Characterizing genomic variation of Arabidopsis thaliana: the roles of geography and climate

Evidence that variation in root anatomy contributes to local adaptation in Mexican native maize

Mexican native maize (Zea mays ssp. mays) is adapted to a wide range of climatic and edaphic conditions. Here, we focus specifically on the potential role of root anatomical variation in this adaptation. Given the investment required to characterize root anatomy, we present a machine-learning approach using environmental descriptors to project trait variation from a relatively small training panel onto a larger panel of genotyped and georeferenced Mexican maize accessions. The resulting models defined potential biologically relevant clines across a complex environment that we used subsequently for genotype-environment association. We found evidence of systematic variation in maize root anatomy across Mexico, notably a prevalence of trait combinations favoring a reduction in axial hydraulic conductance in varieties sourced from cooler, drier highland areas. We discuss our results in the context of previously described water-banking strategies and present candidate genes that are associated with both root anatomical and environmental variation. Our strategy is a refinement of standard environmental genome-wide association analysis that is applicable whenever a training set of georeferenced phenotypic data is available.

New perspectives on the genetic structure of dotted gizzard shad (Konosirus punctatus) based on RAD-seq

To maintain, develop and rationally utilize marine organisms, understanding their genetic structure and habitat adaptation pattern is necessary. Konosirus punctatus, which is a commercial fish species inhabiting the Indo-west Pacific Ocean, has shown an obvious annual global capture and aquaculture production decline due to climate changes and human activities. In the present study, restriction-site associated DNA sequencing (RAD-seq) was used to describe its genome-wide single nucleotide polymorphisms panel (SNPs). Among 146 individuals collected at nine locations scattered in China, Korea and Japan, a set of 632,090 SNPs were identified. Population genetic analysis showed that K. punctatus individuals were divided into two significant genetic clusters. Meanwhile, potential genetic differentiation between northern and southern population of K. punctatus was found. Treemix results indicated that gene flow existed among sampling locations of K. punctatus, especially from southern Japan to others. Moreover, candidate genes associated with habitat adaptations of K. punctatus were identified, which are involved in diverse physiological processes of K. punctatus including growth and development (e.g., KIDINS220, PAN3), substance metabolism (e.g., PGM5) and immune response (e.g., VAV3, CCT7, HSPA12B). Our findings may aid in understanding the possible mechanisms for the population genetic structure and local adaptation of K. punctatus, which is beneficial to establish the management and conservation units of K. punctatus, guiding the rational use of resources, with reference significance for a profound understanding of the adaptative mechanisms of other marine organisms to the environment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-024-00216-2.

Seascapes Shaped the Local Adaptation and Population Structure of South China Coast Yellowfin Seabream (Acanthopagrus latus)

Understanding the genetic composition and regional adaptation of marine species under environmental heterogeneity and fishing pressure is crucial for responsible management. In order to understand the genetic diversity and adaptability of yellowfin seabream (Acanthopagrus latus) along southern China coast, this study was conducted a seascape genome analysis on yellowfin seabream from the ecologically diverse coast, spanning over 1600 km. A total of 92 yellowfin seabream individuals from 15 sites were performed whole-genome resequencing, and 4,383,564 high-quality single nucleotide polymorphisms (SNPs) were called. By conducting a genotype-environment association analysis, 29,951 adaptive and 4,328,299 neutral SNPs were identified. The yellowfin seabream exhibited two distinct population structures, despite high gene flow between sites. The seascape genome analysis revealed that genetic structure was influenced by a variety of factors including salinity gradients, habitat distance, and ocean currents. The frequency of allelic variation at the candidate loci changed with the salinity gradient. Annotation of these loci revealed that most of the genes are associated with osmoregulation, such as kcnab2a, kcnk5a, and slc47a1. These genes are significantly enriched in pathways associated with ion transport including G protein-coupled receptor activity, transmembrane signaling receptor activity, and transporter activity. Overall, our findings provide insights into how seascape heterogeneity affects adaptive evolution, while providing important information for regional management in yellowfin seabream populations.

Landscape genomics reveals adaptive genetic differentiation driven by multiple environmental variables in naked barley on the Qinghai-Tibetan Plateau

Understanding the local adaptation of crops has long been a concern of evolutionary biologists and molecular ecologists. Identifying the adaptive genetic variability in the genome is crucial not only to provide insights into the genetic mechanism of local adaptation but also to explore the adaptation potential of crops. This study aimed to identify the climatic drivers of naked barley landraces and putative adaptive loci driving local adaptation on the Qinghai-Tibetan Plateau (QTP). To this end, a total of 157 diverse naked barley accessions were genotyped using the genotyping-by-sequencing approach, which yielded 3123 high-quality SNPs for population structure analysis and partial redundancy analysis, and 37,636 SNPs for outlier analysis. The population structure analysis indicated that naked barley landraces could be divided into four groups. We found that the genomic diversity of naked barley landraces could be partly traced back to the geographical and environmental diversity of the landscape. In total, 136 signatures associated with temperature, precipitation, and ultraviolet radiation were identified, of which 13 had pleiotropic effects. We mapped 447 genes, including a known gene HvSs1. Some genes involved in cold stress and regulation of flowering time were detected near eight signatures. Taken together, these results highlight the existence of putative adaptive loci in naked barley on QTP and thus improve our current understanding of the genetic basis of local adaptation.

Directional and stabilizing selection shaped morphological, reproductive, and physiological traits of the invader Solidago canadensis

Trait evolution in invasive plant species is important because it can impact demographic parameters key to invasion success. Invasive plant species often show phenotypic clines along geographic and climatic gradients. However, the relative contributions of natural selection and neutral evolutionary processes to phenotypic trait variation among populations of invasive plants remain unclear. A common method to assess whether a trait has been shaped by natural selection or neutral evolutionary processes is to compare the geographical pattern for the trait of interest to the divergence in neutral genetic loci (i.e., Q ST -F ST comparisons). Subsequently, a redundancy analysis (RDA) can facilitate identification of putative agents of natural selection on the trait. Here, we employed both a Q ST -F ST comparisons approach and RDA to infer whether natural selection shaped traits of invasive populations of Solidago canadensis in China and identify the potential environmental drivers of natural selection. We addressed two questions: (1) Did natural selection drive phenotypic trait variation among S. canadensis populations? (2) Did climatic, latitudinal, longitudinal, and altitudinal gradients drive patterns of genetic variation among S. canadensis populations? We found significant directional selection for several morphological and reproductive traits (i.e., Q ST  > F ST) and stabilizing selection for physiological traits (i.e., Q ST  < F ST). The RDA showed that stem biomass of S. canadensis was strongly positively correlated with longitude, while leaf width ratio and specific leaf area were significantly positively correlated with the mean diurnal range. Stem biomass had a strong negative correlation with annual precipitation. Moreover, height of S. canadensis individuals was strongly positively correlated with altitude and precipitation of the wettest quarter. A longitudinal shift in precipitation seasonality likely selected for larger stem biomass in S. canadensis. Overall, these results suggest that longitudinal and altitudinal clines in climate exerted strong selection pressures that shaped the phenotypic traits of S. canadensis.

Population genomic analysis reveals geographic structure and climatic diversification for Macrophomina phaseolina isolated from soybean and dry bean across the United States, Puerto Rico, and Colombia

Macrophomina phaseolina causes charcoal rot, which can significantly reduce yield and seed quality of soybean and dry bean resulting from primarily environmental stressors. Although charcoal rot has been recognized as a warm climate-driven disease of increasing concern under global climate change, knowledge regarding population genetics and climatic variables contributing to the genetic diversity of M. phaseolina is limited. This study conducted genome sequencing for 95 M. phaseolina isolates from soybean and dry bean across the continental United States, Puerto Rico, and Colombia. Inference on the population structure using 76,981 single nucleotide polymorphisms (SNPs) revealed that the isolates exhibited a discrete genetic clustering at the continental level and a continuous genetic differentiation regionally. A majority of isolates from the United States (96%) grouped in a clade with a predominantly clonal genetic structure, while 88% of Puerto Rican and Colombian isolates from dry bean were assigned to a separate clade with higher genetic diversity. A redundancy analysis (RDA) was used to estimate the contributions of climate and spatial structure to genomic variation (11,421 unlinked SNPs). Climate significantly contributed to genomic variation at a continental level with temperature seasonality explaining the most variation while precipitation of warmest quarter explaining the most when spatial structure was accounted for. The loci significantly associated with multivariate climate were found closely to the genes related to fungal stress responses, including transmembrane transport, glycoside hydrolase activity and a heat-shock protein, which may mediate climatic adaptation for M. phaseolina. On the contrary, limited genome-wide differentiation among populations by hosts was observed. These findings highlight the importance of population genetics and identify candidate genes of M. phaseolina that can be used to elucidate the molecular mechanisms that underly climatic adaptation to the changing climate.

Panguiarchaeum symbiosum, a potential hyperthermophilic symbiont in the TACK superphylum

The biology of Korarchaeia remains elusive due to the lack of genome representatives. Here, we reconstruct 10 closely related metagenome-assembled genomes from hot spring habitats and place them into a single species, proposed herein as Panguiarchaeum symbiosum. Functional investigation suggests that Panguiarchaeum symbiosum is strictly anaerobic and grows exclusively in thermal habitats by fermenting peptides coupled with sulfide and hydrogen production to dispose of electrons. Due to its inability to biosynthesize archaeal membranes, amino acids, and purines, this species likely exists in a symbiotic lifestyle similar to DPANN archaea. Population metagenomics and metatranscriptomic analyses demonstrated that genes associated with amino acid/peptide uptake and cell attachment exhibited positive selection and were highly expressed, supporting the proposed proteolytic catabolism and symbiotic lifestyle. Our study sheds light on the metabolism, evolution, and potential symbiotic lifestyle of Panguiarchaeum symbiosum, which may be a unique host-dependent archaeon within the TACK superphylum.

Genotype-environment associations to reveal the molecular basis of environmental adaptation

A fundamental goal in plant biology is to identify and understand the variation underlying plants' adaptation to their environment. Climate change has given new urgency to this goal, as society aims to accelerate adaptation of ecologically important plant species, endangered plant species, and crops to hotter, less predictable climates. In the pre-genomic era, identifying adaptive alleles was painstaking work, leveraging genetics, molecular biology, physiology, and ecology. Now, the rise of genomics and new computational approaches may facilitate this research. Genotype-environment associations (GEAs) use statistical associations between allele frequency and environment of origin to test the hypothesis that allelic variation at a given gene is adapted to local environments. Researchers may scan the genome for GEAs to generate hypotheses on adaptive genetic variants (environmental genome-wide association studies). Despite the rapid adoption of these methods, many important questions remain about the interpretation of GEA findings, which arise from fundamental unanswered questions on the genetic architecture of adaptation and limitations inherent to association-based analyses. We outline strategies to ground GEAs in the underlying hypotheses of genetic architecture and better test GEA-generated hypotheses using genetics and ecophysiology. We provide recommendations for new users who seek to learn about the molecular basis of adaptation. When combined with a rigorous hypothesis testing framework, GEAs may facilitate our understanding of the molecular basis of climate adaptation for plant improvement.

Polymorphisms in alternative oxidase genes from ecotypes of Arabidopsis and rice revealed an environment-induced linkage to altitude and rainfall

We investigated SNPs in alternative oxidase (AOX) genes and their connection to ecotype origins (climate, altitude, and rainfall) by using genomic data sets of Arabidopsis and rice populations from 1190 and 90 ecotypes, respectively. Parameters were defined to detect non-synonymous SNPs in the AOX ORF, which revealed amino acid (AA) changes in AOX1c, AOX1d, and AOX2 from Arabidopsis and AOX1c from rice in comparison to AOX references from Columbia-0 and Japonica ecotypes, respectively. Among these AA changes, Arabidopsis AOX1c_A161E&G165R and AOX1c_R242S revealed a link to high rainfall and high altitude, respectively, while all other changes in Arabidopsis and rice AOX was connected to high altitude and rainfall. Comparative 3D modeling showed that all mutant AOX presented structural differences in relation to the respective references. Molecular docking analysis uncovered lower binding affinity values between AOX and the substrate ubiquinol for most of the identified structures compared to their reference, indicating better enzyme-substrate binding affinities. Thus, our in silico data suggest that the majority of the AA changes found in the available ecotypes will confer better enzyme-subtract interactions and thus indicate environment-related, more efficient AOX activity.

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.

Whole-genome sequencing of a year-round fruiting jackfruit (Artocarpus heterophyllus Lam.) reveals high levels of single nucleotide variation

Jackfruit (Artocarpus heterophyllus Lam.) is the national fruit of Bangladesh and produces fruit in the summer season only. However, jackfruit is not commercially grown in Bangladesh because of an extremely high variation in fruit quality, short seasonal fruiting (June-August) and susceptibility to abiotic stresses. Conversely, a year-round high yielding (ca. 4-fold higher than the seasonal variety) jackfruit variety, BARI Kanthal-3 developed by the Bangladesh Agricultural Research Institute (BARI) derived from a wild accession found in Ramgarh of Chattogram Hiltracts of Bangladesh, provides fruits from September to June. This study aimed to generate a draft whole-genome sequence (WGS) of BARI Kanthal-3 to obtain molecular insights including genes associated with year-round fruiting trait of this important unique variety. The estimated genome size of BARI Kanthal-3 was 1.04-gigabase-pair (Gbp) with a heterozygosity rate of 1.62%. De novo assembly yielded a scaffolded 817.7 Mb genome while a reference-guided approach, yielded 843 Mb of genome sequence. The estimated GC content was 34.10%. Variant analysis revealed that BARI Kanthal-3 included 5.7 M (35%) and 10.4 M (65%) simple and heterozygous single nucleotide polymorphisms (SNPs), and about 90% of all these polymorphisms are in inter-genic regions. Through BUSCO assessment, 97.2% of the core genes were represented in the assembly with 1.3% and 1.5% either fragmented or missing, respectively. By comparing identified orthologous gene groups in BARI Kanthal-3 with five closely and one distantly related species of 10,092 common orthogroups were found across the genomes of the six species. The phylogenetic analysis of the shared orthogroups showed that A. heterophyllus was the closest species to BARI Kanthal-3 and orthogroups related to flowering time were found to be more highly prevalent in BARI Kanthal-3 compared to the other Arctocarpus spp. The findings of this study will help better understanding the evolution, domestication, phylogenetic relationships, year-round fruiting of this highly nutritious fruit crop as well as providing a resource for molecular breeding.

Improving Coconut Using Modern Breeding Technologies: Challenges and Opportunities

Coconut (Cocos nucifera L.) is a perennial palm with a wide range of distribution across tropical islands and coastlines. Multitude use of coconut by nature is important in the socio-economic fabric framework among rural smallholders in producing countries. It is a major source of income for 30 million farmers, while 60 million households rely on the coconut industry directly as farm workers and indirectly through the distribution, marketing, and processing of coconut and coconut-based products. Stagnant production, inadequate planting materials, the effects of climate change, as well as pests and diseases are among the key issues that need to be urgently addressed in the global coconut industry. Biotechnology has revolutionized conventional breeding approaches in creating genetic variation for trait improvement in a shorter period of time. In this review, we highlighted the challenges of current breeding strategies and the potential of biotechnological approaches, such as genomic-assisted breeding, next-generation sequencing (NGS)-based genotyping and genome editing tools in improving the coconut. Also, combining these technologies with high-throughput phenotyping approaches and speed breeding could speed up the rate of genetic gain in coconut breeding to solve problems that have been plaguing the industry for decades.

Assessment of functional relevance of genes associated with local temperature variables in Arabidopsis thaliana

How likely genetic variations associated with environment identified in silico from genome wide association study are functionally relevant to environmental adaptation has been largely unexplored experimentally. Here we analyzed top 29 genes containing polymorphisms associated with local temperature variation (minimum, mean, maximum) among 1129 natural accessions of Arabidopsis thaliana. Their loss-of-function mutants were assessed for growth and stress tolerance at five temperatures. Twenty genes were found to affect growth or tolerance at one or more of these temperatures. Significantly, genes associated with maximum temperature more likely have a detect a function at higher temperature, while genes associated with minimum temperature more likely have a function at lower temperature. In addition, gene variants are distributed more frequently at geographic locations where they apparently offer an enhanced growth or tolerance for five genes tested. Furthermore, variations in a large proportion of the in silico identified genes associated with minimum or mean-temperatures exhibited a significant association with growth phenotypes experimentally assessed at low temperature for a small set of natural accessions. This study shows a functional relevance of gene variants associated with environmental variables and supports the feasibility of the use of local temperature factors in investigating the genetic basis of temperature adaptation.

Temperature-mediated flower size plasticity in Arabidopsis

Organisms can rapidly mitigate the effects of environmental changes by changing their phenotypes, known as phenotypic plasticity. Yet, little is known about the temperature-mediated plasticity of traits that are directly linked to plant fitness such as flower size. We discovered substantial genetic variation in flower size plasticity to temperature both among selfing Arabidopsis thaliana and outcrossing A. arenosa individuals collected from a natural growth habitat. Genetic analysis using a panel of 290 A. thaliana accession and mutant lines revealed that MADS AFFECTING FLOWERING (MAF) 2-5 gene cluster, previously shown to regulate temperature-mediated flowering time, was associated to the flower size plasticity to temperature. Furthermore, our findings pointed that the control of plasticity differs from control of the trait itself. Altogether, our study advances the understanding of genetic and molecular factors underlying plasticity on fundamental fitness traits, such as flower size, in response to future climate scenarios.

Testing the association of relative growth rate and adaptation to climate across natural ecotypes of Arabidopsis

Ecophysiologists have reported a range of relationships, including intrinsic trade-offs across and within species between plant relative growth rate in high resource conditions (RGR) vs adaptation to tolerate cold or arid climates, arising from trait-based mechanisms. Few studies have considered ecotypes within a species, in which the lack of a trade-off would contribute to a wide species range and resilience to climate change. For 15 ecotypes of Arabidopsis thaliana in a common garden we tested for associations between RGR vs adaptation to cold or dry native climates and assessed hypotheses for its mediation by 15 functional traits. Ecotypes native to warmer, drier climates had higher leaf density, leaf mass per area, root mass fraction, nitrogen per leaf area and carbon isotope ratio, and lower osmotic potential at full turgor. Relative growth rate was statistically independent of the climate of the ecotype native range and of individual functional traits. The decoupling of RGR and cold or drought adaptation in Arabidopsis is consistent with multiple stress resistance and avoidance mechanisms for ecotypic climate adaptation and would contribute to the species' wide geographic range and resilience as the climate changes.

How Geography and Climate Shaped the Genomic Diversity of Italian Local Cattle and Sheep Breeds

Simple Summary

In this paper, we study the inter-relationships among geography, climate, and genetics in Italian local cattle and sheep breeds. In terms of genetic diversity, geography (latitude and longitude) appears to play a larger role in sheep (26.4%) than that in cattle (13.8%). Once geography is accounted for, 10.1% of cattle genomic diversity and 13.3% of that of sheep are attributable to climatic effects. Stronger geographic effects in sheep can be related to a combination of higher predomestication genetic variability together with biological and productive specializations. The climate alone seems to have had less impact on the current genetic diversity in both species even if climate and geography are greatly confounded. Results confirm that both species are the result of complex evolutionary histories triggered by interactions between human needs and environmental conditions.

Abstract

Understanding the relationships among geography, climate, and genetics is increasingly important for animal farming and breeding. In this study, we examine these inter-relationships in the context of local cattle and sheep breeds distributed along the Italian territory. To this aim, we used redundancy analysis on genomic data from previous projects combined with geographical coordinates and corresponding climatic data. The effect of geographic factors (latitude and longitude) was more important in sheep (26.4%) than that in cattle (13.8%). Once geography had been partialled out of analysis, 10.1% of cattle genomic diversity and 13.3% of that of sheep could be ascribed to climatic effects. Stronger geographic effects in sheep can be related to a combination of higher pre-domestication genetic variability together with biological and productive specificities. Climate alone seems to have had less impact on current genetic diversity in both species, even if climate and geography are greatly confounded. Results confirm that both species are the result of complex evolutionary histories triggered by interactions between human needs and environmental conditions.

Genome–Environment Associations, an Innovative Tool for Studying Heritable Evolutionary Adaptation in Orphan Crops and Wild Relatives

Leveraging innovative tools to speed up prebreeding and discovery of genotypic sources of adaptation from landraces, crop wild relatives, and orphan crops is a key prerequisite to accelerate genetic gain of abiotic stress tolerance in annual crops such as legumes and cereals, many of which are still orphan species despite advances in major row crops. Here, we review a novel, interdisciplinary approach to combine ecological climate data with evolutionary genomics under the paradigm of a new field of study: genome–environment associations (GEAs). We first exemplify how GEA utilizes in situ georeferencing from genotypically characterized, gene bank accessions to pinpoint genomic signatures of natural selection. We later discuss the necessity to update the current GEA models to predict both regional- and local- or micro-habitat–based adaptation with mechanistic ecophysiological climate indices and cutting-edge GWAS-type genetic association models. Furthermore, to account for polygenic evolutionary adaptation, we encourage the community to start gathering genomic estimated adaptive values (GEAVs) for genomic prediction (GP) and multi-dimensional machine learning (ML) models. The latter two should ideally be weighted by de novo GWAS-based GEA estimates and optimized for a scalable marker subset. We end the review by envisioning avenues to make adaptation inferences more robust through the merging of high-resolution data sources, such as environmental remote sensing and summary statistics of the genomic site frequency spectrum, with the epigenetic molecular functionality responsible for plastic inheritance in the wild. Ultimately, we believe that coupling evolutionary adaptive predictions with innovations in ecological genomics such as GEA will help capture hidden genetic adaptations to abiotic stresses based on crop germplasm resources to assist responses to climate change.

“I shall endeavor to find out how nature’s forces act upon one another, and in what manner the geographic environment exerts its influence on animals and plants. In short, I must find out about the harmony in nature” Alexander von Humboldt—Letter to Karl Freiesleben, June 1799.

A Perspective on Plant Phenomics: Coupling Deep Learning and Near-Infrared Spectroscopy

The trait-based approach in plant ecology aims at understanding and classifying the diversity of ecological strategies by comparing plant morphology and physiology across organisms. The major drawback of the approach is that the time and financial cost of measuring the traits on many individuals and environments can be prohibitive. We show that combining near-infrared spectroscopy (NIRS) with deep learning resolves this limitation by quickly, non-destructively, and accurately measuring a suite of traits, including plant morphology, chemistry, and metabolism. Such an approach also allows to position plants within the well-known CSR triangle that depicts the diversity of plant ecological strategies. The processing of NIRS through deep learning identifies the effect of growth conditions on trait values, an issue that plagues traditional statistical approaches. Together, the coupling of NIRS and deep learning is a promising high-throughput approach to capture a range of ecological information on plant diversity and functioning and can accelerate the creation of extensive trait databases.

Mass Spectrometry Metabolomics and Feature-Based Molecular Networking Reveals Population-Specific Chemistry in Some Species of the Sceletium Genus

The Sceletium genus has been of medicinal importance in southern Africa for millennia and Sceletium tortuosum (Aizoaceae), one of eight species in the genus has gained pharmaceutical importance as an anxiolytic and anti-depressant due to the presence of mesembrine alkaloids. S. tortuosum is used for the manufacture of herbal teas, dietary supplements and other phytopharmaceutical products. This study aimed to provide a metabolomic characterization of S. tortuosum and its sister species as these are not easy to distinguish using morphology alone. Plant samples were thus collected from various locations in the succulent Karoo (South Africa) and analyzed through liquid chromatography-mass spectrometry (LC-MS), using MS^E fragmentation as a putative tool for chemical identities. Metabolomics-based analyses in combination with molecular networking were able to distinguish between the four species of Sceletium based on the presence of 4-(3,4-dimethyoxyphenyl)-4-[2-acetylmethlamino)ethyl]cyclohexanone (m/z 334.2020; RT 6.60 min), mesembrine (m/z 290.1757; RT 5.10 min) and 4'-O-demethylmesembrenol (m/z 276.1597; RT 4.17 min). Metabolomic profiles varied according to the different localities and metabolites occurred at variable quantitative levels in Sceletium ecotypes. Molecular networking provided the added advantage of being able to observe mesembrine alkaloid isomers and coeluting metabolites (from the joubertiamine group) that were difficult to discern without this application. By combining high-throughput metabolomics together with global and feature based-molecular networking, a powerful metabolite profiling platform that is able to discern chemical patterns within and between populations was established. These techniques were able to reveal chemotaxonomic relationships and allowed for the discovery of chemical markers that may be used as part of monitoring protocols during the manufacture of phytopharmaceutical and dietary products based on Sceletium.

Into the range: a latitudinal gradient or a center-margins differentiation of ecological strategies in Arabidopsis thaliana?

BACKGROUND AND AIMS

Determining within-species large-scale variation in phenotypic traits is central to elucidate the drivers of species' ranges. Intraspecific comparisons offer the opportunity to understand how trade-offs and biogeographical history constrain adaptation to contrasted environmental conditions. Here we test whether functional traits, ecological strategies from the CSR scheme and phenotypic plasticity in response to abiotic stress vary along a latitudinal or a center- margins gradient within the native range of Arabidopsis thaliana.

METHODS

We experimentally examined the phenotypic outcomes of plant adaptation at the center and margins of its geographic range using 30 accessions from southern, central and northern Europe. We characterized the variation of traits related to stress tolerance, resource use, colonization ability, CSR strategy scores, survival and fecundity in response to high temperature (34 °C) or frost (- 6 °C), combined with a water deficit treatment.

KEY RESULTS

We found evidence for both a latitudinal and a center-margins differentiation for the traits under scrutiny. Age at maturity, leaf dry matter content, specific leaf area and leaf nitrogen content varied along a latitudinal gradient. Northern accessions presented a greater survival to stress than central and southern accessions. Leaf area, C-scores, R-scores and fruit number followed a center-margins differentiation. Central accessions displayed a higher phenotypic plasticity than northern and southern accessions for most studied traits.

CONCLUSIONS

Traits related to an acquisitive/conservative resource-use trade-off followed a latitudinal gradient. Traits associated with a competition/colonization trade-off differentiated along the historic colonization of the distribution range and then followed a center-margins differentiation. Our findings pinpoint the need to consider the joint effect of evolutionary history and environmental factors when examining phenotypic variation across the distribution range of a species.

Cold stress and freezing tolerance negatively affect the fitness of Arabidopsis thaliana accessions under field and controlled conditions

Higher acclimated freezing tolerance improved winter survival, but reduced reproductive fitness of Arabidopsis thaliana accessions under field and controlled conditions. Low temperature is one of the most important abiotic factors influencing plant fitness and geographical distribution. In addition, cold stress is known to influence crop yield and is therefore of great economic importance. Increased freezing tolerance can be acquired by the process of cold acclimation, but this may be associated with a fitness cost. To assess the influence of cold stress on the fitness of plants, long-term field trials over 5 years were performed with six natural accessions of Arabidopsis thaliana ranging from very tolerant to very sensitive to freezing. Fitness parameters, as seed yield and 1000 seed mass, were measured and correlation analyses with temperature and freezing tolerance data performed. The results were compared with fitness parameters from controlled chamber experiments over 3 years with application of cold priming and triggering conditions. Winter survival and seed yield per plant were positively correlated with temperature in field experiments. In addition, winter survival and 1000 seed mass were correlated with the cold-acclimated freezing tolerance of the selected Arabidopsis accessions. The results provide strong evidence for a trade-off between higher freezing tolerance and reproductive fitness in A. thaliana, which might have ecological impacts in the context of global warming.

Physical geography, isolation by distance and environmental variables shape genomic variation of wild barley (Hordeum vulgare L. ssp. spontaneum) in the Southern Levant

Determining the extent of genetic variation that reflects local adaptation in crop-wild relatives is of interest for the purpose of identifying useful genetic diversity for plant breeding. We investigated the association of genomic variation with geographical and environmental factors in wild barley (Hordeum vulgare L. ssp. spontaneum) populations of the Southern Levant using genotyping by sequencing (GBS) of 244 accessions in the Barley 1K+ collection. The inference of population structure resulted in four genetic clusters that corresponded to eco-geographical habitats and a significant association between lower gene flow rates and geographical barriers, e.g. the Judaean Mountains and the Sea of Galilee. Redundancy analysis (RDA) revealed that spatial autocorrelation explained 45% and environmental variables explained 15% of total genomic variation. Only 4.5% of genomic variation was solely attributed to environmental variation if the component confounded with spatial autocorrelation was excluded. A synthetic environmental variable combining latitude, solar radiation, and accumulated precipitation explained the highest proportion of genomic variation (3.9%). When conditioned on population structure, soil water capacity was the most important environmental variable explaining 1.18% of genomic variation. Genome scans with outlier analysis and genome-environment association studies were conducted to identify adaptation signatures. RDA and outlier methods jointly detected selection signatures in the pericentromeric regions, which have reduced recombination, of the chromosomes 3H, 4H, and 5H. However, selection signatures mostly disappeared after correction for population structure. In conclusion, adaptation to the highly diverse environments of the Southern Levant over short geographical ranges had a limited effect on the genomic diversity of wild barley. This highlighted the importance of nonselective forces in genetic differentiation.

Entailing the Next-Generation Sequencing and Metabolome for Sustainable Agriculture by Improving Plant Tolerance

Crop production is a serious challenge to provide food for the 10 billion individuals forecasted to live across the globe in 2050. The scientists' emphasize establishing an equilibrium among diversity and quality of crops by enhancing yield to fulfill the increasing demand for food supply sustainably. The exploitation of genetic resources using genomics and metabolomics strategies can help generate resilient plants against stressors in the future. The innovation of the next-generation sequencing (NGS) strategies laid the foundation to unveil various plants' genetic potential and help us to understand the domestication process to unmask the genetic potential among wild-type plants to utilize for crop improvement. Nowadays, NGS is generating massive genomic resources using wild-type and domesticated plants grown under normal and harsh environments to explore the stress regulatory factors and determine the key metabolites. Improved food nutritional value is also the key to eradicating malnutrition problems around the globe, which could be attained by employing the knowledge gained through NGS and metabolomics to achieve suitability in crop yield. Advanced technologies can further enhance our understanding in defining the strategy to obtain a specific phenotype of a crop. Integration among bioinformatic tools and molecular techniques, such as marker-assisted, QTLs mapping, creation of reference genome, de novo genome assembly, pan- and/or super-pan-genomes, etc., will boost breeding programs. The current article provides sequential progress in NGS technologies, a broad application of NGS, enhancement of genetic manipulation resources, and understanding the crop response to stress by producing plant metabolites. The NGS and metabolomics utilization in generating stress-tolerant plants/crops without deteriorating a natural ecosystem is considered a sustainable way to improve agriculture production. This highlighted knowledge also provides useful research that explores the suitable resources for agriculture sustainability.

Selective Sweeps and Polygenic Adaptation Drive Local Adaptation along Moisture and Temperature Gradients in Natural Populations of Coast Redwood and Giant Sequoia

Dissecting the genomic basis of local adaptation is a major goal in evolutionary biology and conservation science. Rapid changes in the climate pose significant challenges to the survival of natural populations, and the genomic basis of long-generation plant species is still poorly understood. Here, we investigated genome-wide climate adaptation in giant sequoia and coast redwood, two iconic and ecologically important tree species. We used a combination of univariate and multivariate genotype-environment association methods and a selective sweep analysis using non-overlapping sliding windows. We identified genomic regions of potential adaptive importance, showing strong associations to moisture variables and mean annual temperature. Our results found a complex architecture of climate adaptation in the species, with genomic regions showing signatures of selective sweeps, polygenic adaptation, or a combination of both, suggesting recent or ongoing climate adaptation along moisture and temperature gradients in giant sequoia and coast redwood. The results of this study provide a first step toward identifying genomic regions of adaptive significance in the species and will provide information to guide management and conservation strategies that seek to maximize adaptive potential in the face of climate change.

Genome-Wide SNPs Provide Insights on the Cryptic Genetic Structure and Signatures of Climate Adaption in Amorphophallus albus Germplasms

Domesticated species represent unique systems in which the evolutionary genomic consequences of intensive selective breeding and adaptation can be thoroughly investigated. Amorphophallus albus occurs naturally and is in cultivation throughout the downstream region of the Jinshajiang River in Southwest China. This species is characterised by high konjac glucomannan content, and has been cultivated in China for nearly 2,000 years. To study genetic differentiation and local adaption of A. albus, we sampled 13 distinct local cultivated populations of this species. Restriction site-associated DNA sequencing was conducted with 87 samples, resulting in 24,225 SNPs. The population structure analyses suggest two main genetic groups: one in the relatively upstream region, and one downstream. We found evidence of additional sub-structure within the upstream group, demonstrating the statistical power of genomic SNPs in discovering subtle genetic structure. The environmental and geographic factors were all identified as significant in shaping the genetic differentiation of this species. Notably, the proportion of environmental factors was larger than geographic factors in influencing the population genetic patterns of A. albus. We also discovered loci that were associated with local adaptation. These findings will help us understand the genetic differentiation of this newly domesticated species, thereby informing future breeding programs of A. albus.

Geonomics: forward-time, spatially explicit, and arbitrarily complex landscape genomic simulations

Understanding the drivers of spatial patterns of genomic diversity has emerged as a major goal of evolutionary genetics. The flexibility of forward-time simulation makes it especially valuable for these efforts, allowing for the simulation of arbitrarily complex scenarios in a way that mimics how real populations evolve. Here, we present Geonomics, a Python package for performing complex, spatially explicit, landscape genomic simulations with full spatial pedigrees that dramatically reduces user workload yet remains customizable and extensible because it is embedded within a popular, general-purpose language. We show that Geonomics results are consistent with expectations for a variety of validation tests based on classic models in population genetics and then demonstrate its utility and flexibility with a trio of more complex simulation scenarios that feature polygenic selection, selection on multiple traits, simulation on complex landscapes, and nonstationary environmental change. We then discuss runtime, which is primarily sensitive to landscape raster size, memory usage, which is primarily sensitive to maximum population size and recombination rate, and other caveats related to the model’s methods for approximating recombination and movement. Taken together, our tests and demonstrations show that Geonomics provides an efficient and robust platform for population genomic simulations that capture complex spatial and evolutionary dynamics.

Harnessing Crop Wild Diversity for Climate Change Adaptation

Warming and drought are reducing global crop production with a potential to substantially worsen global malnutrition. As with the green revolution in the last century, plant genetics may offer concrete opportunities to increase yield and crop adaptability. However, the rate at which the threat is happening requires powering new strategies in order to meet the global food demand. In this review, we highlight major recent 'big data' developments from both empirical and theoretical genomics that may speed up the identification, conservation, and breeding of exotic and elite crop varieties with the potential to feed humans. We first emphasize the major bottlenecks to capture and utilize novel sources of variation in abiotic stress (i.e., heat and drought) tolerance. We argue that adaptation of crop wild relatives to dry environments could be informative on how plant phenotypes may react to a drier climate because natural selection has already tested more options than humans ever will. Because isolated pockets of cryptic diversity may still persist in remote semi-arid regions, we encourage new habitat-based population-guided collections for genebanks. We continue discussing how to systematically study abiotic stress tolerance in these crop collections of wild and landraces using geo-referencing and extensive environmental data. By uncovering the genes that underlie the tolerance adaptive trait, natural variation has the potential to be introgressed into elite cultivars. However, unlocking adaptive genetic variation hidden in related wild species and early landraces remains a major challenge for complex traits that, as abiotic stress tolerance, are polygenic (i.e., regulated by many low-effect genes). Therefore, we finish prospecting modern analytical approaches that will serve to overcome this issue. Concretely, genomic prediction, machine learning, and multi-trait gene editing, all offer innovative alternatives to speed up more accurate pre- and breeding efforts toward the increase in crop adaptability and yield, while matching future global food demands in the face of increased heat and drought. In order for these 'big data' approaches to succeed, we advocate for a trans-disciplinary approach with open-source data and long-term funding. The recent developments and perspectives discussed throughout this review ultimately aim to contribute to increased crop adaptability and yield in the face of heat waves and drought events.

Advancing crop genomics from lab to field

Crop genomics remains a key element in ensuring scientific progress to secure global food security. It has been two decades since the sequence of the first plant genome, that of Arabidopsis thaliana, was released, and soon after that the draft sequencing of the rice genome was completed. Since then, the genomes of more than 100 crops have been sequenced, plant genome research has expanded across multiple fronts and the next few years promise to bring further advances spurred by the advent of new technologies and approaches. We are likely to see continued innovations in crop genome sequencing, genetic mapping and the acquisition of multiple levels of biological data. There will be exciting opportunities to integrate genome-scale information across multiple scales of biological organization, leading to advances in our mechanistic understanding of crop biological processes, which will, in turn, provide greater impetus for translation of laboratory results to the field.

Developmental and biophysical determinants of grass leaf size worldwide

One of the most notable ecological trends-described more than 2,300  years ago by Theophrastus-is the association of small leaves with dry and cold climates, which has recently been recognized for eudicotyledonous plants at a global scale^1-3. For eudicotyledons, this pattern has been attributed to the fact that small leaves have a thinner boundary layer that helps to avoid extreme leaf temperatures⁴ and their leaf development results in vein traits that improve water transport under cold or dry climates^5,6. However, the global distribution of leaf size and its adaptive basis have not been tested in the grasses, which represent a diverse lineage that is distinct in leaf morphology and that contributes 33% of terrestrial primary productivity (including the bulk of crop production)⁷. Here we demonstrate that grasses have shorter and narrower leaves under colder and drier climates worldwide. We show that small grass leaves have thermal advantages and vein development that contrast with those of eudicotyledons, but that also explain the abundance of small leaves in cold and dry climates. The worldwide distribution of leaf size in grasses exemplifies how biophysical and developmental processes result in convergence across major lineages in adaptation to climate globally, and highlights the importance of leaf size and venation architecture for grass performance in past, present and future ecosystems.

Connecting tree-ring phenotypes, genetic associations and transcriptomics to decipher the genomic architecture of drought adaptation in a widespread conifer

As boreal forests face significant threats from climate change, understanding evolutionary trajectories of coniferous species has become fundamental to adapting management and conservation to a drying climate. We examined the genomic architecture underlying adaptive variation related to drought tolerance in 43 populations of a widespread boreal conifer, white spruce (Piceaglauca [Moench] Voss), by combining genotype–environment associations, genotype–phenotype associations, and transcriptomics. Adaptive genetic variation was identified by correlating allele frequencies for 6,153 single nucleotide polymorphisms from 2,606 candidate genes with temperature, precipitation and aridity gradients, and testing for significant associations between genotypes and 11 dendrometric and drought‐related traits (i.e., anatomical, growth response and climate‐sensitivity traits) using a polygenic model. We identified a set of 285 genes significantly associated with a climatic factor or a phenotypic trait, including 110 that were differentially expressed in response to drought under greenhouse‐controlled conditions. The interlinked phenotype–genotype–environment network revealed eight high‐confidence genes involved in white spruce adaptation to drought, of which four were drought‐responsive in the expression analysis. Our findings represent a significant step toward the characterization of the genomic basis of drought tolerance and adaptation to climate in conifers, which is essential to enable the establishment of resilient forests in view of new climate conditions.

see also the Perspective by Lars Opgenoorth and Christian Rellstab

Adaptive genetic potential and plasticity of trait variation in the foundation prairie grass Andropogon gerardii across the US Great Plains' climate gradient: Implications for climate change and restoration

Plant response to climate depends on a species' adaptive potential. To address this, we used reciprocal gardens to detect genetic and environmental plasticity effects on phenotypic variation and combined with genetic analyses. Four reciprocal garden sites were planted with three regional ecotypes of Andropogon gerardii, a dominant Great Plains prairie grass, using dry, mesic, and wet ecotypes originating from western KS to Illinois that span 500-1,200 mm rainfall/year. We aimed to answer: (a) What is the relative role of genetic constraints and phenotypic plasticity in controlling phenotypes? (b) When planted in the homesite, is there a trait syndrome for each ecotype? (c) How are genotypes and phenotypes structured by climate? and (d) What are implications of these results for response to climate change and use of ecotypes for restoration? Surprisingly, we did not detect consistent local adaptation. Rather, we detected co-gradient variation primarily for most vegetative responses. All ecotypes were stunted in western KS. Eastward, the wet ecotype was increasingly robust relative to other ecotypes. In contrast, fitness showed evidence for local adaptation in wet and dry ecotypes with wet and mesic ecotypes producing little seed in western KS. Earlier flowering time in the dry ecotype suggests adaptation to end of season drought. Considering ecotype traits in homesite, the dry ecotype was characterized by reduced canopy area and diameter, short plants, and low vegetative biomass and putatively adapted to water limitation. The wet ecotype was robust, tall with high biomass, and wide leaves putatively adapted for the highly competitive, light-limited Eastern Great Plains. Ecotype differentiation was supported by random forest classification and PCA. We detected genetic differentiation and outlier genes associated with primarily precipitation. We identified candidate gene GA1 for which allele frequency associated with plant height. Sourcing of climate adapted ecotypes should be considered for restoration.

Association of genetic and climatic variability in giant sequoia, Sequoiadendron giganteum, reveals signatures of local adaptation along moisture-related gradients

Uncovering the genetic basis of local adaptation is a major goal of evolutionary biology and conservation science alike. In an era of climate change, an understanding of how environmental factors shape adaptive diversity is crucial to predicting species response and directing management. Here, we investigate patterns of genomic variation in giant sequoia, an iconic and ecologically important tree species, using 1,364 bi-allelic single nucleotide polymorphisms (SNPs). We use an F _ST outlier test and two genotype-environment association methods, latent factor mixed models (LFMMs) and redundancy analysis (RDA), to detect complex signatures of local adaptation. Results indicate 79 genomic regions of potential adaptive importance, with limited overlap between the detection methods. Of the 58 loci detected by LFMM, 51 showed strong correlations to a precipitation-driven composite variable and seven to a temperature-related variable. RDA revealed 24 outlier loci with association to climate variables, all of which showed strongest relationship to summer precipitation. Nine candidate loci were indicated by two methods. After correcting for geographic distance, RDA models using climate predictors accounted for 49% of the explained variance and showed significant correlations between SNPs and climatic factors. Here, we present evidence of local adaptation in giant sequoia along gradients of precipitation and provide a first step toward identifying genomic regions of adaptive significance. The results of this study will provide information to guide management strategies that seek to maximize adaptive potential in the face of climate change.

Competition × drought interactions change phenotypic plasticity and the direction of selection on Arabidopsis traits

Populations often exhibit genetic diversity in traits involved in responses to abiotic stressors, but what maintains this diversity is unclear. Arabidopsis thaliana exhibits high within-population variation in drought response. One hypothesis is that competition, varying at small scales, promotes diversity in resource use strategies. However, little is known about natural variation in competition effects on Arabidopsis physiology. We imposed drought and competition treatments on diverse genotypes. We measured resource economics traits, physiology, and fitness to characterize plasticity and selection in response to treatments. Plastic responses to competition differed depending on moisture availability. We observed genotype-drought-competition interactions for relative fitness: competition had little effect on relative fitness under well-watered conditions, whereas competition caused rank changes in fitness under drought. Early flowering was always selected. Higher δ¹³ C was selected only in the harshest treatment (drought and competition). Competitive context significantly changed the direction of selection on aboveground biomass and inflorescence height in well-watered environments. Our results highlight how local biotic conditions modify abiotic selection, in some cases promoting diversity in abiotic stress response. The ability of populations to adapt to environmental change may thus depend on small-scale biotic heterogeneity.

Change in sexual signalling traits outruns morphological divergence across an ecological gradient in the post-glacial radiation of the songbird genus Junco

The relative roles of natural and sexual selection in promoting evolutionary lineage divergence remains controversial and difficult to assess in natural systems. Local adaptation through natural selection is known to play a central role in promoting evolutionary divergence, yet secondary sexual traits can vary widely among species in recent radiations, suggesting that sexual selection may also be important in the early stages of speciation. Here, we compare rates of divergence in ecologically relevant traits (morphology) and sexually selected signalling traits (coloration) relative to neutral structure in genome-wide molecular markers and examine patterns of variation in sexual dichromatism to explore the roles of natural and sexual selection in the diversification of the songbird genus Junco (Aves: Passerellidae). Juncos include divergent lineages in Central America and several dark-eyed junco (J. hyemalis) lineages that diversified recently as the group recolonized North America following the last glacial maximum (ca. 18,000 years ago). We found an accelerated rate of divergence in sexually selected characters relative to ecologically relevant traits. Moreover, sexual dichromatism measurements suggested a positive relationship between the degree of colour divergence and the strength of sexual selection when controlling for neutral genetic distance. We also found a positive correlation between dichromatism and latitude, which coincides with the geographic axis of decreasing lineage age in juncos but also with a steep ecological gradient. Finally, we found significant associations between genome-wide variants linked to functional genes and proxies of both sexual and natural selection. These results suggest that the joint effects of sexual and ecological selection have played a prominent role in the junco radiation.

Ecological, genetic and evolutionary drivers of regional genetic differentiation in Arabidopsis thaliana

BACKGROUND

Disentangling the drivers of genetic differentiation is one of the cornerstones in evolution. This is because genetic diversity, and the way in which it is partitioned within and among populations across space, is an important asset for the ability of populations to adapt and persist in changing environments. We tested three major hypotheses accounting for genetic differentiation-isolation-by-distance (IBD), isolation-by-environment (IBE) and isolation-by-resistance (IBR)-in the annual plant Arabidopsis thaliana across the Iberian Peninsula, the region with the largest genomic diversity. To that end, we sampled, genotyped with genome-wide SNPs, and analyzed 1772 individuals from 278 populations distributed across the Iberian Peninsula.

RESULTS

IBD, and to a lesser extent IBE, were the most important drivers of genetic differentiation in A. thaliana. In other words, dispersal limitation, genetic drift, and to a lesser extent local adaptation to environmental gradients, accounted for the within- and among-population distribution of genetic diversity. Analyses applied to the four Iberian genetic clusters, which represent the joint outcome of the long demographic and adaptive history of the species in the region, showed similar results except for one cluster, in which IBR (a function of landscape heterogeneity) was the most important driver of genetic differentiation. Using spatial hierarchical Bayesian models, we found that precipitation seasonality and topsoil pH chiefly accounted for the geographic distribution of genetic diversity in Iberian A. thaliana.

CONCLUSIONS

Overall, the interplay between the influence of precipitation seasonality on genetic diversity and the effect of restricted dispersal and genetic drift on genetic differentiation emerges as the major forces underlying the evolutionary trajectory of Iberian A. thaliana.

Regional differences in the abiotic environment contribute to genomic divergence within a wild tomato species

The wild currant tomato Solanum pimpinellifolium inhabits a wide range of abiotic habitats across its native range of Ecuador and Peru. Although it has served as a key genetic resource for the improvement of domestic cultivars, little is known about the genetic basis of traits underlying local adaptation in this species, nor what abiotic variables are most important for driving differentiation. Here we use redundancy analysis (RDA) and other multivariate statistical methods (structural equation modelling [SEM] and generalized dissimilarity modelling [GDM]) to quantify the relationship of genomic variation (6,830 single nucleotide polymorphisms [SNPs]) with climate and geography, among 140 wild accessions. RDA, SEM and GDM each identified environment as explaining more genomic variation than geography, suggesting that local adaptation to heterogeneous abiotic habitats may be an important source of genetic diversity in this species. Environmental factors describing temporal variation in precipitation and evaporative demand explained the most SNP variation among accessions, indicating that these forces may represent key selective agents. Lastly, by studying how SNP-environment associations vary throughout the genome (44,064 SNPs), we mapped the location and investigated the functions of loci putatively contributing to climatic adaptations. Together, our findings indicate an important role for selection imposed by the abiotic environment in driving genomic differentiation between populations.

Genomic history and ecology of the geographic spread of rice

Rice (Oryza sativa) is one of the world's most important food crops, and is comprised largely of japonica and indica subspecies. Here, we reconstruct the history of rice dispersal in Asia using whole-genome sequences of more than 1,400 landraces, coupled with geographic, environmental, archaeobotanical and paleoclimate data. Originating around 9,000 yr ago in the Yangtze Valley, rice diversified into temperate and tropical japonica rice during a global cooling event about 4,200 yr ago. Soon after, tropical japonica rice reached Southeast Asia, where it rapidly diversified, starting about 2,500 yr BP. The history of indica rice dispersal appears more complicated, moving into China around 2,000 yr BP. We also identify extrinsic factors that influence genome diversity, with temperature being a leading abiotic factor. Reconstructing the dispersal history of rice and its climatic correlates may help identify genetic adaptations associated with the spread of a key domesticated species.

Imputation of 3 million SNPs in the Arabidopsis regional mapping population

Natural variation has become a prime resource to identify genetic variants that contribute to phenotypic variation. The regional mapping (RegMap) population is one of the most important populations for studying natural variation in Arabidopsis thaliana, and has been used in a large number of association studies and in studies on climatic adaptation. However, only 413 RegMap accessions have been completely sequenced, as part of the 1001 Genomes (1001G) Project, while the remaining 894 accessions have only been genotyped with the Affymetrix 250k chip. As a consequence, most association studies involving the RegMap are either restricted to the sequenced accessions, reducing power, or rely on a limited set of SNPs. Here we impute millions of SNPs to the 894 accessions that are exclusive to the RegMap, using the 1135 accessions of the 1001G Project as the reference panel. We assess imputation accuracy using a novel cross-validation scheme, which we show provides a more reliable measure of accuracy than existing methods. After filtering out low accuracy SNPs, we obtain high-quality genotypic information for 2029 accessions and 3 million markers. To illustrate the benefits of these imputed data, we reconducted genome-wide association studies on five stress-related traits and could identify novel candidate genes.

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

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

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis-regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low-frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis-regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic-acid pathway to local adaptation.

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis-regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low-frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis-regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic-acid pathway to local adaptation.

Natural variation on whole-plant form in the wild is influenced by multivariate soil nutrient characteristics: natural selection acts on root traits

PREMISE

In the complex soil nutrient environments of wild populations of annual plants, in general, low nutrient availability restricts growth and alters root-shoot relationships. However, our knowledge of natural selection on roots in field settings is limited. We sought to determine whether selection acts directly on root traits and to identify which components of the soil environment were potential agents of selection.

METHODS

We studied wild native populations of Arabidopsis thaliana across 4 years, measuring aboveground and belowground traits and analyzing soil nutrients. Using multivariate methods, we examined patterns of natural selection and identified soil attributes that contributed to whole-plant form. In a common garden experiment at two field sites with contrasting soil texture, we examined patterns of selection on root and shoot traits.

RESULTS

In wild populations, we uncovered selection for above- and belowground size and architectural traits. We detected variation through time and identified soil components that influenced fruit production. In the garden experiment, we detected a distinct positive selection for total root length at the site with greater water-holding capacity and negative selection for measures of root architecture at the field site with reduced nutrient availability and water holding capacity.

CONCLUSIONS

Patterns of natural selection on belowground traits varied through time, across field sites and experimental gardens. Simultaneous investigations of above- and belowground traits reveal trait functional relationships on which natural selection can act, highlighting the influence of edaphic features on evolutionary processes in wild annual plant populations.

Effects of two centuries of global environmental variation on phenology and physiology of Arabidopsis thaliana

Intraspecific trait variation is caused by genetic and plastic responses to environment. This intraspecific diversity is captured in immense natural history collections, giving us a window into trait variation across continents and through centuries of environmental shifts. Here we tested if hypotheses based on life history and the leaf economics spectrum explain intraspecific trait changes across global spatiotemporal environmental gradients. We measured phenotypes on a 216-year time series of Arabidopsis thaliana accessions from across its native range and applied spatially varying coefficient models to quantify region-specific trends in trait coordination and trait responses to climate gradients. All traits exhibited significant change across space or through time. For example, δ¹⁵ N decreased over time across much of the range and leaf C:N increased, consistent with predictions based on anthropogenic changes in land use and atmosphere. Plants were collected later in the growing season in more recent years in many regions, possibly because populations shifted toward more spring germination and summer flowering as opposed to fall germination and spring flowering. When climate variables were considered, collection dates were earlier in warmer years, while summer rainfall had opposing associations with collection date depending on regions. There was only a modest correlation among traits, indicating a lack of a single life history/physiology axis. Nevertheless, leaf C:N was low for summer- versus spring-collected plants, consistent with a life history-physiology axis from slow-growing winter annuals to fast-growing spring/summer annuals. Regional heterogeneity in phenotype trends indicates complex responses to spatiotemporal environmental gradients potentially due to geographic genetic variation and climate interactions with other aspects of environment. Our study demonstrates how natural history collections can be used to broadly characterize trait responses to environment, revealing heterogeneity in response to anthropogenic change.

Adaptation to Plant Communities across the Genome of Arabidopsis thaliana

Despite the importance of plant-plant interactions on plant community dynamics and crop yield, our understanding of the adaptive genetics underlying these interactions is still limited and deserves to be investigated in the context of complex and diffuse interactions occurring in plant assemblages. Here, based on 145 natural populations of Arabidopsis thaliana located in south-west of France and characterized for plant communities, we conducted a Genome-Environment Association analysis to finely map adaptive genomic regions of A. thaliana associated with plant community descriptors. To control for correlated abiotic environment effects, we also characterized the populations for a set of biologically meaningful climate and soil variables. A nonnegligible fraction of top single nucleotide polymorphisms was associated with both plant community descriptors and abiotic variables, highlighting the importance of considering the actual abiotic drivers of plant communities to disentangle genetic variants for biotic adaptation from genetic variants for abiotic adaptation. The adaptive loci associated with species abundance were highly dependent on the identity of the neighboring species suggesting a high degree of biotic specialization of A. thaliana to members of its plant interaction network. Moreover, the identification of adaptive loci associated with α-diversity and composition of plant communities supports the ability of A. thaliana to interact simultaneously with multiple plant neighbors, which in turn can help to understand the role of community-wide selection. Altogether, our study highlights that dissecting the genetic basis underlying plant-plant interactions at a regional scale while controlling for abiotic confounding factors can help understanding the adaptive mechanisms modulating natural plant assemblages.

Predicting Adaptive Genetic Variation of Loblolly Pine (Pinus taeda L.) Populations Under Projected Future Climates Based on Multivariate Models

Greenhouse gas emission and global warming are likely to cause rapid climate change within the natural range of loblolly pine over the next few decades, thus bringing uncertainty to their adaptation to the environment. Here, we studied adaptive genetic variation of loblolly pine and correlated genetic variation with bioclimatic variables using multivariate modeling methods—Redundancy Analysis, Generalized Dissimilarity Modeling, and Gradient Forests. Studied trees (N = 299) were originally sampled from their native range across eight states on the east side of the Mississippi River. Genetic variation was calculated using a total of 44,317 single-nucleotide polymorphisms acquired by exome target sequencing. The fitted models were used to predict the adaptive genetic variation on a large spatial and temporal scale. We observed east-to-west spatial genetic variation across the range, which presented evidence of isolation by distance. Different key factors drive adaptation of loblolly pine from different geographical regions. Trees residing near the northeastern edge of the range, spanning across Delaware and Maryland and mountainous areas of  Virginia, North Carolina, South Carolina, and northern Georgia, were identified to be most likely impacted by climate change based on the large difference in genetic composition under current and future climate conditions. This study provides new perspectives on adaptive genetic variation of loblolly pine in response to different climate scenarios, and the results can be used to target particular populations while developing adaptive forest management guidelines.

Divergence in drought-response traits between sympatric species of Mimulus

Differential adaptation to local environmental conditions is thought to be an important driver of speciation. Plants, whose sedentary lifestyle necessitates fine-tuned adaptation to edaphic conditions such as water availability, are often distributed based on these conditions. Populations occupying water-limited habitats may employ a variety of strategies, involving numerous phenotypes, to prevent and withstand desiccation. In sympatry, two closely related Mimulus species-M. guttatus and M. nasutus-occupy distinct microhabitats that differ in seasonal water availability. In a common garden experiment, we characterized natural variation within and between sympatric M. guttatus and M. nasutus in the ability to successfully set seed under well-watered and drought conditions. We also measured key phenotypes for drought adaptation, including developmental timing, plant size, flower size, and stomatal density. Consistent with their microhabitat associations in nature, M. nasutus set seed much more successfully than M. guttatus under water-limited conditions. This divergence in reproductive output under drought was due to differences in mortality after the onset of flowering, with M. nasutus surviving at a much higher rate than M. guttatus. Higher seed set in M. nasutus was mediated, at least in part, by a plastic increase in the rate of late-stage development (i.e., fruit maturation), consistent with the ability of this species to inhabit more ephemeral habitats in the field. Our results suggest adaptation to water availability may be an important factor in species maintenance of these Mimulus taxa in sympatry.

Genomic signatures of seed mass adaptation to global precipitation gradients in sorghum

Seed mass is a key component of adaptation in plants and a determinant of yield in crops. The climatic drivers and genomic basis of seed mass variation remain poorly understood. In the cereal crop Sorghum bicolor, globally-distributed landraces harbor abundant variation in seed mass, which is associated with precipitation in their agroclimatic zones of origin. This study aimed to test the hypothesis that diversifying selection across precipitation gradients, acting on ancestral cereal grain size regulators, underlies seed mass variation in global sorghum germplasm. We tested this hypothesis in a set of 1901 georeferenced and genotyped sorghum landraces, 100-seed mass from common gardens, and bioclimatic precipitation variables. As predicted, 100-seed mass in global germplasm varies significantly among botanical races and is correlated to proxies of the precipitation gradients. With general and mixed linear model genome-wide associations, we identified 29 and 56 of 100 a priori candidate seed size genes with polymorphisms in the top 1% of seed mass association, respectively. Eleven of these genes harbor polymorphisms associated with the precipitation gradient, including orthologs of genes that regulate seed size in other cereals. With FarmCPU, 13 significant SNPs were identified, including one at an a priori candidate gene. Finally, we identified eleven colocalized outlier SNPs associated with seed mass and precipitation that also carry signatures of selection based on F_ST scans and PCAdapt, which represents a significant enrichment. Our findings suggest that seed mass in sorghum was shaped by diversifying selection on drought stress, and can inform genomics-enabled breeding for climate-resilient cereals.