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Objectives Advanced tools and resources are needed to efficiently and sustainably produce food for an increasing world population in the context of variable environmental conditions. The maize genomes to fields (G2F) initiative is a multi-institutional initiative effort that seeks to approach this challenge by developing a flexible and distributed infrastructure addressing emerging problems. G2F has generated large-scale phenotypic, genotypic, and environmental datasets using publicly available inbred lines and hybrids evaluated through a network of collaborators that are part of the G2F’s genotype-by-environment (G × E) project. This report covers the public release of datasets for 2014–2017. Data description Datasets include inbred genotypic information; phenotypic, climatic, and soil measurements and metadata information for each testing location across years. For a subset of inbreds in 2014 and 2015, yield component phenotypes were quantified by image analysis. Data released are accompanied by README descriptions. For genotypic and phenotypic data, both raw data and a version without outliers are reported. For climatic data, a version calibrated to the nearest airport weather station and a version without outliers are reported. The 2014 and 2015 datasets are updated versions from the previously released files [1] while 2016 and 2017 datasets are newly available to the public.

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.

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.

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.

Brassica juncea is an important economic crop of the world; however, the narrow genetic base of this crop has tremendously decreased its crop productivity. As an ancestral species of B. juncea, B. nigra is of great importance in widening the genetic diversity of B. juncea. In the present study, 42 SSR markers were employed to screen the genetic diversity among 83 B. nigra, 16 B. juncea, and other Brassica accessions. The molecular characteristics of 498 virtual B. juncea lines were deduced based on the bands of B. nigra and B. rapa via a virtual allopolyploid strategy, and then compared with natural B. juncea accessions. It was found that B. nigra had rich genetic diversity and could be classified into four subgroups, of which subgroup B-III and subgroup B-IV exhibited the closest and the most distant genetic relationship with B. juncea, respectively. To verify this, a hexaploidy strategy was applied to generated synthetic B. juncea from 20 B. nigra accessions, resulting in 45 new-type B. juncea genotypes. The genetic analyses detected that synthetic B. juncea derived from B. nigra in subgroup B-III was close to natural B. juncea, while B. juncea synthesized with B. nigra from subgroup B-IV exhibited wide genetic diversity and was most distant with current B. juncea. This study revealed a great potential of B. nigra in widening genetic diversity of B. juncea particularly using B. nigra in subgroup B-IV, and is helpful in better understanding of the genetic relationship between B. nigra and B. juncea. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11032-020-01197-7.

High-dimensional and high-throughput genomic, field performance, and environmental data are becoming increasingly available to crop breeding programs, and their integration can facilitate genomic prediction within and across environments and provide insights into the genetic architecture of complex traits and the nature of genotype-by-environment interactions. To partition trait variation into additive and dominance (main effect) genetic and corresponding genetic-by-environment variances, and to identify specific environmental factors that influence genotype-by-environment interactions, we curated and analyzed genotypic and phenotypic data on 1918 maize (Zea mays L.) hybrids and environmental data from 65 testing environments. For grain yield, dominance variance was similar in magnitude to additive variance, and genetic-by-environment variances were more important than genetic main effect variances. Models involving both additive and dominance relationships best fit the data and modeling unique genetic covariances among all environments provided the best characterization of the genotype-by-environment interaction patterns. Similarity of relative hybrid performance among environments was modeled as a function of underlying weather variables, permitting identification of weather covariates driving correlations of genetic effects across environments. The resulting models can be used for genomic prediction of mean hybrid performance across populations of environments tested or for environment-specific predictions. These results can also guide efforts to incorporate high-throughput environmental data into genomic prediction models and predict values in new environments characterized with the same environmental characteristics.

The root system is critical for the survival of nearly all land plants and a key target for improving abiotic stress tolerance, nutrient accumulation, and yield in crop species. Although many methods of root phenotyping exist, within field studies, one of the most popular methods is the extraction and measurement of the upper portion of the root system, known as the root crown, followed by trait quantification based on manual measurements or 2D imaging. However, 2D techniques are inherently limited by the information available from single points of view. Here, we used X-ray computed tomography to generate highly accurate 3D models of maize root crowns and created computational pipelines capable of measuring 71 features from each sample. This approach improves estimates of the genetic contribution to root system architecture and is refined enough to detect various changes in global root system architecture over developmental time as well as more subtle changes in root distributions as a result of environmental differences. We demonstrate that root pulling force, a high-throughput method of root extraction that provides an estimate of root mass, is associated with multiple 3D traits from our pipeline. Our combined methodology can therefore be used to calibrate and interpret root pulling force measurements across a range of experimental contexts or scaled up as a stand-alone approach in large genetic studies of root system architecture.

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.

Understanding how genomic and expression variation is linked to adaptation of plants to local environments is fundamental to the fields of evolutionary biology and species conservation. Using locally adaptedArabidopsis thalianaItaly and Sweden populations, we examine how variation in gene expression under control and cold acclimation conditions, is linked to allele frequency differentiation (AFD); linkage disequilibrium (LD); selective constraint at nonsynonymous sites; and genetic-tradeoff quantitative trait loci (GT-QTL). Our results indicate that contrary to genes showing a main effect in environment (E), expression genotype by environment interactions (GxE) show significantly higher AFD along cis-regulatory and nonsynonymous sites than the neutral expectation; and interestingly, highly differentiated GxE genes show higher expression and inter-species selective constraint than the rest of the genes. When examining the association between genomic signatures of selection along GxE/E genes and GT-QTL, we find that GxE genes showing a high AFD and LD, display a significant and much higher enrichment along GT-QTL than the genome-wide/E set of genes. Nonetheless, E genes show a higher enrichment than the genome-wide control. In summary, our results suggest, that these highly expressed and selectively constrained GxE genes, may have been part of a cold-responsive regulon of E genes that experienced recent selection when migrating to new environments. Candidate GxE genes underlying GT-QTL reveal interesting biological processes that may underlie local adaptation to temperature, including flowering time, light-dependent cold acclimation, freezing tolerance, and response to hypoxia. Finally, we find no evidence linking lower expression of the CBF-dependent freezing tolerance pathway to genetic-tradeoffs and adaptation to warmer climates.

Many genetic studies collect structured multivariate traits that have rich information about the traits encoded in trait covariates, in addition to the genotype and covariate information on individuals. Examples of such data include gene-environment studies where the same geno-type/clone is measured in multiple enviroments, and longitudinal studies where a measurement is taken at multiple time points. We present a flexible multivariate linear mixed model (fMulti-LMM) suitable for genetic analysis of structured multivariate traits. Our model can incorporate low- and high-dimensional trait covariates to test the genetic association across structured multiple traits while capturing the correlations due to individual-to-individual similarity measured by genome-wide markers and trait-to-trait similarity measured by trait covariates.

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.

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.

Carbon isotope ratio (δ13C) and root pulling force (RPF) are associated with dehydration avoidance in plants. The δ13C measures the efficiency of C gain relative to water loss, whereas RPF, the vertical force required to pull plants from the ground, indirectly estimates root‐related dehydration avoidance capacity. To determine quantitative trait loci (QTL) controlling these traits in canola (Brassica napus L.), a mapping population was evaluated in 2011 and 2012 in Fort Collins, CO. The split‐plot experiment had two moisture regimes (main plot) and 148 doubled haploid lines (subplot), replicated three times. Analysis of variance indicated highly significant (P

Explaining variation in life history strategies is a long-standing goal of evolutionary biology. For plants, annual and perennial life histories are thought to reflect adaptation to environments that differ in the frequency of stress events such as drought. Here we test this hypothesis in Heliophila (Brassicaceae), a diverse genus of flowering plants native to Africa, by integrating 34 years of satellite-based drought measurements with 2192 herbaria occurrence records. Consistent with predictions from classic life history theory, we find that perennial Heliophila species occur in environments where droughts are significantly less frequent compared to annuals. These associations are predictive while controlling for phylogeny, lending support to the hypothesis that drought related natural selection has influenced the distributions of these strategies. Additionally, the collection dates of annual and perennial species indicate that annuals escape drought prone seasons during the seed phase of their life cycle. Together, these findings provide empirical support for classic hypotheses about the drivers of life history strategy in plants - that perennials out compete annuals in environments with less frequent drought and that annuals are adapted to environments with more frequent drought by escaping drought prone seasons as seeds.

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., eLife digest Water shortages caused by droughts lead to crop losses that affect billions of people around the world each year. By discovering how wild plants adapt to drought, it may be possible to identify traits and genes that help to improve the growth of crop plants when water is scarce. It has been suggested that plants have adapted to droughts by flowering at times of the year when droughts are less likely to occur. For example, if droughts are more likely to happen in spring, the plants may delay flowering until the summer. Arabidopsis thaliana is a small plant that is found across Eurasia, Africa and North America, including in areas that are prone to drought at different times of the year. Individual plants of the same species may carry different versions of the same gene (known as alleles). Some of these alleles may not work properly and are referred to as loss-of-function alleles. Monroe et al. investigated whether A. thaliana plants carry any loss-of-function alleles that are associated with droughts happening in the spring or summer, and whether they are linked to when those plants will flower. Monroe et al. analyzed satellite images collected over the last 30 years to measure when droughts have occurred. Next, they searched genome sequences of Arabidopsis thaliana for alleles that might help the plants to adapt to droughts in the spring or summer. Combining the two approaches revealed that loss-of-function alleles associated with spring droughts were strongly predicted to be associated with the plants flowering later in the year. Similarly, loss-of-function alleles associated with summer droughts were predicted to be associated with the plants flowering earlier in the year. These findings support the idea that plants can adapt to drought by changing when they produce flowers, and suggest that loss-of-function alleles play a major role in this process. New techniques for editing genes mean it is easier than ever to generate new loss-of-function alleles in specific genes. Therefore, the results presented by Monroe et al. may help researchers to develop new varieties of crop plants that are better adapted to droughts.

Visions of a second green revolution empowered by emerging technologies have called for interdisciplinary syntheses to scale up the discovery of functionally definitive gene variants responsible for climate adaptation in plants. We integrated novel approaches using whole genome sequences and satellite remote sensing to identify natural knockout alleles associated with drought histories in wild Arabidopsis thaliana. Genes identified exhibit signatures of parallel molecular evolution, selection for loss-of-function alleles, and shared associations with flowering time phenotypes in directions consistent with longstanding adaptive hypotheses 7 times more often than expected by chance. Artificial knockout lines then confirmed predicted phenotypes experimentally. These findings further challenge popular assumptions about the adaptive value of genetic loss-of-function in nature and inspire new opportunities for engineering climate resilience in crops.One sentence summaryWhole genome sequences and satellite-detected droughts point to gene knockouts as valuable genetic fuel for climate adaptation.

1169 I. 1170 II. 1170 III. 1172 IV. 1176 V. 1181 VI. 1182 1183 References 1183 SUMMARY: Modern agriculture is facing multiple challenges including the necessity for a substantial increase in production to meet the needs of a burgeoning human population. Water shortage is a deleterious consequence of both population growth and climate change and is one of the most severe factors limiting global crop productivity. Brassica species, particularly canola varieties, are cultivated worldwide for edible oil, animal feed, and biodiesel, and suffer dramatic yield loss upon drought stress. The recent release of the Brassica napus genome supplies essential genetic information to facilitate identification of drought-related genes and provides new information for agricultural improvement in this species. Here we summarize current knowledge regarding drought responses of canola, including physiological and -omics effects of drought. We further discuss knowledge gained through translational biology based on discoveries in the closely related reference species Arabidopsis thaliana and through genetic strategies such as genome-wide association studies and analysis of natural variation. Knowledge of drought tolerance/resistance responses in canola together with research outcomes arising from new technologies and methodologies will inform novel strategies for improvement of drought tolerance and yield in this and other important crop species.

Drought stress imposes major limits on wheat (Triticum aestivum L.) yield and is predicted to increase in frequency due to climate change. The aim of this study was to explore the potential of synthetic hexaploid wheat (SHW) to improve productivity of winter wheat under drought stress. Six SHW lines and four winter wheat cultivars from the U.S. Great Plains were evaluated in 1 m × 10 cm plastic tubes under drought-stressed and well-watered conditions in a greenhouse study. Root morphology, biomass, stomatal attributes, plant water relations, and the response of these traits to drought stress were measured. Traits significantly (P

Soil water availability represents one of the most important selective agents for plants in nature and the single greatest abiotic determinant of agricultural productivity, yet the genetic bases of drought acclimation responses remain poorly understood. Here, we developed a systems-genetic approach to characterize quantitative trait loci (QTLs), physiological traits and genes that affect responses to soil moisture deficit in the TSUxKAS mapping population of Arabidopsis thaliana. To determine the effects of candidate genes underlying QTLs, we analyzed gene expression as a covariate within the QTL model in an effort to mechanistically link markers, RNA expression, and the phenotype. This strategy produced ranked lists of candidate genes for several drought-associated traits, including water use efficiency, growth, abscisic acid concentration (ABA), and proline concentration. As a proof of concept, we recovered known causal loci for several QTLs. For other traits, including ABA, we identified novel loci not previously associated with drought. Furthermore, we documented natural variation at two key steps in proline metabolism and demonstrated that the mitochondrial genome differentially affects genomic QTLs to influence proline accumulation. These findings demonstrate that linking genome, transcriptome, and phenotype data holds great promise to extend the utility of genetic mapping, even when QTL effects are modest or complex.

Significance Local adaptation can occur due to individual genetic variants that increase the fitness of individuals in their home environments but decrease fitness in other environments [genetic trade-offs (GTs)] or genetic variants that increase fitness in one environment but have no effect in other environments [conditional neutrality (CN)]. Here, we show that GT quantitative trait loci (QTLs) for fitness between Italian and Swedish Arabidopsis thaliana exhibit strong population genomic signatures of local adaptation, including elevated levels of allele frequency differentiation, correlations to climatic variables, and recent sweeps. Highly divergent genes between Italy and Sweden populations show evidence of more recent selection in Sweden than Italy, and the biological annotations of these genes suggest interesting mechanisms underlying local adaptation., 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.

The objective of this study was to determine if low stomatal conductance ( g ) increases growth, nitrate (NO 3 − ) assimilation, and nitrogen (N) utilization at elevated CO 2 concentration. Four Arabidopsis ( Arabidopsis thaliana ) near isogenic lines (NILs) differing in g were grown at ambient and elevated CO 2 concentration under low and high NO 3 − supply as the sole source of N. Although g varied by 32% among NILs at elevated CO 2 , leaf intercellular CO 2 concentration varied by only 4% and genotype had no effect on shoot NO 3 – concentration in any treatment. Low- g NILs showed the greatest CO 2 growth increase under N limitation but had the lowest CO 2 growth enhancement under N-sufficient conditions. NILs with the highest and lowest g had similar rates of shoot NO 3 – assimilation following N deprivation at elevated CO 2 concentration. After 5 d of N deprivation, the lowest g NIL had 27% lower maximum carboxylation rate and 23% lower photosynthetic electron transport compared with the highest g NIL. These results suggest that increased growth of low- g NILs under N limitation most likely resulted from more conservative N investment in photosynthetic biochemistry rather than from low g .

Breeding has transformed wild plant species into modern crops, increasing the allocation of their photosynthetic assimilate into grain, fiber, and other products for human use. Despite progress in increasing the harvest index, much of the biomass of crop plants is not utilized. Potential uses for the large amounts of agricultural residues that accumulate are animal fodder or bioenergy, though these may not be economically viable without additional efforts such as targeted breeding or improved processing. We characterized leaf and stem tissue from a diverse set of rice genotypes (varieties) grown in two environments (greenhouse and field) and report bioenergy-related traits across these variables. Among the 16 traits measured, cellulose, hemicelluloses, lignin, ash, total glucose, and glucose yield changed across environments, irrespective of the genotypes. Stem and leaf tissue composition differed for most traits, consistent with their unique functional contributions and suggesting that they are under separate genetic control. Plant variety had the least influence on the measured traits. High glucose yield was associated with high total glucose and hemicelluloses, but low lignin and ash content. Bioenergy yield of greenhouse-grown biomass was higher than field-grown biomass, suggesting that greenhouse studies overestimate bioenergy potential. Nevertheless, glucose yield in the greenhouse predicts glucose yield in the field (ρ = 0.85, p < 0.01) and could be used to optimize greenhouse (GH) and field breeding trials. Overall, efforts to improve cell wall composition for bioenergy require consideration of production environment, tissue type, and variety.

Flowering time and water-use efficiency (WUE) are two ecological traits that are important for plant drought response. To understand the evolutionary significance of natural genetic variation in flowering time, WUE, and WUE plasticity to drought in Arabidopsis thaliana, we addressed the following questions: (1) How are ecophysiological traits genetically correlated within and between different soil moisture environments? (2) Does terminal drought select for early flowering and drought escape? (3) Is WUE plasticity to drought adaptive and/or costly? We measured a suite of ecophysiological and reproductive traits on 234 spring flowering accessions of A. thaliana grown in well-watered and season-ending soil drying treatments, and quantified patterns of genetic variation, correlation, and selection within each treatment. WUE and flowering time were consistently positively genetically correlated. WUE was correlated with WUE plasticity, but the direction changed between treatments. Selection generally favored early flowering and low WUE, with drought favoring earlier flowering significantly more than well-watered conditions. Selection for lower WUE was marginally stronger under drought. There were no net fitness costs of WUE plasticity. WUE plasticity (per se) was globally neutral, but locally favored under drought. Strong genetic correlation between WUE and flowering time may facilitate the evolution of drought escape, or constrain independent evolution of these traits. Terminal drought favored drought escape in these spring flowering accessions of A. thaliana. WUE plasticity may be favored over completely fixed development in environments with periodic drought.

Highlight text This research is the first to examine the genetics of drought adaptive traits in Brassica napus and is supportive of an inherent trade-off between resource investment in reproduction and root development., Drought escape and dehydration avoidance represent alternative strategies for drought adaptation in annual crops. The mechanisms underlying these two strategies are reported to have a negative correlation, suggesting a trade-off. We conducted a quantitative trait locus (QTL) analysis of flowering time and root mass, traits representing each strategy, in Brassica napus to understand if a trade-off exists and what the genetic basis might be. Our field experiment used a genotyped population of doubled haploid lines and included both irrigated and rainfed treatments, allowing analysis of plasticity in each trait. We found strong genetic correlations among all traits, suggesting a trade-off among traits may exist. Summing across traits and treatments we found 20 QTLs, but many of these co-localized to two major QTLs, providing evidence that the trade-off is genetically constrained. To understand the mechanistic relationship between root mass, flowering time, and QTLs, we analysed the data by conditioning upon correlated traits. Our results suggest a causal model where such QTLs affect root mass directly as well as through their impacts on flowering time. Additionally, we used draft Brassica genomes to identify orthologues of well characterized Arabidopsis thaliana flowering time genes as candidate genes. This research provides valuable clues to breeding for drought adaptation as it is the first to analyse the inheritance of the root system in B. napus in relation to drought.

Transpiration is controlled by evaporative demand and stomatal conductance (gs), and there can be substantial genetic variation in gs. A key parameter in empirical models of transpiration is minimum stomatal conductance (g0), a trait that can be measured and has a large effect on gs and transpiration. In Arabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci (QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or ‘crop’ models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation.

Determining the relative contribution of population genetic processes to the distribution of natural variation is a major goal of evolutionary biology. Here, we take advantage of variation in mating system to test the hypothesis that local adaptation is constrained by asexual reproduction. We explored patterns of variation in ecological traits and genome-wide molecular markers in Boechera spatifolia (Brassicaceae), a species that contains both apomictic (asexual) and sexual individuals. Using a combination of quantitative genetics, neutral genetic (SSR) and genome-wide single nucleotide polymorphism, we assessed the hypothesis that asexual lineages should have reduced signatures of adaptation relative to sexual conspecifics. All three measures (traits, SSRs, SNPs) demonstrated that apomicts are genetically distinct from sexuals, regardless of population location. Additionally, phylogenetic clustering revealed that the apomictic group shared a single common ancestor. Across the landscape, sexual genome-wide SNP variation was strongly associated with latitude (r(2) > 0.9), indicating that sexual populations have differentiated across an environmental gradient. Furthermore, flowering time and growth rate, as assessed in a common garden, strongly covary with the elevation and latitude of the source population. Despite a wide geographic distribution that largely overlaps with sexual populations, there was little evidence for differentiation in molecular markers or quantitative characters among apomictic populations. Combined, these data indicated that, in contrast to asexual populations, sexual populations show evidence of local adaptation.

Plant water relations are critical for determining the distribution, persistence, and fitness of plant species. Studying the genetic basis of ecologically relevant traits, however, can be complicated by their complex genetic, physiological, and developmental basis and their interaction with the environment. Water use efficiency (WUE), the ratio of photosynthetic carbon assimilation to stomatal conductance to water, is a dynamic trait with tremendous ecological and agricultural importance whose genetic control is poorly understood. In the present study, we use a quantitative trait locus-mapping approach to locate, fine-map, clone, confirm, and characterize an allelic substitution that drives differences in WUE among natural accessions of Arabidopsis thaliana. We show that a single amino acid substitution in an abscisic acid-responsive kinase, AtMPK12, causes reduction in WUE, and we confirm its functional role using transgenics. We further demonstrate that natural alleles at AtMPK12 differ in their response to cellular and environmental cues, with the allele from the Cape Verde Islands (CVI) being less responsive to hormonal inhibition of stomatal opening and more responsive to short-term changes in vapor pressure deficit. We also show that the CVI allele results in constitutively larger stomata. Together, these differences cause higher stomatal conductance and lower WUE compared with the common allele. These physiological changes resulted in reduced whole-plant transpiration efficiency and reduced fitness under water-limited compared with well-watered conditions. Our work demonstrates how detailed analysis of naturally segregating functional variation can uncover the molecular and physiological basis of a key trait associated with plant performance in ecological and agricultural settings.

Organisms inhabiting different environments are often locally adapted, and yet despite a considerable body of theory, the genetic basis of local adaptation is poorly understood. Unanswered questions include the number and effect sizes of adaptive loci, whether locally favored loci reduce fitness elsewhere (i.e., fitness tradeoffs), and whether a lack of genetic variation limits adaptation. To address these questions, we mapped quantitative trait loci (QTL) for total fitness in 398 recombinant inbred lines derived from a cross between locally adapted populations of the highly selfing plant Arabidopsis thaliana from Sweden and Italy and grown for 3 consecutive years at the parental sites (>40,000 plants monitored). We show that local adaptation is controlled by relatively few genomic regions of small to modest effect. A third of the 15 fitness QTL we detected showed evidence of tradeoffs, which contrasts with the minimal evidence for fitness tradeoffs found in previous studies. This difference may reflect the power of our multiyear study to distinguish conditionally neutral QTL from those that reflect fitness tradeoffs. In Sweden, but not in Italy, the local genotype underlying fitness QTL was often maladaptive, suggesting that adaptation there is constrained by a lack of adaptive genetic variation, attributable perhaps to genetic bottlenecks during postglacial colonization of Scandinavia or to recent changes in selection regime caused by climate change. Our results suggest that adaptation to markedly different environments can be achieved through changes in relatively few genomic regions, that fitness tradeoffs are common, and that lack of genetic variation can limit adaptation.

The regulation of gene expression is crucial for an organism's development and response to stress, and an understanding of the evolution of gene expression is of fundamental importance to basic and applied biology. To improve this understanding, we conducted expression quantitative trait locus (eQTL) mapping in the Tsu-1 (Tsushima, Japan) × Kas-1 (Kashmir, India) recombinant inbred line population of Arabidopsis thaliana across soil drying treatments. We then used genome resequencing data to evaluate whether genomic features (promoter polymorphism, recombination rate, gene length, and gene density) are associated with genes responding to the environment (E) or with genes with genetic variation (G) in gene expression in the form of eQTLs. We identified thousands of genes that responded to soil drying and hundreds of main-effect eQTLs. However, we identified very few statistically significant eQTLs that interacted with the soil drying treatment (GxE eQTL). Analysis of genome resequencing data revealed associations of several genomic features with G and E genes. In general, E genes had lower promoter diversity and local recombination rates. By contrast, genes with eQTLs (G) had significantly greater promoter diversity and were located in genomic regions with higher recombination. These results suggest that genomic architecture may play an important a role in the evolution of gene expression.

Over the last two decades, Aegilops triuncialis (barbed goatgrass) has rapidly spread into many annual grassland and serpentine soil sites within California, USA. The capacity of this species to invade edaphically stressful serpentine soil is especially unusual. It is unclear whether genetic differentiation, phenotypic plasticity, or both have allowed A. triuncialis to invade competitive (i.e. high productivity non-serpentine annual grassland) and edaphically stressful (i.e. low productivity serpentine) environments. We used a reciprocal transplant field experiment to examine the effects of plasticity and genetic variation on A. triuncialis phenology and demography along invasion fronts associated with interspecific competition and edaphic gradients. We reciprocally transplanted seeds collected behind invasion fronts (core subpopulations) and along invasion fronts (edge subpopulations). For both gradient types we measured higher reproduction and population growth at invasion front edges. This was true for both edge and core subpopulation seed sources, suggesting that phenotypic plasticity may facilitate invasive spread. Consistent planting site effects indicated that phenotypic plasticity is a primary contributor to A. triuncialis demographic responses along interspecific competition gradients. In contrast, significant seed source effects suggest genetic differentiation along invasion fronts in serpentine edaphic gradients. Although persistent maternal environmental effects cannot be ruled out entirely, seed source effects suggest genetic differences between serpentine subpopulations located behind and beyond the invasion fronts for plant survival, plant size, total seed production, and individual seed size. Rapid expansion of A. triuncialis in California may reflect an evolutionary capacity in this species for both phenotypic plasticity and genetic differentiation.

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.

a b s t r a c t Aegilops cylindrica Host (jointed goatgrass) is an exotic invasive weed in the western United States that causes economic loss due to competition with winter wheat (Triticum aestivum L.) and contamination of wheat grain. Further, because Ae. cylindrica is a wild relative of wheat, interspecific hybridization is a possible mechanism for the introgression of advantageous genes from wheat to the weedy species. The risk of introgression of traits conferring environmental stress tolerance, such as drought tolerance, from transgenic wheat has not been studied and is of high concern because it could increase the weed's competitiveness with wheat, as well as its ability to invade novel habitats. Genetic diversity has been reported among western U.S. Ae. cylindrica accessions, however, studies to determine whether genetic diversity relates to phenotypic diversity have been limited. Here, 30 accessions of Ae. cylindrica from the western U.S. were evaluated over two years at two Colorado locations: Haxtun in 2008-2009 and Fort Collins in 2009-2010. Days to flowering, plant height, number of tillers produced per plant, number of spikelets per spike, and number of spikelets per plant were evaluated under rain-fed and irrigated conditions. Results indicate significant (P < 0.01) variation among accessions for each of the traits for both years. Additionally, in 2009-2010 there was a significant (P < 0.01) effect of irrigation on all traits, except days to flowering. Similarly, all traits except days to flowering showed a significant effect of the interaction of accession with treatment (P < 0.05) in 2009-2010. The study shows that variation exists in traits related to competitive ability and fitness. Our data also suggest differences among accessions in sensitivity to water availability. This observation needs to be confirmed in additional environments. Implications of our results for evaluation of transgene introgression are discussed. © 2012 Elsevier B.V. All rights reserved.

The lack of resistant source has greatly restrained resistance breeding of rapeseed (Brassica napus, AACC) against Sclerotinia sclerotiorum which causes severe yield losses in rapeseed production all over the world. Recently, several wild Brassica oleracea accessions (CC) with high level of resistance have been identified (Mei et al. in Euphytica 177:393-400, 2011), bringing a new hope to improve Sclerotinia resistance of rapeseed. To map quantitative trait loci (QTL) for Sclerotinia resistance from wild B. oleracea, an F2 population consisting of 149 genotypes, with several clones of each genotypes, was developed from one F1 individual derived from the cross between a resistant accession of wild B. oleracea (B. incana) and a susceptible accession of cultivated B. oleracea var. alboglabra. The F2 population was evaluated for Sclerotinia reaction in 2009 and 2010 under controlled condition. Significant differences among genotypes and high heritability for leaf and stem reaction indicated that genetic components accounted for a large portion of the phenotypic variance. A total of 12 QTL for leaf resistance and six QTL for stem resistance were identified in 2 years, each explaining 2.2-28.4 % of the phenotypic variation. The combined effect of alleles from wild B. oleracea reduced the relative susceptibility by 22.5 % in leaves and 15 % in stems on average over 2 years. A 12.8-cM genetic region on chromosome C09 of B. oleracea consisting of two major QTL intervals for both leaf and stem resistance was assigned into a 2.7-Mb genomic region on chromosome A09 of B. rapa, harboring about 30 putative resistance-related genes. Significant negative corrections were found between flowering time and relative susceptibility of leaf and stem. The association of flowering time with Sclerotinia resistance is discussed.

Genomic data have the potential to revolutionize the delineation of conservation units (CUs) by allowing the detection of adaptive genetic variation, which is otherwise difficult for rare, endangered species. In contrast to previous recommendations, we propose that the use of neutral versus adaptive markers should not be viewed as alternatives. Rather, neutral and adaptive markers provide different types of information that should be combined to make optimal management decisions. Genetic patterns at neutral markers reflect the interaction of gene flow and genetic drift that affects genome-wide variation within and among populations. This population genetic structure is what natural selection operates on to cause adaptive divergence. Here, we provide a new framework to integrate data on neutral and adaptive markers to protect biodiversity.

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.

Jointed goatgrass is an exotic species introduced into the western United States from Eurasia. The weed is an agricultural pest infesting winter wheat fields and causing economic loss. Common ancestry between the two species enables interspecific hybridization, thus providing a mechanism for gene flow to occur. This can facilitate the accumulation of novel genes, which could increase the wild species' competitiveness with wheat and its ability to invade novel habitats. Interest in the development of transgenic wheat cultivars has increased the concern for interspecific gene flow. Gene introgression requires recurrent backcrossing to the weedy species after the initial hybridization event. Field experiments were conducted at two locations in Colorado in 2007–2008 and 2008–2009, with jointed goatgrass acting as the sole source of viable pollen for fertilization of transplanted hybrid plants. Backcrossing rates were determined by conducting germination studies on spikes collected from a total of 206 hybrid plants. Pollination by jointed goatgrass led to the production of 463 BC1plants from seed produced on these 206 hybrid plants. Ninety-five percent confidence intervals estimate the rate of backcrossing at 0.028 to 0.306% and 0.077 to 0.604%, with medians of 0.062 and 0.152%, respectively, at the two locations. The results demonstrate that backcrossing to jointed goatgrass can occur, despite low rates of hybrid fertility. Subsequent backcrossing would make it likely that a wheat gene conferring a selective advantage will introgress into the weedy population. For the U.S. Great Plains, it is possible that transgenic wheat cultivars will be released in the future and determining proper management of these cultivars is necessary to minimize hybridization and advantageous gene introgression into weedy relatives.

Biofuels provide a promising route of producing energy while reducing reliance on petroleum. Developing sustainable liquid fuel production from cellulosic feedstock is a major challenge and will require significant breeding efforts to maximize plant biomass production. Our approach to elucidating genes and genetic pathways that can be targeted for improving biomass production is to exploit the combination of genomic tools and genetic diversity in rice (Oryza sativa). In this study, we analyzed a diverse set of 20 recently resequenced rice varieties for variation in biomass traits at several different developmental stages. The traits included plant size and architecture, aboveground biomass, and underlying physiological processes. We found significant genetic variation among the 20 lines in all morphological and physiological traits. Although heritability estimates were significant for all traits, heritabilities were higher in traits relating to plant size and architecture than for physiological traits. Trait variation was largely explained by variety and breeding history (advanced versus landrace) but not by varietal groupings (indica, japonica, and aus). In the context of cellulosic biofuels development, cell wall composition varied significantly among varieties. Surprisingly, photosynthetic rates among the varieties were inversely correlated with biomass accumulation. Examining these data in an evolutionary context reveals that rice varieties have achieved high biomass production via independent developmental and physiological pathways, suggesting that there are multiple targets for biomass improvement. Future efforts to identify loci and networks underlying this functional variation will facilitate the improvement of biomass traits in other grasses being developed as energy crops.