Metabolic Pathway of Natural Antioxidants, Antioxidant Enzymes and ROS Providence

Based on the origin, we can classify different types of stress. Environmental factors, such as high light intensity, adverse temperature, drought, or soil salinity, are summarized as abiotic stresses and discriminated from biotic stresses that are exerted by pathogens and herbivores, for instance. It was an unexpected observation that overproduction of reactive oxygen species (ROS) is a common response to all kinds of stress investigated so far. With respect to applied aspects in agriculture and crop breeding, this observation allows using ROS production as a measure to rank the stress perception of individual plants. ROS are important messengers in cell signaling, but exceeding a concentration threshold causes damage. This requires fine-tuning of ROS production and degradation rates. In general, there are two options to control cellular ROS levels, (I) ROS scavenging at the expense of antioxidant consumption and (II) enzyme-controlled degradation of ROS. As antioxidants are limited in quantity, the first strategy only allows temporarily buffering of a certain cellular ROS level. This way, it prevents spells of eventually damaging ROS concentrations. In this review, we focus on the second strategy. We discuss how enzyme-controlled degradation of ROS integrates into plant metabolism. Enzyme activities can be continuously operative. Cellular homeostasis can be achieved by regulation of respective gene expression and subsequent regulation of the enzyme activities. A better understanding of this interplay allows for identifying traits for stress tolerance breeding of crops. As a side effect, the result also may be used to identify cultivation methods modifying crop metabolism, thus resulting in special crop quality.

Genome-wide association studies dissect the G × E interaction for agronomic traits in a worldwide collection of safflowers (Carthamus tinctorius L.)

Genome-wide association studies were conducted using a globally diverse safflower (Carthamus tinctorius L.) Genebank collection for grain yield (YP), days to flowering (DF), plant height (PH), 500 seed weight (SW), seed oil content (OL), and crude protein content (PR) in four environments (sites) that differed in water availability. Phenotypic variation was observed for all traits. YP exhibited low overall genetic correlations (rGoverall) across sites, while SW and OL had high rGoverall and high pairwise genetic correlations (rGij) across all pairwise sites. In total, 92 marker-trait associations (MTAs) were identified using three methods, single locus genome-wide association studies (GWAS) using a mixed linear model (MLM), the Bayesian multi-locus method (BayesR), and meta-GWAS. MTAs with large effects across all sites were detected for OL, SW, and PR, and MTAs specific for the different water stress sites were identified for all traits. Five MTAs were associated with multiple traits; 4 of 5 MTAs were variously associated with the three traits of SW, OL, and PR. This study provided insights into the phenotypic variability and genetic architecture of important safflower agronomic traits under different environments.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01295-8.

Phenotypic and Methylome Responses to Salt Stress in Arabidopsis thaliana Natural Accessions

Salt stress threatens plant growth, development and crop yields, and has become a critical global environmental issue. Increasing evidence has suggested that the epigenetic mechanism such as DNA methylation can mediate plant response to salt stress through transcriptional regulation and transposable element (TE) silencing. However, studies exploring genome-wide methylation dynamics under salt stress remain limited, in particular, for studies on multiple genotypes. Here, we adopted four natural accessions of the model species Arabidopsis thaliana and investigated the phenotypic and genome-wide methylation responses to salt stress through whole-genome bisulfite sequencing (WGBS). We found that salt stress significantly changed plant phenotypes, including plant height, rosette diameter, fruit number, and aboveground biomass, and the change in biomass tended to depend on accessions. Methylation analysis revealed that genome-wide methylation patterns depended primarily on accessions, and salt stress caused significant methylation changes in ∼ 0.1% cytosines over the genomes. About 33.5% of these salt-induced differential methylated cytosines (DMCs) were located to transposable elements (TEs). These salt-induced DMCs were mainly hypermethylated and accession-specific. TEs annotated to have DMCs (DMC-TEs) across accessions were found mostly belonged to the superfamily of Gypsy, a type II transposon, indicating a convergent DMC dynamic on TEs across different genetic backgrounds. Moreover, 8.0% of salt-induced DMCs were located in gene bodies and their proximal regulatory regions. These DMCs were also accession-specific, and genes annotated to have DMCs (DMC-genes) appeared to be more accession-specific than DMC-TEs. Intriguingly, both accession-specific DMC-genes and DMC-genes shared by multiple accessions were enriched in similar functions, including methylation, gene silencing, chemical homeostasis, polysaccharide catabolic process, and pathways relating to shifts between vegetative growth and reproduction. These results indicate that, across different genetic backgrounds, methylation changes may have convergent functions in post-transcriptional, physiological, and phenotypic modulation under salt stress. These convergent methylation dynamics across accession may be autonomous from genetic variation or due to convergent genetic changes, which requires further exploration. Our study provides a more comprehensive picture of genome-wide methylation dynamics under salt stress, and highlights the importance of exploring stress response mechanisms from diverse genetic backgrounds.

A B73×Palomero Toluqueño mapping population reveals local adaptation in Mexican highland maize

Generations of farmer selection in the central Mexican highlands have produced unique maize varieties adapted to the challenges of the local environment. In addition to possessing great agronomic and cultural value, Mexican highland maize represents a good system for the study of local adaptation and acquisition of adaptive phenotypes under cultivation. In this study, we characterize a recombinant inbred line population derived from the B73 reference line and the Mexican highland maize variety Palomero Toluqueño. B73 and Palomero Toluqueño showed classic rank-changing differences in performance between lowland and highland field sites, indicative of local adaptation. Quantitative trait mapping identified genomic regions linked to effects on yield components that were conditionally expressed depending on the environment. For the principal genomic regions associated with ear weight and total kernel number, the Palomero Toluqueño allele conferred an advantage specifically in the highland site, consistent with local adaptation. We identified Palomero Toluqueño alleles associated with expression of characteristic highland traits, including reduced tassel branching, increased sheath pigmentation and the presence of sheath macrohairs. The oligogenic architecture of these three morphological traits supports their role in adaptation, suggesting they have arisen from consistent directional selection acting at distinct points across the genome. We discuss these results in the context of the origin of phenotypic novelty during selection, commenting on the role of de novo mutation and the acquisition of adaptive variation by gene flow from endemic wild relatives.

Analysis of genotype-by-environment interactions in a maize mapping population

Genotype-by-environment interactions are a significant challenge for crop breeding as well as being important for understanding the genetic basis of environmental adaptation. In this study, we analyzed genotype-by-environment interactions in a maize multiparent advanced generation intercross population grown across 5 environments. We found that genotype-by-environment interactions contributed as much as genotypic effects to the variation in some agronomically important traits. To understand how genetic correlations between traits change across environments, we estimated the genetic variance–covariance matrix in each environment. Changes in genetic covariances between traits across environments were common, even among traits that show low genotype-by-environment variance. We also performed a genome-wide association study to identify markers associated with genotype-by-environment interactions but found only a small number of significantly associated markers, possibly due to the highly polygenic nature of genotype-by-environment interactions in this population.

Phenotypic plasticity in plant height shaped by interaction between genetic loci and diurnal temperature range

Phenotypic plasticity is observed widely in plants and often studied with reaction norms for adult plant or end-of-season traits. Uncovering genetic, environmental and developmental patterns behind the observed phenotypic variation under natural field conditions is needed. Using a sorghum (Sorghum bicolor) genetic population evaluated for plant height in seven natural field conditions, we investigated the major pattern that differentiated these environments. We then examined the physiological relevance of the identified environmental index by investigating the developmental trajectory of the population with multistage height measurements in four additional environments and conducting crop growth modelling. We found that diurnal temperature range (DTR) during the rapid growth period of sorghum development was an effective environmental index. Three genetic loci (Dw1, Dw3 and qHT7.1) were consistently detected for individual environments, reaction-norm parameters across environments and growth-curve parameters through the season. Their genetic effects changed dynamically along the environmental gradient and the developmental stage. A conceptual model with three-dimensional reaction norms was proposed to showcase the interconnecting components: genotype, environment and development. Beyond genomic and environmental analyses, further integration of development and physiology at the whole-plant and molecular levels into complex trait dissection would enhance our understanding of mechanisms underlying phenotypic variation.

A Method for Identifying Environmental Stimuli and Genes Responsible for Genotype-by-Environment Interactions From a Large-Scale Multi-Environment Data Set

It has not been fully understood in real fields what environment stimuli cause the genotype-by-environment (G × E) interactions, when they occur, and what genes react to them. Large-scale multi-environment data sets are attractive data sources for these purposes because they potentially experienced various environmental conditions. Here we developed a data-driven approach termed Environmental Covariate Search Affecting Genetic Correlations (ECGC) to identify environmental stimuli and genes responsible for the G × E interactions from large-scale multi-environment data sets. ECGC was applied to a soybean (Glycine max) data set that consisted of 25,158 records collected at 52 environments. ECGC illustrated what meteorological factors shaped the G × E interactions in six traits including yield, flowering time, and protein content and when these factors were involved in the interactions. For example, it illustrated the relevance of precipitation around sowing dates and hours of sunshine just before maturity to the interactions observed for yield. Moreover, genome-wide association mapping on the sensitivities to the identified stimuli discovered candidate and known genes responsible for the G × E interactions. Our results demonstrate the capability of data-driven approaches to bring novel insights on the G × E interactions observed in fields.

Cardiac physiology and metabolic gene expression during late organogenesis among F. heteroclitus embryo families from crosses between pollution-sensitive and -resistant parents

BACKGROUND

The teleost fish Fundulus heteroclitus inhabit estuaries heavily polluted with persistent and bioaccumulative chemicals. While embryos of parents from polluted sites are remarkably resistant to toxic sediment and develop normally, embryos of parents from relatively clean estuaries, when treated with polluted sediment extracts, are developmentally delayed, displaying deformities characteristic of pollution-induced embryotoxicity. To gain insight into parental effects on sensitive and resistant phenotypes during late organogenesis, we established sensitive, resistant, and crossed embryo families using five female and five male parents from relatively clean and predominantly PAH-polluted estuaries each, measured heart rates, and quantified individual embryo expression of 179 metabolic genes.

RESULTS

Pollution-induced embryotoxicity manifested as morphological deformities, significant developmental delays, and altered cardiac physiology was evident among sensitive embryos resulting from crosses between females and males from relatively clean estuaries. Significantly different heart rates among several geographically unrelated populations of sensitive, resistant, and crossed embryo families during late organogenesis and pre-hatching suggest site-specific adaptive cardiac physiology phenotypes relative to pollution exposure. Metabolic gene expression patterns (32 genes, 17.9%, at p < 0.05; 11 genes, 6.1%, at p < 0.01) among the embryo families indicate maternal pollutant deposition in the eggs and parental effects on gene expression and metabolic alterations.

CONCLUSION

Heart rate differences among sensitive, resistant, and crossed embryos is a reliable phenotype for further explorations of adaptive mechanisms. While metabolic gene expression patterns among embryo families are suggestive of parental effects on several differentially expressed genes, a definitive adaptive signature and metabolic cost of resistant phenotypes is unclear and shows unexpected sensitive-resistant crossed embryo expression profiles. Our study highlights physiological and metabolic gene expression differences during a critical embryonic stage among pollution sensitive, resistant, and crossed embryo families, which may contribute to underlying resistance mechanisms observed in natural F. heteroclitus populations living in heavily contaminated estuaries.

Genetic Bases of Complex Traits: From Quantitative Trait Loci to Prediction

Conceived as a general introduction to the book, this chapter is a reminder of the core concepts of genetic mapping and molecular marker-based prediction. It provides an overview of the principles and the evolution of methods for mapping the variation of complex traits, and methods for QTL-based prediction of human disease risk and animal and plant breeding value. The principles of linkage-based and linkage disequilibrium-based QTL mapping methods are described in the context of the simplest, single-marker, methods. Methodological evolutions are analysed in relation with their ability to account for the complexity of the genotype-phenotype relations. Main characteristics of the genetic architecture of complex traits, drawn from QTL mapping works using large populations of unrelated individuals, are presented. Methods combining marker-QTL association data into polygenic risk score that captures part of an individual's susceptibility to complex diseases are reviewed. Principles of best linear mixed model-based prediction of breeding value in animal- and plant-breeding programs using phenotypic and pedigree data, are summarized and methods for moving from BLUP to marker-QTL BLUP are presented. Factors influencing the additional genetic progress achieved by using molecular data and rules for their optimization are discussed.

Diversity in nonlinear responses to soil moisture shapes evolutionary constraints in Brachypodium

Water availability is perhaps the greatest environmental determinant of plant yield and fitness. However, our understanding of plant-water relations is limited because-like many studies of organism-environment interaction-it is primarily informed by experiments considering performance at two discrete levels-wet and dry-rather than as a continuously varying environmental gradient. Here, we used experimental and statistical methods based on function-valued traits to explore genetic variation in responses to a continuous soil moisture gradient in physiological and morphological traits among 10 genotypes across two species of the model grass genus Brachypodium. We find that most traits exhibit significant genetic variation and nonlinear responses to soil moisture variability. We also observe differences in the shape of these nonlinear responses between traits and genotypes. Emergent phenomena arise from this variation including changes in trait correlations and evolutionary constraints as a function of soil moisture. Our results point to the importance of considering diversity in nonlinear organism-environment relationships to understand plastic and evolutionary responses to changing climates.

Genetic architecture of the metabolic pathway of salicylic acid biosynthesis in Populus

Salicylic acid (SA) is a vital hormone for adaptive responses to biotic and abiotic stresses, which facilitates growth-immunity trade-offs in plants. However, the genetic regulatory networks underlying the metabolic pathway of SA biosynthesis in perennial species remain unclear. Here, we integrated genome-wide association study (GWAS) with metabolite and expression profiling methodologies to dissect the genetic architecture of SA biosynthesis in Populus. First, we quantified nine intermediate metabolites of SA biosynthesis in 300 unrelated Populus tomentosa Carr. individuals. Then, we used a systematic genetic strategy to identify candidate genes for constructing the genetic regulatory network of SA biosynthesis. We focused on WRKY70, an efficient transcription factor, as the key causal gene in the regulatory network, and combined the novel genes coordinating the accumulation of SA. Finally, we identified eight GWAS signals and eight expression quantitative trait loci situated in a selective sweep, and showed the presence of large allele frequency differences among the three geographic populations, revealing that candidate genes subject to selection were involved in SA biosynthesis. This study provides an integrated strategy for dissecting the genetic architecture of the metabolic pathway of SA biosynthesis in Populus, thereby enhancing our understanding of genetic regulation of SA biosynthesis in trees, and accelerating marker-assisted breeding efforts toward high-resistance elite varieties of Populus.

Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for maize QTL mapping

Stomata are adjustable pores on leaf surfaces that regulate the tradeoff of CO2 uptake with water vapor loss, thus having critical roles in controlling photosynthetic carbon gain and plant water use. The lack of easy, rapid methods for phenotyping epidermal cell traits have limited discoveries about the genetic basis of stomatal patterning. A high-throughput epidermal cell phenotyping pipeline is presented here and used for quantitative trait loci (QTL) mapping in field-grown maize (Zea mays). The locations and sizes of stomatal complexes and pavement cells on images acquired by an optical topometer from mature leaves were automatically determined. Computer estimated stomatal complex density (SCD; R2 = 0.97) and stomatal complex area (SCA; R2 = 0.71) were strongly correlated with human measurements. Leaf gas exchange traits were genetically correlated with the dimensions and proportions of stomatal complexes (rg = 0.39-0.71) but did not correlate with SCD. Heritability of epidermal traits was moderate to high (h2 = 0.42-0.82) across two field seasons. Thirty-six QTL were consistently identified for a given trait in both years. Twenty-four clusters of overlapping QTL for multiple traits were identified, with univariate versus multivariate single marker analysis providing evidence consistent with pleiotropy in multiple cases. Putative orthologs of genes known to regulate stomatal patterning in Arabidopsis (Arabidopsis thaliana) were located within some, but not all, of these regions. This study demonstrates how discovery of the genetic basis for stomatal patterning can be accelerated in maize, a C4 model species where these processes are poorly understood.

Transgenerational effects of parent plant competition on offspring development in contrasting conditions

Conditions during a parent's lifetime can induce phenotypic changes in offspring, providing a potentially important source of variation in natural populations. Yet, to date, biotic factors have seldom been tested as sources of transgenerational effects in plants. In a greenhouse experiment with the generalist annual Polygonum persicaria, we tested for effects of parental competition on offspring by growing isogenic parent plants either individually or in competitive arrays and comparing their seedling progeny in contrasting growth environments. Offspring of competing vs. non-competing parents showed significantly altered development, resulting in greater biomass and total leaf area, but only when growing in neighbor or simulated canopy shade, rather than sunny dry conditions. A follow-up experiment in which parent plants instead competed in dry soil found that offspring in dry soil had slightly reduced growth, both with and without competitors. In neither experiment were effects of parental competition explained by changes in seed provisioning, suggesting a more complex mode of regulatory inheritance. We hypothesize that parental competition in moist soil (i.e., primarily for light) confers specific developmental effects that are beneficial for light-limited offspring, while parental competition in dry soil (i.e., primarily for belowground resources) produces offspring of slightly lower overall quality. Together, these results indicate that competitive conditions during the parental generation can contribute significantly to offspring variation, but these transgenerational effects will depend on the abiotic resources available to both parents and progeny.

Adaptive variation and plasticity in non-structural carbohydrate storage in a temperate tree species

Trees' total amount of non-structural carbohydrate (NSC) stores and the proportion of these stores residing as insoluble starch are vital traits for individuals living in variable environments. However, our understanding of how stores vary in response to environmental stress is poorly understood as the genetic component of storage is rarely accounted for in studies. Here, we quantified variation in NSC traits in branch samples taken from over 600 clonally transplanted black cottonwood (Populus trichocarpa) trees grown in two common gardens. We found heritable variation in both total NSC stores and the proportion of stores in starch (H²_TNC  = 0.19, H²_PropStarch  = 0.31), indicating a substantial genetic component of variation. In addition, we found high amounts of plasticity in both traits in response to cold temperatures and significant genotype-by-environment (GxE) interactions in the total amount of NSC stored (54% of P is GxE). This finding of high GxE indicates extensive variation across trees in their response to environment, which may explain why previous studies of carbohydrate stores' responses to stress have failed to converge on a consistent pattern. Overall, we found high amounts of environmental and genetic variation in NSC storage concentrations, which may bolster species against future climate change.

Transcriptomic responses and physiological changes to cold stress among natural populations provide insights into local adaptation of weeping forsythia

Genetic mechanisms of species local adaptation are an emerging topic of great interest in evolutionary biology and molecular ecology. In this study, we compared the changes of physiological and phenotypic indexes and gene expression of four weeping forsythia populations under cold stress through a common garden experiment. Physiological and phenotypic results showed that there were differences in cold tolerance among populations. cold tolerance of high the latitude population (HBWZ) was the strongest, followed by the middle latitude population (SXWL), while the low latitude populations (SXHM) and (SXLJ) expressed the weakest cold tolerance. We identified significant differences in gene expression of cold tolerance related pathways and ontologies, including genes of oxylipin and isoquinoline alkaloid biosynthetic process, galactose, tyrosine and unsaturated fatty acids metabolism, among these populations under the same experimental temperature treatments. Even under the same degree of stress, there were notable differences in gene expression among natural populations. In this study, we present a working model of weeping forsythia populations which evolved in the context of different intensities of cold stress. Our study provides new insights for comprehending the genetic mechanisms of local adaptation for non-model species.

Phenotypic Plasticity Contributes to Maize Adaptation and Heterosis

Plant phenotypic plasticity describes altered phenotypic performance of an individual when grown in different environments. Exploring genetic architecture underlying plant plasticity variation may help mitigate the detrimental effects of a rapidly changing climate on agriculture, but little research has been done in this area to date. In the present study, we established a population of 976 maize F₁ hybrids by crossing 488 diverse inbred lines with two elite testers. Genome-wide association study identified hundreds of quantitative trait loci associated with phenotypic plasticity variation across diverse F₁ hybrids, the majority of which contributed very little variance, in accordance with the polygenic nature of these traits. We identified several quantitative trait locus regions that may have been selected during the tropical-temperate adaptation process. We also observed heterosis in terms of phenotypic plasticity, in addition to the traditional genetic value differences measured between hybrid and inbred lines, and the pattern of which was affected by genetic background. Our results demonstrate a landscape of phenotypic plasticity in maize, which will aid in the understanding of its genetic architecture, its contribution to adaptation and heterosis, and how it may be exploited for future maize breeding in a rapidly changing environment.

Unraveling the roles of genotype and environment in the expression of plant defense phenotypes

Phenotypic variability results from interactions between genotype and environment and is a major driver of ecological and evolutionary interactions. Measuring the relative contributions of genetic variation, the environment, and their interaction to phenotypic variation remains a fundamental goal of evolutionary ecology.In this study, we assess the question: How do genetic variation and local environmental conditions interact to influence phenotype within a single population? We explored this question using seed from a single population of common milkweed, Asclepias syriaca, in northern Michigan. We first measured resistance and resistance traits of 14 maternal lines in two common garden experiments (field and greenhouse) to detect genetic variation within the population. We carried out a reciprocal transplant experiment with three of these maternal lines to assess effects of local environment on phenotype. Finally, we compared the phenotypic traits measured in our experiments with the phenotypic traits of the naturally growing maternal genets to be able to compare relative effect of genetic and environmental variation on naturally occurring phenotypic variation. We measured defoliation levels, arthropod abundances, foliar cardenolide concentrations, foliar latex exudation, foliar carbon and nitrogen concentrations, and plant growth.We found a striking lack of correlation in trait expression of the maternal lines between the common gardens, or between the common gardens and the naturally growing maternal genets, suggesting that environment plays a larger role in phenotypic trait variation of this population. We found evidence of significant genotype-by-environment interactions for all traits except foliar concentrations of nitrogen and cardenolide. Milkweed resistance to chewing herbivores was associated more strongly with the growing environment. We observed no variation in foliar cardenolide concentrations among maternal lines but did observe variation among maternal lines in foliar latex exudation.Overall, our data reveal powerful genotype-by-environment interactions on the expression of most resistance traits in milkweed.

Correlation and co-localization of QTL for stomatal density, canopy temperature, and productivity with and without drought stress in Setaria

Mechanistic modeling indicates that stomatal conductance could be reduced to improve water use efficiency (WUE) in C4 crops. Genetic variation in stomatal density and canopy temperature was evaluated in the model C4 genus, Setaria. Recombinant inbred lines (RILs) derived from a Setaria italica×Setaria viridis cross were grown with ample or limiting water supply under field conditions in Illinois. An optical profilometer was used to rapidly assess stomatal patterning, and canopy temperature was measured using infrared imaging. Stomatal density and canopy temperature were positively correlated but both were negatively correlated with total above-ground biomass. These trait relationships suggest a likely interaction between stomatal density and the other drivers of water use such as stomatal size and aperture. Multiple quantitative trait loci (QTL) were identified for stomatal density and canopy temperature, including co-located QTL on chromosomes 5 and 9. The direction of the additive effect of these QTL on chromosome 5 and 9 was in accordance with the positive phenotypic relationship between these two traits. This, along with prior experiments, suggests a common genetic architecture between stomatal patterning and WUE in controlled environments with canopy transpiration and productivity in the field, while highlighting the potential of Setaria as a model to understand the physiology and genetics of WUE in C4 species.

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

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

Transcriptome and physiological analyses provide insights into the leaf epicuticular wax accumulation mechanism in yellowhorn

Plantations and production of yellowhorn, one of the most important woody oil and urban greening trees widely cultivated in northern China, have gradually become limited by drought stress. The epicuticular wax layer plays a key role in the protection of yellowhorn trees from drought and other stresses. However, there is no research on the mechanism of wax loading in yellowhorn trees. In this study, we investigated the anatomical and physiological characteristics of leaves from different germplasm resources and different parts of the same tree and compared their cuticle properties. In addition, the different expression patterns of genes involved in wax accumulation were analyzed, and a coexpression network was built based on transcriptome sequencing data. Morphological and physiological comparisons found that the sun leaves from the outer part of the crown had thicker epicuticular wax, which altered the permeability and improved the drought resistance of leaves, than did shade leaves. Based on transcriptome data, a total of 3008 and 1324 differentially expressed genes (DEGs) were identified between the sun leaves and shade leaves in glossy- and non-glossy-type germplasm resources, respectively. We identified 138 DEGs involved in wax biosynthesis and transport, including structural genes (such as LACS8, ECH1, and ns-LTP) and transcription factors (such as MYB, WRKY, and bHLH transcription factor family proteins). The coexpression network showed a strong correlation between these DEGs. The differences in gene expression patterns between G- and NG-type germplasm resources under different light conditions were very clear. These results not only provide a theoretical basis for screening and developing drought-resistant yellowhorn germplasm resources but also provide a data platform to reveal the wax accumulation process of yellowhorn leaves.

Genetic determinants of seed protein plasticity in response to the environment in Medicago truncatula

As the frequency of extreme environmental events is expected to increase with climate change, identifying candidate genes for stabilizing the protein composition of legume seeds or optimizing this in a given environment is increasingly important. To elucidate the genetic determinants of seed protein plasticity, major seed proteins from 200 ecotypes of Medicago truncatula grown in four contrasting environments were quantified after one-dimensional electrophoresis. The plasticity index of these proteins was recorded for each genotype as the slope of Finlay and Wilkinson's regression and then used for genome-wide association studies (GWASs), enabling the identification of candidate genes for determining this plasticity. This list was enriched in genes related to transcription, DNA repair and signal transduction, with many of them being stress responsive. Other over-represented genes were related to sulfur and aspartate family pathways leading to the synthesis of the nutritionally essential amino acids methionine and lysine. By placing these genes in metabolic pathways, and using a M. truncatula mutant impaired in regenerating methionine from S-methylmethionine, we discovered that methionine recycling pathways are major contributors to globulin composition establishment and plasticity. These data provide a unique resource of genes that can be targeted to mitigate negative impacts of environmental stresses on seed protein composition.

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.

Multiple modes of selection can influence the role of phenotypic plasticity in species' invasions: Evidence from a manipulative field experiment

In exploring the roles of phenotypic plasticity in the establishment and early evolution of invading species, little empirical attention has been given to the importance of correlational selection acting upon suites of functionally related plastic traits in nature. We illustrate how this lack of attention has limited our ability to evaluate plasticity's role during invasion and also, the costs and benefits of plasticity. We addressed these issues by transplanting clones of European-derived Plantago lanceolata L. genotypes into two temporally variable habitats in the species' introduced range in North America. Phenotypic selection analyses were performed for each habitat to estimate linear, quadratic, and correlational selection on phenotypic trait values and plasticities in the reproductive traits: flowering onset and spike and scape lengths. Also, we measured pairwise genetic correlations for our "colonists." Results showed that (a) correlational selection acted on trait plasticity after transplantation, (b) selection favored certain combinations of genetically correlated and uncorrelated trait values and plasticities, and (c) using signed, instead of absolute, values of plasticity in analyses facilitated the detection of correlational selection on trait value-plasticity combinations and their adaptive value. Based on our results, we urge future studies on species invasions to (a) measure correlational selection and (b) retain signed values of plasticity in order to better discriminate between adaptive and maladaptive plasticity.

QTL x environment interactions underlie ionome divergence in switchgrass

Ionomics measures elemental concentrations in biological organisms and provides a snapshot of physiology under different conditions. In this study, we evaluate genetic variation of the ionome in outbred, perennial switchgrass in three environments across the species' native range, and explore patterns of genotype-by-environment interactions. We grew 725 clonally replicated genotypes of a large full sib family from a four-way linkage mapping population, created from deeply diverged upland and lowland switchgrass ecotypes, at three common gardens. Concentrations of 18 mineral elements were determined in whole post-anthesis tillers using ion coupled plasma mass spectrometry (ICP-MS). These measurements were used to identify quantitative trait loci (QTL) with and without QTL-by-environment interactions (QTLxE) using a multi-environment QTL mapping approach. We found that element concentrations varied significantly both within and between switchgrass ecotypes, and GxE was present at both the trait and QTL level. Concentrations of 14 of the 18 elements were under some genetic control, and 77 QTL were detected for these elements. 74% of QTL colocalized multiple elements, half of QTL exhibited significant QTLxE, and roughly equal numbers of QTL had significant differences in magnitude and sign of their effects across environments. The switchgrass ionome is under moderate genetic control and by loci with highly variable effects across environments.

Establishment of Regional Phytoremediation Buffer Systems for Ecological Restoration in the Great Lakes Basin, USA. I. Genotype × Environment Interactions

Poplar remediation systems are ideal for reducing runoff, cleaning groundwater, and delivering ecosystem services to the North American Great Lakes and globally. We used phyto-recurrent selection (PRS) to establish sixteen phytoremediation buffer systems (phyto buffers) (buffer groups: 2017 × 6; 2018 × 5; 2019 × 5) throughout the Lake Superior and Lake Michigan watersheds comprised of twelve PRS-selected clones each year. We tested for differences in genotypes, environments, and their interactions for health, height, diameter, and volume from ages one to four years. All trees had optimal health. Mean first-, second-, and third-year volume ranged from 71 ± 26 to 132 ± 39 cm3; 1440 ± 575 to 5765 ± 1132 cm3; and 8826 ± 2646 to 10,530 ± 2110 cm3, respectively. Fourth-year mean annual increment of 2017 buffer group trees ranged from 1.1 ± 0.7 to 7.8 ± 0.5 Mg ha−1 yr−1. We identified generalist varieties with superior establishment across a broad range of buffers (‘DM114’, ‘NC14106’, ‘99038022’, ‘99059016’) and specialist clones uniquely adapted to local soil and climate conditions (‘7300502’, ‘DN5’, ‘DN34’, ‘DN177’, ‘NM2’, ‘NM5’, ‘NM6’). Using generalists and specialists enhances the potential for phytoremediation best management practices that are geographically robust, being regionally designed yet globally relevant.

Multisite evaluation of phenotypic plasticity for specialized metabolites, some involved in carrot quality and disease resistance

Renewed consumer demand motivates the nutritional and sensory quality improvement of fruits and vegetables. Specialized metabolites being largely involved in nutritional and sensory quality of carrot, a better knowledge of their phenotypic variability is required. A metabolomic approach was used to evaluate phenotypic plasticity level of carrot commercial varieties, over three years and a wide range of cropping environments spread over several geographical areas in France. Seven groups of metabolites have been quantified by HPLC or GC methods: sugars, carotenoids, terpenes, phenolic compounds, phenylpropanoids and polyacetylenes. A large variation in root metabolic profiles was observed, in relation with environment, variety and variety by environment interaction effects in decreasing order of importance. Our results show a clear diversity structuration based on metabolite content. Polyacetylenes, β-pinene and α-carotene were identified mostly as relatively stable varietal markers, exhibiting static stability. Nevertheless, environment effect was substantial for a large part of carrot metabolic profile and various levels of phenotypic plasticity were observed depending on metabolites and varieties. A strong difference of environmental sensitivity between varieties was observed for several compounds, particularly myristicin, 6MM and D-germacrene, known to be involved in responses to biotic and abiotic stress. This work provides useful information about plasticity in the perspective of carrot breeding and production. A balance between constitutive content and environmental sensitivity for key metabolites should be reached for quality improvement in carrot and other vegetables.

Review: Plant eco-evolutionary responses to climate change: Emerging directions

Contemporary climate change is exposing plant populations to novel combinations of temperatures, drought stress, [CO₂] and other abiotic and biotic conditions. These changes are rapidly disrupting the evolutionary dynamics of plants. Despite the multifactorial nature of climate change, most studies typically manipulate only one climatic factor. In this opinion piece, we explore how climate change factors interact with each other and with biotic pressures to alter evolutionary processes. We evaluate the ramifications of climate change across life history stages,and examine how mating system variation influences population persistence under rapid environmental change. Furthermore, we discuss how spatial and temporal mismatches between plants and their mutualists and antagonists could affect adaptive responses to climate change. For example, plant-virus interactions vary from highly pathogenic to mildly facilitative, and are partly mediated by temperature, moisture availability and [CO₂]. Will host plants exposed to novel, stressful abiotic conditions be more susceptible to viral pathogens? Finally, we propose novel experimental approaches that could illuminate how plants will cope with unprecedented global change, such as resurrection studies combined with experimental evolution, genomics or epigenetics.

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.

The evolution of group differences in changing environments

The selection pressures that have shaped the evolution of complex traits in humans remain largely unknown, and in some contexts highly contentious, perhaps above all where they concern mean trait differences among groups. To date, the discussion has focused on whether such group differences have any genetic basis, and if so, whether they are without fitness consequences and arose via random genetic drift, or whether they were driven by selection for different trait optima in different environments. Here, we highlight a plausible alternative: that many complex traits evolve under stabilizing selection in the face of shifting environmental effects. Under this scenario, there will be rapid evolution at the loci that contribute to trait variation, even when the trait optimum remains the same. These considerations underscore the strong assumptions about environmental effects that are required in ascribing trait differences among groups to genetic differences.

The Potential for Genotype-by-Environment Interactions to Maintain Genetic Variation in a Model Legume-Rhizobia Mutualism

The maintenance of genetic variation in mutualism-related traits is key for understanding mutualism evolution, yet the mechanisms maintaining variation remain unclear. We asked whether genotype-by-environment (G×E) interaction is a potential mechanism maintaining variation in the model legume-rhizobia system, Medicago truncatula-Ensifer meliloti. We planted 50 legume genotypes in a greenhouse under ambient light and shade to reflect reduced carbon availability for plants. We found an expected reduction under shaded conditions for plant performance traits, such as leaf number, aboveground and belowground biomass, and a mutualism-related trait, nodule number. We also found G×E for nodule number, with ∼83% of this interaction due to shifts in genotype fitness rank order across light environments, coupled with strong positive directional selection on nodule number regardless of light environment. Our results suggest that G×E can maintain genetic variation in a mutualism-related trait that is under consistent positive directional selection across light environments.

Genotype by environment interaction for gene expression in Drosophila melanogaster

The genetics of phenotypic responses to changing environments remains elusive. Using whole-genome quantitative gene expression as a model, here we study how the genetic architecture of regulatory variation in gene expression changed in a population of fully sequenced inbred Drosophila melanogaster strains when flies developed in different environments (25 °C and 18 °C). We find a substantial fraction of the transcriptome exhibited genotype by environment interaction, implicating environmentally plastic genetic architecture of gene expression. Genetic variance in expression increases at 18 °C relative to 25 °C for most genes that have a change in genetic variance. Although the majority of expression quantitative trait loci (eQTLs) for the gene expression traits in the two environments are shared and have similar effects, analysis of the environment-specific eQTLs reveals enrichment of binding sites for two transcription factors. Finally, although genotype by environment interaction in gene expression could potentially disrupt genetic networks, the co-expression networks are highly conserved across environments. Genes with higher network connectivity are under stronger stabilizing selection, suggesting that stabilizing selection on expression plays an important role in promoting network robustness.

Examining the molecular mechanisms contributing to the success of an invasive species across different ecosystems

Invasive species provide an opportune system to investigate how populations respond to new environments. Baby's breath (Gypsophila paniculata) was introduced to North America in the 1800s and has since spread throughout the United States and western Canada. We used an RNA-seq approach to explore how molecular processes contribute to the success of invasive populations with similar genetic backgrounds across distinct habitats. Transcription profiles were constructed from seedlings collected from a sand dune ecosystem in Petoskey, MI (PSMI), and a sagebrush ecosystem in Chelan, WA (CHWA). We assessed differential gene expression and identified SNPs within differentially expressed genes. We identified 1,146 differentially expressed transcripts across all sampled tissues between the two populations. GO processes enriched in PSMI were associated with nutrient starvation, while enriched processes in CHWA were associated with abiotic stress. Only 7.4% of the differentially expressed transcripts contained SNPs differing in allele frequencies of at least 0.5 between populations. Common garden studies found the two populations differed in germination rate and seedling emergence success. Our results suggest the success of G. paniculata in these two environments is likely due to plasticity in specific molecular processes responding to different environmental conditions, although some genetic divergence may be contributing to these differences.

Detection of QTLs for genotype × environment interactions in tomato seeds and seedlings

Seed quality and seedling establishment are the most important factors affecting successful crop development. They depend on the genetic background and are acquired during seed maturation and therefor, affected by the maternal environment under which the seeds develop. There is little knowledge about the genetic and environmental factors that affect seed quality and seedling establishment. The aim of this study is to identify the loci and possible molecular mechanisms involved in acquisition of seed quality and how these are controlled by adverse maternal conditions. For this, we used a tomato recombinant inbred line (RIL) population consisting of 100 lines which were grown under two different nutritional environmental conditions, high phosphate and low nitrate. Most of the seed germination traits such as maximum germination percentage (G_max ), germination rate (t₅₀ ) and uniformity (U₈₄₁₆ ) showed ample variation between genotypes and under different germination conditions. This phenotypic variation leads to identification of quantitative trait loci (QTLs) which were dependent on genetic factors, but also on the interaction with the maternal environment (QTL × E). Further studies of these QTLs may ultimately help to predict the effect of different maternal environmental conditions on seed quality and seedling establishment which will be very useful to improve the production of high-performance seeds.

Multiscale computational models can guide experimentation and targeted measurements for crop improvement

Computational models of plants have identified gaps in our understanding of biological systems, and have revealed ways to optimize cellular processes or organ-level architecture to increase productivity. Thus, computational models are learning tools that help direct experimentation and measurements. Models are simplifications of complex systems, and often simulate specific processes at single scales (e.g. temporal, spatial, organizational, etc.). Consequently, single-scale models are unable to capture the critical cross-scale interactions that result in emergent properties of the system. In this perspective article, we contend that to accurately predict how a plant will respond in an untested environment, it is necessary to integrate mathematical models across biological scales. Computationally mimicking the flow of biological information from the genome to the phenome is an important step in discovering new experimental strategies to improve crops. A key challenge is to connect models across biological, temporal and computational (e.g. CPU versus GPU) scales, and then to visualize and interpret integrated model outputs. We address this challenge by describing the efforts of the international Crops in silico consortium.

The platform GrowScreen-Agar enables identification of phenotypic diversity in root and shoot growth traits of agar grown plants

BACKGROUND

Root system architecture and especially its plasticity in acclimation to variable environments play a crucial role in the ability of plants to explore and acquire efficiently soil resources and ensure plant productivity. Non-destructive measurement methods are indispensable to quantify dynamic growth traits. For closing the phenotyping gap, we have developed an automated phenotyping platform, GrowScreen-Agar, for non-destructive characterization of root and shoot traits of plants grown in transparent agar medium.

RESULTS

The phenotyping system is capable to phenotype root systems and correlate them to whole plant development of up to 280 Arabidopsis plants within 15 min. The potential of the platform has been demonstrated by quantifying phenotypic differences within 78 Arabidopsis accessions from the 1001 genomes project. The chosen concept 'plant-to-sensor' is based on transporting plants to the imaging position, which allows for flexible experimental size and design. As transporting causes mechanical vibrations of plants, we have validated that daily imaging, and consequently, moving plants has negligible influence on plant development. Plants are cultivated in square Petri dishes modified to allow the shoot to grow in the ambient air while the roots grow inside the Petri dish filled with agar. Because it is common practice in the scientific community to grow Arabidopsis plants completely enclosed in Petri dishes, we compared development of plants that had the shoot inside with that of plants that had the shoot outside the plate. Roots of plants grown completely inside the Petri dish grew 58% slower, produced a 1.8 times higher lateral root density and showed an etiolated shoot whereas plants whose shoot grew outside the plate formed a rosette. In addition, the setup with the shoot growing outside the plate offers the unique option to accurately measure both, leaf and root traits, non-destructively, and treat roots and shoots separately.

CONCLUSIONS

Because the GrowScreen-Agar system can be moved from one growth chamber to another, plants can be phenotyped under a wide range of environmental conditions including future climate scenarios. In combination with a measurement throughput enabling phenotyping a large set of mutants or accessions, the platform will contribute to the identification of key genes.

Genomic-based root plasticity to enhance abiotic stress adaptation and edible yield in grain crops

Phenotypic plasticity refers to changes expressed by a genotype across different environments and is one of the major means by which plants cope with environmental variability. Multi-fold differences in phenotypic plasticity have been noted across crops, with wild ancestors and landraces being more plastic than crops when under stress. Plasticity in response to abiotic stress adaptation, plant architecture, physio-reproductive and quality traits are multi-genic (QTL). Plasticity QTL (pQTL) were either collocated with main effect QTL and QEI (QTL × environment interaction) or located independently from the main effect QTL. For example, variations in root plasticity have been successfully introgressed to enhance abiotic stress adaptation in rice. The independence of genetic control of a trait and of its plasticity suggests that breeders may select for high or low plasticity in combination with high or low performance of economically important traits. Trait plasticity in stressful environments may be harnessed through breeding stress-tolerant crops. There exists a genetic cost associated with plasticity, so a better understanding of the trade-offs between plasticity and productivity is warranted prior to undertaking breeding for plasticity traits together with productivity in stress environments.

Dynamic genetic architecture of yeast response to environmental perturbation shed light on origin of cryptic genetic variation

Cryptic genetic variation could arise from, for example, Gene-by-Gene (G-by-G) or Gene-by-Environment (G-by-E) interactions. The underlying molecular mechanisms and how they influence allelic effects and the genetic variance of complex traits is largely unclear. Here, we empirically explored the role of environmentally influenced epistasis on the suppression and release of cryptic variation by reanalysing a dataset of 4,390 haploid yeast segregants phenotyped on 20 different media. The focus was on 130 epistatic loci, each contributing to segregant growth in at least one environment and that together explained most (69–100%) of the narrow sense heritability of growth in the individual environments. We revealed that the epistatic growth network reorganised upon environmental changes to alter the estimated marginal (additive) effects of the individual loci, how multi-locus interactions contributed to individual segregant growth and the level of expressed genetic variance in growth. The estimated additive effects varied most across environments for loci that were highly interactive network hubs in some environments but had few or no interactors in other environments, resulting in changes in total genetic variance across environments. This environmentally dependent epistasis was thus an important mechanism for the suppression and release of cryptic variation in this population. Our findings increase the understanding of the complex genetic mechanisms leading to cryptic variation in populations, providing a basis for future studies on the genetic maintenance of trait robustness and development of genetic models for studying and predicting selection responses for quantitative traits in breeding and evolution.

Many biological traits are polygenic, with complex interplay between underlying genes and the surrounding environment. As a result, individuals with the same allele might have distinctive phenotypes due to differences in the polygenic background and/or the environment. Such differences often create additional genetic variation that is highly relevant to quantitative and evolutionary genetics by limiting our ability to accurately predict the phenotypes in medical or agricultural applications and providing opportunities for long term evolution. Previously, yeast growth regulating genes were found to be organised in large interacting networks. Here, we found that these networks were reorganised upon environmental changes, and that this resulted in altered effect sizes of individual genes, and how the whole network contributed to growth and the level of total genetic variance, providing a basis for future studies on the genetic maintenance of trait robustness and development of genetic models for studying and predicting selection responses for quantitative traits.

Additive and mostly adaptive plastic responses of gene expression to multiple stress in Tribolium castaneum

Gene expression is known to be highly responsive to the environment and important for adjustment of metabolism but there is also growing evidence that differences in gene regulation contribute to species divergence and differences among locally adapted populations. However, most studies so far investigated populations when divergence had already occurred. Selection acting on expression levels at the onset of adaptation to an environmental change has not been characterized. Understanding the mechanisms is further complicated by the fact that environmental change is often multivariate, meaning that organisms are exposed to multiple stressors simultaneously with potentially interactive effects. Here we use a novel approach by combining fitness and whole-transcriptome data in a large-scale experiment to investigate responses to drought, heat and their combination in Tribolium castaneum. We found that fitness was reduced by both stressors and their combined effect was almost additive. Expression data showed that stressor responses were acting independently and did not interfere physiologically. Since we measured expression and fitness within the same individuals, we were able to estimate selection on gene expression levels. We found that variation in fitness can be attributed to gene expression variation and that selection pressures were environment dependent and opposite between control and stress conditions. We could further show that plastic responses of expression were largely adaptive, i.e. in the direction that should increase fitness.

Dynamic effects of interacting genes underlying rice flowering-time phenotypic plasticity and global adaptation

The phenotypic variation of living organisms is shaped by genetics, environment, and their interaction. Understanding phenotypic plasticity under natural conditions is hindered by the apparently complex environment and the interacting genes and pathways. Herein, we report findings from the dissection of rice flowering-time plasticity in a genetic mapping population grown in natural long-day field environments. Genetic loci harboring four genes originally discovered for their photoperiodic effects (Hd1, Hd2, Hd5, and Hd6) were found to differentially respond to temperature at the early growth stage to jointly determine flowering time. The effects of these plasticity genes were revealed with multiple reaction norms along the temperature gradient. By coupling genomic selection and the environmental index, accurate performance predictions were obtained. Next, we examined the allelic variation in the four flowering-time genes across the diverse accessions from the 3000 Rice Genomes Project and constructed haplotypes at both individual-gene and multigene levels. The geographic distribution of haplotypes revealed their preferential adaptation to different temperature zones. Regions with lower temperatures were dominated by haplotypes sensitive to temperature changes, whereas the equatorial region had a majority of haplotypes that are less responsive to temperature. By integrating knowledge from genomics, gene cloning and functional characterization, and environment quantification, we propose a conceptual model with multiple levels of reaction norms to help bridge the gaps among individual gene discovery, field-level phenotypic plasticity, and genomic diversity and adaptation.

Exploration of the Yield Potential of Mesoamerican Wild Common Beans From Contrasting Eco-Geographic Regions by Nested Recombinant Inbred Populations

Genetic analyses and utilization of wild genetic variation for crop improvement in common bean (Phaseolus vulgaris L.) have been hampered by yield evaluation difficulties, identification of advantageous variation, and linkage drag. The lack of adaptation to cultivation conditions and the existence of highly structured populations make association mapping of diversity panels not optimal. Joint linkage mapping of nested populations avoids the later constraint, while populations crossed with a common domesticated parent allow the evaluation of wild variation within a more adapted background. Three domesticated by wild backcrossed-inbred-line populations (BC₁S₄) were developed using three wild accessions representing the full range of rainfall of the Mesoamerican wild bean distribution crossed to the elite drought tolerant domesticated parent SEA 5. These populations were evaluated under field conditions in three environments, two fully irrigated trials in two seasons and a simulated terminal drought in the second season. The goal was to test if these populations responded differently to drought stress and contained progenies with higher yield than SEA 5, not only under drought but also under water-watered conditions. Results revealed that the two populations derived from wild parents of the lower rainfall regions produced lines with higher yield compared to the domesticated parent in the three environments, i.e., both in the drought-stressed environment and in the well-watered treatments. Several progeny lines produced yields, which on average over the three environments were 20% higher than the SEA 5 yield. Twenty QTLs for yield were identified in 13 unique regions on eight of the 11 chromosomes of common bean. Five of these regions showed at least one wild allele that increased yield over the domesticated parent. The variation explained by these QTLs ranged from 0.6 to 5.4% of the total variation and the additive effects ranged from -164 to 277 kg ha^-1, with evidence suggesting allelic series for some QTLs. Our results underscore the potential of wild variation, especially from drought-stressed regions, for bean crop improvement as well the identification of regions for efficient marker-assisted introgression.

Genetic variance for behavioural 'predictability' of stress response

Genetic factors underpinning phenotypic variation are required if natural selection is to result in adaptive evolution. However, evolutionary and behavioural ecologists typically focus on variation among individuals in their average trait values and seek to characterize genetic contributions to this. As a result, less attention has been paid to if and how genes could contribute towards within-individual variance or trait 'predictability'. In fact, phenotypic 'predictability' can vary among individuals, and emerging evidence from livestock genetics suggests this can be due to genetic factors. Here, we test this empirically using repeated measures of a behavioural stress response trait in a pedigreed population of wild-type guppies. We ask (a) whether individuals differ in behavioural predictability and (b) whether this variation is heritable and so evolvable under selection. Using statistical methodology from the field of quantitative genetics, we find support for both hypotheses and also show evidence of a genetic correlation structure between the behavioural trait mean and individual predictability. We show that investigating sources of variability in trait predictability is statistically tractable and can yield useful biological interpretation. We conclude that, if widespread, genetic variance for 'predictability' will have major implications for the evolutionary causes and consequences of phenotypic variation.

The Genetic Architecture for Phenotypic Plasticity of the Rice Grain Ionome

The ionome of the rice grain is crucial for the health of populations that consume rice as a staple food. However, the contribution of phenotypic plasticity to the variation of rice grain ionome and the genetic architecture of phenotypic plasticity are poorly understood. In this study, we investigated the rice grain ionome of a rice diversity panel in up to eight environments. A considerable proportion of phenotypic variance can be attributed to phenotypic plasticity. Then, phenotypic plasticity and mean phenotype were quantified using Bayesian Finlay-Wilkinson regression, and a significant correlation between them was observed. However, the genetic architecture of mean phenotype was distinct from that of phenotypic plasticity. Also, the correlation between them was mainly attributed to the phenotypic divergence between rice subspecies. Furthermore, the results of whole-genome regression analysis showed that the genetic loci related to phenotypic plasticity can explain a considerable proportion of the phenotypic variance in some environments, especially for Cd, Cu, Mn, and Zn. Our study not only sheds light on the genetic architecture of phenotypic plasticity of the rice grain ionome but also suggests that the genetic loci which related to phenotypic plasticity are valuable in rice grain ionome improvement breeding.

Life History Variation as a Model for Understanding Trade-Offs in Plant-Environment Interactions

All plants must allocate limited resources to survival, growth, and reproduction. In natural species, allocation strategies reflect trade-offs between survivorship risk and subsequent fitness benefits and are therefore central to a species' ecology. Artificial selection on allocation has generated high-yielding crops that often invest the bare minimum in defense or longevity. Ecological, genetic, and evolutionary analyses of plant life history - particularly with respect to longevity and resource allocation along an axis from annual to perennial species - provides a framework to evaluate trade-offs in plant-environment interactions in natural and managed systems. Recent efforts to develop new model plant systems for research and to increase agricultural resilience and efficiency by developing herbaceous perennial crops motivates our critical assessment of traditional assumptions regarding differences between annual and perennial plant species. Here, we review our present understanding of the genetic basis of physiological, developmental, and anatomical differences in wild and crop species and reach two broad conclusions. First, that perenniality and annuality should be considered syndromes comprised of many interacting traits, and that elucidating the genetic basis of these traits is required to assess models of evolution and to develop successful breeding strategies. Modern phenomic and biotechnology tools will facilitate these enquiries. Second, many classic assumptions about the difference between the two syndromes are supported by limited evidence. Throughout this Review, we highlight key knowledge gaps in the proximate and ultimate mechanisms driving life history variation, and suggest empirical approaches to parameterize trade-offs and to make progress in this critical area of direct relevance to ecology and plant performance in a changing world.

Trait-environment interactions affect plant establishment success during restoration

Establishment and persistence are central to community assembly and are determined by how traits interact with the environment to determine performance (trait-environment interactions). Community assembly studies have rarely considered such trait-environment interactions, however, which can lead to incorrect inferences about how traits affect assembly. We evaluated how functional traits, environmental conditions, and trait-environment interactions structure plant establishment, as a measure of performance. Within 12 prairie restorations created by sowing 70 species, we quantified environmental conditions and counted individuals of each seeded species to quantify first-year establishment. Three trait-environment interactions structured establishment. Leaf nitrogen interacted with herbivore pressure, as low leaf nitrogen species established relatively better under higher herbivory than species with high leaf nitrogen. Soil moisture interacted with root mass fraction (RMF), with low-RMF species establishing better with low soil moisture and higher-RMF species better on wetter soils. Specific leaf area (SLA) interacted with light availability, as low-SLA species established better under high light conditions and high-SLA species under low light conditions. Our work illustrates how community assembly can be better described by trait-environment interactions than correlating traits or environment with performance. This knowledge can assist species selection to maximize restoration success.

The coding loci of evolution and domestication: current knowledge and implications for bio-inspired genome editing

One promising application of CRISPR/Cas9 is to create targeted mutations to introduce traits of interest into domesticated organisms. However, a major current limitation for crop and livestock improvement is to identify the precise genes and genetic changes that must be engineered to obtain traits of interest. Here, we discuss the advantages of bio-inspired genome editing, i.e. the engineered introduction of natural mutations that have already been associated with traits of interest in other lineages (breeds, populations or species). To obtain a landscape view of potential targets for genome editing, we used Gephebase (www.gephebase.org), a manually curated database compiling published data about the genes responsible for evolutionary and domesticated changes across eukaryotes, and examined the &gt;1200 mutations that have been identified in the coding regions of more than 700 genes in animals, plants and yeasts. We observe that our genetic knowledge is relatively important for certain traits, such as xenobiotic resistance, and poor for others. We also note that protein-null alleles, often owing to nonsense and frameshift mutations, represent a large fraction of the known loci of domestication (42% of identified coding mutations), compared with intraspecific (27%) and interspecific evolution (11%). Although this trend may be subject to detection, publication and curation biases, it is consistent with the idea that breeders have selected large-effect mutations underlying adaptive traits in specific settings, but that these mutations and associated phenotypes would not survive the vagaries of changing external and internal environments. Our compilation of the loci of evolution and domestication uncovers interesting options for bio-inspired and transgene-free genome editing.

Environmental variation impacts trait expression and selection in the legume-rhizobium symbiosis

PREMISE

The ecological outcomes of mutualism are well known to shift across abiotic or biotic environments, but few studies have addressed how different environments impact evolutionary responses, including the intensity of selection on and the expression of genetic variance in key mutualism-related traits.

METHODS

We planted 30 maternal lines of the legume Medicago lupulina in four field common gardens and compared our measures of selection on and genetic variance in nodulation, a key trait reflecting legume investment in the symbiosis, with those from a previous greenhouse experiment using the same 30 M. lupulina lines.

RESULTS

We found that both the mean and genetic variance for nodulation were much greater in the greenhouse than in the field and that the form of selection on nodulation significantly differed across environments. We also found significant genotype-by-environment (G × E) effects for fitness-related traits that were generated by differences in the rank order of plant lines among environments.

CONCLUSIONS

Overall, our results suggest that the expression of genotypic variation and selection on nodulation differ across environments. In the field, significant rank-order changes for plant fitness potentially help maintain genetic variation in natural populations, even in the face of directional or stabilizing selection.

Plants are intelligent, here's how

HYPOTHESES

The drive to survive is a biological universal. Intelligent behaviour is usually recognized when individual organisms including plants, in the face of fiercely competitive or adverse, real-world circumstances, change their behaviour to improve their probability of survival.

SCOPE

This article explains the potential relationship of intelligence to adaptability and emphasizes the need to recognize individual variation in intelligence showing it to be goal directed and thus being purposeful. Intelligent behaviour in single cells and microbes is frequently reported. Individual variation might be underpinned by a novel learning mechanism, described here in detail. The requirements for real-world circumstances are outlined, and the relationship to organic selection is indicated together with niche construction as a good example of intentional behaviour that should improve survival. Adaptability is important in crop development but the term may be complex incorporating numerous behavioural traits some of which are indicated.

CONCLUSION

There is real biological benefit to regarding plants as intelligent both from the fundamental issue of understanding plant life but also from providing a direction for fundamental future research and in crop breeding.

Genomics of Long- and Short-Term Adaptation in Maize and Teosintes

Maize is an excellent model for the study of plant adaptation. Indeed, post domestication maize quickly adapted to a host of new environments across the globe. And work over the last decade has begun to highlight the role of the wild relatives of maize-the teosintes Zea mays ssp. parviglumis and ssp. mexicana-as excellent models for dissecting long-term local adaptation.Although human-driven selection associated with maize domestication has been extensively studied, the genetic basis of natural variation is still poorly understood. Here we review studies on the genetic basis of adaptation and plasticity in maize and its wild relatives. We highlight a range of different processes that contribute to adaptation and discuss evidence from natural, cultivated, and experimental populations. From an applied perspective, understanding the genetic bases of adaptation and the contribution of plasticity will provide us with new tools to both better understand and mitigate the effect of climate changes on natural and cultivated populations.

Two reproductive traits show contrasting genetic architectures in Plantago lanceolata

In many species, temperature-sensitive phenotypic plasticity (i.e., an individual's phenotypic response to temperature) displays a positive correlation with latitude, a pattern presumed to reflect local adaptation. This geographical pattern raises two general questions: (a) Do a few large-effect genes contribute to latitudinal variation in a trait? (b) Is the thermal plasticity of different traits regulated pleiotropically? To address the questions, we crossed individuals of Plantago lanceolata derived from northern and southern European populations. Individuals naturally exhibited high and low thermal plasticity in floral reflectance and flowering time. We grew parents and offspring in controlled cool- and warm-temperature environments, mimicking what plants would encounter in nature. We obtained genetic markers via genotype-by-sequencing, produced the first recombination map for this ecologically important nonmodel species, and performed quantitative trait locus (QTL) mapping of thermal plasticity and single-environment values for both traits. We identified a large-effect QTL that largely explained the reflectance plasticity differences between northern and southern populations. We identified multiple smaller-effect QTLs affecting aspects of flowering time, one of which affected flowering time plasticity. The results indicate that the genetic architecture of thermal plasticity in flowering is more complex than for reflectance. One flowering time QTL showed strong cytonuclear interactions under cool temperatures. Reflectance and flowering plasticity QTLs did not colocalize, suggesting little pleiotropic genetic control and freedom for independent trait evolution. Such genetic information about the architecture of plasticity is environmentally important because it informs us about the potential for plasticity to offset negative effects of climate change.