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

Integrating evolutionary genomics of forest trees to inform future tree breeding amid rapid climate change

Global climate change is leading to rapid and drastic shifts in environmental conditions, posing threats to biodiversity and nearly all life forms worldwide. Forest trees serve as foundational components of terrestrial ecosystems and play a crucial and leading role in combating and mitigating the adverse effects of extreme climate events, despite their own vulnerability to these threats. Therefore, understanding and monitoring how natural forests respond to rapid climate change is a key priority for biodiversity conservation. Recent progress in evolutionary genomics, driven primarily by cutting-edge multi-omics technologies, offers powerful new tools to address several key issues. These include precise delineation of species and evolutionary units, inference of past evolutionary histories and demographic fluctuations, identification of environmentally adaptive variants, and measurement of genetic load levels. As the urgency to deal with more extreme environmental stresses grows, understanding the genomics of evolutionary history, local adaptation, future responses to climate change, and conservation and restoration of natural forest trees will be critical for research at the nexus of global change, population genomics, and conservation biology. In this review, we explore the application of evolutionary genomics to assess the effects of global climate change using multi-omics approaches and discuss the outlook for breeding of climate-adapted trees.

Forest genomics in the Caucasus through the lens of its dominant tree species - Fagus orientalis

The last glacial period is known to have greatly influenced the demographic history of temperate forest trees, with important range contractions and post-glacial expansions that led to the formation of multiple genetic lineages and secondary contact zones in the Northern Hemisphere. These dynamics have been extensively studied for European and North American species but are still poorly understood in other temperate regions of rich biodiversity such as the Caucasus. Our study helps filling that gap by deciphering the genomic landscapes of F. orientalis across the South Caucasus. The use of genome-wide data confirmed a past demographic history strongly influenced by the Last Glacial Maximum, revealing two disjunct glacial refugia in the Colchis and Hyrcanian regions. The resulting patterns of genetic diversity, load and differentiation are not always concordant across the region, with genetic load pinpointing the location of the glacial refugia more efficiently than genetic diversity alone. The Hyrcanian forests show depleted genetic diversity and substantial isolation, even if long-distance gene flow is still present with the main centre of diversity in the Greater Caucasus. Finally, we characterize a strong heterogeneity of genetic diversity and differentiation along the species chromosomes, with noticeably a first chromosome showing low diversity and weak differentiation.

Diving into broad-scale and high-resolution population genomics to decipher drivers of structure and climatic vulnerability in a marine invertebrate

Species with widespread distributions play a crucial role in our understanding of climate change impacts on population structure. In marine species, population structure is often governed by both high connectivity potential and selection across strong environmental gradients. Despite the complexity of factors influencing marine populations, studying species with broad distribution can provide valuable insights into the relative importance of these factors and the consequences of climate-induced alterations across environmental gradients. We used the northern shrimp Pandalus borealis and its wide latitudinal distribution to identify current drivers of population structure and predict the species' vulnerability to climate change. A total of 1514 individuals sampled across 24° latitude were genotyped at high geographic (54 stations) and genetic (14,331 SNPs) resolutions to assess genetic variation and environmental correlations. Four populations were identified in addition to finer substructure associated with local adaptation. Geographic patterns of neutral population structure reflected predominant oceanographic currents, while a significant proportion of the genetic variation was associated with gradients in salinity and temperature. Adaptive landscapes generated using climate projections suggest a larger genomic offset in the southern extent of the P. borealis range, where shrimp had the largest adaptive standing genetic variation. Our genomic results combined with recent observations point to further deterioration in southern regions and an impending vulnerable status in the regions at higher latitudes for P. borealis. They also provide rare insights into the drivers of population structure and climatic vulnerability of a widespread meroplanktonic species, which is crucial to understanding future challenges associated with invertebrates essential to ecosystem functioning.

Predicting species invasiveness with genomic data: Is genomic offset related to establishment probability?

Predicting the risk of establishment and spread of populations outside their native range represents a major challenge in evolutionary biology. Various methods have recently been developed to estimate population (mal)adaptation to a new environment with genomic data via so-called Genomic Offset (GO) statistics. These approaches are particularly promising for studying invasive species but have still rarely been used in this context. Here, we evaluated the relationship between GO and the establishment probability of a population in a new environment using both in silico and empirical data. First, we designed invasion simulations to evaluate the ability to predict establishment probability of two GO computation methods (Geometric GO and Gradient Forest) under several conditions. Additionally, we aimed to evaluate the interpretability of absolute Geometric GO values, which theoretically represent the adaptive genetic distance between populations from distinct environments. Second, utilizing public empirical data from the crop pest species Bactrocera tryoni, a fruit fly native from Northern Australia, we computed GO between "source" populations and a diverse range of locations within invaded areas. This practical application of GO within the context of a biological invasion underscores its potential in providing insights and guiding recommendations for future invasion risk assessment. Overall, our results suggest that GO statistics represent good predictors of the establishment probability and may thus inform invasion risk, although the influence of several factors on prediction performance (e.g., propagule pressure or admixture) will need further investigation.

A genome-wide genetic association study reveals SNPs significantly associated with environmental variables and specific leaf area in European beech

European beech is negatively affected by climate change and a further growth decline is predicted for large parts of its distribution range. Despite the importance of this species, little is known about its genetic adaptation and especially the genetic basis of its physiological traits. Here, we used genotyping by sequencing to identify SNPs in 43 German European beech populations growing under different environmental conditions. In total, 28 of these populations were located along a precipitation and temperature gradient in northern Germany, and single tree-based hydraulic and morphological traits were available. We obtained a set of 13,493 high-quality SNPs that were used for environmental and SNP-trait association analysis. In total, 22 SNPs were identified that were significantly associated with environmental variables or specific leaf area (SLA). Several SNPs were located in genes related to stress response. The majority of the significant SNPs were located in non-coding (intergenic and intronic) regions. These may be in linkage disequilibrium with the causative coding or regulatory regions. Our study gives insights into the genetic basis of abiotic adaptation in European beech, and provides genetic resources that can be used in future studies on this species. Besides clear patterns of local adaptation to environmental conditions of the investigated populations, the analyzed morphological and hydraulic traits explained most of the explainable genetic variation. Thus, they could successfully be altered in tree breeding programs, which may help to increase the adaptation of European beech to changing environmental conditions in the future.

Bringing traits back into the equation: A roadmap to understand species redistribution

Ecological and evolutionary theories have proposed that species traits should be important in mediating species responses to contemporary climate change; yet, empirical evidence has so far provided mixed evidence for the role of behavioral, life history, or ecological characteristics in facilitating or hindering species range shifts. As such, the utility of trait-based approaches to predict species redistribution under climate change has been called into question. We develop the perspective, supported by evidence, that trait variation, if used carefully can have high potential utility, but that past analyses have in many cases failed to identify an explanatory value for traits by not fully embracing the complexity of species range shifts. First, we discuss the relevant theory linking species traits to range shift processes at the leading (expansion) and trailing (contraction) edges of species distributions and highlight the need to clarify the mechanistic basis of trait-based approaches. Second, we provide a brief overview of range shift-trait studies and identify new opportunities for trait integration that consider range-specific processes and intraspecific variability. Third, we explore the circumstances under which environmental and biotic context dependencies are likely to affect our ability to identify the contribution of species traits to range shift processes. Finally, we propose that revealing the role of traits in shaping species redistribution may likely require accounting for methodological variation arising from the range shift estimation process as well as addressing existing functional, geographical, and phylogenetic biases. We provide a series of considerations for more effectively integrating traits as well as extrinsic and methodological factors into species redistribution research. Together, these analytical approaches promise stronger mechanistic and predictive understanding that can help society mitigate and adapt to the effects of climate change on biodiversity.

Predicting the future of our oceans-Evaluating genomic forecasting approaches in marine species

Climate change is restructuring biodiversity on multiple scales and there is a pressing need to understand the downstream ecological and genomic consequences of this change. Recent advancements in the field of eco-evolutionary genomics have sought to include evolutionary processes in forecasting species' responses to climate change (e.g., genomic offset), but to date, much of this work has focused on terrestrial species. Coastal and offshore species, and the fisheries they support, may be even more vulnerable to climate change than their terrestrial counterparts, warranting a critical appraisal of these approaches in marine systems. First, we synthesize knowledge about the genomic basis of adaptation in marine species, and then we discuss the few examples where genomic forecasting has been applied in marine systems. Next, we identify the key challenges in validating genomic offset estimates in marine species, and we advocate for the inclusion of historical sampling data and hindcasting in the validation phase. Lastly, we describe a workflow to guide marine managers in incorporating these predictions into the decision-making process.

Rapid diversification of grey mangroves (Avicennia marina) driven by geographic isolation and extreme environmental conditions in the Arabian Peninsula

Biological systems occurring in ecologically heterogeneous and spatially discontinuous habitats provide an ideal opportunity to investigate the relative roles of neutral and selective factors in driving lineage diversification. The grey mangroves (Avicennia marina) of Arabia occur at the northern edge of the species' range and are subject to variable, often extreme, environmental conditions, as well as historic large fluctuations in habitat availability and connectivity resulting from Quaternary glacial cycles. Here, we analyse fully sequenced genomes sampled from 19 locations across the Red Sea, the Arabian Sea and the Persian/Arabian Gulf (PAG) to reconstruct the evolutionary history of the species in the region and to identify adaptive mechanisms of lineage diversification. Population structure and phylogenetic analyses revealed marked genetic structure correlating with geographic distance and highly supported clades among and within the seas surrounding the Arabian Peninsula. Demographic modelling showed times of divergence consistent with recent periods of geographic isolation and low marine connectivity during glaciations, suggesting the presence of (cryptic) glacial refugia in the Red Sea and the PAG. Significant migration was detected within the Red Sea and the PAG, and across the Strait of Hormuz to the Arabian Sea, suggesting gene flow upon secondary contact among populations. Genetic-environment association analyses revealed high levels of adaptive divergence and detected signs of multi-loci local adaptation driven by temperature extremes and hypersalinity. These results support a process of rapid diversification resulting from the combined effects of historical factors and ecological selection and reveal mangrove peripheral environments as relevant drivers of lineage diversity.

Populus cathayana genome and population resequencing provide insights into its evolution and adaptation

Populus cathayana Rehder, an indigenous poplar species of ecological and economic importance, is widely distributed in a high-elevation range from southwest to northeast China. Further development of this species as a sustainable poplar resource has been hindered by a lack of genome information the at the population level. Here, we produced a chromosome-level genome assembly of P. cathayana, covering 406.55 Mb (scaffold N50 = 20.86 Mb) and consisting of 19 chromosomes, with 35 977 protein-coding genes. Subsequently, we made a genomic variation atlas of 438 wild individuals covering 36 representative geographic areas of P. cathayana, which were divided into four geographic groups. It was inferred that the Northwest China regions served as the genetic diversity centers and a population bottleneck happened during the history of P. cathayana. By genotype-environment association analysis, 947 environment-association loci were significantly associated with temperature, solar radiation, precipitation, and altitude variables. We identified local adaptation genes involved in DNA repair and UV radiation response, among which UVR8, HY5, and CUL4 had key roles in high-altitude adaptation of P. cathayana. Predictions of adaptive potential under future climate conditions showed that P. cathayana populations in areas with drastic climate change were anticipated to have greater maladaptation risk. These results provide comprehensive insights for understanding wild poplar evolution and optimizing adaptive potential in molecular breeding.

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.

Local adaptation and future climate vulnerability in a wild rodent

As climate change continues, species pushed outside their physiological tolerance limits must adapt or face extinction. When change is rapid, adaptation will largely harness ancestral variation, making the availability and characteristics of that variation of critical importance. Here, we used whole-genome sequencing and genetic-environment association analyses to identify adaptive variation and its significance in the context of future climates in a small Palearctic mammal, the bank vole (Clethrionomys glareolus). We found that peripheral populations of bank vole in Britain are already at the extreme bounds of potential genetic adaptation and may require an influx of adaptive variation in order to respond. Analyses of adaptive loci suggest regional differences in climate variables select for variants that influence patterns of population adaptive resilience, including genes associated with antioxidant defense, and support a pattern of thermal/hypoxic cross-adaptation. Our findings indicate that understanding potential shifts in genomic composition in response to climate change may be key to predicting species' fate under future climates.

Individual-based landscape genomics for conservation: An analysis pipeline

Landscape genomics can harness environmental and genetic data to inform conservation decisions by providing essential insights into how landscapes shape biodiversity. The massive increase in genetic data afforded by the genomic era provides exceptional resolution for answering critical conservation genetics questions. The accessibility of genomic data for non-model systems has also enabled a shift away from population-based sampling to individual-based sampling, which now provides accurate and robust estimates of genetic variation that can be used to examine the spatial structure of genomic diversity, population connectivity and the nature of environmental adaptation. Nevertheless, the adoption of individual-based sampling in conservation genetics has been slowed due, in large part, to concerns over how to apply methods developed for population-based sampling to individual-based sampling schemes. Here, we discuss the benefits of individual-based sampling for conservation and describe how landscape genomic methods, paired with individual-based sampling, can answer fundamental conservation questions. We have curated key landscape genomic methods into a user-friendly, open-source workflow, which we provide as a new R package, A Landscape Genomics Analysis Toolkit in R (algatr). The algatr package includes novel added functionality for all of the included methods and extensive vignettes designed with the primary goal of making landscape genomic approaches more accessible and explicitly applicable to conservation biology.

Whole genome analyses reveal weak signatures of population structure and environmentally associated local adaptation in an important North American pollinator, the bumble bee Bombus vosnesenskii

Studies of species that experience environmental heterogeneity across their distributions have become an important tool for understanding mechanisms of adaptation and predicting responses to climate change. We examine population structure, demographic history and environmentally associated genomic variation in Bombus vosnesenskii, a common bumble bee in the western USA, using whole genome resequencing of populations distributed across a broad range of latitudes and elevations. We find that B. vosnesenskii exhibits minimal population structure and weak isolation by distance, confirming results from previous studies using other molecular marker types. Similarly, demographic analyses with Sequentially Markovian Coalescent models suggest that minimal population structure may have persisted since the last interglacial period, with genomes from different parts of the species range showing similar historical effective population size trajectories and relatively small fluctuations through time. Redundancy analysis revealed a small amount of genomic variation explained by bioclimatic variables. Environmental association analysis with latent factor mixed modelling (LFMM2) identified few outlier loci that were sparsely distributed throughout the genome and although a few putative signatures of selective sweeps were identified, none encompassed particularly large numbers of loci. Some outlier loci were in genes with known regulatory relationships, suggesting the possibility of weak selection, although compared with other species examined with similar approaches, evidence for extensive local adaptation signatures in the genome was relatively weak. Overall, results indicate B. vosnesenskii is an example of a generalist with a high degree of flexibility in its environmental requirements that may ultimately benefit the species under periods of climate change.

First genome-wide data from Italian European beech (Fagus sylvatica L.): Strong and ancient differentiation between Alps and Apennines

The European beech (Fagus sylvatica L.) is one of the most widespread forest trees in Europe whose distribution and intraspecific diversity has been largely shaped by repeated glacial cycles. Previous studies, mainly based on palaeobotanical evidence and a limited set of chloroplast and nuclear genetic markers, highlighted a complex phylogeographic scenario, with southern and western Europe characterized by a rather heterogeneous genetic structure, as a result of recolonization from different glacial refugia. Despite its ecological and economic importance, the genome of this broad-leaved tree has only recently been assembled, and its intra-species genomic diversity is still largely unexplored. Here, we performed whole-genome resequencing of nine Italian beech individuals sampled from two stands located in the Alpine and Apennine mountain ranges. We investigated patterns of genetic diversity at chloroplast, mitochondrial and nuclear genomes and we used chloroplast genomes to reconstruct a temporally-resolved phylogeny. Results allowed us to test European beech differentiation on a whole-genome level and to accurately date their divergence time. Our results showed comparable, relatively high levels of genomic diversity in the two populations and highlighted a clear differentiation at chloroplast, mitochondrial and nuclear genomes. The molecular clock analysis indicated an ancient split between the Alpine and Apennine populations, occurred between the Günz and the Riss glaciations (approximately 660 kyrs ago), suggesting a long history of separation for the two gene pools. This information has important conservation implications in the context of adaptation to ongoing climate changes.

Biodiversity protection against anthropogenic climate change: Conservation prioritization of Castanea sativa in the South Caucasus based on genetic and ecological metrics

The climate drives species distribution and genetic diversity; the latter defines the adaptability of populations and species. The ongoing climate crisis induces tree decline in many regions, compromising the mitigation potential of forests. Scientific-based strategies for prioritizing forest tree populations are critical to managing the impact of climate change. Identifying future climate refugia, which are locations naturally buffering the negative impact of climate change, may facilitate local conservation. In this work, we conducted the populations' prioritization for Castanea sativa (sweet chestnut), a Neogene relict growing in the Caucasus global biodiversity hotspot. We generated genetic and ecological metrics for 21 sites in Georgia and Azerbaijan, which cover the natural range of sweet chestnut across the region. We demonstrated that climate primarily drives the pattern of genetic diversity in C. sativa, proved with a significant isolation-by-environment model. In future, climate change may significantly reorganize the species' genetic diversity, inducing even some genetic loss, especially in the very distinct eastern fringe of the species range in Azerbaijan. Based on our combined approach, we mapped populations suitable for ex situ and in situ conservation, accounting for genetic variability and the location of future climate refugia.

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.

Oak stands along an elevation gradient have different molecular strategies for regulating bud phenology

BACKGROUND

Global warming raises serious concerns about the persistence of species and populations locally adapted to their environment, simply because of the shift it produces in their adaptive landscape. For instance, the phenological cycle of tree species may be strongly affected by higher winter temperatures and late frost in spring. Given the variety of ecosystem services they provide, the question of forest tree adaptation has received increasing attention in the scientific community and catalyzed research efforts in ecology, evolutionary biology and functional genomics to study their adaptive capacity to respond to such perturbations.

RESULTS

In the present study, we used an elevation gradient in the Pyrenees Mountains to explore the gene expression network underlying dormancy regulation in natural populations of sessile oak stands sampled along an elevation cline and potentially adapted to different climatic conditions mainly driven by temperature. By performing analyses of gene expression in terminal buds we identified genes displaying significant dormancy, elevation or dormancy-by-elevation interaction effects. Our Results highlighted that low- and high-altitude populations have evolved different molecular strategies for minimizing late frost damage and maximizing the growth period, thereby increasing potentially their respective fitness in these contrasting environmental conditions. More particularly, population from high elevation overexpressed genes involved in the inhibition of cell elongation and delaying flowering time while genes involved in cell division and flowering, enabling buds to flush earlier were identified in population from low elevation.

CONCLUSION

Our study made it possible to identify key dormancy-by-elevation responsive genes revealing that the stands analyzed in this study have evolved distinct molecular strategies to adapt their bud phenology in response to temperature.

A novel synthesis of two decades of microsatellite studies on European beech reveals decreasing genetic diversity from glacial refugia

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

Supplementary Information

The online version contains supplementary material available at 10.1007/s11295-022-01577-4.

Aridity and cold temperatures drive divergent adjustments of European beech xylem anatomy, hydraulics and leaf physiological traits

Understanding plant trait coordination and variance across climatic gradients is critical for assessing forests' adaptive potential to climate change. We measured 11 hydraulic, anatomical and leaf-level physiological traits in European beech (Fagus sylvatica L.) along a moisture and temperature gradient in the French Alps. We assessed how traits covaried, and how their population-level variances shifted along the gradient. The intrapopulation variances of vessel size and xylem-specific conductivity reduced in colder locations as narrow vessels were observed in response to low temperature. This decreased individual-level water transport capacity compared with the warmer and more xeric sites. Conversely, the maximum stomatal conductance and Huber value variances were constrained in the arid and warm locations, where trees showed restricted gas exchange and higher xylem-specific conductivity. The populations growing under drier and warmer conditions presented wide variance for the xylem anatomical and hydraulic traits. Our results suggest that short-term physiological acclimation to raising aridity and heat in southern beech populations may occur mainly at the leaf level. Furthermore, the wide variance of the xylem anatomical and hydraulic traits at these sites may be advantageous since more heterogeneous hydraulic conductivity could imply populations' greater tree-tree complementarity and resilience against climatic variability. Our study highlights that both intrapopulation trait variance and trait network analysis are key approaches for understanding species adaptation and the acclimation potential to a shifting environment.

Past climatic refugia and landscape resistance explain spatial genetic structure in Oriental beech in the South Caucasus

Predicting species-level effects of climatic changes requires unraveling the factors affecting the spatial genetic composition. However, disentangling the relative contribution of historical and contemporary drivers is challenging. By applying landscape genetics and species distribution modeling, we investigated processes that shaped the neutral genetic structure of Oriental beech (Fagus orientalis), aiming to assess the potential risks involved due to possible future distribution changes in the species. Using nuclear microsatellites, we analyze 32 natural populations from the Georgia and Azerbaijan (South Caucasus). We found that the species colonization history is the most important driver of the genetic pattern. The detected west-east gradient of genetic differentiation corresponds strictly to the Colchis and Hyrcanian glacial refugia. A significant signal of associations to environmental variables suggests that the distinct genetic composition of the Azerbaijan and Hyrcanian stands might also be structured by the local climate. Oriental beech retains an overall high diversity; however, in the context of projected habitat loss, its genetic resources might be greatly impoverished. The most affected are the Azerbaijan and Hyrcanian populations, for which the detected genetic impoverishment may enhance their vulnerability to environmental change. Given the adaptive potential of range-edge populations, the loss of these populations may ultimately affect the specie's adaptation, and thus the stability and resilience of forest ecosystems in the Caucasus ecoregion. Our study is the first approximation of the potential risks involved, inducing far-reaching conclusions about the need of maintaining the genetic resources of Oriental beech for a species' capacity to cope with environmental change.

Geriatric nutritional risk index is associated with retinopathy in patients with type 2 diabetes

The geriatric nutritional risk index (GNRI) is a nutrition-related risk assessment tool and has been used in various clinical settings. The relationship between body mass index (BMI) and the associated risk of diabetic retinopathy (DR) remains inconclusive. We aimed to evaluate the association between GNRI and DR in patients with type 2 diabetes. We included a total of 1359 patients with type 2 diabetes who followed up in our diabetes clinic and underwent fundus photographic examinations from August 2006 to February 2014. DR was assessed by retinal ophthalmologists using comprehensive ophthalmologic examinations. Patients were divided into tertiles according to their GNRI category. Patients in a lower GNRI tertile tended to have a higher proportion of nonproliferative DR (NPDR) and proliferative DR (PDR) compared with those in the other tertiles. The risk of PDR was higher in patients included in GNRI tertile 1 (Odds ratio (OR) 2.252, 95% Confidence Interval (CI) 1.080–4.823, P = 0.033) and GNRI tertile 2 (OR 2.602, 95% CI 1.323–5.336, P = 0.007) compared with those in GNRI tertile 3. In patients with lower GNRIs, the prevalence of DR was higher than in those with higher GNRIs. When GNRI was compared with BMI using the area under the curve, overall accuracy was high in GNRI. The risk of PDR was high in patients with low GNRI and there is an inverse association between GNRI scores and prevalence of DR. GNRI might be a useful tool to predict DR in patients with type 2 diabetes.

The evolutionary heritage and ecological uniqueness of Scots pine in the Caucasus ecoregion is at risk of climate changes

Scots pine is one of the most widely occurring pines, but future projections suggest a large reduction in its range, mostly at the southern European limits. A significant part of its range is located in the Caucasus, a global hot-spot of diversity. Pine forests are an important reservoir of biodiversity and endemism in this region. We explored demographic and biogeographical processes that shaped the genetic diversity of Scots pine in the Caucasus ecoregion and its probable future distribution under different climate scenarios. We found that the high genetic variability of the Caucasian populations mirrors a complex glacial and postglacial history that had a unique evolutionary trajectory compared to the main range in Europe. Scots pine currently grows under a broad spectrum of climatic conditions in the Caucasus, which implies high adaptive potential in the past. However, the current genetic resources of Scots pine are under high pressure from climate change. From our predictions, over 90% of the current distribution of Scots pine may be lost in this century. By threatening the stability of the forest ecosystems, this would dramatically affect the biodiversity of the Caucasus hot-spot.

MrIML: Multi-response interpretable machine learning to model genomic landscapes

We introduce a new R package "MrIML" ("Mister iml"; Multi-response Interpretable Machine Learning). MrIML provides a powerful and interpretable framework that enables users to harness recent advances in machine learning to quantify multilocus genomic relationships, to identify loci of interest for future landscape genetics studies, and to gain new insights into adaptation across environmental gradients. Relationships between genetic variation and environment are often nonlinear and interactive; these characteristics have been challenging to address using traditional landscape genetic approaches. Our package helps capture this complexity and offers functions that fit and interpret a wide range of highly flexible models that are routinely used for single-locus landscape genetics studies but are rarely extended to estimate response functions for multiple loci. To demonstrate the package's broad functionality, we test its ability to recover landscape relationships from simulated genomic data. We also apply the package to two empirical case studies. In the first, we model genetic variation of North American balsam poplar (Populus balsamifera, Salicaceae) populations across environmental gradients. In the second case study, we recover the landscape and host drivers of feline immunodeficiency virus genetic variation in bobcats (Lynx rufus). The ability to model thousands of loci collectively and compare models from linear regression to extreme gradient boosting, within the same analytical framework, has the potential to be transformative. The MrIML framework is also extendable and not limited to modelling genetic variation; for example, it can quantify the environmental drivers of microbiomes and coinfection dynamics.

Genetic signatures of divergent selection in European beech (Fagus sylvatica L.) are associated with the variation in temperature and precipitation across its distribution range

High genetic variation and extensive gene flow may help forest trees with adapting to ongoing climate change, yet the genetic bases underlying their adaptive potential remain largely unknown. We investigated range-wide patterns of potentially adaptive genetic variation in 64 populations of European beech (Fagus sylvatica L.) using 270 SNPs from 139 candidate genes involved either in phenology or in stress responses. We inferred neutral genetic structure and processes (drift and gene flow) and performed differentiation outlier analyses and gene-environment association (GEA) analyses to detect signatures of divergent selection. Beech range-wide genetic structure was consistent with the species' previously identified postglacial expansion scenario and recolonization routes. Populations showed high diversity and low differentiation along the major expansion routes. A total of 52 loci were found to be putatively under selection and 15 of them turned up in multiple GEA analyses. Temperature and precipitation related variables were equally represented in significant genotype-climate associations. Signatures of divergent selection were detected in the same proportion for stress response and phenology-related genes. The range-wide adaptive genetic structure of beech appears highly integrated, suggesting a balanced contribution of phenology and stress-related genes to local adaptation, and of temperature and precipitation regimes to genetic clines. Our results imply a best-case scenario for the maintenance of high genetic diversity during range shifts in beech (and putatively other forest trees) with a combination of gene flow maintaining within-population neutral diversity and selection maintaining between-population adaptive differentiation.

AlleleShift: an R package to predict and visualize population-level changes in allele frequencies in response to climate change

Background

At any particular location, frequencies of alleles that are associated with adaptive traits are expected to change in future climates through local adaption and migration, including assisted migration (human-implemented when climate change is more rapid than natural migration rates). Making the assumption that the baseline frequencies of alleles across environmental gradients can act as a predictor of patterns in changed climates (typically future but possibly paleo-climates), a methodology is provided by AlleleShift of predicting changes in allele frequencies at the population level.

Methods

The prediction procedure involves a first calibration and prediction step through redundancy analysis (RDA), and a second calibration and prediction step through a generalized additive model (GAM) with a binomial family. As such, the procedure is fundamentally different to an alternative approach recently proposed to predict changes in allele frequencies from canonical correspondence analysis (CCA). The RDA step is based on the Euclidean distance that is also the typical distance used in Analysis of Molecular Variance (AMOVA). Because the RDA step or CCA approach sometimes predict negative allele frequencies, the GAM step ensures that allele frequencies are in the range of 0 to 1.

Results

AlleleShift provides data sets with predicted frequencies and several visualization methods to depict the predicted shifts in allele frequencies from baseline to changed climates. These visualizations include 'dot plot' graphics (function shift.dot.ggplot), pie diagrams (shift.pie.ggplot), moon diagrams (shift.moon.ggplot), 'waffle' diagrams (shift.waffle.ggplot) and smoothed surface diagrams of allele frequencies of baseline or future patterns in geographical space (shift.surf.ggplot). As these visualizations were generated through the ggplot2 package, methods of generating animations for a climate change time series are straightforward, as shown in the documentation of AlleleShift and in the supplemental videos.

Availability

AlleleShift is available as an open-source R package from https://cran.r-project.org/package=AlleleShift and https://github.com/RoelandKindt/AlleleShift. Genetic input data is expected to be in the adegenet::genpop format, which can be generated from the adegenet::genind format. Climate data is available from various resources such as WorldClim and Envirem.

Annual aboveground carbon uptake enhancements from assisted gene flow in boreal black spruce forests are not long-lasting

Assisted gene flow between populations has been proposed as an adaptive forest management strategy that could contribute to the sequestration of carbon. Here we provide an assessment of the mitigation potential of assisted gene flow in 46 populations of the widespread boreal conifer Picea mariana, grown in two 42-year-old common garden experiments and established in contrasting Canadian boreal regions. We use a dendroecological approach taking into account phylogeographic structure to retrospectively analyse population phenotypic variability in annual aboveground net primary productivity (NPP). We compare population NPP phenotypes to detect signals of adaptive variation and/or the presence of phenotypic clines across tree lifespans, and assess genotype-by-environment interactions by evaluating climate and NPP relationships. Our results show a positive effect of assisted gene flow for a period of approximately 15 years following planting, after which there was little to no effect. Although not long lasting, well-informed assisted gene flow could accelerate the transition from carbon source to carbon sink after disturbance.

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.

Genomic Prediction of (Mal)Adaptation Across Current and Future Climatic Landscapes

Signals of local adaptation have been found in many plants and animals, highlighting the heterogeneity in the distribution of adaptive genetic variation throughout species ranges. In the coming decades, global climate change is expected to induce shifts in the selective pressures that shape this adaptive variation. These changes in selective pressures will likely result in varying degrees of local climate maladaptation and spatial reshuffling of the underlying distributions of adaptive alleles. There is a growing interest in using population genomic data to help predict future disruptions to locally adaptive gene-environment associations. One motivation behind such work is to better understand how the effects of changing climate on populations’ short-term fitness could vary spatially across species ranges. Here we review the current use of genomic data to predict the disruption of local adaptation across current and future climates. After assessing goals and motivationsunderlying the approach, we review the main steps and associated statistical methods currently in use and explore our current understanding of the limits and future potential of using genomics to predict climate change (mal)adaptation.