The evolutionary genomics of species' responses to climate change

The influence of temperature and genomic variation on intracranial EEG measures in people with epilepsy

Heatwaves have serious impacts on human health and constitute a key health concern from anthropogenic climate change. People have different individual tolerance for heatwaves or unaccustomed temperatures. Those with epilepsy may be particularly affected by temperature as the electroclinical hallmarks of brain excitability in epilepsy (inter-ictal epileptiform discharges and seizures) are influenced by a range of physiological and non-physiological conditions. Heatwaves are becoming more common and may affect brain excitability. Leveraging spontaneous heatwaves during periods of intracranial EEG recording in participants with epilepsy in a non-air-conditioned telemetry unit at the National Hospital for Neurology and Neurosurgery in London from May to August 2015-22, we examined the impact of heatwaves on brain excitability. In London, a heatwave is defined as three or more consecutive days with daily maximum temperatures ≥28°C. For each participant, we counted inter-ictal epileptiform discharges using four 10-min segments within, and outside of, heatwaves during periods of intracranial EEG recording. Additionally, we counted all clinical and subclinical seizures within, and outside of, heatwaves. We searched for causal rare genetic variants and calculated the epilepsy PRS. Nine participants were included in the study (six men, three women), median age 30 years (range 24-39). During heatwaves, there was a significant increase in the number of inter-ictal epileptiform discharges in three participants. Five participants had more seizures during the heatwave period, and as a group, there were significantly more seizures during the heatwaves. Genetic data, available for eight participants, showed none had known rare, genetically-determined epilepsies, whilst all had high polygenic risk scores for epilepsy. For some people with epilepsy, and not just those with known, rare, temperature-sensitive epilepsies, there is an association between heatwaves and increased brain excitability. These preliminary data require further validation and exploration, as they raise concerns about the impact of heatwaves directly on brain health.

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.

Experimental Evolution in a Warming World: The Omics Era

A comprehensive understanding of the genetic mechanisms that shape species responses to thermal variation is essential for more accurate predictions of the impacts of climate change on biodiversity. Experimental evolution with high-throughput resequencing approaches (evolve and resequence) is a highly effective tool that has been increasingly employed to elucidate the genetic basis of adaptation. The number of thermal evolve and resequence studies is rising, yet there is a dearth of efforts to integrate this new wealth of knowledge. Here, we review this literature showing how these studies have contributed to increase our understanding on the genetic basis of thermal adaptation. We identify two major trends: highly polygenic basis of thermal adaptation and general lack of consistency in candidate targets of selection between studies. These findings indicate that the adaptive responses to specific environments are rather independent. A review of the literature reveals several gaps in the existing research. Firstly, there is a paucity of studies done with organisms of diverse taxa. Secondly, there is a need to apply more dynamic and ecologically relevant thermal environments. Thirdly, there is a lack of studies that integrate genomic changes with changes in life history and behavioral traits. Addressing these issues would allow a more in-depth understanding of the relationship between genotype and phenotype. We highlight key methodological aspects that can address some of the limitations and omissions identified. These include the need for greater standardization of methodologies and the utilization of new technologies focusing on the integration of genomic and phenotypic variation in the context of thermal adaptation.

Benefit-Sharing by Design: A Call to Action for Human Genomics Research

The ethical standards for the responsible conduct of human research have come a long way; however, concerns surrounding equity remain in human genetics and genomics research. Addressing these concerns will help society realize the full potential of human genomics research. One outstanding concern is the fair and equitable sharing of benefits from research on human participants. Several international bodies have recognized that benefit-sharing can be an effective tool for ethical research conduct, but international laws, including the Convention on Biological Diversity and its Nagoya Protocol on Access and Benefit-Sharing, explicitly exclude human genetic and genomic resources. These agreements face significant challenges that must be considered and anticipated if similar principles are applied in human genomics research. We propose that benefit-sharing from human genomics research can be a bottom-up effort and embedded into the existing research process. We propose the development of a "benefit-sharing by design" framework to address concerns of fairness and equity in the use of human genomic resources and samples and to learn from the aspirations and decade of implementation of the Nagoya Protocol.

Conserving Evolutionary Potential: Combining Landscape Genomics with Established Methods to Inform Plant Conservation

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.

Local adaptation of Pinus leiophylla under climate and land use change models in the Avocado Belt of Michoacán

Climate change and land use change are two main drivers of global biodiversity decline, decreasing the genetic diversity that populations harbour and altering patterns of local adaptation. Landscape genomics allows measuring the effect of these anthropogenic disturbances on the adaptation of populations. However, both factors have rarely been considered simultaneously. Based on a set of 3660 SNPs from which 130 were identified as outliers by a genome-environment association analysis (LFMM), we modelled the spatial turnover of allele frequencies in 19 localities of Pinus leiophylla across the Avocado Belt in Michoacán state, Mexico. Then, we evaluated the effect of climate change and land use change scenarios, in addition to evaluating assisted gene flow strategies and connectivity metrics across the landscape to identify priority conservation areas for the species. We found that localities in the centre-east of the Avocado Belt would be more vulnerable to climate change, while localities in the western area are more threatened by land conversion to avocado orchards. Assisted gene flow actions could aid in mitigating both threats. Connectivity patterns among forest patches will also be modified by future habitat loss, with central and eastern parts of the Avocado Belt maintaining the highest connectivity. These results suggest that areas with the highest priority for conservation are in the eastern part of the Avocado Belt, including the Monarch Butterfly Biosphere Reserve. This work is useful as a framework that incorporates distinct layers of information to provide a more robust representation of the response of tree populations to anthropogenic disturbances.

Patterns and effects of gene flow on adaptation across spatial scales: implications for management

Gene flow can have rapid effects on adaptation and is an important evolutionary tool available when undertaking biological conservation and restoration. This tool is underused partly because of the perceived risk of outbreeding depression and loss of mean fitness when different populations are crossed. In this article, we briefly review some theory and empirical findings on how genetic variation is distributed across species ranges, describe known patterns of gene flow in nature with respect to environmental gradients, and highlight the effects of gene flow on adaptation in small or stressed populations in challenging environments (e.g., at species range limits). We then present a case study involving crosses at varying spatial scales among mountain populations of a trigger plant (Stylidium armeria: Stylidiaceae) in the Australian Alps to highlight how some issues around gene flow effects can be evaluated. We found evidence of outbreeding depression in seed production at greater geographic distances. Nevertheless, we found no evidence of maladaptive gene flow effects in likelihood of germination, plant performance (size), and performance variance, suggesting that gene flow at all spatial scales produces offspring with high adaptive potential. This case study demonstrates a path to evaluating how increasing sources of gene flow in managed wild and restored populations could identify some offspring with high fitness that could bolster the ability of populations to adapt to future environmental changes. We suggest further ways in which managers and researchers can act to understand and consider adaptive gene flow in natural and conservation contexts under rapidly changing conditions.

Evolutionary genomics of climatic adaptation and resilience to climate change in alfalfa

Given the escalating impact of climate change on agriculture and food security, gaining insights into the evolutionary dynamics of climatic adaptation and uncovering climate-adapted variation can empower the breeding of climate-resilient crops to face future climate change. Alfalfa (Medicago sativa subsp. sativa), the queen of forages, shows remarkable adaptability across diverse global environments, making it an excellent model for investigating species responses to climate change. In this study, we performed population genomic analyses using genome resequencing data from 702 accessions of 24 Medicago species to unravel alfalfa's climatic adaptation and genetic susceptibility to future climate change. We found that interspecific genetic exchange has contributed to the gene pool of alfalfa, particularly enriching defense and stress-response genes. Intersubspecific introgression between M. sativa subsp. falcata (subsp. falcata) and alfalfa not only aids alfalfa's climatic adaptation but also introduces genetic burden. A total of 1671 genes were associated with climatic adaptation, and 5.7% of them were introgressions from subsp. falcata. By integrating climate-associated variants and climate data, we identified populations that are vulnerable to future climate change, particularly in higher latitudes of the Northern Hemisphere. These findings serve as a clarion call for targeted conservation initiatives and breeding efforts. We also identified pre-adaptive populations that demonstrate heightened resilience to climate fluctuations, illuminating a pathway for future breeding strategies. Collectively, this study enhances our understanding about the local adaptation mechanisms of alfalfa and facilitates the breeding of climate-resilient alfalfa cultivars, contributing to effective agricultural strategies for facing future climate change.

Incorporating adaptive genomic variation into predictive models for invasion risk assessment

Global climate change is expected to accelerate biological invasions, necessitating accurate risk forecasting and management strategies. However, current invasion risk assessments often overlook adaptive genomic variation, which plays a significant role in the persistence and expansion of invasive populations. Here we used Molgula manhattensis, a highly invasive ascidian, as a model to assess its invasion risks along Chinese coasts under climate change. Through population genomics analyses, we identified two genetic clusters, the north and south clusters, based on geographic distributions. To predict invasion risks, we employed the gradient forest and species distribution models to calculate genomic offset and species habitat suitability, respectively. These approaches yielded distinct predictions: the gradient forest model suggested a greater genomic offset to future climatic conditions for the north cluster (i.e., lower invasion risks), while the species distribution model indicated higher future habitat suitability for the same cluster (i.e, higher invasion risks). By integrating these models, we found that the south cluster exhibited minor genome-niche disruptions in the future, indicating higher invasion risks. Our study highlights the complementary roles of genomic offset and habitat suitability in assessing invasion risks under climate change. Moreover, incorporating adaptive genomic variation into predictive models can significantly enhance future invasion risk predictions and enable effective management strategies for biological invasions in the future.

Genomics for monitoring and understanding species responses to global climate change

All life forms across the globe are experiencing drastic changes in environmental conditions as a result of global climate change. These environmental changes are happening rapidly, incur substantial socioeconomic costs, pose threats to biodiversity and diminish a species' potential to adapt to future environments. Understanding and monitoring how organisms respond to human-driven climate change is therefore a major priority for the conservation of biodiversity in a rapidly changing environment. Recent developments in genomic, transcriptomic and epigenomic technologies are enabling unprecedented insights into the evolutionary processes and molecular bases of adaptation. This Review summarizes methods that apply and integrate omics tools to experimentally investigate, monitor and predict how species and communities in the wild cope with global climate change, which is by genetically adapting to new environmental conditions, through range shifts or through phenotypic plasticity. We identify advantages and limitations of each method and discuss future research avenues that would improve our understanding of species' evolutionary responses to global climate change, highlighting the need for holistic, multi-omics approaches to ecosystem monitoring during global climate change.

Genomic insights into local adaptation and phenotypic diversity of Wenchang chickens

Wenchang chicken, a prized local breed in Hainan Province of China renowned for its exceptional adaptability to tropical environments and good meat quality, is deeply favored by the public. However, an insufficient understanding of its population architecture and the unclear genetic basis that governs its typical attributes have posed challenges in the protection and breeding of this precious breed. To address these gaps, we conducted whole-genome resequencing on 200 Wenchang chicken samples derived from 10 distinct strains, and we gathered data on an array of 21 phenotype traits. Population genomics analysis unveiled distinctive population structures in Wenchang chickens, primarily attributed to strong artificial selection for different feather colors. Selection sweep analysis identified a group of candidate genes, including PCDH9, DPF3, CDIN1, and SUGCT, closely linked to adaptations that enhance resilience in tropical island habitats. Genome-wide association studies (GWAS) highlighted potential candidate genes associated with diverse feather color traits, encompassing TYR, RAB38, TRPM1, GABARAPL2, CDH1, ZMIZ1, LYST, MC1R, and SASH1. Through the comprehensive analysis of high-quality genomic and phenotypic data across diverse Wenchang chicken resource groups, this study unveils the intricate genetic backgrounds and population structures of Wenchang chickens. Additionally, it identifies multiple candidate genes linked to environmental adaptation, feather color variations, and production traits. These insights not only provide genetic reference for the purification and breeding of Wenchang chickens but also broaden our understanding of the genetic basis of phenotypic diversity in chickens.

Genomic evidence for rediploidization and adaptive evolution following the whole-genome triplication

Whole-genome duplication (WGD), or polyploidy, events are widespread and significant in the evolutionary history of angiosperms. However, empirical evidence for rediploidization, the major process where polyploids give rise to diploid descendants, is still lacking at the genomic level. Here we present chromosome-scale genomes of the mangrove tree Sonneratia alba and the related inland plant Lagerstroemia speciosa. Their common ancestor has experienced a whole-genome triplication (WGT) approximately 64 million years ago coinciding with a period of dramatic global climate change. Sonneratia, adapting mangrove habitats, experienced extensive chromosome rearrangements post-WGT. We observe the WGT retentions display sequence and expression divergence, suggesting potential neo- and sub-functionalization. Strong selection acting on three-copy retentions indicates adaptive value in response to new environments. To elucidate the role of ploidy changes in genome evolution, we improve a model of the polyploidization-rediploidization process based on genomic evidence, contributing to the understanding of adaptive evolution during climate change.

Climatic and soil characteristics account for the genetic structure of the invasive cactus moth Cactoblastis cactorum, in its native range in Argentina

Background

Knowledge of the physical and environmental conditions that may limit the migration of invasive species is crucial to assess the potential for expansion outside their native ranges. The cactus moth, Cactoblastis cactorum, is native to South America (Argentina, Paraguay, Uruguay and Brazil) and has been introduced and invaded the Caribbean and southern United States, among other regions. In North America there is an ongoing process of range expansion threatening cacti biodiversity of the genus Opuntia and the commercial profits of domesticated Opuntia ficus-indica.

Methods

To further understand what influences the distribution and genetic structure of this otherwise important threat to native and managed ecosystems, in the present study we combined ecological niche modeling and population genetic analyses to identify potential environmental barriers in the native region of Argentina. Samples were collected on the host with the wider distribution range, O. ficus-indica.

Results

Significant genetic structure was detected using 10 nuclear microsatellites and 24 sampling sites. At least six genetic groups delimited by mountain ranges, salt flats and wetlands were mainly located to the west of the Dry Chaco ecoregion. Niche modeling supports that this region has high environmental suitability where the upper soil temperature and humidity, soil carbon content and precipitation were the main environmental factors that explain the presence of the moth. Environmental filters such as the upper soil layer may be critical for pupal survival and consequently for the establishment of populations in new habitats, whereas the presence of available hosts is a necessary conditions for insect survival, upper soil and climatic characteristics will determine the opportunities for a successful establishment.

Genomics empowering conservation action and improvement of celery in the face of climate change

MAIN CONCLUSION

Integration of genomic approaches like whole genome sequencing, functional genomics, evolutionary genomics, and CRISPR/Cas9-based genome editing has accelerated the improvement of crop plants including leafy vegetables like celery in the face of climate change. The anthropogenic climate change is a real peril to the existence of life forms on our planet, including human and plant life. Climate change is predicted to be a significant threat to biodiversity and food security in the coming decades and is rapidly transforming global farming systems. To avoid the ghastly future in the face of climate change, the elucidation of shifts in the geographical range of plant species, species adaptation, and evolution is necessary for plant scientists to develop climate-resilient strategies. In the post-genomics era, the increasing availability of genomic resources and integration of multifaceted genomics elements is empowering biodiversity conservation action, restoration efforts, and identification of genomic regions adaptive to climate change. Genomics has accelerated the true characterization of crop wild relatives, genomic variations, and the development of climate-resilient varieties to ensure food security for 10 billion people by 2050. In this review, we have summarized the applications of multifaceted genomic tools, like conservation genomics, whole genome sequencing, functional genomics, genome editing, pangenomics, in the conservation and adaptation of plant species with a focus on celery, an aromatic and medicinal Apiaceae vegetable. We focus on how conservation scientists can utilize genomics and genomic data in conservation and improvement.

Comparative Study of Potential Habitats for Simulium qinghaiense (Diptera: Simuliidae) in the Huangshui River Basin, Qinghai-Tibet Plateau: An Analysis Using Four Ecological Niche Models and Optimized Approaches

The Huangshui River, a vital tributary in the upper reaches of the Yellow River within the eastern Qinghai-Tibet Plateau, is home to the endemic black fly species S. qinghaiense. In this study, we conducted a systematic survey of the distribution of the species in the Huangshui River basin, revealing its predominant presence along the river's main stem. Based on four ecological niche models-MaxEnt with parameter optimization; GARP; BIOCLIM; and DOMAIN-we conduct a comparative analysis; evaluating the accuracy of AUC and Kappa values. Our findings indicate that optimizing parameters significantly improves the MaxEnt model's predictive accuracy by reducing complexity and overfitting. Furthermore, all four models exhibit higher accuracy compared to a random model, with MaxEnt demonstrating the highest AUC and Kappa values (0.9756 and 0.8118, respectively), showcasing significant superiority over the other models (p < 0.05). Evaluation of predictions from the four models elucidates that potential areas of S. qinghaiense in the Huangshui River basin are primarily concentrated in the central and southern areas, with precipitation exerting a predominant influence. Building upon these results, we utilized the MaxEnt model to forecast changes in suitable areas and distribution centers during the Last Interglacial (LIG), Mid-Holocene (MH), and future periods under three climate scenarios. The results indicate significantly smaller suitable areas during LIG and MH compared to the present, with the center of distribution shifting southeastward from the Qilian Mountains to the central part of the basin. In the future, suitable areas under different climate scenarios are expected to contract, with the center of distribution shifting southeastward. These findings provide important theoretical references for monitoring, early warning, and control measures for S. qinghaiense in the region, contributing to ecological health assessment.

Space-for-time substitutions in climate change ecology and evolution

In an epoch of rapid environmental change, understanding and predicting how biodiversity will respond to a changing climate is an urgent challenge. Since we seldom have sufficient long-term biological data to use the past to anticipate the future, spatial climate-biotic relationships are often used as a proxy for predicting biotic responses to climate change over time. These 'space-for-time substitutions' (SFTS) have become near ubiquitous in global change biology, but with different subfields largely developing methods in isolation. We review how climate-focussed SFTS are used in four subfields of ecology and evolution, each focussed on a different type of biotic variable - population phenotypes, population genotypes, species' distributions, and ecological communities. We then examine the similarities and differences between subfields in terms of methods, limitations and opportunities. While SFTS are used for a wide range of applications, two main approaches are applied across the four subfields: spatial in situ gradient methods and transplant experiments. We find that SFTS methods share common limitations relating to (i) the causality of identified spatial climate-biotic relationships and (ii) the transferability of these relationships, i.e. whether climate-biotic relationships observed over space are equivalent to those occurring over time. Moreover, despite widespread application of SFTS in climate change research, key assumptions remain largely untested. We highlight opportunities to enhance the robustness of SFTS by addressing key assumptions and limitations, with a particular emphasis on where approaches could be shared between the four subfields.

Landscape genomics analysis provides insights into future climate change-driven risk in rhesus macaque

Climate change significantly affects the suitability of wildlife habitats. Thus, understanding how animals adapt ecologically and genetically to climate change is important for targeted species protection. Rhesus macaques (Macaca mulatta) are widely distributed and multi-climatically adapted primates. This study explored how rhesus macaques adapt to climate change by integrating ecological and genetic methods and applying species distribution models (SDMs) and a gradient forest (GF) model. The findings suggested that temperature seasonality primarily affects habitat suitability and indicated that climate change will have a dramatic impact on macaque populations in the future. We also applied genotype-environment association (GEA) analyses and selection signature analyses to identify genes associated with climate change and provide possible explanations for the adaptation of rhesus macaques to climatic environments. The population genomics analyses suggested that the Taihang population has the highest genomic vulnerability with inbreeding and low heterozygosity. Combined with the higher ecological vulnerability, additional conservation strategies are required for this population under higher risk of climate change. Our work measured the impact of climate change and enabled the identification of populations that exhibit high vulnerability to severe climate change. Such information is useful for selecting populations of rhesus macaques as subject of long-term monitoring or evolutionary rescue under future climate change.

Contrasting whole-genome and reduced representation sequencing for population demographic and adaptive inference: an alpine mammal case study

Genomes capture the adaptive and demographic history of a species, but the choice of sequencing strategy and sample size can impact such inferences. We compared whole genome and reduced representation sequencing approaches to study the population demographic and adaptive signals of the North American mountain goat (Oreamnos americanus). We applied the restriction site-associated DNA sequencing (RADseq) approach to 254 individuals and whole genome resequencing (WGS) approach to 35 individuals across the species range at mid-level coverage (9X) and to 5 individuals at high coverage (30X). We used ANGSD to estimate the genotype likelihoods and estimated the effective population size (Ne), population structure, and explicitly modelled the demographic history with δaδi and MSMC2. The data sets were overall concordant in supporting a glacial induced vicariance and extremely low Ne in mountain goats. We evaluated a set of climatic variables and geographic location as predictors of genetic diversity using redundancy analysis. A moderate proportion of total variance (36% for WGS and 21% for RADseq data sets) was explained by geography and climate variables; both data sets support a large impact of drift and some degree of local adaptation. The empirical similarities of WGS and RADseq presented herein reassuringly suggest that both approaches will recover large demographic and adaptive signals in a population; however, WGS offers several advantages over RADseq, such as inferring adaptive processes and calculating runs-of-homozygosity estimates. Considering the predicted climate-induced changes in alpine environments and the genetically depauperate mountain goat, the long-term adaptive capabilities of this enigmatic species are questionable.

Impact of climate change on the geographical distribution and niche dynamics of Gastrodia elata

Background

Gastrodia elata is widely used in China as a valuable herbal medicine. Owing to its high medicinal and nutrient value, wild resources of G. elata have been overexploited and its native areas have been severely damaged. Understanding the impacts of climate change on the distribution of this endangered species is important for the conservation and sustainable use of G. elata.

Methods

We used the optimized maximum entropy model to simulate the potential distribution of G. elata under contemporary and future time periods (1970-2000, 2050s, 2070s, and 2090s) and different climate change scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Under these conditions, we investigated the key environmental factors influencing the distribution of G. elata as well as the spatial and temporal characteristics of its niche dynamics.

Results

With high Maxent model accuracy (AUCmean = 0.947 ± 0.012, and the Kappa value is 0.817), our analysis revealed that annual precipitation, altitude, and mean temperature of driest quarter are the most important environmental factors influencing the distribution of G. elata. Under current bioclimatic conditions, the potentially suitable area for G. elata in China is 71.98 × 10⁴ km², while the highly suitable region for G. elata growth is 7.28 × 10⁴ km². Our models for three future periods under four climate change scenarios indicate that G. elata can maintain stable distributions in southern Shaanxi, southwestern Hubei, and around the Sichuan basin, as these areas are highly suitable for its growth. However, the center of the highly suitable areas of G. elata shift depending on different climatic scenarios. The values of niche overlap for G. elata show a decreasing trend over the forecasted periods, of which the niche overlap under the SSP3-7.0 scenario shows the greatest decrease.

Discussions

Under the condition of global climate change in the future, our study provides basic reference data for the conservation and sustainable utilization of the valuable and endangered medicinal plant G. elata. It is important to carefully choose the protection area of G. elata wild resources according the suitable area conditions modeled. Moreover, these findings will be valuable for providing insights into the breeding and artificial cultivation of this plant, including the selection of suitable areas for planting.

Key triggers of adaptive genetic variability of sessile oak [Q. petraea (Matt.) Liebl.] from the Balkan refugia: outlier detection and association of SNP loci from ddRAD-seq data

Knowledge on the genetic composition of Quercus petraea in south-eastern Europe is limited despite the species' significant role in the re-colonisation of Europe during the Holocene, and the diverse climate and physical geography of the region. Therefore, it is imperative to conduct research on adaptation in sessile oak to better understand its ecological significance in the region. While large sets of SNPs have been developed for the species, there is a continued need for smaller sets of SNPs that are highly informative about the possible adaptation to this varied landscape. By using double digest restriction site associated DNA sequencing data from our previous study, we mapped RAD-seq loci to the Quercus robur reference genome and identified a set of SNPs putatively related to drought stress-response. A total of 179 individuals from eighteen natural populations at sites covering heterogeneous climatic conditions in the southeastern natural distribution range of Q. petraea were genotyped. The detected highly polymorphic variant sites revealed three genetic clusters with a generally low level of genetic differentiation and balanced diversity among them but showed a north-southeast gradient. Selection tests showed nine outlier SNPs positioned in different functional regions. Genotype-environment association analysis of these markers yielded a total of 53 significant associations, explaining 2.4-16.6% of the total genetic variation. Our work exemplifies that adaptation to drought may be under natural selection in the examined Q. petraea populations.

Multigenic resistance to Xylella fastidiosa in wild grapes (Vitis sps.) and its implications within a changing climate

Xylella fastidiosa is a bacterium that infects crops like grapevines, coffee, almonds, citrus and olives. There is little understanding of the genes that contribute to plant resistance, the genomic architecture of resistance, and the potential role of climate in shaping resistance, in part because major crops like grapevines (Vitis vinifera) are not resistant to the bacterium. Here we study a wild grapevine species, V. arizonica, that segregates for resistance. Using genome-wide association, we identify candidate resistance genes. Resistance-associated kmers are shared with a sister species of V. arizonica but not with more distant species, suggesting that resistance evolved more than once. Finally, resistance is climate dependent, because individuals from low ( < 10 °C) temperature locations in the wettest quarter were typically susceptible to infection, likely reflecting a lack of pathogen pressure in colder climates. In fact, climate is as effective a predictor of resistance phenotypes as some genetic markers. We extend our climate observations to additional crops, predicting that increased pathogen pressure is more likely for grapevines and almonds than some other susceptible crops.

Genomic insights into genetic diversity and local adaptation of a dominant desert steppe feather grass, Stipa breviflora Griseb

Investigating the genetic mechanisms of local adaptation is critical to understanding how species adapt to heterogeneous environments. In the present study, we analyzed restriction site-associated DNA sequencing (RADseq) data in order to explore genetic diversity, genetic structure, genetic differentiation, and local adaptation of Stipa breviflora. In total, 135 individual plants were sequenced and 25,786 polymorphic loci were obtained. We found low genetic diversity (He = 0.1284) within populations of S. breviflora. Four genetic clusters were identified along its distribution range. The Mantel test, partial Mantel test, and multiple matrix regression with randomization (MMRR) indicate that population differentiation was caused by both geographic distance and environmental factors. Through the F_ST outlier test and environmental association analysis (EAA), 113 candidate loci were identified as putatively adaptive loci. RPK2 and CPRF1, which are associated with meristem maintenance and light responsiveness, respectively, were annotated. To explore the effects of climatic factors on genetic differentiation and local adaptation of S. breviflora, gradient forest (GF) analysis was applied to 25,786 single nucleotide polymorphisms (SNPs) and 113 candidate loci, respectively. The results showed that both temperature and precipitation affected the genetic differentiation of S. breviflora, and precipitation was strongly related to local adaptation. Our study provides a theoretical basis for understanding the local adaptation of S. breviflora.

An integrated eco-evolutionary framework to predict population-level responses of climate-sensitive pathogens

It is critical to gain insight into how climate change impacts evolutionary responses within climate-sensitive pathogen populations, such as increased resilience, opportunistic responses and the emergence of dominant variants from highly variable genomic backgrounds and subsequent global dispersal. This review proposes a framework to support such analysis, by combining genomic evolutionary analysis with climate time-series data in a novel spatiotemporal dataframe for use within machine learning applications, to understand past and future evolutionary pathogen responses to climate change. Recommendations are presented to increase the feasibility of interdisciplinary applications, including the importance of robust spatiotemporal metadata accompanying genome submission to databases. Such workflows will inform accessible public health tools and early-warning systems, to aid decision-making and mitigate future human health threats.

Genome Scan of Rice Landrace Populations Collected Across Time Revealed Climate Changes' Selective Footprints in the Genes Network Regulating Flowering Time

Analyses of the genetic bases of plant adaptation to climate changes, using genome-scan approaches, are often conducted on natural populations, under hypothesis of out-crossing reproductive regime. We report here on a study based on diachronic sampling (1980 and 2011) of the autogamous crop species, Oryza sativa and Oryza glaberrima, in the tropical forest and the Sudanian savannah of West Africa. First, using historical meteorological data we confirmed changes in temperatures (+ 1 °C on average) and rainfall regime (less predictable and reduced amount) in the target areas. Second, phenotyping the populations for phenology, we observed significantly earlier heading time in the 2010 samples. Third, implementing two genome-scan methods (one of which specially developed for selfing species) on genotyping by sequencing genotypic data of the two populations, we detected 31 independent selection footprints. Gene ontology analysis detected significant enrichment of these selection footprints in genes involved in reproductive processes. Some of them bore known heading time QTLs and genes, including OsGI, Hd1 and OsphyB. This rapid adaptive evolution, originated from subtle changes in the standing variation in genetic network regulating heading time, did not translate into predominance of multilocus genotypes, as it is often the case in selfing plants, and into notable selective sweeps. The high adaptive potential observed results from the multiline genetic structure of the rice landraces, and the rather large and imbricated genetic diversity of the rice meta-population at the farm, the village and the region levels, that hosted the adaptive variants in multiple genetic backgrounds before the advent of the environmental selective pressure. Our results illustrate the evolution of in situ diversity through processes of human and natural selection, and provide a model for rice breeding and cultivars deployment strategies aiming resilience to climate changes. It also calls for further development of population genetic models for adaptation of plant populations to environmental changes. To our best knowledge, this is the first study dealing with climate-changes' selective footprint in crops.

Population genomics unravels the Holocene history of bread wheat and its relatives

Deep knowledge of crop biodiversity is essential to improving global food security. Despite bread wheat serving as a keystone crop worldwide, the population history of bread wheat and its relatives, both cultivated and wild, remains elusive. By analysing whole-genome sequences of 795 wheat accessions, we found that bread wheat originated from the southwest coast of the Caspian Sea and underwent a slow speciation process, lasting ~3,300 yr owing to persistent gene flow from its relatives. Soon after, bread wheat spread across Eurasia and reached Europe, South Asia and East Asia ~7,000 to ~5,000 yr ago, shaping a diversified but occasionally convergent adaptive landscape in novel environments. By contrast, the cultivated relatives of bread wheat experienced a population decline by ~82% over the past ~2,000 yr due to the food choice shift of humans. Further biogeographical modelling predicted a continued population shrinking of many bread wheat relatives in the coming decades because of their vulnerability to the changing climate. These findings will guide future efforts in protecting and utilizing wheat biodiversity to enhance global wheat production.

Molecular mechanisms of adaptive evolution in wild animals and plants

Wild animals and plants have developed a variety of adaptive traits driven by adaptive evolution, an important strategy for species survival and persistence. Uncovering the molecular mechanisms of adaptive evolution is the key to understanding species diversification, phenotypic convergence, and inter-species interaction. As the genome sequences of more and more non-model organisms are becoming available, the focus of studies on molecular mechanisms of adaptive evolution has shifted from the candidate gene method to genetic mapping based on genome-wide scanning. In this study, we reviewed the latest research advances in wild animals and plants, focusing on adaptive traits, convergent evolution, and coevolution. Firstly, we focused on the adaptive evolution of morphological, behavioral, and physiological traits. Secondly, we reviewed the phenotypic convergences of life history traits and responding to environmental pressures, and the underlying molecular convergence mechanisms. Thirdly, we summarized the advances of coevolution, including the four main types: mutualism, parasitism, predation and competition. Overall, these latest advances greatly increase our understanding of the underlying molecular mechanisms for diverse adaptive traits and species interaction, demonstrating that the development of evolutionary biology has been greatly accelerated by multi-omics technologies. Finally, we highlighted the emerging trends and future prospects around the above three aspects of adaptive evolution.

Climate-induced range shifts drive adaptive response via spatio-temporal sieving of alleles

Quaternary climate fluctuations drove many species to shift their geographic ranges, in turn shaping their genetic structures. Recently, it has been argued that adaptation may have accompanied species range shifts via the "sieving" of genotypes during colonisation and establishment. However, this has not been directly demonstrated, and knowledge remains limited on how different evolutionary forces, which are typically investigated separately, interacted to jointly mediate species responses to past climatic change. Here, through whole-genome re-sequencing of over 1200 individuals of the carnation Dianthus sylvestris coupled with integrated population genomic and gene-environment models, we reconstruct the past neutral and adaptive landscape of this species as it was shaped by the Quaternary glacial cycles. We show that adaptive responses emerged concomitantly with the post-glacial range shifts and expansions of this species in the last 20 thousand years. This was due to the heterogenous sieving of adaptive alleles across space and time, as populations expanded out of restrictive glacial refugia into the broader and more heterogeneous range of habitats available in the present-day inter-glacial. Our findings reveal a tightly-linked interplay of migration and adaptation under past climate-induced range shifts, which we show is key to understanding the spatial patterns of adaptive variation we see in species today.

Hybridization and introgression are prevalent in Southern European Erysimum (Brassicaceae) species

BACKGROUND AND AIMS

Hybridization is a common and important force in plant evolution. One of its outcomes is introgression - the transfer of small genomic regions from one taxon to another by hybridization and repeated backcrossing. This process is believed to be common in glacial refugia, where range expansions and contractions can lead to cycles of sympatry and isolation, creating conditions for extensive hybridization and introgression. Polyploidization is another genome-wide process with a major influence on plant evolution. Both hybridization and polyploidization can have complex effects on plant evolution. However, these effects are often difficult to understand in recently evolved species complexes.

METHODS

We combined flow cytometry, analyses of transcriptomic sequences and pollen tube growth assays to investigate the consequences of polyploidization, hybridization and introgression on the recent evolution of several Erysimum (Brassicaceae) species from the South of the Iberian Peninsula, a well-known glacial refugium. This species complex differentiated in the last 2 million years, and its evolution has been hypothesized to be determined mainly by polyploidization, interspecific hybridization and introgression.

KEY RESULTS

Our results support a scenario of widespread hybridization involving both extant and 'ghost' taxa. Several taxa studied here, most notably those with purple corollas, are polyploids, probably of allopolyploid origin. Moreover, hybridization in this group might be an ongoing phenomenon, as pre-zygotic barriers appeared weak in many cases.

CONCLUSIONS

The evolution of Erysimum spp. has been determined by hybridization to a large extent. Species with purple (polyploids) and yellow flowers (mostly diploid) exhibit a strong signature of introgression in their genomes, indicating that hybridization occurred regardless of colour and across ploidy levels. Although the adaptive value of such genomic exchanges remains unclear, our results demonstrate the significance of hybridization for plant diversification, which should be taken into account when studying plant evolution.

ChIP-seq profiling of H3K4me3 and H3K27me3 in an invasive insect, Bactrocera dorsalis

Introduction: While it has been suggested that histone modifications can facilitate animal responses to rapidly changing environments, few studies have profiled whole-genome histone modification patterns in invasive species, leaving the regulatory landscape of histone modifications in invasive species unclear. Methods: Here, we screen genome-wide patterns of two important histone modifications, trimethylated Histone H3 Lysine 4 (H3K4me3) and trimethylated Histone H3 Lysine 27 (H3K27me3), in adult thorax muscles of a notorious invasive pest, the Oriental fruit fly Bactrocera dorsalis (Hendel) (Diptera: Tephritidae), using Chromatin Immunoprecipitation with high-throughput sequencing (ChIP-seq). Results: We identified promoters featured by the occupancy of H3K4me3, H3K27me3 or bivalent histone modifications that were respectively annotated with unique genes key to muscle development and structure maintenance. In addition, we found H3K27me3 occupied the entire body of genes, where the average enrichment was almost constant. Transcriptomic analysis indicated that H3K4me3 is associated with active gene transcription, and H3K27me3 is mostly associated with transcriptional repression. Importantly, we identified genes and putative motifs modified by distinct histone modification patterns that may possibly regulate flight activity. Discussion: These findings provide the first evidence of histone modification signature in B. dorsalis, and will be useful for future studies of epigenetic signature in other invasive insect species.

Using landscape genomics to assess local adaptation and genomic vulnerability of a perennial herb Tetrastigma hemsleyanum (Vitaceae) in subtropical China

Understanding adaptive genetic variation of plant populations and their vulnerabilities to climate change are critical to preserve biodiversity and subsequent management interventions. To this end, landscape genomics may represent a cost-efficient approach for investigating molecular signatures underlying local adaptation. Tetrastigma hemsleyanum is, in its native habitat, a widespread perennial herb of warm-temperate evergreen forest in subtropical China. Its ecological and medicinal values constitute a significant revenue for local human populations and ecosystem. Using 30,252 single nucleotide polymorphisms (SNPs) derived from reduced-representation genome sequencing in 156 samples from 24 sites, we conducted a landscape genomics study of the T. hemsleyanum to elucidate its genomic variation across multiple climate gradients and genomic vulnerability to future climate change. Multivariate methods identified that climatic variation explained more genomic variation than that of geographical distance, which implied that local adaptation to heterogeneous environment might represent an important source of genomic variation. Among these climate variables, winter precipitation was the strongest predictor of the contemporary genetic structure. F _ST outlier tests and environment association analysis totally identified 275 candidate adaptive SNPs along the genetic and environmental gradients. SNP annotations of these putatively adaptive loci uncovered gene functions associated with modulating flowering time and regulating plant response to abiotic stresses, which have implications for breeding and other special agricultural aims on the basis of these selection signatures. Critically, modelling revealed that the high genomic vulnerability of our focal species via a mismatch between current and future genotype-environment relationships located in central-northern region of the T. hemsleyanum's range, where populations require proactive management efforts such as assistant adaptation to cope with ongoing climate change. Taken together, our results provide robust evidence of local climate adaption for T. hemsleyanum and further deepen our understanding of adaptation basis of herbs in subtropical China.

A decade of population genetics studies of scleractinian corals: A systematic review

Coral reefs are the most diverse marine ecosystems. However, coral cover has decreased worldwide due to natural disturbances, climate change, and local anthropogenic drivers. In recent decades, various genetic methods and molecular markers have been developed to assess genetic diversity, structure, and connectivity in different coral species to determine the vulnerability of their populations. This review aims to identify population genetic studies of scleractinian corals in the last decade (2010-2020), and the techniques and molecular markers used. Bibliometric analysis was conducted to identify journals and authors working in this field. We then calculated the number of genetic studies by species and ecoregion based on data obtained from 178 studies found in Scopus and Web of Science. Coral Reefs and Molecular Ecology were the main journals published population genetics studies, and microsatellites are the most widely used molecular markers. The Caribbean, Australian Barrier Reef, and South Kuroshio in Japan are among the ecoregions with the most population genetics data. In contrast, we found limited information about the Coral Triangle, a region with the highest biodiversity and key to coral reef conservation. Notably, only 117 (out of 1500 described) scleractinian coral species have genetic studies. This review emphasizes which coral species have been studied and highlights remaining gaps and locations where such data is critical for coral conservation.

Cell-type-specific co-expression inference from single cell RNA-sequencing data

The inference of gene co-expressions from microarray and RNA-sequencing data has led to rich insights on biological processes and disease mechanisms. However, the bulk samples analyzed in most studies are a mixture of different cell types. As a result, the inferred co-expressions are confounded by varying cell type compositions across samples and only offer an aggregated view of gene regulations that may be distinct across different cell types. The advancement of single cell RNA-sequencing (scRNA-seq) technology has enabled the direct inference of co-expressions in specific cell types, facilitating our understanding of cell-type-specific biological functions. However, the high sequencing depth variations and measurement errors in scRNA-seq data present significant challenges in inferring cell-type-specific gene co-expressions, and these issues have not been adequately addressed in the existing methods. We propose a statistical approach, CS-CORE, for estimating and testing cell-type-specific co-expressions, built on a general expression-measurement model that explicitly accounts for sequencing depth variations and measurement errors in the observed single cell data. Systematic evaluations show that most existing methods suffer from inflated false positives and biased co-expression estimates and clustering analysis, whereas CS-CORE has appropriate false positive control, unbiased co-expression estimates, good statistical power and satisfactory performance in downstream co-expression analysis. When applied to analyze scRNA-seq data from postmortem brain samples from Alzheimer’s disease patients and controls and blood samples from COVID-19 patients and controls, CS-CORE identified cell-type-specific co-expressions and differential co-expressions that were more reproducible and/or more enriched for relevant biological pathways than those inferred from other methods.

The Fate of Endemic Species Specialized in Island Habitat under Climate Change in a Mediterranean High Mountain

Mediterranean high-mountain endemic species are particularly vulnerable to climatic changes in temperature, precipitation and snow-cover dynamics. Sierra Nevada (Spain) is a biodiversity hotspot in the western Mediterranean, with an enormous plant species richness and endemicity. Moehringia fontqueri is a threatened endemic plant restricted to north-facing siliceous rocks along a few ridges of the eastern Sierra Nevada. To guide conservation actions against climate change effects, here we propose the simultaneous assessment of the current reproductive success and the possible species' range changes between current and future climatic conditions, assessing separately different subpopulations by altitude. Reproductive success was tested through the seed-set data analysis. The species' current habitat suitability was modeled in Maxent using species occurrences, topographic, satellite and climatic variables. Future habitat suitability was carried out for two climatic scenarios (RCP 2.6 and 8.5). The results showed the lowest reproductive success at the lowest altitudes, and vice versa at the highest altitudes. Habitat suitability decreased by 80% from current conditions to the worst-case scenario (RCP 8.5). The lowest subpopulations were identified as the most vulnerable to climate change effects while the highest ones were the nearest to future suitable habitats. Our simultaneous assessment of reproductive success and habitat suitability aims to serve as a model to guide conservation, management and climate change mitigation strategies through adaptive management to safeguard the persistence of the maximum genetic pool of Mediterranean high-mountain plants threatened by climate change.

Genomic insights into local adaptation and future climate-induced vulnerability of a keystone forest tree in East Asia

Rapid global climate change is posing a substantial threat to biodiversity. The assessment of population vulnerability and adaptive capacity under climate change is crucial for informing conservation and mitigation strategies. Here we generate a chromosome-scale genome assembly and re-sequence genomes of 230 individuals collected from 24 populations for Populus koreana, a pioneer and keystone tree species in temperate forests of East Asia. We integrate population genomics and environmental variables to reveal a set of climate-associated single-nucleotide polymorphisms, insertion/deletions and structural variations, especially numerous adaptive non-coding variants distributed across the genome. We incorporate these variants into an environmental modeling scheme to predict a highly spatiotemporal shift of this species in response to future climate change. We further identify the most vulnerable populations that need conservation priority and many candidate genes and variants that may be useful for forest tree breeding with special aims. Our findings highlight the importance of integrating genomic and environmental data to predict adaptive capacity of a key forest to rapid climate change in the future.

De novo assembly and annotation of the transcriptome of the endangered seagrass Zostera capensis: Insights from differential gene expression under thermal stress

Seagrasses are important marine ecosystem engineers but anthropogenic impacts and climate change have led to numerous population declines globally. In South Africa, Zostera capensis is endangered due to fragmented populations and heavy anthropogenic pressures on estuarine ecosystems that house the core of the populations. Addressing questions of how pressures such as climate change affect foundational species, including Z. capensis are crucial to supporting their conservation and underpin restoration efforts. Here we use ecological transcriptomics to study key functional responses of Z. capensis through quantification of gene expression after thermal stress and present the first reference transcriptome of Z. capensis. Four de novo reference assemblies (Trinity, IDBA-tran, RNAspades, SOAPdenovo) filtered through the EvidentialGene pipeline resulted in 153,755 transcripts with a BUSCO score of 66.1% for completeness. Differential expression analysis between heat stressed (32 °C for three days) and pre-warming plants identified genes involved in photosynthesis, oxidative stress, translation, metabolic and biosynthetic processes in the Z. capensis thermal stress response. This reference transcriptome is a significant contribution to the limited available genomic resources for Z. capensis and represents a vital tool for addressing questions around the species restoration and potential functional responses to warming marine environments.

Data-driven, participatory characterization of farmer varieties discloses teff breeding potential under current and future climates

In smallholder farming systems, traditional farmer varieties of neglected and underutilized species (NUS) support the livelihoods of millions of growers and consumers. NUS combine cultural and agronomic value with local adaptation, and transdisciplinary methods are needed to fully evaluate their breeding potential. Here, we assembled and characterized the genetic diversity of a representative collection of 366 Ethiopian teff (Eragrostis tef) farmer varieties and breeding materials, describing their phylogenetic relations and local adaptation on the Ethiopian landscape. We phenotyped the collection for its agronomic performance, involving local teff farmers in a participatory variety evaluation. Our analyses revealed environmental patterns of teff genetic diversity and allowed us to identify 10 genetic clusters associated with climate variation and with uneven spatial distribution. A genome-wide association study was used to identify loci and candidate genes related to phenology, yield, local adaptation, and farmers’ appreciation. The estimated teff genomic offset under climate change scenarios highlighted an area around lake Tana where teff cropping may be most vulnerable to climate change. Our results show that transdisciplinary approaches may efficiently propel untapped NUS farmer varieties into modern breeding to foster more resilient and sustainable cropping systems.

Small farms support the livelihoods of about two billion people worldwide. Smallholder farmers often rely on local varieties of crops and use less irrigation and fertilizer than large producers. But smallholdings can be vulnerable to weather events and climate change. Data-driven research approaches may help to identify the needs of farmers, taking into account traditional knowledge and cultural practices to enhance the sustainability of certain crops.

Teff is a cereal crop that plays a critical role in the culture and diets of Ethiopian communities. It is also a super food appreciated on international markets for its nutritional value. Rural smallholder farmers in Ethiopia rely on the crop for subsistence and income and make up the bulk of the country’s agricultural system. Many grow local varieties with tremendous genetic diversity. Scientists, in collaboration with farmers, could tap that diversity to produce more productive or climate-resilient types of teff, both for national and international markets.

Woldeyohannes, Iohannes et al. produced the first large-scale genetic, agronomic and climatic study of traditional teff varieties. In the experiments, Woldeyohannes and Iohannes et al. sequenced the genomes of 366 Ethiopian teff varieties and evaluated their agronomic value in common gardens. The team collaborated with 35 local farmers to understand their preference of varieties and traits. They then conducted a genome-wide association study to assess the crops’ productivity and their adaptations to local growing conditions and farmer preferences. Genetic changes that speed up teff maturation and flowering time could meet small farmers’ needs to secure teff harvest. Woldeyohannes, Iohannes et al. also identified a region in Ethiopia, where local teff varieties may struggle to adapt to climate change. Genetic modifications may help the crop to adapt to frequent droughts that may be a common characteristic of future climates.

The experiments reveal the importance of incorporating traditional knowledge from smallholder farmers into data-driven crop improvement efforts considering genetics and climate science. This multidisciplinary approach may help to improve food security and protect local genetic diversity on small farms. It may also help to ensure that agricultural advances fairly and equitably benefit small farmers.

Exploiting spatial dimensions to enable parallelized continuous directed evolution

Current strategies to improve the throughput of continuous directed evolution technologies often involve complex mechanical fluid-controlling system or robotic platforms, which limits their popularization and application in general laboratories. Inspired by our previous study on bacterial range expansion, in this study, we report a system termed SPACE for rapid and extensively parallelizable evolution of biomolecules by introducing spatial dimensions into the landmark phage-assisted continuous evolution system. Specifically, M13 phages and chemotactic Escherichia coli cells were closely inoculated onto a semisolid agar. The phages came into contact with the expanding front of the bacterial range, and then comigrated with the bacteria. This system leverages competition over space, wherein evolutionary progress is closely associated with the production of spatial patterns, allowing the emergence of improved or new protein functions. In a prototypical problem, SPACE remarkably simplified the process and evolved the promoter recognition of T7 RNA polymerase (RNAP) to a library of 96 random sequences in parallel. These results establish SPACE as a simple, easy to implement, and massively parallelizable platform for continuous directed evolution in general laboratories.

Unifying climate change biology across realms and taxa

A major challenge in modern biology is to understand extinction risk from climate change across all realms. Recent research has revealed that physiological tolerance, behavioral thermoregulation, and small elevation shifts are dominant coping strategies on land, whereas large-scale latitudinal shifts are more important in the ocean. Freshwater taxa may face the highest global extinction risks. Nevertheless, some species in each realm face similar risks because of shared adaptive, dispersal, or physiological tolerances and abilities. Taking a cross-realm perspective offers unique research opportunities because confounding physical factors in one realm are often disaggregated in another realm. Cross-realm, across taxa, and other forms of climate change biology synthesis are needed to advance our understanding of emergent patterns of risk across all life.

Evolutionary Ecology of Plant-Arthropod Interactions in Light of the "Omics" Sciences: A Broad Guide

Aboveground plant-arthropod interactions are typically complex, involving herbivores, predators, pollinators, and various other guilds that can strongly affect plant fitness, directly or indirectly, and individually, synergistically, or antagonistically. However, little is known about how ongoing natural selection by these interacting guilds shapes the evolution of plants, i.e., how they affect the differential survival and reproduction of genotypes due to differences in phenotypes in an environment. Recent technological advances, including next-generation sequencing, metabolomics, and gene-editing technologies along with traditional experimental approaches (e.g., quantitative genetics experiments), have enabled far more comprehensive exploration of the genes and traits involved in complex ecological interactions. Connecting different levels of biological organization (genes to communities) will enhance the understanding of evolutionary interactions in complex communities, but this requires a multidisciplinary approach. Here, we review traditional and modern methods and concepts, then highlight future avenues for studying the evolution of plant-arthropod interactions (e.g., plant-herbivore-pollinator interactions). Besides promoting a fundamental understanding of plant-associated arthropod communities' genetic background and evolution, such knowledge can also help address many current global environmental challenges.

Understanding the biology of species' ranges: when and how does evolution change the rules of ecological engagement?

Understanding processes that limit species' ranges has been a core issue in ecology and evolutionary biology for many decades, and has become increasingly important given the need to predict the responses of biological communities to rapid environmental change. However, we still have a poor understanding of evolution at range limits and its capacity to change the ecological 'rules of engagement' that define these communities, as well as the time frame over which this occurs. Here we link papers in the current volume to some key concepts involved in the interactions between evolutionary and ecological processes at species' margins. In particular, we separate hypotheses about species' margins that focus on hard evolutionary limits, which determine how genotypes interact with their environment, from those concerned with soft evolutionary limits, which determine where and when local adaptation can persist in space and time. We show how theoretical models and empirical studies highlight conditions under which gene flow can expand local limits as well as contain them. In doing so, we emphasize the complex interplay between selection, demography and population structure throughout a species' geographical and ecological range that determines its persistence in biological communities. However, despite some impressively detailed studies on range limits, particularly in invertebrates and plants, few generalizations have emerged that can predict evolutionary responses at ecological margins. We outline some directions for future work such as considering the impact of structural genetic variants and metapopulation structure on limits, and the interaction between range limits and the evolution of mating systems and non-random dispersal. This article is part of the theme issue 'Species' ranges in the face of changing environments (Part II)'.

Supporting in situ conservation of the genetic diversity of crop wild relatives using genomic technologies

The last decade has witnessed huge technological advances in genomics, particularly in DNA sequencing. Here, we review the actual and potential application of genomics in supporting in situ conservation of crop wild relatives (CWRs). In addition to helping in prioritization of protection of CWR taxa and in situ conservation sites, genome analysis is allowing the identification of novel alleles that need to be prioritized for conservation. Genomics is enabling the identification of potential sources of important adaptive traits that can guide the establishment or enrichment of in situ genetic reserves. Genomic tools also have the potential for developing a robust framework for monitoring and reporting genome‐based indicators of genetic diversity changes associated with factors such as land use or climate change. These tools have been demonstrated to have an important role in managing the conservation of populations, supporting sustainable access and utilization of CWR diversity, enhancing accelerated domestication of new crops and forensic genomics thus preventing misappropriation of genetic resources. Despite this great potential, many policy makers and conservation managers have failed to recognize and appreciate the need to accelerate the application of genomics to support the conservation and management of biodiversity in CWRs to underpin global food security. Funding and inadequate genomic expertise among conservation practitioners also remain major hindrances to the widespread application of genomics in conservation.

Individual-based eco-evolutionary models for understanding adaptation in changing seas

As climate change threatens species' persistence, predicting the potential for species to adapt to rapidly changing environments is imperative for the development of effective conservation strategies. Eco-evolutionary individual-based models (IBMs) can be useful tools for achieving this objective. We performed a literature review to identify studies that apply these tools in marine systems. Our survey suggested that this is an emerging area of research fuelled in part by developments in modelling frameworks that allow simulation of increasingly complex ecological, genetic and demographic processes. The studies we identified illustrate the promise of this approach and advance our understanding of the capacity for adaptation to outpace climate change. These studies also identify limitations of current models and opportunities for further development. We discuss three main topics that emerged across studies: (i) effects of genetic architecture and non-genetic responses on adaptive potential; (ii) capacity for gene flow to facilitate rapid adaptation; and (iii) impacts of multiple stressors on persistence. Finally, we demonstrate the approach using simple simulations and provide a framework for users to explore eco-evolutionary IBMs as tools for understanding adaptation in changing seas.

Climate differently influences the genomic patterns of two sympatric marine fish species

Climate influences population genetic variation in marine species. Capturing these impacts remains challenging for marine fishes which disperse over large geographical scales spanning steep environmental gradients. It requires the extensive spatial sampling of individuals or populations, representative of seascape heterogeneity, combined with a set of highly informative molecular markers capable of revealing climatic-associated genetic variations. We explored how space, dispersal and environment shape the genomic patterns of two sympatric fish species in the Mediterranean Sea, which ranks among the oceanic basins most affected by climate change and human pressure. We hypothesized that the population structure and climate-associated genomic signatures of selection would be stronger in the less mobile species, as restricted gene flow tends to facilitate the fixation of locally adapted alleles. To test our hypothesis, we genotyped two species with contrasting dispersal abilities: the white seabream Diplodus sargus and the striped red mullet Mullus surmuletus. We collected 823 individuals and used genotyping by sequencing (GBS) to detect 8,206 single nucleotide polymorphisms (SNPs) for the seabream and 2,794 for the mullet. For each species, we identified highly differentiated genomic regions (i.e. outliers) and disentangled the relative contribution of space, dispersal and environmental variables (climate, marine primary productivity) on the outliers' genetic structure to test the prevalence of gene flow and local adaptation. We observed contrasting patterns of gene flow and adaptive genetic variation between the two species. The seabream showed a distinct Alboran sea population and panmixia across the Mediterranean Sea. The mullet revealed additional differentiation within the Mediterranean Sea that was significantly correlated to summer and winter temperatures, as well as marine primary productivity. Functional annotation of the climate-associated outlier SNPs then identified candidate genes involved in heat tolerance that could be examined to further predict species' responses to climate change. Our results illustrate the key steps of a comparative seascape genomics study aiming to unravel the evolutionary processes at play in marine species, to better anticipate their response to climate change. Defining population adaptation capacities and environmental niches can then serve to incorporate evolutionary processes into species conservation planning.