Jesse R. Lasky

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

Arabidopsis thaliana inhabits diverse climates and exhibits varied phenology across its range. Although A. thaliana is an extremely well‐studied model species, the relationship between geography, growing season climate and its genetic variation is poorly characterized. We used redundancy analysis (RDA) to quantify the association of genomic variation [214 051 single nucleotide polymorphisms (SNPs)] with geography and climate among 1003 accessions collected from 447 locations in Eurasia. We identified climate variables most correlated with genomic variation, which may be important selective gradients related to local adaptation across the species range. Climate variation among sites of origin explained slightly more genomic variation than geographical distance. Large‐scale spatial gradients and early spring temperatures explained the most genomic variation, while growing season and summer conditions explained the most after controlling for spatial structure. SNP variation in Scandinavia showed the greatest climate structure among regions, possibly because of relatively consistent phenology and life history of populations in this region. Climate variation explained more variation among nonsynonymous SNPs than expected by chance, suggesting that much of the climatic structure of SNP correlations is due to changes in coding sequence that may underlie local adaptation.

Get the science right when paying for nature's services

Few projects adequately address design and evaluation Payments for Ecosystem Services (PES) mechanisms leverage economic and social incentives to shape how people influence natural processes and achieve conservation and sustainability goals. Beneficiaries of natures goods and services pay owners or stewards of ecosystems that produce those services, with payments contingent on service provision (1, 2). Integrating scientific knowledge and methods into PES is critical (3, 4). Yet many projects are based on weak scientific foundations, and effectiveness is rarely evaluated with the rigor necessary for scaling up and understanding the importance of these approaches as policy instruments and conservation tools (2, 5, 6). Part of the problem is the lack of simple, yet rigorous, scientific principles and guidelines to accommodate PES design and guide research and analyses that foster evaluations of effectiveness (4). As scientists and practitioners from government, nongovernment, academic, and finance institutions, we propose a set of such guidelines and principles.

Trait-mediated assembly processes predict successional changes in community diversity of tropical forests

Significance The assembly of ecological communities results from multiple mechanisms acting concurrently. Disentangling their relative importance represents a major challenge. Our study quantifies the relative importance of four trait-mediated mechanisms and associated changes in functional diversity over succession. We leverage the rapid community assembly in tropical successional forests and the rich information in functional trait data and spatially explicit long-term tree demographic data. Trait correlations with average species survival rates were the most important processes affecting survival and linked to a decrease in wood trait diversity during succession. Simultaneously, evidence for stabilizing niche differences associated with leaf traits was reflected in increasing leaf functional diversity. Our results suggest mechanisms by which individual performance affects successional change in community-wide diversity. Interspecific differences in relative fitness can cause local dominance by a single species. However, stabilizing interspecific niche differences can promote local diversity. Understanding these mechanisms requires that we simultaneously quantify their effects on demography and link these effects to community dynamics. Successional forests are ideal systems for testing assembly theory because they exhibit rapid community assembly. Here, we leverage functional trait and long-term demographic data to build spatially explicit models of successional community dynamics of lowland rainforests in Costa Rica. First, we ask what the effects and relative importance of four trait-mediated community assembly processes are on tree survival, a major component of fitness. We model trait correlations with relative fitness differences that are both density-independent and -dependent in addition to trait correlations with stabilizing niche differences. Second, we ask how the relative importance of these trait-mediated processes relates to successional changes in functional diversity. Tree dynamics were more strongly influenced by trait-related interspecific variation in average survival than trait-related responses to neighbors, with wood specific gravity (WSG) positively correlated with greater survival. Our findings also suggest that competition was mediated by stabilizing niche differences associated with specific leaf area (SLA) and leaf dry matter content (LDMC). These drivers of individual-level survival were reflected in successional shifts to higher SLA and LDMC diversity but lower WSG diversity. Our study makes significant advances to identifying the links between individual tree performance, species functional traits, and mechanisms of tropical forest succession.

Intron-mediated alternative splicing of Arabidopsis P5CS1 and its association with natural variation in proline and climate adaptation.

Drought-induced proline accumulation is widely observed in plants but its regulation and adaptive value are not as well understood. Proline accumulation of the Arabidopsis accession Shakdara (Sha) was threefold less than that of Landsberg erecta (Ler) and quantitative trait loci mapping identified a reduced function allele of the proline synthesis enzyme Δ1-pyrroline-5-carboxylate synthetase1 (P5CS1) as a basis for the lower proline of Sha. Sha P5CS1 had additional TA repeats in intron 2 and a G-to-T transversion in intron 3 that were sufficient to promote alternative splicing and production of a nonfunctional transcript lacking exon 3 (exon 3-skip P5CS1). In Sha, and additional accessions with the same intron polymorphisms, the nonfunctional exon 3-skip P5CS1 splice variant constituted as much as half of the total P5CS1 transcript. In a larger panel of Arabidopsis accessions, low water potential-induced proline accumulation varied by 10-fold and variable production of exon 3-skip P5CS1 among accessions was an important, but not the sole, factor underlying variation in proline accumulation. Population genetic analyses suggest that P5CS1 may have evolved under positive selection, and more extensive correlation of exon 3-skip P5CS1 production than proline abundance with climate conditions of natural accessions also suggest a role of P5CS1 in local adaptation to the environment. These data identify a unique source of alternative splicing in plants, demonstrate a role of exon 3-skip P5CS1 in natural variation of proline metabolism, and suggest an association of P5CS1 and its alternative splicing with environmental adaptation.

Pleiotropy of FRIGIDA enhances the potential for multivariate adaptation.

An evolutionary response to selection requires genetic variation; however, even if it exists, then the genetic details of the variation can constrain adaptation. In the simplest case, unlinked loci and uncorrelated phenotypes respond directly to multivariate selection and permit unrestricted paths to adaptive peaks. By contrast, ‘antagonistic’ pleiotropic loci may constrain adaptation by affecting variation of many traits and limiting the direction of trait correlations to vectors that are not favoured by selection. However, certain pleiotropic configurations may improve the conditions for adaptive evolution. Here, we present evidence that the Arabidopsis thaliana gene FRI (FRIGIDA) exhibits ‘adaptive’ pleiotropy, producing trait correlations along an axis that results in two adaptive strategies. Derived, low expression FRI alleles confer a ‘drought escape’ strategy owing to fast growth, low water use efficiency and early flowering. By contrast, a dehydration avoidance strategy is conferred by the ancestral phenotype of late flowering, slow growth and efficient water use during photosynthesis. The dehydration avoidant phenotype was recovered when genotypes with null FRI alleles were transformed with functional alleles. Our findings indicate that the well-documented effects of FRI on phenology result from differences in physiology, not only a simple developmental switch.

Genome-environment associations in sorghum landraces predict adaptive traits

Genome-environment associations and phenotypic analyses may reveal the basis of environmental adaptation. Improving environmental adaptation in crops is essential for food security under global change, but phenotyping adaptive traits remains a major bottleneck. If associations between single-nucleotide polymorphism (SNP) alleles and environment of origin in crop landraces reflect adaptation, then these could be used to predict phenotypic variation for adaptive traits. We tested this proposition in the global food crop Sorghum bicolor, characterizing 1943 georeferenced landraces at 404,627 SNPs and quantifying allelic associations with bioclimatic and soil gradients. Environment explained a substantial portion of SNP variation, independent of geographical distance, and genic SNPs were enriched for environmental associations. Further, environment-associated SNPs predicted genotype-by-environment interactions under experimental drought stress and aluminum toxicity. Our results suggest that genomic signatures of environmental adaptation may be useful for crop improvement, enhancing germplasm identification and marker-assisted selection. Together, genome-environment associations and phenotypic analyses may reveal the basis of environmental adaptation.

Genome-Wide Association Mapping Combined with Reverse Genetics Identifies New Effectors of Low Water Potential-Induced Proline Accumulation in Arabidopsis

Genome-wide association analysis and spatial patterning of single-nucleotide polymorphism data guide reverse genetics to identify new genes linking stress-induced proline accumulation with cellular redox and energy status. Arabidopsis (Arabidopsis thaliana) exhibits natural genetic variation in drought response, including varying levels of proline (Pro) accumulation under low water potential. As Pro accumulation is potentially important for stress tolerance and cellular redox control, we conducted a genome-wide association (GWAS) study of low water potential-induced Pro accumulation using a panel of natural accessions and publicly available single-nucleotide polymorphism (SNP) data sets. Candidate genomic regions were prioritized for subsequent study using metrics considering both the strength and spatial clustering of the association signal. These analyses found many candidate regions likely containing gene(s) influencing Pro accumulation. Reverse genetic analysis of several candidates identified new Pro effector genes, including thioredoxins and several genes encoding Universal Stress Protein A domain proteins. These new Pro effector genes further link Pro accumulation to cellular redox and energy status. Additional new Pro effector genes found include the mitochondrial protease LON1, ribosomal protein RPL24A, protein phosphatase 2A subunit A3, a MADS box protein, and a nucleoside triphosphate hydrolase. Several of these new Pro effector genes were from regions with multiple SNPs, each having moderate association with Pro accumulation. This pattern supports the use of summary approaches that incorporate clusters of SNP associations in addition to consideration of individual SNP probability values. Further GWAS-guided reverse genetics promises to find additional effectors of Pro accumulation. The combination of GWAS and reverse genetics to efficiently identify new effector genes may be especially applicable for traits difficult to analyze by other genetic screening methods.

Natural Variation in Abiotic Stress Responsive Gene Expression and Local Adaptation to Climate in Arabidopsis thaliana

Gene expression varies widely in natural populations, yet the proximate and ultimate causes of this variation are poorly known. Understanding how variation in gene expression affects abiotic stress tolerance, fitness, and adaptation is central to the field of evolutionary genetics. We tested the hypothesis that genes with natural genetic variation in their expression responses to abiotic stress are likely to be involved in local adaptation to climate in Arabidopsis thaliana. Specifically, we compared genes with consistent expression responses to environmental stress (expression stress responsive, “eSR”) to genes with genetically variable responses to abiotic stress (expression genotype-by-environment interaction, “eGEI”). We found that on average genes that exhibited eGEI in response to drought or cold had greater polymorphism in promoter regions and stronger associations with climate than those of eSR genes or genomic controls. We also found that transcription factor binding sites known to respond to environmental stressors, especially abscisic acid responsive elements, showed significantly higher polymorphism in drought eGEI genes in comparison to eSR genes. By contrast, eSR genes tended to exhibit relatively greater pairwise haplotype sharing, lower promoter diversity, and fewer nonsynonymous polymorphisms, suggesting purifying selection or selective sweeps. Our results indicate that cis-regulatory evolution and genetic variation in stress responsive gene expression may be important mechanisms of local adaptation to climatic selective gradients.

Detecting spatial genetic signatures of local adaptation in heterogeneous landscapes

The spatial structure of the environment (e.g. the configuration of habitat patches) may play an important role in determining the strength of local adaptation. However, previous studies of habitat heterogeneity and local adaptation have largely been limited to simple landscapes, which poorly represent the multiscale habitat structure common in nature. Here, we use simulations to pursue two goals: (i) we explore how landscape heterogeneity, dispersal ability and selection affect the strength of local adaptation, and (ii) we evaluate the performance of several genotype–environment association (GEA) methods for detecting loci involved in local adaptation. We found that the strength of local adaptation increased in spatially aggregated selection regimes, but remained strong in patchy landscapes when selection was moderate to strong. Weak selection resulted in weak local adaptation that was relatively unaffected by landscape heterogeneity. In general, the power of detection methods closely reflected levels of local adaptation. False‐positive rates (FPRs), however, showed distinct differences across GEA methods based on levels of population structure. The univariate GEA approach had high FPRs (up to 55%) under limited dispersal scenarios, due to strong isolation by distance. By contrast, multivariate, ordination‐based methods had uniformly low FPRs (0–2%), suggesting these approaches can effectively control for population structure. Specifically, constrained ordinations had the best balance of high detection and low FPRs and will be a useful addition to the GEA toolkit. Our results provide both theoretical and practical insights into the conditions that shape local adaptation and how these conditions impact our ability to detect selection.

Trait‐mediated effects of environmental filtering on tree community dynamics

Summary 1. Individual performance is a function of an individual’s traits and its environment. This function, known as an environmental filter, varies in space and affects community composition. However, filters are poorly characterized because dispersal patterns can obscure environmental effects, and few studies utilize longitudinal data linking individual performance to environment. 2. We model the effects of environmental filters on demographic rates of nearly all tree species (99) in a 25-ha subtropical rain forest plot. We develop a hierarchical Bayesian model of environmental filtering, drawing inspiration from classic studies of intraspecific natural selection. We characterize the specific environmental gradients and trait axes most important in filtering of demographic rates across species. 3. We found that stronger filtering along a given trait axis corresponded to less spatial variation in the value of favoured traits. 4. Environmental gradients associated with filtering were different for growth versus survivorship. 5. Species maximum height was under the strongest filtering for growth, with shorter species favoured on convex ridges. Shorter stature species may be favoured on ridges because trees on ridges experience higher wind damage and lower soil moisture. 6. Wood density filtering had the strongest effects on survival. Steep slopes and high available P in the soil favoured species with low-density wood. Such sites may be favourable for fast-growing species that exploit resource-rich environments. 7. Synthesis: We characterized trait-mediated environmental filters that may underlie spatial niche differentiation and life-history trade-offs, which can promote species coexistence. Filtering along trait axes with the strongest effects on local community composition, that is, traits with the strongest filtering, may necessarily have a weaker potential to promote species coexistence across the plot. The weak spatial variation in filters with strong effects on demography may result from long-term processes affecting the species pool that favour habitat generalist strategies.