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.

Natural variation identifies new effectors of water-use efficiency in Arabidopsis.

Water-use efficiency (WUE) is the ratio of biomass produced per unit of water consumed; thus, it can be altered by genetic factors that affect either side of the ratio. In the present study, we exploited natural variation for WUE to discover loci affecting either biomass accumulation or water use as factors affecting WUE. Genome-wide association studies (GWAS) using integrated WUE measured through carbon isotope discrimination (δ13C) of Arabidopsis thaliana accessions identified genomic regions associated with WUE. Reverse genetic analysis of 70 candidate genes selected based on the GWAS results and transcriptome data identified 25 genes affecting WUE as measured by gravimetric and δ13C analyses. Mutants of four genes had higher WUE than wild type, while mutants of the other 21 genes had lower WUE. The differences in WUE were caused by either altered biomass or water consumption (or both). Stomatal density (SD) was not a primary cause of altered WUE in these mutants. Leaf surface temperatures indicated that transpiration differed for mutants of 16 genes, but generally biomass accumulation had a greater effect on WUE. The genes we identified are involved in diverse cellular processes, including hormone and calcium signaling, meristematic activity, photosynthesis, flowering time, leaf/vasculature development, and cell wall composition; however, none of them had been previously linked to WUE. Thus, our study successfully identified effectors of WUE that can be used to understand the genetic basis of WUE and improve crop productivity.

Vegetative phase change causes age-dependent changes in phenotypic plasticity.

Phenotypic plasticity allows organisms to optimize traits for their environment. As organisms age, they experience diverse environments that benefit from varying degrees of phenotypic plasticity. Developmental transitions can control these age-dependent changes in plasticity, and as such, the timing of these transitions can determine when plasticity changes in an organism. Here, we investigate how the transition from juvenile-to adult-vegetative development known as vegetative phase change (VPC) contributes to age-dependent changes in phenotypic plasticity and how the timing of this transition responds to environment using both natural accessions and mutant lines in the model plant Arabidopsis thaliana. We found that the adult phase of vegetative development has greater plasticity in leaf morphology than the juvenile phase and confirmed that this difference in plasticity is caused by VPC using mutant lines. Furthermore, we found that the timing of VPC, and therefore the time when increased plasticity is acquired, varies significantly across genotypes and environments. The consistent age-dependent changes in plasticity caused by VPC suggest that VPC may be adaptive. This genetic and environmental variation in the timing of VPC indicates the potential for population-level adaptive evolution of VPC.

Genomics of sorghum local adaptation to a parasitic plant.

Host-parasite coevolution can maintain high levels of genetic diversity in traits involved in species interactions. In many systems, host traits exploited by parasites are constrained by use in other functions, leading to complex selective pressures across space and time. Here, we study genome-wide variation in the staple crop Sorghum bicolor (L.) Moench and its association with the parasitic weed Striga hermonthica (Delile) Benth., a major constraint to food security in Africa. We hypothesize that geographic selection mosaics across gradients of parasite occurrence maintain genetic diversity in sorghum landrace resistance. Suggesting a role in local adaptation to parasite pressure, multiple independent loss-of-function alleles at sorghum LOW GERMINATION STIMULANT 1 (LGS1) are broadly distributed among African landraces and geographically associated with S. hermonthica occurrence. However, low frequency of these alleles within S. hermonthica-prone regions and their absence elsewhere implicate potential trade-offs restricting their fixation. LGS1 is thought to cause resistance by changing stereochemistry of strigolactones, hormones that control plant architecture and below-ground signaling to mycorrhizae and are required to stimulate parasite germination. Consistent with trade-offs, we find signatures of balancing selection surrounding LGS1 and other candidates from analysis of genome-wide associations with parasite distribution. Experiments with CRISPR-Cas9-edited sorghum further indicate that the benefit of LGS1-mediated resistance strongly depends on parasite genotype and abiotic environment and comes at the cost of reduced photosystem gene expression. Our study demonstrates long-term maintenance of diversity in host resistance genes across smallholder agroecosystems, providing a valuable comparison to both industrial farming systems and natural communities.

Diversity and extinction risk are inversely related at a global scale.

Increases in biodiversity often lead to greater, and less variable, levels of ecosystem functioning. However, whether species are less likely to go extinct in more diverse ecosystems is unclear. We use comprehensive estimates of avian taxonomic, phylogenetic and functional diversity to characterise the global relationship between multiple dimensions of diversity and extinction risk in birds, focusing on contemporary threat status and latent extinction risk. We find that more diverse assemblages have lower mean IUCN threat status despite being composed of species with attributes that make them more vulnerable to extinction, such as large body size or small range size. Indeed, the reduction in current threat status associated with greater diversity far outweighs the increased risk associated with the accumulation of extinction-prone species in more diverse assemblages. Our results suggest that high diversity reduces extinction risk, and that species conservation targets may therefore best be achieved by maintaining high levels of overall biodiversity in natural ecosystems.

Host genomic influence on bacterial composition in the switchgrass rhizosphere.

Host genetic variation can shape the diversity and composition of associated microbiomes, which may reciprocally influence host traits and performance. While the genetic basis of phenotypic diversity of plant populations in nature has been studied, comparatively little research has investigated the genetics of host effects on their associated microbiomes. Switchgrass (Panicum virgatum) is a highly outcrossing, perennial, grass species with substantial locally adaptive diversity across its native North American range. Here, we compared 383 switchgrass accessions in a common garden to determine the host genotypic influence on rhizosphere bacterial composition. We hypothesized that the composition and diversity of rhizosphere bacterial assemblages would differentiate due to genotypic differences between hosts (potentially due to root phenotypes and associated life history variation). We observed higher alpha diversity of bacteria associated with upland ecotypes and tetraploids, compared to lowland ecotypes and octoploids, respectively. Alpha diversity correlated negatively with flowering time and plant height, indicating that bacterial composition varies along switchgrass life history axes. Narrow-sense heritability (h2 ) of the relative abundance of 21 core bacterial families was observed. Overall compositional differences among tetraploids, due to genetic variation, supports widespread genotypic influence on the rhizosphere microbiome. Tetraploids were only considered due to complexities associated with the octoploid genomes. Lastly, a genome-wide association study identified 1861 single-nucleotide polymorphisms associated with 110 families and genes containing them related to potential regulatory functions. Our findings suggest that switchgrass genomic and life-history variation influences bacterial composition in the rhizosphere, potentially due to host adaptation to local environments.

Combining population genomics and fitness QTLs to identify the genetics of local adaptation in Arabidopsis thaliana.

Evidence for adaptation to different climates in the model species Arabidopsis thaliana is seen in reciprocal transplant experiments, but the genetic basis of this adaptation remains poorly understood. Field-based quantitative trait locus (QTL) studies provide direct but low-resolution evidence for the genetic basis of local adaptation. Using high-resolution population genomic approaches, we examine local adaptation along previously identified genetic trade-off (GT) and conditionally neutral (CN) QTLs for fitness between locally adapted Italian and Swedish A. thaliana populations [Ågren J, et al. (2013) Proc Natl Acad Sci USA 110:21077-21082]. We find that genomic regions enriched in high FST SNPs colocalize with GT QTL peaks. Many of these high FST regions also colocalize with regions enriched for SNPs significantly correlated to climate in Eurasia and evidence of recent selective sweeps in Sweden. Examining unfolded site frequency spectra across genes containing high FST SNPs suggests GTs may be due to more recent adaptation in Sweden than Italy. Finally, we collapse a list of thousands of genes spanning GT QTLs to 42 genes that likely underlie the observed GTs and explore potential biological processes driving these trade-offs, from protein phosphorylation, to seed dormancy and longevity. Our analyses link population genomic analyses and field-based QTL studies of local adaptation, and emphasize that GTs play an important role in the process of local adaptation.

What processes must we understand to forecast regional-scale population dynamics?

An urgent challenge facing biologists is predicting the regional-scale population dynamics of species facing environmental change. Biologists suggest that we must move beyond predictions based on phenomenological models and instead base predictions on underlying processes. For example, population biologists, evolutionary biologists, community ecologists and ecophysiologists all argue that the respective processes they study are essential. Must our models include processes from all of these fields? We argue that answering this critical question is ultimately an empirical exercise requiring a substantial amount of data that have not been integrated for any system to date. To motivate and facilitate the necessary data collection and integration, we first review the potential importance of each mechanism for skilful prediction. We then develop a conceptual framework based on reaction norms, and propose a hierarchical Bayesian statistical framework to integrate processes affecting reaction norms at different scales. The ambitious research programme we advocate is rapidly becoming feasible due to novel collaborations, datasets and analytical tools.

Effects of genomic and functional diversity on stand-level productivity and performance of non-native Arabidopsis.

Biodiversity can affect the properties of groups of organisms, such as ecosystem function and the persistence of colonizing populations. Genomic data offer a newly available window to diversity, complementary to other measures like taxonomic or phenotypic diversity. We tested whether native genetic diversity in field experimental stands of Arabidopsis thaliana affected their aboveground biomass and fecundity in their colonized range. We constructed some stands of genotypes that we a priori predicted would differ in performance or show overyielding. We found no relationship between genetic diversity and stand total biomass. However, increasing stand genetic diversity increased fecundity in high-resource conditions. Polyculture (multiple genotype) stands consistently yielded less biomass than expected based on the yields of component genotypes in monoculture. This under-yielding was strongest in stands with late-flowering and high biomass genotypes, potentially due to interference competition by these genotypes. Using a new implementation of association mapping, we identified genetic loci whose diversity was associated with stand-level yield, revealing a major flowering time locus associated with under-yielding of polycultures. Our field experiment supports community ecology studies that find a range of diversity-function relationships. Nevertheless, our results suggest diversity in colonizing propagule pools can enhance population fitness. Furthermore, interference competition among genotypes differing in flowering time might limit the advantages of polyculture.

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.

Natural Variation in 9-Cis-Epoxycartenoid Dioxygenase 3 and ABA Accumulation.

The stress hormone abscisic acid (ABA) is critical for drought resistance; however, mechanisms controlling ABA levels are unclear. At low water potential, ABA accumulation in the Arabidopsis (Arabidopsis thaliana) accession Shahdara (Sha) was less than that in Landsberg erecta (Ler) or Columbia. Analysis of a Ler × Sha recombinant inbred line population revealed a single major-effect quantitative trait locus for ABA accumulation, which included 9-cis-epoxycarotenoid dioxygenase3 (NCED3) as a candidate gene. NCED3 encodes a rate-limiting enzyme for stress-induced ABA synthesis. Complementation experiments indicated that Sha has a reduced-function NCED3 allele. Compared with Ler, Sha did not have reduced NCED3 gene expression or protein level but did have four amino acid substitutions within NCED3. Sha differed from Ler in the apparent molecular mass of NCED3, indicative of altered NCED3 proteolytic processing in the chloroplast. Site-directed mutagenesis demonstrated that substitution at amino acid 271 was critical for the altered NCED3 molecular mass pattern, while the other Sha NCED3 polymorphisms were also involved in the reduced ABA accumulation. Sha did not have a reduced level of thylakoid-bound NCED3 but did differ from Ler in the apparent molecular mass of stromal NCED3. As Sha was not impaired in known factors critical for NCED3 function in ABA synthesis (expression, chloroplast import, and thylakoid binding), the differences between Ler and Sha NCED3 may affect NCED3 activity or other factors influencing NCED3 function. These results identify functionally important sites on NCED3 and indicate a complex pattern of NCED3 posttranslational regulation in the chloroplast.

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.

Natural variation identifies genes affecting drought-induced abscisic acid accumulation in Arabidopsis thaliana.

Accumulation of the stress hormone abscisic acid (ABA) in response to drought and low water-potential controls many downstream acclimation mechanisms. However, mechanisms controlling ABA accumulation itself are less known. There was a 10-fold range of variation in ABA levels among nearly 300 Arabidopsis thaliana accessions exposed to the same low water-potential severity. Genome-wide association analysis (GWAS) identified genomic regions containing clusters of ABA-associated SNPs. Candidate genes within these regions included few genes with known stress or ABA-related function. The GWAS data were used to guide reverse genetic analysis, which found effectors of ABA accumulation. These included plasma-membrane-localized signaling proteins such as receptor-like kinases, aspartic protease, a putative lipid-binding START domain protein, and other membrane proteins of unknown function as well as a RING U-box protein and possible effect of tonoplast transport on ABA accumulation. Putative loss-of-function polymorphisms within the START domain protein were associated with climate factors at accession sites of origin, indicating its potential involvement in drought adaptation. Overall, using ABA accumulation as a basis for a combined GWAS-reverse genetic strategy revealed the broad natural variation in low-water-potential-induced ABA accumulation and was successful in identifying genes that affect ABA levels and may act in upstream drought-related sensing and signaling mechanisms. ABA effector loci were identified even when each one was of incremental effect, consistent with control of ABA accumulation being distributed among the many branches of ABA metabolism or mediated by genes with partially redundant function.

Comparing methods for detecting multilocus adaptation with multivariate genotype-environment associations.

Identifying adaptive loci can provide insight into the mechanisms underlying local adaptation. Genotype-environment association (GEA) methods, which identify these loci based on correlations between genetic and environmental data, are particularly promising. Univariate methods have dominated GEA, despite the high dimensional nature of genotype and environment. Multivariate methods, which analyse many loci simultaneously, may be better suited to these data as they consider how sets of markers covary in response to environment. These methods may also be more effective at detecting adaptive processes that result in weak, multilocus signatures. Here, we evaluate four multivariate methods and five univariate and differentiation-based approaches, using published simulations of multilocus selection. We found that Random Forest performed poorly for GEA. Univariate GEAs performed better, but had low detection rates for loci under weak selection. Constrained ordinations, particularly redundancy analysis (RDA), showed a superior combination of low false-positive and high true-positive rates across all levels of selection. These results were robust across the demographic histories, sampling designs, sample sizes and weak population structure tested here. The value of combining detections from different methods was variable and depended on the study goals and knowledge of the drivers of selection. Re-analysis of genomic data from grey wolves highlighted the unique, covarying sets of adaptive loci that could be identified using RDA. Although additional testing is needed, this study indicates that RDA is an effective means of detecting adaptation, including signatures of weak, multilocus selection, providing a powerful tool for investigating the genetic basis of local adaptation.

Topography and neighborhood crowding can interact to shape species growth and distribution in a diverse Amazonian forest.

Abiotic constraints and biotic interactions act simultaneously to shape communities. However, these community assembly mechanisms are often studied independently, which can limit understanding of how they interact to affect species dynamics and distributions. We develop a hierarchical Bayesian neighborhood modeling approach to quantify the simultaneous effects of topography and crowding by neighbors on the growth of 124,704 individual stems ≥1 cm DBH for 1,047 tropical tree species in a 25-ha mapped rainforest plot in Amazonian Ecuador. We build multi-level regression models to evaluate how four key functional traits (specific leaf area, maximum tree size, wood specific gravity and seed mass) mediate tree growth response to topography and neighborhood crowding. Tree growth is faster in valleys than on ridges and is reduced by neighborhood crowding. Topography and crowding interact to influence tree growth in ~10% of the species. Specific leaf area, maximum tree size and seed mass are associated with growth responses to topography, but not with responses to neighborhood crowding or with the interaction between topography and crowding. In sum, our study reveals that topography and neighborhood crowding each influence tree growth in tropical forests, but act largely independently in shaping species distributions. While traits were associated with species response to topography, their role in species response to neighborhood crowding was less clear, which suggests that trait effects on neighborhood dynamics may depend on the direction (negative/positive) and degree of symmetry of biotic interactions. Our study emphasizes the importance of simultaneously assessing the individual and interactive role of multiple mechanisms in shaping species dynamics in high diversity tropical systems.

Molecular, genetic and evolutionary analysis of a paracentric inversion in Arabidopsis thaliana.

Chromosomal inversions can provide windows onto the cytogenetic, molecular, evolutionary and demographic histories of a species. Here we investigate a paracentric 1.17-Mb inversion on chromosome 4 of Arabidopsis thaliana with nucleotide precision of its borders. The inversion is created by Vandal transposon activity, splitting an F-box and relocating a pericentric heterochromatin segment in juxtaposition with euchromatin without affecting the epigenetic landscape. Examination of the RegMap panel and the 1001 Arabidopsis genomes revealed more than 170 inversion accessions in Europe and North America. The SNP patterns revealed historical recombinations from which we infer diverse haplotype patterns, ancient introgression events and phylogenetic relationships. We find a robust association between the inversion and fecundity under drought. We also find linkage disequilibrium between the inverted region and the early flowering Col-FRIGIDA allele. Finally, SNP analysis elucidates the origin of the inversion to South-Eastern Europe approximately 5000 years ago and the FRI-Col allele to North-West Europe, and reveals the spreading of a single haplotype to North America during the 17th to 19th century. The 'American haplotype' was identified from several European localities, potentially due to return migration.

Predicting Responses to Contemporary Environmental Change Using Evolutionary Response Architectures.

Rapid environmental change currently presents a major threat to global biodiversity and ecosystem functions, and understanding impacts on individual populations is critical to creating reliable predictions and mitigation plans. One emerging tool for this goal is high-throughput sequencing technology, which can now be used to scan the genome for signs of environmental selection in any species and any system. This explosion of data provides a powerful new window into the molecular mechanisms of adaptation, and although there has been some success in using genomic data to predict responses to selection in fields such as agriculture, thus far genomic data are rarely integrated into predictive frameworks of future adaptation in natural populations. Here, we review both theoretical and empirical studies of adaptation to rapid environmental change, focusing on areas where genomic data are poised to contribute to our ability to estimate species and population persistence and adaptation. We advocate for the need to study and model evolutionary response architectures, which integrate spatial information, fitness estimates, and plasticity with genetic architecture. Understanding how these factors contribute to adaptive responses is essential in efforts to predict the responses of species and ecosystems to future environmental change.

Topological features of a gene co-expression network predict patterns of natural diversity in environmental response.

Molecular interactions affect the evolution of complex traits. For instance, adaptation may be constrained by pleiotropic or epistatic effects, both of which can be reflected in the structure of molecular interaction networks. To date, empirical studies investigating the role of molecular interactions in phenotypic evolution have been idiosyncratic, offering no clear patterns. Here, we investigated the network topology of genes putatively involved in local adaptation to two abiotic stressors-drought and cold-in Arabidopsis thaliana Our findings suggest that the gene-interaction topologies for both cold and drought stress response are non-random, with genes that show genetic variation in drought expression response (eGxE) being significantly more peripheral and cold response genes being significantly more central than genes which do not show GxE. We suggest that the observed topologies reflect different constraints on the genetic pathways involved in environmental response. The approach presented here may inform predictive models linking genetic variation in molecular signalling networks with phenotypic variation, specifically traits involved in environmental response.

Interactive effects of water limitation and elevated temperature on the physiology, development and fitness of diverse accessions of Brachypodium distachyon.

An enduring question in plant physiology and evolution is how single genotypes of plants optimize performance in diverse, often highly variable, environments. We grew 35 natural accessions of the grass Brachypodium distachyon in four environments in the glasshouse, contrasting soil water deficit, elevated temperature and their interaction. We modeled treatment, genotype and interactive effects on leaf-level and whole-plant traits, including fecundity. We also assessed the relationship between glasshouse-measured traits and parameters related to climate at the place of origin. We found abundant genetic variation in both constitutive and induced traits related to plant-water relations. Most traits showed strong interaction between temperature and water availability, and we observed genotype-by-environment interaction for several traits. Notably, leaf free proline abundance showed a strong effect of genotype × temperature × water. We found strong associations between phenology, biomass and water use efficiency (WUE) with parameters describing climate of origin. Plants respond to multiple stressors in ways not directly predictable from single stressors, underscoring the complex and trait-specific mechanisms of environmental response. Climate-trait correlations support a role for WUE and phenology in local adaptation to climate in B. distachyon.