Phenotypic and genome-wide association with the local environment of Arabidopsis

Agricultural landscape genomics to increase crop resilience

Populations are continually adapting to their environment. Knowledge of which populations and individuals harbor unique and agriculturally useful variations has the potential to accelerate crop adaptation to the increasingly challenging environments predicted for the coming century. Landscape genomics, which identifies associations between environmental and genomic variation, provides a means for obtaining this knowledge. However, despite extensive efforts to assemble and characterize ex situ collections of crops and their wild relatives, gaps remain in the genomic and environmental datasets needed to robustly implement this approach. This article outlines the history of landscape genomics, which, to date, has mainly been used in conservation and evolutionary studies, provides an overview of crops and wild relative collections that have the necessary data for implementation and identifies areas where new data generation is needed. We find that 60% of the crops covered by the International Treaty on Plant Genetic Resources for Food and Agriculture lack the data necessary to conduct this kind of analysis, necessitating identification of crops in need of more collections, sequencing, or phenotyping. By highlighting these aspects, we aim to help develop agricultural landscape genomics as a sub-discipline that brings together evolutionary genetics, landscape ecology, and plant breeding, ultimately enhancing the development of resilient and adaptable crops for future environmental challenges.

Warm temperature perceived at the vegetative stage affects progeny seed germination in natural accessions of Arabidopsis thaliana

Temperatures perceived early in the life cycle of mother plants can affect the germination of the offspring seeds. In Arabidopsis thaliana, vernalisation-insensitive mutants showed altered germination response to elevated maternal temperature, hence revealing a strong genetic determinism. However, the genetic control of this maternal effect and its prevalence across natural populations remain unclear. Here, we exposed a collection of European accessions of A. thaliana to increased temperature during the vegetative phase and assessed germination in their progeny to identify the genetic basis of transgenerational germination response. We found that genotypes with rapidly germinating progeny after early maternal exposure to elevated temperature originated from regions with low-light radiation. Combining genome-wide association, expression analysis and functional assays across multiple genetic backgrounds, we show a central role for PHYB in mediating the response to maternally perceived temperature at the vegetative stage. Differential gene expression analysis in leaves identified a similar genetic network as previously found in seed endosperm under elevated temperature, supporting the pleiotropic involvement of PHYB signalling across different tissues and stages. This provides evidence that complex environmental responses modulated by the maternal genotype can rely on a consistent set of genes yet produce different effects at the different stages of exposure.

Enhancing Crop Resilience: The Role of Plant Genetics, Transcription Factors, and Next-Generation Sequencing in Addressing Salt Stress

Salt stress is a major abiotic stressor that limits plant growth, development, and agricultural productivity, especially in regions with high soil salinity. With the increasing salinization of soils due to climate change, developing salt-tolerant crops has become essential for ensuring food security. This review consolidates recent advances in plant genetics, transcription factors (TFs), and next-generation sequencing (NGS) technologies that are pivotal for enhancing salt stress tolerance in crops. It highlights critical genes involved in ion homeostasis, osmotic adjustment, and stress signaling pathways, which contribute to plant resilience under saline conditions. Additionally, specific TF families, such as DREB, NAC (NAM, ATAF, and CUC), and WRKY, are explored for their roles in activating salt-responsive gene networks. By leveraging NGS technologies-including genome-wide association studies (GWASs) and RNA sequencing (RNA-seq)-this review provides insights into the complex genetic basis of salt tolerance, identifying novel genes and regulatory networks that underpin adaptive responses. Emphasizing the integration of genetic tools, TF research, and NGS, this review presents a comprehensive framework for accelerating the development of salt-tolerant crops, contributing to sustainable agriculture in saline-prone areas.

Allelic variants confer Arabidopsis adaptation to small regional environmental differences

Natural populations of Arabidopsis thaliana provide powerful systems to study the adaptation of wild plant species. Previous research has predominantly focused on global populations or accessions collected from regions with diverse climates. However, little is known about the genetics underlying adaptation in regions with mild environmental clines. We have examined a diversity panel consisting of 192 A. thaliana accessions collected from the Netherlands, a region with limited climatic variation. Despite the relatively uniform climate, we identified evidence of local adaptation within this population. Notably, semidwarf accessions, due to mutation of the GIBBERELLIC ACID REQUIRING 5 (GA5) gene, occur at a relatively high frequency near the coast and these displayed enhanced tolerance to high wind velocities. Additionally, we evaluated the performance of the population under iron deficiency conditions and found that allelic variation in the FE SUPEROXIDE DISMUTASE 3 (FSD3) gene affects tolerance to low iron levels. Moreover, we explored patterns of local adaptation to environmental clines in temperature and precipitation, observing that allelic variation at LA RELATED PROTEIN 1C (LARP1c) likely affects drought tolerance. Not only is the genetic variation observed in a diversity panel of A. thaliana collected in a region with mild environmental clines comparable to that in collections sampled over larger geographic ranges but it is also sufficiently rich to elucidate the genetic and environmental factors underlying natural plant adaptation.

Tracing the Evolutionary History of the Temperature-Sensing Prion-like Domain in EARLY FLOWERING 3 Highlights the Uniqueness of AtELF3

Plants have evolved mechanisms to anticipate and adjust their growth and development in response to environmental changes. Understanding the key regulators of plant performance is crucial to mitigate the negative influence of global climate change on crop production. EARLY FLOWERING 3 (ELF3) is one such regulator playing a critical role in the circadian clock and thermomorphogenesis. In Arabidopsis thaliana, ELF3 contains a prion-like domain (PrLD) that acts as a thermosensor, facilitating liquid-liquid phase separation at high ambient temperatures. To assess the conservation of this function across the plant kingdom, we traced the evolutionary emergence of ELF3, with a focus on the presence of PrLDs. We found that the PrLD, primarily influenced by the length of polyglutamine (polyQ) repeats, is most prominent in Brassicales. Analyzing 319 natural A. thaliana accessions, we confirmed the previously described wide range of polyQ length variation in AtELF3, but found it to be only weakly associated with geographic origin, climate conditions, and classic temperature-responsive phenotypes. Interestingly, similar polyQ length variation was not observed in several other investigated Bassicaceae species. Based on these findings, available prediction tools and limited experimental evidence, we conclude that the emergence of PrLD, and particularly polyQ length variation, is unlikely to be a key driver of environmental adaptation. Instead, it likely adds an additional layer to ELF3's role in thermomorphogenesis in A. thaliana, with its relevance in other species yet to be confirmed.

Dual-trait genomic analysis in highly stratified Arabidopsis thaliana populations using genome-wide association summary statistics

Genome-wide association study (GWAS) is a powerful tool to identify genomic loci underlying complex traits. However, the application in natural populations comes with challenges, especially power loss due to population stratification. Here, we introduce a bivariate analysis approach to a GWAS dataset of Arabidopsis thaliana. We demonstrate the efficiency of dual-phenotype analysis to uncover hidden genetic loci masked by population structure via a series of simulations. In real data analysis, a common allele, strongly confounded with population structure, is discovered to be associated with late flowering and slow maturation of the plant. The discovered genetic effect on flowering time is further replicated in independent datasets. Using Mendelian randomization analysis based on summary statistics from our GWAS and expression QTL scans, we predicted and replicated a candidate gene AT1G11560 that potentially causes this association. Further analysis indicates that this locus is co-selected with flowering-time-related genes. The discovered pleiotropic genotype-phenotype map provides new insights into understanding the genetic correlation of complex traits.

Biologically meaningful genome interpretation models to address data underdetermination for the leaf and seed ionome prediction in Arabidopsis thaliana

Genome interpretation (GI) encompasses the computational attempts to model the relationship between genotype and phenotype with the goal of understanding how the first leads to the second. While traditional approaches have focused on sub-problems such as predicting the effect of single nucleotide variants or finding genetic associations, recent advances in neural networks (NNs) have made it possible to develop end-to-end GI models that take genomic data as input and predict phenotypes as output. However, technical and modeling issues still need to be fixed for these models to be effective, including the widespread underdetermination of genomic datasets, making them unsuitable for training large, overfitting-prone, NNs. Here we propose novel GI models to address this issue, exploring the use of two types of transfer learning approaches and proposing a novel Biologically Meaningful Sparse NN layer specifically designed for end-to-end GI. Our models predict the leaf and seed ionome in A.thaliana, obtaining comparable results to our previous over-parameterized model while reducing the number of parameters by 8.8 folds. We also investigate how the effect of population stratification influences the evaluation of the performances, highlighting how it leads to (1) an instance of the Simpson's Paradox, and (2) model generalization limitations.

Natural variation in CYCLIC NUCLEOTIDE-GATED ION CHANNEL 4 reveals a novel role of calcium signaling in vegetative phase change in Arabidopsis

The timing of vegetative phase change (VPC) in plants is regulated by a temporal decline in the expression of miR156. Both exogenous cues and endogenous factors, such as temperature, light, sugar, nutrients, and epigenetic regulators, have been shown to affect VPC by altering miR156 expression. However, the genetic basis of natural variation in VPC remains largely unexplored. Here, we conducted a genome-wide association study on the variation of the timing of VPC in Arabidopsis. We identified CYCLIC NUCLEOTIDE-GATED ION CHANNEL 4 (CNGC4) as a significant locus associated with the diversity of VPC. Mutations in CNGC4 delayed VPC, accompanied by an increased expression level of miR156 and a corresponding decrease in SQUAMOSA PROMOTER BINDING-LIKE (SPL) gene expression. Furthermore, mutations in CNGC2 and CATION EXCHANGER 1/3 (CAX1/3) also led to a delay in VPC. Polymorphisms in the CNGC4 promoter contribute to the natural variation in CNGC4 expression and the diversity of VPC. Specifically, the early CNGC4 variant promotes VPC and enhances plant adaptation to local environments. In summary, our findings offer genetic insights into the natural variation in VPC in Arabidopsis, and reveal a previously unidentified role of calcium signaling in the regulation of VPC.

Oryza CLIMtools: A genome-environment association resource reveals adaptive roles for heterotrimeric G proteins in the regulation of rice agronomic traits

Modern crop varieties display a degree of mismatch between their current distributions and the suitability of the local climate for their productivity. To address this issue, we present Oryza CLIMtools (https://gramene.org/CLIMtools/oryza_v1.0/), the first resource for pan-genome prediction of climate-associated genetic variants in a crop species. Oryza CLIMtools consists of interactive web-based databases that enable the user to (1) explore the local environments of traditional rice varieties (landraces) in South-East Asia and (2) investigate the environment by genome associations for 658 Indica and 283 Japonica rice landrace accessions collected from georeferenced local environments and included in the 3K Rice Genomes Project. We demonstrate the value of these resources by identifying an interplay between flowering time and temperature in the local environment that is facilitated by adaptive natural variation in OsHD2 and disrupted by a natural variant in OsSOC1. Prior quantitative trait locus analysis has suggested the importance of heterotrimeric G proteins in the control of agronomic traits. Accordingly, we analyzed the climate associations of natural variants in the different heterotrimeric G protein subunits. We identified a coordinated role of G proteins in adaptation to the prevailing potential evapotranspiration gradient and revealed their regulation of key agronomic traits, including plant height and seed and panicle length. We conclude by highlighting the prospect of targeting heterotrimeric G proteins to produce climate-resilient crops.

Genome-wide association study identifies a novel BMI1A QTL allele that confers FLC expression diversity in Arabidopsis thaliana

Identification and understanding of the genetic basis of natural variations in plants are essential for comprehending their phenotypic adaptation. Here, we report a genome-wide association study (GWAS) of FLOWERING LOCUS C (FLC) expression in 727 Arabidopsis accessions. We identified B LYMPHOMA MOLONEY MURINE LEUKEMIA VIRUS INSERTION REGION 1 HOMOLOG 1A (BMI1A) as a causal gene for one of the FLC expression quantitative trait loci (QTLs). Loss of function in BMI1A increases FLC expression and delays flowering time at 16 °C significantly compared with the wild type (Col-0). BMI1A activity is required for histone H3 lysine 27 trimethylation (H3K27me3) accumulation at the FLC, MADS AFFECTING FLOWERING 4 (MAF4), and MAF5 loci at low ambient temperature. We further uncovered two BMI1A haplotypes associated with the natural variation in FLC expression and flowering time at 16 °C, and demonstrated that polymorphisms in the BMI1A promoter region are the main contributor. Different BMI1A haplotypes are strongly associated with geographical distribution, and the low ambient temperature-sensitive BMI1A variants are associated with a lower mean temperature of the driest quarter of their collection sites compared with the temperature-non-responsive variants, indicating that the natural variations in BMI1A have adaptive functions in FLC expression and flowering time regulation. Therefore, our results provide new insights into the natural variations in FLC expression and flowering time diversity in plants.

Oryza CLIMtools: A Genome-Environment Association Resource Reveals Adaptive Roles for Heterotrimeric G Proteins in the Regulation of Rice Agronomic Traits

Modern crop varieties display a degree of mismatch between their current distributions and the suitability of the local climate for their productivity. To this end, we present Oryza CLIMtools (https://gramene.org/CLIMtools/oryza_v1.0/), the first resource for pan-genome prediction of climate-associated genetic variants in a crop species. Oryza CLIMtools consists of interactive web-based databases that allow the user to: i) explore the local environments of traditional rice varieties (landraces) in South-Eastern Asia, and; ii) investigate the environment by genome associations for 658 Indica and 283 Japonica rice landrace accessions collected from georeferenced local environments and included in the 3K Rice Genomes Project. We exemplify the value of these resources, identifying an interplay between flowering time and temperature in the local environment that is facilitated by adaptive natural variation in OsHD2 and disrupted by a natural variant in OsSOC1. Prior QTL analysis has suggested the importance of heterotrimeric G proteins in the control of agronomic traits. Accordingly, we analyzed the climate associations of natural variants in the different heterotrimeric G protein subunits. We identified a coordinated role of G proteins in adaptation to the prevailing Potential Evapotranspiration gradient and their regulation of key agronomic traits including plant height and seed and panicle length. We conclude by highlighting the prospect of targeting heterotrimeric G proteins to produce crops that are climate resilient.

Genetic adaptations in the population history of Arabidopsis thaliana

A population encounters a variety of environmental stresses, so the full source of its resilience can only be captured by collecting all the signatures of adaptation to the selection of the local environment in its population history. Based on the multiomic data of Arabidopsis thaliana, we constructed a database of phenotypic adaptations (p-adaptations) and gene expression (e-adaptations) adaptations in the population. Through the enrichment analysis of the identified adaptations, we inferred a likely scenario of adaptation that is consistent with the biological evidence from experimental work. We analyzed the dynamics of the allele frequencies at the 23,880 QTLs of 174 traits and 8,618 eQTLs of 1,829 genes with respect to the total SNPs in the genomes and identified 650 p-adaptations and 3,925 e-adaptations [false discovery rate (FDR) = 0.05]. The population underwent large-scale p-adaptations and e-adaptations along 4 lineages. Extremely cold winters and short summers prolonged seed dormancy and expanded the root system architecture. Low temperatures prolonged the growing season, and low light intensity required the increased chloroplast activity. The subtropical and humid environment enhanced phytohormone signaling pathways in response to the biotic and abiotic stresses. Exposure to heavy metals selected alleles for lower heavy metal uptake from soil, lower growth rate, lower resistance to bacteria, and higher expression of photosynthetic genes were selected. The p-adaptations are directly interpretable, while the coadapted gene expressions reflect the physiological requirements for the adaptation. The integration of this information characterizes when and where the population has experienced environmental stress and how the population responded at the molecular level.

Indirect genetic effects are shaped by demographic history and ecology in Arabidopsis thaliana

The phenotype of an individual can be affected by the genes of its conspecifics through indirect genetic effects (IGEs). IGEs have been studied across different organisms including wild and domesticated animals and plants, but little is known about their genetic architecture. Here, in a large-scale intraspecific interaction experiment, we show that the contribution of IGEs to the biomass variation of Arabidopsis thaliana is comparable to values classically reported in animals. Moreover, we identify 11 loci explaining 85.1% of the variability in IGEs. We find that positive IGE alleles (that is, those with positive effects on neighbour biomass) occur both in relict accessions from southern Eurasia and in post-glacial colonizers from northern Scandinavia, and that they are likely to have two divergent origins: for nine loci, they evolved in the post-glacial colonizers independently from the relicts, while the two others were introgressed in the post-glacial colonizer from the relicts. Finally, we find that variation in IGEs probably reflects divergent adaptations to the contrasting environments of the edges and the centre of the native range of the species. These findings reveal a surprisingly tractable genetic basis of IGEs in A. thaliana that is shaped by the ecology and the demographic history of the species.

Genome-wide association study unveils ascorbate regulation by PAS/LOV PROTEIN during high light acclimation

Varying light conditions elicit metabolic responses as part of acclimation with changes in ascorbate levels being an important component. Here, we adopted a genome-wide association-based approach to characterize the response in ascorbate levels on high light (HL) acclimation in a panel of 315 Arabidopsis (Arabidopsis thaliana) accessions. These studies revealed statistically significant SNPs for total and reduced ascorbate under HL conditions at a locus in chromosome 2. Ascorbate levels under HL and the region upstream and within PAS/LOV PROTEIN (PLP) were strongly associated. Intriguingly, subcellular localization analyses revealed that the PLPA and PLPB splice variants co-localized with VITAMIN C DEFECTIVE2 (VTC2) and VTC5 in both the cytosol and nucleus. Yeast 2-hybrid and bimolecular fluorescence complementation analyses revealed that PLPA and PLPB interact with VTC2 and that blue light diminishes this interaction. Furthermore, PLPB knockout mutants were characterized by 1.5- to 1.7-fold elevations in their ascorbate levels, whereas knockout mutants of the cry2 cryptochromes displayed 1.2- to 1.3-fold elevations compared to WT. Our results collectively indicate that PLP plays a critical role in the elevation of ascorbate levels, which is a signature response of HL acclimation. The results strongly suggest that this is achieved via the release of the inhibitory effect of PLP on VTC2 upon blue light illumination, as the VTC2-PLPB interaction is stronger under darkness. The conditional importance of the cryptochrome receptors under different environmental conditions suggests a complex hierarchy underpinning the environmental control of ascorbate levels. However, the data we present here clearly demonstrate that PLP dominates during HL acclimation.

Crop adaptation to climate change: An evolutionary perspective

The disciplines of evolutionary biology and plant and animal breeding have been intertwined throughout their development, with responses to artificial selection yielding insights into the action of natural selection and evolutionary biology providing statistical and conceptual guidance for modern breeding. Here we offer an evolutionary perspective on a grand challenge of the 21st century: feeding humanity in the face of climate change. We first highlight promising strategies currently under way to adapt crops to current and future climate change. These include methods to match crop varieties with current and predicted environments and to optimize breeding goals, management practices, and crop microbiomes to enhance yield and sustainable production. We also describe the promise of crop wild relatives and recent technological innovations such as speed breeding, genomic selection, and genome editing for improving environmental resilience of existing crop varieties or for developing new crops. Next, we discuss how methods and theory from evolutionary biology can enhance these existing strategies and suggest novel approaches. We focus initially on methods for reconstructing the evolutionary history of crops and their pests and symbionts, because such historical information provides an overall framework for crop-improvement efforts. We then describe how evolutionary approaches can be used to detect and mitigate the accumulation of deleterious mutations in crop genomes, identify alleles and mutations that underlie adaptation (and maladaptation) to agricultural environments, mitigate evolutionary trade-offs, and improve critical proteins. Continuing feedback between the evolution and crop biology communities will ensure optimal design of strategies for adapting crops to climate change.

Metabolome plasticity in 241 Arabidopsis thaliana accessions reveals evolutionary cold adaptation processes

Acclimation and adaptation of metabolism to a changing environment are key processes for plant survival and reproductive success. In the present study, 241 natural accessions of Arabidopsis (Arabidopsis thaliana) were grown under two different temperature regimes, 16 °C and 6 °C, and growth parameters were recorded, together with metabolite profiles, to investigate the natural genome × environment effects on metabolome variation. The plasticity of metabolism, which was captured by metabolic distance measures, varied considerably between accessions. Both relative growth rates and metabolic distances were predictable by the underlying natural genetic variation of accessions. Applying machine learning methods, climatic variables of the original growth habitats were tested for their predictive power of natural metabolic variation among accessions. We found specifically habitat temperature during the first quarter of the year to be the best predictor of the plasticity of primary metabolism, indicating habitat temperature as the causal driver of evolutionary cold adaptation processes. Analyses of epigenome- and genome-wide associations revealed accession-specific differential DNA-methylation levels as potentially linked to the metabolome and identified FUMARASE2 as strongly associated with cold adaptation in Arabidopsis accessions. These findings were supported by calculations of the biochemical Jacobian matrix based on variance and covariance of metabolomics data, which revealed that growth under low temperatures most substantially affects the accession-specific plasticity of fumarate and sugar metabolism. Our findings indicate that the plasticity of metabolic regulation is predictable from the genome and epigenome and driven evolutionarily by Arabidopsis growth habitats.

Plant genome resequencing and population genomics: Current status and future prospects

Advances in DNA sequencing technology have sparked a genomics revolution, driving breakthroughs in plant genetics and crop breeding. Recently, the focus has shifted from cataloging genetic diversity in plants to exploring their functional significance and delivering beneficial alleles for crop improvement. This transformation has been facilitated by the increasing adoption of whole-genome resequencing. In this review, we summarize the current progress of population-based genome resequencing studies and how these studies affect crop breeding. A total of 187 land plants from 163 countries have been resequenced, comprising 54 413 accessions. As part of resequencing efforts 367 traits have been surveyed and 86 genome-wide association studies have been conducted. Economically important crops, particularly cereals, vegetables, and legumes, have dominated the resequencing efforts, leaving a gap in 49 orders, including Lycopodiales, Liliales, Acorales, Austrobaileyales, and Commelinales. The resequenced germplasm is distributed across diverse geographic locations, providing a global perspective on plant genomics. We highlight genes that have been selected during domestication, or associated with agronomic traits, and form a repository of candidate genes for future research and application. Despite the opportunities for cross-species comparative genomics, many population genomic datasets are not accessible, impeding secondary analyses. We call for a more open and collaborative approach to population genomics that promotes data sharing and encourages contribution-based credit policy. The number of plant genome resequencing studies will continue to rise with the decreasing DNA sequencing costs, coupled with advances in analysis and computational technologies. This expansion, in terms of both scale and quality, holds promise for deeper insights into plant trait genetics and breeding design.

Rock, scissors, paper: How RNA structure informs function

RNA can fold back on itself to adopt a wide range of structures. These range from relatively simple hairpins to intricate 3D folds and can be accompanied by regulatory interactions with both metabolites and macromolecules. The last 50 yr have witnessed elucidation of an astonishing array of RNA structures including transfer RNAs, ribozymes, riboswitches, the ribosome, the spliceosome, and most recently entire RNA structuromes. These advances in RNA structural biology have deepened insight into fundamental biological processes including gene editing, transcription, translation, and structure-based detection and response to temperature and other environmental signals. These discoveries reveal that RNA can be relatively static, like a rock; that it can have catalytic functions of cutting bonds, like scissors; and that it can adopt myriad functional shapes, like paper. We relate these extraordinary discoveries in the biology of RNA structure to the plant way of life. We trace plant-specific discovery of ribozymes and riboswitches, alternative splicing, organellar ribosomes, thermometers, whole-transcriptome structuromes and pan-structuromes, and conclude that plants have a special set of RNA structures that confer unique types of gene regulation. We finish with a consideration of future directions for the RNA structure-function field.

Adaptive protein evolution through length variation of short tandem repeats in Arabidopsis

Intrinsically disordered protein regions are of high importance for biotic and abiotic stress responses in plants. Tracts of identical amino acids accumulate in these regions and can vary in length over generations because of expansions and retractions of short tandem repeats at the genomic level. However, little attention has been paid to what extent length variation is shaped by natural selection. By environmental association analysis on 2514 length variable tracts in 770 whole-genome sequenced Arabidopsis thaliana, we show that length variation in glutamine and asparagine amino acid homopolymers, as well as in interaction hotspots, correlate with local bioclimatic habitat. We determined experimentally that the promoter activity of a light-stress gene depended on polyglutamine length variants in a disordered transcription factor. Our results show that length variations affect protein function and are likely adaptive. Length variants modulating protein function at a global genomic scale has implications for understanding protein evolution and eco-evolutionary biology.

On the hidden temporal dynamics of plant adaptation

Adaptation to a wide range of environments is a major driver of plant diversity. It is now possible to catalog millions of potential adaptive genomic differences segregating between environments within a plant species in a single experiment. Understanding which of these changes contributes to adaptive phenotypic divergence between plant populations is a major goal of evolutionary biologists and crop breeders. In this review, we briefly highlight the approaches frequently used to understand the genetic basis of adaptive phenotypes in plants, and we discuss some of the limitations of these methods. We propose that direct observation of the process of adaptation using multigenerational studies and whole genome sequencing is a crucial missing component of recent studies of plant adaptation because it complements several shortcomings of sampling-based techniques.

Assessment of functional relevance of genes associated with local temperature variables in Arabidopsis thaliana

How likely genetic variations associated with environment identified in silico from genome wide association study are functionally relevant to environmental adaptation has been largely unexplored experimentally. Here we analyzed top 29 genes containing polymorphisms associated with local temperature variation (minimum, mean, maximum) among 1129 natural accessions of Arabidopsis thaliana. Their loss-of-function mutants were assessed for growth and stress tolerance at five temperatures. Twenty genes were found to affect growth or tolerance at one or more of these temperatures. Significantly, genes associated with maximum temperature more likely have a detect a function at higher temperature, while genes associated with minimum temperature more likely have a function at lower temperature. In addition, gene variants are distributed more frequently at geographic locations where they apparently offer an enhanced growth or tolerance for five genes tested. Furthermore, variations in a large proportion of the in silico identified genes associated with minimum or mean-temperatures exhibited a significant association with growth phenotypes experimentally assessed at low temperature for a small set of natural accessions. This study shows a functional relevance of gene variants associated with environmental variables and supports the feasibility of the use of local temperature factors in investigating the genetic basis of temperature adaptation.

Natural variation in root suberization is associated with local environment in Arabidopsis thaliana

Genetic signature of climate adaptation has been widely recognized across the genome of many organisms; however, the eco-physiological basis for linking genomic polymorphisms with local adaptations remains largely unexplored. Using a panel of 218 world-wide Arabidopsis accessions, we characterized the natural variation in root suberization by quantifying 16 suberin monomers. We explored the associations between suberization traits and 126 climate variables. We conducted genome-wide association analysis and integrated previous genotype-environment association (GEA) to identify the genetic bases underlying suberization variation and their involvements in climate adaptation. Root suberin content displays extensive variation across Arabidopsis populations and significantly correlates with local moisture gradients and soil characteristics. Specifically, enhanced suberization is associated with drier environments, higher soil cation-exchange capacity, and lower soil pH; higher proportional levels of very-long-chain suberin is negatively correlated with moisture availability, lower soil gravel content, and higher soil silt fraction. We identified 94 putative causal loci and experimentally proved that GPAT6 is involved in C16 suberin biosynthesis. Highly significant associations between the putative genes and environmental variables were observed. Roots appear highly responsive to environmental heterogeneity via regulation of suberization, especially the suberin composition. The patterns of suberization-environment correlation and the suberin-related GEA fit the expectations of local adaptation for the polygenic suberization trait.

Testing the association of relative growth rate and adaptation to climate across natural ecotypes of Arabidopsis

Ecophysiologists have reported a range of relationships, including intrinsic trade-offs across and within species between plant relative growth rate in high resource conditions (RGR) vs adaptation to tolerate cold or arid climates, arising from trait-based mechanisms. Few studies have considered ecotypes within a species, in which the lack of a trade-off would contribute to a wide species range and resilience to climate change. For 15 ecotypes of Arabidopsis thaliana in a common garden we tested for associations between RGR vs adaptation to cold or dry native climates and assessed hypotheses for its mediation by 15 functional traits. Ecotypes native to warmer, drier climates had higher leaf density, leaf mass per area, root mass fraction, nitrogen per leaf area and carbon isotope ratio, and lower osmotic potential at full turgor. Relative growth rate was statistically independent of the climate of the ecotype native range and of individual functional traits. The decoupling of RGR and cold or drought adaptation in Arabidopsis is consistent with multiple stress resistance and avoidance mechanisms for ecotypic climate adaptation and would contribute to the species' wide geographic range and resilience as the climate changes.

Genome resequencing clarifies phylogeny and reveals patterns of selection in the toxicogenomics model Pimephales promelas

Background

The fathead minnow (Pimephales promelas) is a model species for toxicological research. A high-quality genome reference sequence is available, and genomic methods are increasingly used in toxicological studies of the species. However, phylogenetic relationships within the genus remain incompletely known and little population-genomic data are available for fathead minnow despite the potential effects of genetic background on toxicological responses. On the other hand, a wealth of extant samples is stored in museum collections that in principle allow fine-scale analysis of contemporary and historical genetic variation.

Methods

Here we use short-read shotgun resequencing to investigate sequence variation among and within Pimephales species. At the genus level, our objectives were to resolve phylogenetic relationships and identify genes with signatures of positive diversifying selection. At the species level, our objective was to evaluate the utility of archived-sample resequencing for detecting selective sweeps within fathead minnow, applied to a population introduced to the San Juan River of the southwestern United States sometime prior to 1950.

Results

We recovered well-supported but discordant phylogenetic topologies for nuclear and mitochondrial sequences that we hypothesize arose from mitochondrial transfer among species. The nuclear tree supported bluntnose minnow (P. notatus) as sister to fathead minnow, with the slim minnow (P. tenellus) and bullhead minnow (P. vigilax) more closely related to each other. Using multiple methods, we identified 11 genes that have diversified under positive selection within the genus. Within the San Juan River population, we identified selective-sweep regions overlapping several sets of related genes, including both genes that encode the giant sarcomere protein titin and the two genes encoding the MTORC1 complex, a key metabolic regulator. We also observed elevated polymorphism and reduced differentation among populations (F_ST) in genomic regions containing certain immune-gene clusters, similar to what has been reported in other taxa. Collectively, our data clarify evolutionary relationships and selective pressures within the genus and establish museum archives as a fruitful resource for characterizing genomic variation. We anticipate that large-scale resequencing will enable the detection of genetic variants associated with environmental toxicants such as heavy metals, high salinity, estrogens, and agrichemicals, which could be exploited as efficient biomarkers of exposure in natural populations.

Experimental demonstration and pan-structurome prediction of climate-associated riboSNitches in Arabidopsis

Background

Genome-wide association studies (GWAS) aim to correlate phenotypic changes with genotypic variation. Upon transcription, single nucleotide variants (SNVs) may alter mRNA structure, with potential impacts on transcript stability, macromolecular interactions, and translation. However, plant genomes have not been assessed for the presence of these structure-altering polymorphisms or “riboSNitches.”

Results

We experimentally demonstrate the presence of riboSNitches in transcripts of two Arabidopsis genes, ZINC RIBBON 3 (ZR3) and COTTON GOLGI-RELATED 3 (CGR3), which are associated with continentality and temperature variation in the natural environment. These riboSNitches are also associated with differences in the abundance of their respective transcripts, implying a role in regulating the gene's expression in adaptation to local climate conditions. We then computationally predict riboSNitches transcriptome-wide in mRNAs of 879 naturally inbred Arabidopsis accessions. We characterize correlations between SNPs/riboSNitches in these accessions and 434 climate descriptors of their local environments, suggesting a role of these variants in local adaptation. We integrate this information in CLIMtools V2.0 and provide a new web resource, T-CLIM, that reveals associations between transcript abundance variation and local environmental variation.

Conclusion

We functionally validate two plant riboSNitches and, for the first time, demonstrate riboSNitch conditionality dependent on temperature, coining the term “conditional riboSNitch.” We provide the first pan-genome-wide prediction of riboSNitches in plants. We expand our previous CLIMtools web resource with riboSNitch information and with 1868 additional Arabidopsis genomes and 269 additional climate conditions, which will greatly facilitate in silico studies of natural genetic variation, its phenotypic consequences, and its role in local adaptation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02656-4.

Adaptive significance of flowering time variation across natural seasonal environments in Arabidopsis thaliana

The relevance of flowering time variation and plasticity to climate adaptation requires a comprehensive empirical assessment. We investigated natural selection and the genetic architecture of flowering time in Arabidopsis through field experiments in Europe across multiple sites and seasons. We estimated selection for flowering time, plasticity and canalization. Loci associated with flowering time, plasticity and canalization by genome-wide association studies were tested for a geographic signature of climate adaptation. Selection favored early flowering and increased canalization, except at the northernmost site, but was rarely detected for plasticity. Genome-wide association studies revealed significant associations with flowering traits and supported a substantial polygenic inheritance. Alleles associated with late flowering, including functional FRIGIDA variants, were more common in regions experiencing high annual temperature variation. Flowering time plasticity to fall vs spring and summer environments was associated with GIGANTEA SUPPRESSOR 5, which promotes early flowering under decreasing day length and temperature. The finding that late flowering genotypes and alleles are associated with climate is evidence for past adaptation. Real-time phenotypic selection analysis, however, reveals pervasive contemporary selection for rapid flowering in agricultural settings across most of the species range. The response to this selection may involve genetic shifts in environmental cuing compared to the ancestral state.

Genetic architecture of variation in Arabidopsis thaliana rosettes

Rosette morphology across Arabidopsis accessions exhibits considerable variation. Here we report a high-throughput phenotyping approach based on automatic image analysis to quantify rosette shape and dissect the underlying genetic architecture. Shape measurements of the rosettes in a core set of Recombinant Inbred Lines from an advanced mapping population (Multiparent Advanced Generation Inter-Cross or MAGIC) derived from inter-crossing 19 natural accessions. Image acquisition and analysis was scaled to extract geometric descriptors from time stamped images of growing rosettes. Shape analyses revealed heritable morphological variation at early juvenile stages and QTL mapping resulted in over 116 chromosomal regions associated with trait variation within the population. Many QTL linked to variation in shape were located near genes related to hormonal signalling and signal transduction pathways while others are involved in shade avoidance and transition to flowering. Our results suggest rosette shape arises from modular integration of sub-organ morphologies and can be considered a functional trait subjected to selective pressures of subsequent morphological traits. On an applied aspect, QTLs found will be candidates for further research on plant architecture.

Cold stress and freezing tolerance negatively affect the fitness of Arabidopsis thaliana accessions under field and controlled conditions

Higher acclimated freezing tolerance improved winter survival, but reduced reproductive fitness of Arabidopsis thaliana accessions under field and controlled conditions. Low temperature is one of the most important abiotic factors influencing plant fitness and geographical distribution. In addition, cold stress is known to influence crop yield and is therefore of great economic importance. Increased freezing tolerance can be acquired by the process of cold acclimation, but this may be associated with a fitness cost. To assess the influence of cold stress on the fitness of plants, long-term field trials over 5 years were performed with six natural accessions of Arabidopsis thaliana ranging from very tolerant to very sensitive to freezing. Fitness parameters, as seed yield and 1000 seed mass, were measured and correlation analyses with temperature and freezing tolerance data performed. The results were compared with fitness parameters from controlled chamber experiments over 3 years with application of cold priming and triggering conditions. Winter survival and seed yield per plant were positively correlated with temperature in field experiments. In addition, winter survival and 1000 seed mass were correlated with the cold-acclimated freezing tolerance of the selected Arabidopsis accessions. The results provide strong evidence for a trade-off between higher freezing tolerance and reproductive fitness in A. thaliana, which might have ecological impacts in the context of global warming.

Entailing the Next-Generation Sequencing and Metabolome for Sustainable Agriculture by Improving Plant Tolerance

Crop production is a serious challenge to provide food for the 10 billion individuals forecasted to live across the globe in 2050. The scientists' emphasize establishing an equilibrium among diversity and quality of crops by enhancing yield to fulfill the increasing demand for food supply sustainably. The exploitation of genetic resources using genomics and metabolomics strategies can help generate resilient plants against stressors in the future. The innovation of the next-generation sequencing (NGS) strategies laid the foundation to unveil various plants' genetic potential and help us to understand the domestication process to unmask the genetic potential among wild-type plants to utilize for crop improvement. Nowadays, NGS is generating massive genomic resources using wild-type and domesticated plants grown under normal and harsh environments to explore the stress regulatory factors and determine the key metabolites. Improved food nutritional value is also the key to eradicating malnutrition problems around the globe, which could be attained by employing the knowledge gained through NGS and metabolomics to achieve suitability in crop yield. Advanced technologies can further enhance our understanding in defining the strategy to obtain a specific phenotype of a crop. Integration among bioinformatic tools and molecular techniques, such as marker-assisted, QTLs mapping, creation of reference genome, de novo genome assembly, pan- and/or super-pan-genomes, etc., will boost breeding programs. The current article provides sequential progress in NGS technologies, a broad application of NGS, enhancement of genetic manipulation resources, and understanding the crop response to stress by producing plant metabolites. The NGS and metabolomics utilization in generating stress-tolerant plants/crops without deteriorating a natural ecosystem is considered a sustainable way to improve agriculture production. This highlighted knowledge also provides useful research that explores the suitable resources for agriculture sustainability.

Location-Dependent DNA Methylation Signatures in a Clonal Invasive Crayfish

DNA methylation is an important epigenetic modification that has been repeatedly implied in organismal adaptation. However, many previous studies that have linked DNA methylation patterns to environmental parameters have been limited by confounding factors, such as cell-type heterogeneity and genetic variation. In this study, we analyzed DNA methylation variation in marbled crayfish, a clonal and invasive freshwater crayfish that is characterized by a largely tissue-invariant methylome and negligible genetic variation. Using a capture-based subgenome bisulfite sequencing approach that covers a small, variably methylated portion of the marbled crayfish genome, we identified specific and highly localized DNA methylation signatures for specimens from geographically and ecologically distinct wild populations. These results were replicated both biologically and technically by re-sampling at different time points and by using independent methodology. Finally, we show specific methylation signatures for laboratory animals and for laboratory animals that were reared at a lower temperature. Our results thus demonstrate the existence of context-dependent DNA methylation signatures in a clonal animal.

Characterization of the genetic basis of local adaptation of wheat landraces from Iran and Pakistan using genome-wide association study

Characterization of genomic regions underlying adaptation of landraces can reveal a quantitative genetics framework for local wheat (Triticum aestivum L.) adaptability. A collection of 512 wheat landraces from the eastern edge of the Fertile Crescent in Iran and Pakistan were genotyped using genome-wide single nucleotide polymorphism markers generated by genotyping-by-sequencing. The minor allele frequency (MAF) and the heterozygosity (H) of Pakistani wheat landraces (MAF = 0.19, H = 0.008) were slightly higher than the Iranian wheat landraces (MAF = 0.17, H = 0.005), indicating that Pakistani landraces were slightly more genetically diverse. Population structure analysis clearly separated the Pakistani landraces from Iranian landraces, which indicates two separate adaptability trajectories. The large-scale agro-climatic data of seven variables were quite dissimilar between Iran and Pakistan as revealed by the correlation coefficients. Genome-wide association study identified 91 and 58 loci using agroclimatic data, which likely underpin local adaptability of the wheat landraces from Iran and Pakistan, respectively. Selective sweep analysis identified significant hits on chromosomes 4A, 4B, 6B, 7B, 2D, and 6D, which were colocalized with the loci associated with local adaptability and with some known genes related to flowering time and grain size. This study provides insight into the genetic diversity with emphasis on the genetic architecture of loci involved in adaptation to local environments, which has breeding implications.

Global Genetic Heterogeneity in Adaptive Traits

Understanding the genetic architecture of complex traits is a major objective in biology. The standard approach for doing so is genome-wide association studies (GWAS), which aim to identify genetic polymorphisms responsible for variation in traits of interest. In human genetics, consistency across studies is commonly used as an indicator of reliability. However, if traits are involved in adaptation to the local environment, we do not necessarily expect reproducibility. On the contrary, results may depend on where you sample, and sampling across a wide range of environments may decrease the power of GWAS because of increased genetic heterogeneity. In this study, we examine how sampling affects GWAS in the model plant species Arabidopsis thaliana. We show that traits like flowering time are indeed influenced by distinct genetic effects in local populations. Furthermore, using gene expression as a molecular phenotype, we show that some genes are globally affected by shared variants, whereas others are affected by variants specific to subpopulations. Remarkably, the former are essentially all cis-regulated, whereas the latter are predominately affected by trans-acting variants. Our result illustrate that conclusions about genetic architecture can be extremely sensitive to sampling and population structure.

Length variation in short tandem repeats affects gene expression in natural populations of Arabidopsis thaliana

The genetic basis for the fine-tuned regulation of gene expression is complex and ultimately influences the phenotype and thus the local adaptation of natural populations. Short tandem repeats (STRs) consisting of repetitive DNA motifs have been shown to regulate gene expression. STRs are variable in length within a population and serve as a heritable, but semi-reversible, reservoir of standing genetic variation. For sessile organisms, such as plants, STRs could be of major importance in fine-tuning gene expression as a response to a shifting local environment. Here, we used a transcriptome dataset from natural accessions of Arabidopsis thaliana to investigate population-wide gene expression patterns in light of genome-wide STR variation. We empirically modeled gene expression as a response to the STR length within and around the gene and demonstrated that an association between gene expression and STR length variation is unequivocally present in the sampled population. To support our model, we explored the promoter activity in a transcriptional regulator involved in root hair formation and provided experimentally determined causality between coding sequence length variation and promoter activity. Our results support a general link between gene expression variation and STR length variation in A. thaliana.

Determinants of root system architecture for future-ready, stress-resilient crops

Climate change hampers food safety and food security. Crop breeding has been boosting superior quantity traits such as yield, but roots have often been overlooked in spite of their role in the whole plant physiology. New evidence is emerging on the relevance of root system architecture in coping with the environment. Here, we review determinants of root system architecture, mainly based on studies on Arabidopsis, and we discuss how breeding for appropriate root architecture may help obtain plants that are better adapted or resilient to abiotic and biotic stresses, more productive, and more efficient for soil and water use. We also highlight recent advances in phenotyping high-tech platforms and genotyping techniques that may further help to understand the mechanisms of root development and how roots control relationships between plants and soil. An integrated approach is proposed that combines phenotyping and genotyping information via bioinformatic analyses and reveals genetic control of root system architecture, paving the way for future research on plant breeding.

Using precision phenotyping to inform de novo domestication

An update on the use of precision phenotyping to assess the potential of lesser cultivated species as candidates for de novo domestication or similar development for future agriculture.

Integration of omics data to unravel root microbiome recruitment

The plant microbiome plays an essential role in supporting plant growth and health, but plant molecular mechanisms underlying its recruitment are still unclear. Multi-omics data integration methods can be used to unravel new signalling relationships. Here, we review the effects of plant genetics and root exudates on root microbiome recruitment, and discuss methodological advances in data integration approaches that can help us to better understand and optimise the crop-microbiome interaction for a more sustainable agriculture.

ABA Metabolism and Homeostasis in Seed Dormancy and Germination

Abscisic acid (ABA) is a key hormone that promotes dormancy during seed development on the mother plant and after seed dispersal participates in the control of dormancy release and germination in response to environmental signals. The modulation of ABA endogenous levels is largely achieved by fine-tuning, in the different seed tissues, hormone synthesis by cleavage of carotenoid precursors and inactivation by 8'-hydroxylation. In this review, we provide an overview of the current knowledge on ABA metabolism in developing and germinating seeds; notably, how environmental signals such as light, temperature and nitrate control seed dormancy through the adjustment of hormone levels. A number of regulatory factors have been recently identified which functional relationships with major transcription factors, such as ABA INSENSITIVE3 (ABI3), ABI4 and ABI5, have an essential role in the control of seed ABA levels. The increasing importance of epigenetic mechanisms in the regulation of ABA metabolism gene expression is also described. In the last section, we give an overview of natural variations of ABA metabolism genes and their effects on seed germination, which could be useful both in future studies to better understand the regulation of ABA metabolism and to identify candidates as breeding materials for improving germination properties.

Advancing crop genomics from lab to field

Crop genomics remains a key element in ensuring scientific progress to secure global food security. It has been two decades since the sequence of the first plant genome, that of Arabidopsis thaliana, was released, and soon after that the draft sequencing of the rice genome was completed. Since then, the genomes of more than 100 crops have been sequenced, plant genome research has expanded across multiple fronts and the next few years promise to bring further advances spurred by the advent of new technologies and approaches. We are likely to see continued innovations in crop genome sequencing, genetic mapping and the acquisition of multiple levels of biological data. There will be exciting opportunities to integrate genome-scale information across multiple scales of biological organization, leading to advances in our mechanistic understanding of crop biological processes, which will, in turn, provide greater impetus for translation of laboratory results to the field.

Genetic variation, environment and demography intersect to shape Arabidopsis defense metabolite variation across Europe

Plants produce diverse metabolites to cope with the challenges presented by complex and ever-changing environments. These challenges drive the diversification of specialized metabolites within and between plant species. However, we are just beginning to understand how frequently new alleles arise controlling specialized metabolite diversity and how the geographic distribution of these alleles may be structured by ecological and demographic pressures. Here, we measure the variation in specialized metabolites across a population of 797 natural Arabidopsis thaliana accessions. We show that a combination of geography, environmental parameters, demography and different genetic processes all combine to influence the specific chemotypes and their distribution. This showed that causal loci in specialized metabolism contain frequent independently generated alleles with patterns suggesting potential within-species convergence. This provides a new perspective about the complexity of the selective forces and mechanisms that shape the generation and distribution of allelic variation that may influence local adaptation.

Since plants cannot move, they have evolved chemical defenses to help them respond to changes in their surroundings. For example, where animals run from predators, plants may produce toxins to put predators off. This approach is why plants are such a rich source of drugs, poisons, dyes and other useful substances. The chemicals plants produce are known as specialized metabolites, and they can change a lot between, and even within, plant species. The variety of specialized metabolites is a result of genetic changes and evolution over millions of years.

Evolution is a slow process, yet plants are able to rapidly develop new specialized metabolites to protect them from new threats. Even different populations of the same species produce many distinct metabolites that help them survive in their surroundings. However, the factors that lead plants to produce new metabolites are not well understood, and it is not known how this affects genetic variation.

To gain a better understanding of this process, Katz et al. studied 797 European variants of a common weed species called Arabidopsis thaliana, which is widely studied. The investigation found that many factors affect the range of specialized metabolites in each variant. These included local geography and environment, as well as genetics and population history (demography). Katz et al. revealed a pattern of relationships between the variants that could mirror their evolutionary history as the species spread and adapted to new locations.

These results highlight the complex network of factors that affect plant evolution. Rapid diversification is key to plant survival in new and changing environments and has resulted in a wide range of specialized metabolites. As such they are of interest both for studying plant evolution and for understanding their ecology. Expanding similar work to more populations and other species will broaden the scope of our ability to understand how plants adapt to their surroundings.

Genetic architecture and adaptation of flowering time among environments

The genetic basis of flowering time changes across environments, and pleiotropy may limit adaptive evolution of populations in response to local conditions. However, little information is known about how genetic architecture changes among environments. We used genome-wide association studies (GWAS) in Boechera stricta (Graham) Al-Shehbaz, a relative of Arabidopsis, to examine flowering variation among environments and associations with climate conditions in home environments. Also, we used molecular population genetics to search for evidence of historical natural selection. GWAS found 47 significant quantitative trait loci (QTLs) that influence flowering time in one or more environments, control plastic changes in phenology between experiments, or show associations with climate in sites of origin. Genetic architecture of flowering varied substantially among environments. We found that some pairs of QTLs showed similar patterns of pleiotropy across environments. A large-effect QTL showed molecular signatures of adaptive evolution and is associated with climate in home environments. The derived allele at this locus causes later flowering and predominates in sites with greater water availability. This work shows that GWAS of climate associations and ecologically important traits across diverse environments can be combined with molecular signatures of natural selection to elucidate ecological genetics of adaptive evolution.

Evolvability and evolutionary rescue

The survival prospects of threatened species or populations can sometimes be improved by adaptive change. Such evolutionary rescue is particularly relevant when the threat comes from changing environments, or when long-term population persistence requires range expansion into new habitats. Conservation biologists are therefore often interested in whether or not populations or lineages show a disposition for adaptive evolution, that is, if they are evolvable. Here, we discuss four alternative perspectives that target different causes of evolvability and outline some of the key challenges those perspectives are designed to address. Standing genetic variation provides one familiar estimate of evolvability. Yet, the mere presence of genetic variation is often insufficient to predict if a population will adapt, or how it will adapt. The reason is that adaptive change not only depends on genetic variation, but also on the extent to which this genetic variation can be realized as adaptive phenotypic variation. This requires attention to developmental systems and how plasticity influences evolutionary potential. Finally, we discuss how a better understanding of the different factors that contribute to evolvability can be exploited in conservation practice.

AtMAD: Arabidopsis thaliana multi-omics association database

Integration analysis of multi-omics data provides a comprehensive landscape for understanding biological systems and mechanisms. The abundance of high-quality multi-omics data (genomics, transcriptomics, methylomics and phenomics) for the model organism Arabidopsis thaliana enables scientists to study the genetic mechanism of many biological processes. However, no resource is available to provide comprehensive and systematic multi-omics associations for Arabidopsis. Here, we developed an Arabidopsis thaliana Multi-omics Association Database (AtMAD, http://www.megabionet.org/atmad), a public repository for large-scale measurements of associations between genome, transcriptome, methylome, pathway and phenotype in Arabidopsis, designed for facilitating identification of eQTL, emQTL, Pathway-mQTL, Phenotype-pathway, GWAS, TWAS and EWAS. Candidate variants/methylations/genes were identified in AtMAD for specific phenotypes or biological processes, many of them are supported by experimental evidence. Based on the multi-omics association strategy, we have identified 11 796 cis-eQTLs and 10 119 trans-eQTLs. Among them, 68 837 environment-eQTL associations and 149 622 GWAS-eQTL associations were identified and stored in AtMAD. For expression–methylation quantitative trait loci (emQTL), we identified 265 776 emQTLs and 122 344 pathway-mQTLs. For TWAS and EWAS, we obtained 62 754 significant phenotype-gene associations and 3 993 379 significant phenotype-methylation associations, respectively. Overall, the multi-omics associated network in AtMAD will provide new insights into exploring biological mechanisms of plants at multi-omics levels.

Enviromics in breeding: applications and perspectives on envirotypic-assisted selection

We propose the application of enviromics to breeding practice, by which the similarity among sites assessed on an "omics" scale of environmental attributes drives the prediction of unobserved genotype performances. Genotype by environment interaction (GEI) studies in plant breeding have focused mainly on estimating genetic parameters over a limited number of experimental trials. However, recent geographic information system (GIS) techniques have opened new frontiers for better understanding and dealing with GEI. These advances allow increasing selection accuracy across all sites of interest, including those where experimental trials have not yet been deployed. Here, we introduce the term enviromics, within an envirotypic-assisted breeding framework. In summary, likewise genotypes at DNA markers, any particular site is characterized by a set of "envirotypes" at multiple "enviromic" markers corresponding to environmental variables that may interact with the genetic background, thus providing informative breeding re-rankings for optimized decisions over different environments. Based on simulated data, we illustrate an index-based enviromics method (the "GIS-GEI") which, due to its higher granular resolution than standard methods, allows for: (1) accurate matching of sites to their most appropriate genotypes; (2) better definition of breeding areas that have high genetic correlation to ensure selection gains across environments; and (3) efficient determination of the best sites to carry out experiments for further analyses. Environmental scenarios can also be optimized for productivity improvement and genetic resources management, especially in the current outlook of dynamic climate change. Envirotyping provides a new class of markers for genetic studies, which are fairly inexpensive, increasingly available and transferable across species. We envision a promising future for the integration of enviromics approaches into plant breeding when coupled with next-generation genotyping/phenotyping and powerful statistical modeling of genetic diversity.

Polygenic adaptation: a unifying framework to understand positive selection

Most adaption processes have a polygenic genetic basis, but even with the recent explosive growth of genomic data we are still lacking a unified framework describing the dynamics of selected alleles. Building on recent theoretical and empirical work we introduce the concept of adaptive architecture, which extends the genetic architecture of an adaptive trait by factors influencing its adaptive potential and population genetic principles. Because adaptation can be typically achieved by many different combinations of adaptive alleles (redundancy), we describe how two characteristics - heterogeneity among loci and non-parallelism between replicated populations - are hallmarks for the characterization of polygenic adaptation in evolving populations. We discuss how this unified framework can be applied to natural and experimental populations.

Identification of Genes Conferring Plant Salt Tolerance using GWAS: Current Success and Perspectives

An understanding of the molecular mechanisms that underlie plant salt tolerance is important for both economic and scientific interests. Genome-wide association study (GWAS) is a promising approach to pinpoint genes that confer plant salt tolerance. With the advancement of supporting technology and methodology, GWAS has enabled the discovery of genes that play central roles in regulating plant salt tolerance in the past decade. Here, I highlight recent successful GWAS work in unveiling the molecular factors underlying plant salt tolerance and discuss the concerns and opportunities in conducting such experiments. It is anticipated that GWAS will be increasingly successful in the identification of key genes that are useful for crop improvement.

Hierarchical Canonical Correlation Analysis Reveals Phenotype, Genotype, and Geoclimate Associations in Plants

The local environment of the geographical origin of plants shaped their genetic variations through environmental adaptation. While the characteristics of the local environment correlate with the genotypes and other genomic features of the plants, they can also be indicative of genotype-phenotype associations providing additional information relevant to environmental dependence. In this study, we investigate how the geoclimatic features from the geographical origin of the Arabidopsis thaliana accessions can be integrated with genomic features for phenotype prediction and association analysis using advanced canonical correlation analysis (CCA). In particular, we propose a novel method called hierarchical canonical correlation analysis (HCCA) to combine mutations, gene expressions, and DNA methylations with geoclimatic features for informative coprojections of the features. HCCA uses a condition number of the cross-covariance between pairs of datasets to infer a hierarchical structure for applying CCA to combine the data. In the experiments on Arabidopsis thaliana data from 1001 Genomes and 1001 Epigenomes projects and climatic, atmospheric, and soil environmental variables combined by CLIMtools, HCCA provided a joint representation of the genomic data and geoclimate data for better prediction of the special flowering time at 10°C (FT10) of Arabidopsis thaliana. We also extended HCCA with information from a protein-protein interaction (PPI) network to guide the feature learning by imposing network modules onto the genomic features, which are shown to be useful for identifying genes with more coherent functions correlated with the geoclimatic features. The findings in this study suggest that environmental data comprise an important component in plant phenotype analysis. HCCA is a useful data integration technique for phenotype prediction, and a better understanding of the interactions between gene functions and environment as more useful functional information is introduced by coprojections of multiple genomic datasets.

Metabolomics of red-light-induced stomatal opening in Arabidopsis thaliana: Coupling with abscisic acid and jasmonic acid metabolism

Environmental stimuli-triggered stomatal movement is a key physiological process that regulates CO₂ uptake and water loss in plants. Stomata are defined by pairs of guard cells that perceive and transduce external signals, leading to cellular volume changes and consequent stomatal aperture change. Within the visible light spectrum, red light induces stomatal opening in intact leaves. However, there has been debate regarding the extent to which red-light-induced stomatal opening arises from direct guard cell sensing of red light versus indirect responses as a result of red light influences on mesophyll photosynthesis. Here we identify conditions that result in red-light-stimulated stomatal opening in isolated epidermal peels and enlargement of protoplasts, firmly establishing a direct guard cell response to red light. We then employ metabolomics workflows utilizing gas chromatography mass spectrometry and liquid chromatography mass spectrometry for metabolite profiling and identification of Arabidopsis guard cell metabolic signatures in response to red light in the absence of the mesophyll. We quantified 223 metabolites in Arabidopsis guard cells, with 104 found to be red light responsive. These red-light-modulated metabolites participate in the tricarboxylic acid cycle, carbon balance, phytohormone biosynthesis and redox homeostasis. We next analyzed selected Arabidopsis mutants, and discovered that stomatal opening response to red light is correlated with a decrease in guard cell abscisic acid content and an increase in jasmonic acid content. The red-light-modulated guard cell metabolome reported here provides fundamental information concerning autonomous red light signaling pathways in guard cells.

Range-wide neutral and adaptive genetic structure of an endemic herb from Amazonian Savannas

Conserving genetic diversity in rare and narrowly distributed endemic species is essential to maintain their evolutionary potential and minimize extinction risk under future environmental change. In this study we assess neutral and adaptive genetic structure and genetic diversity in Brasilianthus carajensis (Melastomataceae), an endemic herb from Amazonian Savannas. Using RAD sequencing we identified a total of 9365 SNPs in 150 individuals collected across the species' entire distribution range. Relying on assumption-free genetic clustering methods and environmental association tests we then compared neutral with adaptive genetic structure. We found three neutral and six adaptive genetic clusters, which could be considered management units (MU) and adaptive units (AU), respectively. Pairwise genetic differentiation (F _ST) ranged between 0.024 and 0.048, and even though effective population sizes were below 100, no significant inbreeding was found in any inferred cluster. Nearly 10 % of all analysed sequences contained loci associated with temperature and precipitation, from which only 25 sequences contained annotated proteins, with some of them being very relevant for physiological processes in plants. Our findings provide a detailed insight into genetic diversity, neutral and adaptive genetic structure in a rare endemic herb, which can help guide conservation and management actions to avoid the loss of unique genetic variation.

Adaptation to Plant Communities across the Genome of Arabidopsis thaliana

Despite the importance of plant-plant interactions on plant community dynamics and crop yield, our understanding of the adaptive genetics underlying these interactions is still limited and deserves to be investigated in the context of complex and diffuse interactions occurring in plant assemblages. Here, based on 145 natural populations of Arabidopsis thaliana located in south-west of France and characterized for plant communities, we conducted a Genome-Environment Association analysis to finely map adaptive genomic regions of A. thaliana associated with plant community descriptors. To control for correlated abiotic environment effects, we also characterized the populations for a set of biologically meaningful climate and soil variables. A nonnegligible fraction of top single nucleotide polymorphisms was associated with both plant community descriptors and abiotic variables, highlighting the importance of considering the actual abiotic drivers of plant communities to disentangle genetic variants for biotic adaptation from genetic variants for abiotic adaptation. The adaptive loci associated with species abundance were highly dependent on the identity of the neighboring species suggesting a high degree of biotic specialization of A. thaliana to members of its plant interaction network. Moreover, the identification of adaptive loci associated with α-diversity and composition of plant communities supports the ability of A. thaliana to interact simultaneously with multiple plant neighbors, which in turn can help to understand the role of community-wide selection. Altogether, our study highlights that dissecting the genetic basis underlying plant-plant interactions at a regional scale while controlling for abiotic confounding factors can help understanding the adaptive mechanisms modulating natural plant assemblages.