses under two climate change scenarios. These analyses predicted substantial habitat loss and strong genetic shifts necessary for adaptation to future habitats, with the greatest vulnerability predicted for high-elevation desert populations. Our results provide new insight into the complexity of local adaptation in salmonids, and important predictions regarding future responses of redband trout to climate change.

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Conservation units (CUs) are important tools for supporting the implementation of standardized management practices for exploited species. Following the adoption of the Wild Salmon Policy in Canada, CUs were defined for Pacific salmon based on characteristics related to ecotype, life history and genetic variation using microsatellite markers as indirect measures of local adaptation. Genomic data sets have the potential to improve the definition of CUs by reducing variance around estimates of population genetic parameters, thereby increasing the power to detect more subtle patterns of population genetic structure and by providing an opportunity to incorporate adaptive information more directly with the identification of variants putatively under selection. We used one of the largest genomic data sets recently published for a nonmodel species, comprising 5662 individual Coho salmon (Oncorhynchus kisutch) from 149 sampling locations and a total of 24,542 high-quality SNPs obtained using genotyping-by-sequencing and mapped to the Coho salmon reference genome to (1) evaluate the current delineation of CUs for Coho in Canada and (2) compare patterns of population structure observed using neutral and outlier loci from genotype-environment association analyses to determine whether separate CUs that capture adaptive diversity are needed. Our results reflected CU boundaries on the whole, with the majority of sampling locations managed in the same CU clustering together within genetic groups. However, additional groups that are not currently represented by CUs were also uncovered. We observed considerable overlap in the genetic clusters identified using neutral or candidate loci, indicating a general congruence in patterns of genetic variation driven by local adaptation and gene flow in this species. Consequently, we suggest that the current CU boundaries for Coho salmon are largely well-suited for meeting the Canadian Wild Salmon Policy's objective of defining biologically distinct groups, but we highlight specific areas where CU boundaries may be refined.