A large-effect fitness trade-off across environments is explained by a single mutation affecting cold acclimation.

Identifying the genetic basis of local adaptation and fitness trade-offs across environments is a central goal of evolutionary biology. Cold acclimation is an adaptive plastic response for surviving seasonal freezing, and costs of acclimation may be a general mechanism for fitness trade-offs across environments in temperate zone species. Starting with locally adapted ecotypes of Arabidopsis thaliana from Italy and Sweden, we examined the fitness consequences of a naturally occurring functional polymorphism in CBF2. This gene encodes a transcription factor that is a major regulator of cold-acclimated freezing tolerance and resides within a locus responsible for a genetic trade-off for long-term mean fitness. We estimated the consequences of alternate genotypes of CBF2 on 5-y mean fitness and fitness components at the native field sites by comparing near-isogenic lines with alternate genotypes of CBF2 to their genetic background ecotypes. The effects of CBF2 were validated at the nucleotide level using gene-edited lines in the native genetic backgrounds grown in simulated parental environments. The foreign CBF2 genotype in the local genetic background reduced long-term mean fitness in Sweden by more than 10%, primarily via effects on survival. In Italy, fitness was reduced by more than 20%, primarily via effects on fecundity. At both sites, the effects were temporally variable and much stronger in some years. The gene-edited lines confirmed that CBF2 encodes the causal variant underlying this genetic trade-off. Additionally, we demonstrated a substantial fitness cost of cold acclimation, which has broad implications for potential maladaptive responses to climate change.

Cannabinoids function in defense against chewing herbivores in Cannabis sativa L.

In the decades since the first cannabinoids were identified by scientists, research has focused almost exclusively on the function and capacity of cannabinoids as medicines and intoxicants for humans and other vertebrates. Very little is known about the adaptive value of cannabinoid production, though several hypotheses have been proposed including protection from ultraviolet radiation, pathogens, and herbivores. To test the prediction that genotypes with greater concentrations of cannabinoids will have reduced herbivory, a segregating F2 population of Cannabis sativa was leveraged to conduct lab- and field-based bioassays investigating the function of cannabinoids in mediating interactions with chewing herbivores. In the field, foliar cannabinoid concentration was inversely correlated with chewing herbivore damage. On detached leaves, Trichoplusia ni larvae consumed less leaf area and grew less when feeding on leaves with greater concentrations of cannabinoids. Scanning electron and light microscopy were used to characterize variation in glandular trichome morphology. Cannabinoid-free genotypes had trichomes that appeared collapsed. To isolate cannabinoids from confounding factors, artificial insect diet was amended with cannabinoids in a range of physiologically relevant concentrations. Larvae grew less and had lower rates of survival as cannabinoid concentration increased. These results support the hypothesis that cannabinoids function in defense against chewing herbivores.

Ecological genetics of local adaptation in Arabidopsis: An 8-year field experiment.

There is considerable evidence for local adaptation in nature, yet important questions remain regarding its genetic basis. How many loci are involved? What are their effect sizes? What is the relative importance of conditional neutrality versus genetic trade-offs? Here we address these questions in the self-pollinating, annual plant Arabidopsis thaliana. We used 400 recombinant inbred lines (RILs) derived from two locally adapted populations in Italy and Sweden, grew the RILs and parents at the parental locations, and mapped quantitative trait loci (QTL) for mean fitness (fruits/seedling planted). We previously published results from the first 3 years of the study, and here add five additional years, providing a unique opportunity to assess how temporal variation in selection might affect QTL detection and classification. We found 10 adaptive and one maladaptive QTL in Italy, and six adaptive and four maladaptive QTL in Sweden. The discovery of maladaptive QTL at both sites suggests that even locally adapted populations are not always at their genotypic optimum. Mean effect sizes for adaptive QTL, 0.97 and 0.55 fruits in Italy and Sweden, respectively, were large relative to the mean fitness of the RILs (approximately 8 fruits/seedling planted at both sites). Both genetic trade-offs (four cases) and conditional neutrality (seven cases) contribute to local adaptation in this system. The 8-year dataset provided greater power to detect QTL and to estimate their locations compared to our previous 3-year study, identifying one new genetic trade-off and resolving one genetic trade-off into two conditionally adaptive QTL.

Climate change challenges, plant science solutions.

Climate change is a defining challenge of the 21st century, and this decade is a critical time for action to mitigate the worst effects on human populations and ecosystems. Plant science can play an important role in developing crops with enhanced resilience to harsh conditions (e.g. heat, drought, salt stress, flooding, disease outbreaks) and engineering efficient carbon-capturing and carbon-sequestering plants. Here, we present examples of research being conducted in these areas and discuss challenges and open questions as a call to action for the plant science community.

Genome-wide polymorphism and genic selection in feral and domesticated lineages of Cannabis sativa.

A comprehensive understanding of the degree to which genomic variation is maintained by selection versus drift and gene flow is lacking in many important species such as Cannabis sativa (C. sativa), one of the oldest known crops to be cultivated by humans worldwide. We generated whole genome resequencing data across diverse samples of feralized (escaped domesticated lineages) and domesticated lineages of C. sativa. We performed analyses to examine population structure, and genome wide scans for FST, balancing selection, and positive selection. Our analyses identified evidence for sub-population structure and further support the Asian origin hypothesis of this species. Feral plants sourced from the U.S. exhibited broad regions on chromosomes 4 and 10 with high F̄ST which may indicate chromosomal inversions maintained at high frequency in this sub-population. Both our balancing and positive selection analyses identified loci that may reflect differential selection for traits favored by natural selection and artificial selection in feral versus domesticated sub-populations. In the U.S. feral sub-population, we found six loci related to stress response under balancing selection and one gene involved in disease resistance under positive selection, suggesting local adaptation to new climates and biotic interactions. In the marijuana sub-population, we identified the gene SMALLER TRICHOMES WITH VARIABLE BRANCHES 2 to be under positive selection which suggests artificial selection for increased tetrahydrocannabinol yield. Overall, the data generated, and results obtained from our study help to form a better understanding of the evolutionary history in C. sativa.

Root Pulling Force Across Drought in Maize Reveals Genotype by Environment Interactions and Candidate Genes.

High-throughput, field-based characterization of root systems for hundreds of genotypes in thousands of plots is necessary for breeding and identifying loci underlying variation in root traits and their plasticity. We designed a large-scale sampling of root pulling force, the vertical force required to extract the root system from the soil, in a maize diversity panel under differing irrigation levels for two growing seasons. We then characterized the root system architecture of the extracted root crowns. We found consistent patterns of phenotypic plasticity for root pulling force for a subset of genotypes under differential irrigation, suggesting that root plasticity is predictable. Using genome-wide association analysis, we identified 54 SNPs as statistically significant for six independent root pulling force measurements across two irrigation levels and four developmental timepoints. For every significant GWAS SNP for any trait in any treatment and timepoint we conducted post hoc tests for genotype-by-environment interaction, using a mixed model ANOVA. We found that 8 of the 54 SNPs showed significant GxE. Candidate genes underlying variation in root pulling force included those involved in nutrient transport. Although they are often treated separately, variation in the ability of plant roots to sense and respond to variation in environmental resources including water and nutrients may be linked by the genes and pathways underlying this variation. While functional validation of the identified genes is needed, our results expand the current knowledge of root phenotypic plasticity at the whole plant and gene levels, and further elucidate the complex genetic architecture of maize root systems.

Quantitative trait loci controlling agronomic and biochemical traits in Cannabis sativa.

Understanding the genetic basis of complex traits is a fundamental goal of evolutionary genetics. Yet, the genetics controlling complex traits in many important species such as hemp (Cannabis sativa) remain poorly investigated. Because hemp's change in legal status with the 2014 and 2018 U.S. Federal Farm Bills, interest in the genetics controlling its numerous agriculturally important traits has steadily increased. To better understand the genetics of agriculturally important traits in hemp, we developed an F2 population by crossing two phenotypically distinct hemp cultivars (Carmagnola and USO31). Using whole-genome sequencing, we mapped quantitative trait loci (QTL) associated with variation in numerous agronomic and biochemical traits. A total of 69 loci associated with agronomic (34) and biochemical (35) trait variation were identified. We found that most QTL co-localized, suggesting that the phenotypic distinctions between Carmagnola and USO31 are largely controlled by a small number of loci. We identified TINY and olivetol synthase as candidate genes underlying co-localized QTL clusters for agronomic and biochemical traits, respectively. We functionally validated the olivetol synthase candidate by expressing the alleles in yeast. Gas chromatography-mass spectrometry assays of extracts from these yeast colonies suggest that the USO31 olivetol synthase is functionally less active and potentially explains why USO31 produces lower cannabinoids compared to Carmagnola. Overall, our results help modernize the genomic understanding of complex traits in hemp.

An integrated framework reinstating the environmental dimension for GWAS and genomic selection in crops.

Identifying mechanisms and pathways involved in gene-environment interplay and phenotypic plasticity is a long-standing challenge. It is highly desirable to establish an integrated framework with an environmental dimension for complex trait dissection and prediction. A critical step is to identify an environmental index that is both biologically relevant and estimable for new environments. With extensive field-observed complex traits, environmental profiles, and genome-wide single nucleotide polymorphisms for three major crops (maize, wheat, and oat), we demonstrated that identifying such an environmental index (i.e., a combination of environmental parameter and growth window) enables genome-wide association studies and genomic selection of complex traits to be conducted with an explicit environmental dimension. Interestingly, genes identified for two reaction-norm parameters (i.e., intercept and slope) derived from flowering time values along the environmental index were less colocalized for a diverse maize panel than for wheat and oat breeding panels, agreeing with the different diversity levels and genetic constitutions of the panels. In addition, we showcased the usefulness of this framework for systematically forecasting the performance of diverse germplasm panels in new environments. This general framework and the companion CERIS-JGRA analytical package should facilitate biologically informed dissection of complex traits, enhanced performance prediction in breeding for future climates, and coordinated efforts to enrich our understanding of mechanisms underlying phenotypic variation.

The population genomics of adaptive loss of function.

Discoveries of adaptive gene knockouts and widespread losses of complete genes have in recent years led to a major rethink of the early view that loss-of-function alleles are almost always deleterious. Today, surveys of population genomic diversity are revealing extensive loss-of-function and gene content variation, yet the adaptive significance of much of this variation remains unknown. Here we examine the evolutionary dynamics of adaptive loss of function through the lens of population genomics and consider the challenges and opportunities of studying adaptive loss-of-function alleles using population genetics models. We discuss how the theoretically expected existence of allelic heterogeneity, defined as multiple functionally analogous mutations at the same locus, has proven consistent with empirical evidence and why this impedes both the detection of selection and causal relationships with phenotypes. We then review technical progress towards new functionally explicit population genomic tools and genotype-phenotype methods to overcome these limitations. More broadly, we discuss how the challenges of studying adaptive loss of function highlight the value of classifying genomic variation in a way consistent with the functional concept of an allele from classical population genetics.

Deployment of Lidar from a Ground Platform: Customizing a Low-Cost, Information-Rich and User-Friendly Application for Field Phenomics Research.

Using sensors and electronic systems for characterization of plant traits provides valuable digital inputs to support complex analytical modeling in genetics research. In field applications, frequent sensor deployment enables the study of the dynamics of these traits and their interaction with the environment. This study focused on implementing lidar (light detection and ranging) technology to generate 2D displacement data at high spatial resolution and extract plant architectural parameters, namely canopy height and cover, in a diverse population of 252 maize (Zea mays L.) genotypes. A prime objective was to develop the mechanical and electrical subcomponents for field deployment from a ground vehicle. Data reduction approaches were implemented for efficient same-day post-processing to generate by-plot statistics. The lidar system was successfully deployed six times in a span of 42 days. Lidar data accuracy was validated through independent measurements in a subset of 75 experimental units. Manual and lidar-derived canopy height measurements were compared resulting in root mean square error (RMSE) = 0.068 m and r2 = 0.81. Subsequent genome-wide association study (GWAS) analyses for quantitative trait locus (QTL) identification and comparisons of genetic correlations and heritabilities for manual and lidar-based traits showed statistically significant associations. Low-cost, field-ready lidar of computational simplicity make possible timely phenotyping of diverse populations in multiple environments.

Drought regimens predict life history strategies in Heliophila.

Explaining variation in life history strategies is an enduring goal of evolutionary biology and ecology. Early theory predicted that for plants, annual and perennial life histories reflect adaptations to environments that experience alternative drought regimens. Nevertheless, empirical support for this hypothesis from comparative analyses remains lacking. Here, we test classic life history theory in Heliophila L. (Brassicaceae), a diverse genus of flowering plants native to Africa, controlling for phylogeny and integrating 34 yr of satellite-based drought detection with 2192 herbaria occurrence records. We find that the common ancestor of these species was likely to be an annual, and that perenniality and annuality have repeatedly evolved, an estimated seven and five times, respectively. By comparing historical drought regimens, we show that annuals rather than perennial species occur in environments where droughts are significantly more frequent. We also find evidence that annual plants adapt to predictable drought regimens by escaping drought-prone seasons as seeds. These results yield compelling support for longstanding theoretical predictions by revealing the importance of drought frequency and predictability to explain plant life history. More broadly, this work highlights scalable approaches, integrating herbaria records and remote sensing to address outstanding questions in evolutionary ecology.

Drought adaptation in Arabidopsis thaliana by extensive genetic loss-of-function.

Interdisciplinary syntheses are needed to scale up discovery of the environmental drivers and molecular basis of adaptation in nature. Here we integrated novel approaches using whole genome sequences, satellite remote sensing, and transgenic experiments to study natural loss-of-function alleles associated with drought histories in wild Arabidopsis thaliana. The genes we identified exhibit population genetic signatures of parallel molecular evolution, selection for loss-of-function, and shared associations with flowering time phenotypes in directions consistent with longstanding adaptive hypotheses seven times more often than expected by chance. We then confirmed predicted phenotypes experimentally in transgenic knockout lines. These findings reveal the importance of drought timing to explain the evolution of alternative drought tolerance strategies and further challenge popular assumptions about the adaptive value of genetic loss-of-function in nature. These results also motivate improved species-wide sequencing efforts to better identify loss-of-function variants and inspire new opportunities for engineering climate resilience in crops.

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.

Within-species trade-offs in plant-stimulated soil enzyme activity and growth, flowering, and seed size.

Soil microbial communities affect species demographic rates of plants. In turn, plants influence the composition and function of the soil microbiome, potentially resulting in beneficial feedbacks that alter their fitness and establishment. For example, differences in the ability to stimulate soil enzyme activity among plant lineages may affect plant growth and reproduction. We used a common garden study to test differences in plant-stimulated soil enzyme activity between lineages of the same species across developmental stages. Lineages employed different strategies whereby growth, days to flowering and seed size traded-off with plant-stimulated soil enzyme activity. Specifically, the smaller seeded lineage stimulated more enzyme activity at the early stage of development and flowered earlier while the larger seeded lineage sustained lower but consistent enzyme activity through development. We suggest that these lineages, which are both successful invaders, employ distinct strategies (a colonizer and a competitor) and differ in their influence on soil microbial activity. Synthesis. The ability to influence the soil microbial community by plants may be an important trait that trades off with growth, flowering, and seed size for promoting plant establishment, reproduction, and invasion.

Genetic Costs of Domestication and Improvement.

The "cost of domestication" hypothesis posits that the process of domesticating wild species can result in an increase in the number, frequency, and/or proportion of deleterious genetic variants that are fixed or segregating in the genomes of domesticated species. This cost may limit the efficacy of selection and thus reduce genetic gains in breeding programs for these species. Understanding when and how deleterious mutations accumulate can also provide insight into fundamental questions about the interplay of demography and selection. Here we describe the evolutionary processes that may contribute to deleterious variation accrued during domestication and improvement, and review the available evidence for "the cost of domestication" in animal and plant genomes. We identify gaps and explore opportunities in this emerging field, and finally offer suggestions for researchers and breeders interested in understanding or avoiding the consequences of an increased number or frequency of deleterious variants in domesticated species.

TSPmap, a tool making use of traveling salesperson problem solvers in the efficient and accurate construction of high-density genetic linkage maps.

BACKGROUND: Recent advances in nucleic acid sequencing technologies have led to a dramatic increase in the number of markers available to generate genetic linkage maps. This increased marker density can be used to improve genome assemblies as well as add much needed resolution for loci controlling variation in ecologically and agriculturally important traits. However, traditional genetic map construction methods from these large marker datasets can be computationally prohibitive and highly error prone. RESULTS: We present TSPmap, a method which implements both approximate and exact Traveling Salesperson Problem solvers to generate linkage maps. We demonstrate that for datasets with large numbers of genomic markers (e.g. 10,000) and in multiple population types generated from inbred parents, TSPmap can rapidly produce high quality linkage maps with low sensitivity to missing and erroneous genotyping data compared to two other benchmark methods, JoinMap and MSTmap. TSPmap is open source and freely available as an R package. CONCLUSIONS: With the advancement of low cost sequencing technologies, the number of markers used in the generation of genetic maps is expected to continue to rise. TSPmap will be a useful tool to handle such large datasets into the future, quickly producing high quality maps using a large number of genomic markers.

Screening for Natural Variation in Water Use Efficiency Traits in a Diversity Set of Brassica napus L. Identifies Candidate Variants in Photosynthetic Assimilation.

Seed yield and quality of crop species are significantly reduced by water deficit. Stable isotope screening (δ13C) of a diversity set of 147 accessions of Brassica napus grown in the field identified several accessions with extremes in water use efficiency (WUE). We next conducted an investigation of the physiological characteristics of selected natural variants with high and low WUE to understand how these characteristics translate to differences in WUE. We identified an interesting Spring accession, G302 (Mozart), that exhibited the highest WUE in the field and high CO2 assimilation rates coupled with an increased electron transport capacity (Jmax) under the imposed conditions. Differences in stomatal density and stomatal index did not translate to differences in stomatal conductance in the investigated accessions. Stomatal conductance response to exogenous ABA was analyzed in selected high and low WUE accessions. Spring lines showed little variation in response to exogenous ABA, while one Semi-Winter line (SW047) showed a significantly more rapid response to exogenous ABA, that corresponded to the high WUE indicated by δ13C measurements. This research illustrates the importance of examining natural variation at a physiological level for investigation of the underlying mechanisms influencing the diversity of carbon isotope discrimination values in the field and identifies natural variants in B. napus with improved WUE and potential relevant traits.

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice.

To ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. Here we demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor-intensive measures of flowering time, height, biomass, grain yield, and harvest index. Genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.

Mutation Accumulation in an Asexual Relative of Arabidopsis.

Asexual populations experience weaker responses to natural selection, which causes deleterious mutations to accumulate over time. Additionally, stochastic loss of individuals free of deleterious mutations can lead to an irreversible increase in mutational load in asexuals (the "click" in Muller's Ratchet). Here we report on the genomic divergence and distribution of mutations across eight sympatric pairs of sexual and apomictic (asexual) Boechera (Brassicaceae) genotypes. We show that apomicts harbor a greater number of derived mutations than sympatric sexual genotypes. Furthermore, in phylogenetically constrained sites that are subject to contemporary purifying selection, the ancestral, conserved allele is more likely to be retained in sexuals than apomicts. These results indicate that apomictic lineages accumulate mutations at otherwise conserved sites more often than sexuals, and support the conclusion that deleterious mutation accumulation can be a powerful force in the evolution of asexual higher plants.

Genetics of water use physiology in locally adapted Arabidopsis thaliana.

Identifying the genetic basis of adaptation to climate has long been a goal in evolutionary biology and has applications in agriculture. Adaptation to drought represents one important aspect of local adaptation, and drought is the major factor limiting agricultural yield. We examined local adaptation between Sweden and Italy Arabidopsis thaliana ecotypes, which show contrasting levels of water availability in their local environments. To identify quantitative trait loci (QTL) controlling water use physiology traits and adaptive trait QTL (genomic regions where trait QTL and fitness QTL colocalize), we performed QTL mapping on 374F9 recombinant inbred lines in well-watered and terminal drought conditions. We found 72 QTL (32 in well-watered, 31 in drought, 9 for plasticity) across five water use physiology traits: δ(13)C, rosette area, dry rosette weight, leaf water content and percent leaf nitrogen. Some of these genomic regions colocalize with fitness QTL and with other physiology QTL in defined hotspots. In addition, we found evidence of both constitutive and inducible water use physiology QTL. Finally, we identified highly divergent candidate genes, in silico. Our results suggest that many genes with minor effects may influence adaptation through water use physiology and that pleiotropic water use physiology QTL have fitness consequences.