Long-term climate change and periodic environmental extremes threaten food and fuel security¹and global crop productivity^2–4. Although molecular and adaptive breeding strategies can buffer the effects of climatic stress and improve crop resilience⁵, these approaches require sufficient knowledge of the genes that underlie productivity and adaptation⁶—knowledge that has been limited to a small number of well-studied model systems. Here we present the assembly and annotation of the large and complex genome of the polyploid bioenergy crop switchgrass (Panicum virgatum). Analysis of biomass and survival among 732 resequenced genotypes, which were grown across 10 common gardens that span 1,800 km of latitude, jointly revealed extensive genomic evidence of climate adaptation. Climate–gene–biomass associations were abundant but varied considerably among deeply diverged gene pools. Furthermore, we found that gene flow accelerated climate adaptation during the postglacial colonization of northern habitats through introgression of alleles from a pre-adapted northern gene pool. The polyploid nature of switchgrass also enhanced adaptive potential through the fractionation of gene function, as there was an increased level of heritable genetic diversity on the nondominant subgenome. In addition to investigating patterns of climate adaptation, the genome resources and gene–trait associations developed here provide breeders with the necessary tools to increase switchgrass yield for the sustainable production of bioenergy.

Plants demonstrate a broad range of responses to environmental shifts. One of the most remarkable responses is plasticity, which is the ability of a single plant genotype to produce different phenotypes in response to environmental stimuli. As with all traits, the ability of plasticity to evolve depends on the presence of underlying genetic diversity within a population. A common approach for evaluating the role of genetic variation in driving differences in plasticity has been to study genotype-by-environment interactions (G × E). G × E occurs when genotypes produce different phenotypic trait values in response to different environments. In this review, we highlight progress and promising methods for identifying the key environmental and genetic drivers of G × E. Specifically, methodological advances in using algorithmic and multivariate approaches to understand key environmental drivers combined with new genomic innovations can greatly increase our understanding about molecular responses to environmental stimuli. These developing approaches can be applied to proliferating common garden networks that capture broad natural environmental gradients to unravel the underlying mechanisms of G × E. An increased understanding of G × E can be used to enhance the resilience and productivity of agronomic systems.

We present unresolved questions in plant abiotic stress biology as posed by 15 research groups with expertise spanning eco-physiology to cell and molecular biology. Common themes of these questions include the need to better understand how plants detect water availability, temperature, salinity, and rising carbon dioxide (CO₂) levels; how environmental signals interface with endogenous signaling and development (e.g. circadian clock and flowering time); and how this integrated signaling controls downstream responses (e.g. stomatal regulation, proline metabolism, and growth versus defense balance). The plasma membrane comes up frequently as a site of key signaling and transport events (e.g. mechanosensing and lipid-derived signaling, aquaporins). Adaptation to water extremes and rising CO₂ affects hydraulic architecture and transpiration, as well as root and shoot growth and morphology, in ways not fully understood. Environmental adaptation involves tradeoffs that limit ecological distribution and crop resilience in the face of changing and increasingly unpredictable environments. Exploration of plant diversity within and among species can help us know which of these tradeoffs represent fundamental limits and which ones can be circumvented by bringing new trait combinations together. Better defining what constitutes beneficial stress resistance in different contexts and making connections between genes and phenotypes, and between laboratory and field observations, are overarching challenges.

Water limitation is one of the most important factors limiting crop productivity world‐wide and has likely been an important selective regime influencing the evolution of plant physiology. Understanding the genetic and physiological basis of drought adaptation is therefore important for improving crops as well as for understanding the evolution of wild species. Here, results are presented from quantitative trait loci (QTL) mapping of flowering time (a drought escape mechanism) and carbon stable isotope ratio (δ¹³C) (a drought‐avoidance mechanism) in Arabidopsis thaliana. Whole‐genome scans were performed using multiple‐QTL models for both additive and epistatic QTL effects. We mapped five QTL affecting flowering time and five QTL affecting δ¹³C, but two genomic regions contained QTL with effects on both traits, suggesting a potential pleiotropic relationship. In addition, we observed QTL–QTL interaction for both traits. Two δ¹³C QTL were captured in near‐isogenic lines to further characterize their physiological basis. These experiments revealed allelic effects on δ¹³C through the upstream trait of stomatal conductance with subsequent consequences for whole plant transpiration efficiency and water loss. Our findings document considerable natural genetic variation in whole‐plant, drought resistance physiology of Arabidopsis and highlight the value of quantitative genetic approaches for exploring functional relationships regulating physiology.

Environmental stress is a major driver of ecological community dynamics and agricultural productivity. This is especially true for soil water availability, because drought is the greatest abiotic inhibitor of worldwide crop yields. Here, we test the genetic basis of drought responses in the genetic model for C₄ perennial grasses, Panicum hallii, through population genomics, field-scale gene-expression (eQTL) analysis, and comparison of two complete genomes. While gene expression networks are dominated by local cis-regulatory elements, we observe three genomic hotspots of unlinked trans-regulatory loci. These regulatory hubs are four times more drought responsive than the genome-wide average. Additionally, cis- and trans-regulatory networks are more likely to have opposing effects than expected under neutral evolution, supporting a strong influence of compensatory evolution and stabilizing selection. These results implicate trans-regulatory evolution as a driver of drought responses and demonstrate the potential for crop improvement in drought-prone regions through modification of gene regulatory networks.

Arabidopsis thaliana, like many species, is characterized by abundant genetic variation. This variation is rapidly being cataloged at the sequence level, but careful dissection of genetic variation in whole-organism responses to stresses encountered in the natural environment are lacking; this functional variation can be exploited as a natural mutant screen to determine gene function. Here, we document physiological and transcriptomic response to soil drying in 17 natural accessions of Arabidopsis. By imposing ecologically realistic stress conditions, we found that acclimation in Arabidopsis involved a strong signature of increased investment in photosynthesis, carbohydrate turnover, and root growth. Our results extend previous work in the Columbia accession suggesting that abscisic acid signaling pathways play an important role in drought stress response. We also identified several mechanisms, including an increase in leaf nitrogen concentration and upregulation of two-component signaling relays, that were common to most natural accessions but had not been identified in studies using only the Columbia accession. Principal component analysis reveals strong correlations between suites of genes and specific physiological responses to stress. The functional variants we identified may represent adaptive mutations in natural habitats and useful variants for agronomic improvement of crop species.