Evolutionary pathways to lower biomass allocation to the seed coat in crops: insights from allometric scaling.

Crops generally have seeds larger than their wild progenitors´ and with reduced dormancy. In wild plants, seed mass and allocation to the seed coat (a proxy for physical dormancy) scale allometrically so that larger seeds tend to allocate less to the coats. Larger seeds and lightweight coats might thus have evolved as correlated traits in crops. We tested whether 34 crops and 22 of their wild progenitors fit the allometry described in the literature, which would indicate co-selection of both traits during crop evolution. Deviations from the allometry would suggest that other evolutionary processes contribute to explain the emergence of larger, lightweight-coated seeds in crops. Crops fitted the scaling slope but deviated from its intercept in a consistent way: Seed coats of crops were lighter than expected by their seed size. The wild progenitors of crops displayed the same trend, indicating that deviations cannot be solely attributed to artificial selection during or after domestication. The evolution of seeds with small coats in crops likely resulted from a combination of various pressures, including the selection of wild progenitors with coats smaller than other wild plants, further decreases during early evolution under cultivation, and indirect selection due to the seed coat-seed size allometry.

Plant-herbivore interactions: Experimental demonstration of genetic variability in plant-plant signalling.

Plant-herbivore interactions mediated by plant-plant signalling have been documented in different species but its within-species variability has hardly been quantified. Here, we tested if herbivore foraging activity on plants was influenced by a prior contact with a damaged plant and if the effect of such plant-plant signalling was variable across 113 natural genotypes of Arabidopsis thaliana. We filmed the activity of the generalist herbivore Cornu aspersum during 1 h on two plants differing only in a prior contact with a damaged plant or not. We recorded each snails' first choice, and measured its first duration on a plant, the proportion of time spent on both plants and leaf consumption. Overall, plant-plant signalling modified the foraging activity of herbivores in A. thaliana. On average, snails spent more time and consumed more of plants that experienced a prior contact with a damaged plant. However, the effects of plant-plant signalling on snail behaviour was variable: depending on genotype identity, plant-plant signalling made undamaged plants more repellant or attractive to snails. Genome-wide associations revealed that genes related to stress coping ability and jasmonate pathway were associated to this variation. Together, our findings highlight the adaptive significance of plant-plant signalling for plant-herbivore interactions.

AraDiv: a dataset of functional traits and leaf hyperspectral reflectance of Arabidopsis thaliana.

Data from functional trait databases have been increasingly used to address questions related to plant diversity and trait-environment relationships. However, such databases provide intraspecific data that combine individual records obtained from distinct populations at different sites and, hence, environmental conditions. This prevents distinguishing sources of variation (e.g., genetic-based variation vs. phenotypic plasticity), a necessary condition to test for adaptive processes and other determinants of plant phenotypic diversity. Consequently, individual traits measured under common growing conditions and encompassing within-species variation across the occupied geographic range have the potential to leverage trait databases with valuable data for functional and evolutionary ecology. Here, we recorded 16 functional traits and leaf hyperspectral reflectance (NIRS) data for 721 widely distributed Arabidopsis thaliana natural accessions grown in a common garden experiment. These data records, together with meteorological variables obtained during the experiment, were assembled to create the AraDiv dataset. AraDiv is a comprehensive dataset of A. thaliana's intraspecific variability that can be explored to address questions at the interface of genetics and ecology.

Domestication provides durum wheat with protection from locust herbivory.

Lower plant resistance to herbivores following domestication has been suggested as the main cause for higher feeding damage in crops than in wild progenitors. While herbivore compensatory feeding has also been proposed as a possible mechanism for raised damage in crops with low nutritional quality, predictions regarding the effects of plant domestication on nutritional quality for herbivores remain unclear. In particular, data on primary metabolites, even major macronutrients, measured in the organs consumed by herbivores, are scarce. In this study, we used a collection of 10 accessions of wild ancestors and 10 accessions of modern progenies of Triticum turgidum to examine whether feeding damage and selectivity by nymphs of Locusta migratoria primarily depended on five leaf traits related to structural resistance or nutrient profiles. Our results unexpectedly showed that locusts favored wild ancestors over domesticated accessions and that leaf toughness and nitrogen and soluble protein contents increased with the domestication process. Furthermore, the quantitative relationship between soluble protein and digestible carbohydrates was found to poorly meet the specific requirements of the herbivore, in all wheat accessions, both wild and modern. The increase in leaf structural resistance to herbivores in domesticated tetraploid wheat accessions suggested that resource allocation trade-offs between growth and herbivory resistance may have been disrupted by domestication in the vegetative organs of this species. Since domestication did not result in a loss of nutritional quality in the leaves of the tetraploid wheat, our results rather provides evidence for a role of the content of plants in nonnutritive nitrogenous secondary compounds, possibly deterrent or toxic, at least for grasshopper herbivores.

Increasing plant group productivity through latent genetic variation for cooperation.

Historic yield advances in the major crops have, to a large extent, been achieved by selection for improved productivity of groups of plant individuals such as high-density stands. Research suggests that such improved group productivity depends on "cooperative" traits (e.g., erect leaves, short stems) that-while beneficial to the group-decrease individual fitness under competition. This poses a problem for some traditional breeding approaches, especially when selection occurs at the level of individuals, because "selfish" traits will be selected for and reduce yield in high-density monocultures. One approach, therefore, has been to select individuals based on ideotypes with traits expected to promote group productivity. However, this approach is limited to architectural and physiological traits whose effects on growth and competition are relatively easy to anticipate. Here, we developed a general and simple method for the discovery of alleles promoting cooperation in plant stands. Our method is based on the game-theoretical premise that alleles increasing cooperation benefit the monoculture group but are disadvantageous to the individual when facing noncooperative neighbors. Testing the approach using the model plant Arabidopsis thaliana, we found a major effect locus where the rarer allele was associated with increased cooperation and productivity in high-density stands. The allele likely affects a pleiotropic gene, since we find that it is also associated with reduced root competition but higher resistance against disease. Thus, even though cooperation is considered evolutionarily unstable except under special circumstances, conflicting selective forces acting on a pleiotropic gene might maintain latent genetic variation for cooperation in nature. Such variation, once identified in a crop, could rapidly be leveraged in modern breeding programs and provide efficient routes to increase yields.

Solving the grand challenge of phenotypic integration: allometry across scales.

Phenotypic integration is a concept related to the cascade of trait relationships from the lowest organizational levels, i.e. genes, to the highest, i.e. whole-organism traits. However, the cause-and-effect linkages between traits are notoriously difficult to determine. In particular, we still lack a mathematical framework to model the relationships involved in the integration of phenotypic traits. Here, we argue that allometric models developed in ecology offer testable mathematical equations of trait relationships across scales. We first show that allometric relationships are pervasive in biology at different organizational scales and in different taxa. We then present mechanistic models that explain the origin of allometric relationships. In addition, we emphasized that recent studies showed that natural variation does exist for allometric parameters, suggesting a role for genetic variability, selection and evolution. Consequently, we advocate that it is time to examine the genetic determinism of allometries, as well as to question in more detail the role of genome size in subsequent scaling relationships. More broadly, a possible-but so far neglected-solution to understand phenotypic integration is to examine allometric relationships at different organizational levels (cell, tissue, organ, organism) and in contrasted species.

A Perspective on Plant Phenomics: Coupling Deep Learning and Near-Infrared Spectroscopy.

The trait-based approach in plant ecology aims at understanding and classifying the diversity of ecological strategies by comparing plant morphology and physiology across organisms. The major drawback of the approach is that the time and financial cost of measuring the traits on many individuals and environments can be prohibitive. We show that combining near-infrared spectroscopy (NIRS) with deep learning resolves this limitation by quickly, non-destructively, and accurately measuring a suite of traits, including plant morphology, chemistry, and metabolism. Such an approach also allows to position plants within the well-known CSR triangle that depicts the diversity of plant ecological strategies. The processing of NIRS through deep learning identifies the effect of growth conditions on trait values, an issue that plagues traditional statistical approaches. Together, the coupling of NIRS and deep learning is a promising high-throughput approach to capture a range of ecological information on plant diversity and functioning and can accelerate the creation of extensive trait databases.

The genetic interaction of REVOLUTA and WRKY53 links plant development, senescence, and immune responses.

In annual plants, tight coordination of successive developmental events is of primary importance to optimize performance under fluctuating environmental conditions. The recent finding of the genetic interaction of WRKY53, a key senescence-related gene with REVOLUTA, a master regulator of early leaf patterning, raises the question of how early and late developmental events are connected. Here, we investigated the developmental and metabolic consequences of an alteration of the REVOLUTA and WRKY53 gene expression, from seedling to fruiting. Our results show that REVOLUTA critically controls late developmental phases and reproduction while inversely WRKY53 determines vegetative growth at early developmental stages. We further show that these regulators of distinct developmental phases frequently, but not continuously, interact throughout ontogeny and demonstrated that their genetic interaction is mediated by the salicylic acid (SA). Moreover, we showed that REVOLUTA and WRKY53 are keys regulatory nodes of development and plant immunity thought their role in SA metabolic pathways, which also highlights the role of REV in pathogen defence. Together, our findings demonstrate how late and early developmental events are tightly intertwined by molecular hubs. These hubs interact with each other throughout ontogeny, and participate in the interplay between plant development and immunity.

Into the range: a latitudinal gradient or a center-margins differentiation of ecological strategies in Arabidopsis thaliana?

BACKGROUND AND AIMS: Determining within-species large-scale variation in phenotypic traits is central to elucidate the drivers of species' ranges. Intraspecific comparisons offer the opportunity to understand how trade-offs and biogeographical history constrain adaptation to contrasted environmental conditions. Here we test whether functional traits, ecological strategies from the CSR scheme and phenotypic plasticity in response to abiotic stress vary along a latitudinal or a center- margins gradient within the native range of Arabidopsis thaliana. METHODS: We experimentally examined the phenotypic outcomes of plant adaptation at the center and margins of its geographic range using 30 accessions from southern, central and northern Europe. We characterized the variation of traits related to stress tolerance, resource use, colonization ability, CSR strategy scores, survival and fecundity in response to high temperature (34 °C) or frost (- 6 °C), combined with a water deficit treatment. KEY RESULTS: We found evidence for both a latitudinal and a center-margins differentiation for the traits under scrutiny. Age at maturity, leaf dry matter content, specific leaf area and leaf nitrogen content varied along a latitudinal gradient. Northern accessions presented a greater survival to stress than central and southern accessions. Leaf area, C-scores, R-scores and fruit number followed a center-margins differentiation. Central accessions displayed a higher phenotypic plasticity than northern and southern accessions for most studied traits. CONCLUSIONS: Traits related to an acquisitive/conservative resource-use trade-off followed a latitudinal gradient. Traits associated with a competition/colonization trade-off differentiated along the historic colonization of the distribution range and then followed a center-margins differentiation. Our findings pinpoint the need to consider the joint effect of evolutionary history and environmental factors when examining phenotypic variation across the distribution range of a species.

Natural variation at FLM splicing has pleiotropic effects modulating ecological strategies in Arabidopsis thaliana.

Investigating the evolution of complex phenotypes and the underlying molecular bases of their variation is critical to understand how organisms adapt to their environment. Applying classical quantitative genetics on a segregating population derived from a Can-0xCol-0 cross, we identify the MADS-box transcription factor FLOWERING LOCUS M (FLM) as a player of the phenotypic variation in plant growth and color. We show that allelic variation at FLM modulates plant growth strategy along the leaf economics spectrum, a trade-off between resource acquisition and resource conservation, observable across thousands of plant species. Functional differences at FLM rely on a single intronic substitution, disturbing transcript splicing and leading to the accumulation of non-functional FLM transcripts. Associations between this substitution and phenotypic and climatic data across Arabidopsis natural populations, show how noncoding genetic variation at a single gene might be adaptive through pleiotropic effects.

Weeds: Against the Rules?

Establishing laws of plant and ecosystems functioning has been an overarching objective of functional and evolutionary ecology. However, most theories neglect the role of human activities in creating novel ecosystems characterized by species assemblages and environmental factors that are not observed in natural systems. We argue that agricultural weeds, as an emblematic case of such an 'ecological novelty', constitute an original and underutilized model for challenging current concepts in ecology and evolution. We highlight key aspects of weed ecology and evolutionary biology that can help to test and recast ecological and evolutionary laws in a changing world. We invite ecologists to seize upon weeds as a model system to improve our understanding of the short-term and long-term dynamics of ecological systems in the Anthropocene.

Natural variation of Arabidopsis thaliana responses to Cauliflower mosaic virus infection upon water deficit.

Plant virus pathogenicity is expected to vary with changes in the abiotic environment that affect plant physiology. Conversely, viruses can alter the host plant response to additional stimuli from antagonism to mutualism depending on the virus, the host plant and the environment. Ecological theory, specifically the CSR framework of plant strategies developed by Grime and collaborators, states that plants cannot simultaneously optimize resistance to both water deficit and pathogens. Here, we investigated the vegetative and reproductive performance of 44 natural accessions of A. thaliana originating from the Iberian Peninsula upon simultaneous exposure to soil water deficit and viral infection by the Cauliflower mosaic virus (CaMV). Following the predictions of Grime's CSR theory, we tested the hypothesis that the ruderal character of a plant genotype is positively related to its tolerance to virus infection regardless of soil water availability. Our results showed that CaMV infection decreased plant vegetative performance and annihilated reproductive success of all accessions. In general, water deficit decreased plant performance, but, despite differences in behavior, ranking of accessions tolerance to CaMV was conserved under water deficit. Ruderality, quantified from leaf traits following a previously published procedure, varied significantly among accessions, and was positively correlated with tolerance to viral infection under both well-watered and water deficit conditions, although the latter to a lesser extent. Also, in accordance with the ruderal character of the accession and previous findings, our results suggest that accession tolerance to CaMV infection is positively correlated with early flowering. Finally, plant survival to CaMV infection increased under water deficit. The complex interactions between plant, virus and abiotic environment are discussed in terms of the variation in plant ecological strategies at the intraspecific level.

Leaf economics and slow-fast adaptation across the geographic range of Arabidopsis thaliana.

Life history strategies of most organisms are constrained by resource allocation patterns that follow a 'slow-fast continuum'. It opposes slow growing and long-lived organisms with late investment in reproduction to those that grow faster, have earlier and larger reproductive effort and a short longevity. In plants, the Leaf Economics Spectrum (LES) depicts a leaf-level trade-off between the rate of carbon assimilation and leaf lifespan, as stressed in functional ecology from interspecific comparative studies. However, it is still unclear how the LES is connected to the slow-fast syndrome. Interspecific comparisons also impede a deep exploration of the linkage between LES variation and adaptation to climate. Here, we measured growth, morpho-physiological and life-history traits, at both the leaf and whole-plant levels, in 378 natural accessions of Arabidopsis thaliana. We found that the LES is tightly linked to variation in whole-plant functioning, and aligns with the slow-fast continuum. A genetic analysis further suggested that phenotypic differentiation results from the selection of different slow-fast strategies in contrasted climates. Slow growing and long-lived plants were preferentially found in cold and arid habitats while fast growing and short-lived ones in more favorable habitats. Our findings shed light on the role of the slow-fast continuum for plant adaptation to climate. More broadly, they encourage future studies to bridge functional ecology, genetics and evolutionary biology to improve our understanding of plant adaptation to environmental changes.

Secondary metabolites have more influence than morphophysiological traits on litter decomposability across genotypes of Arabidopsis thaliana.

Although interspecific variation in plant phenotype is recognised to impact afterlife processes such as litter decomposability, it is still unclear which traits and selection pressures explain these relationships. Examining intraspecific variation is crucial to identify and compare trait effects on decomposability, and investigate the potential role of natural selection. We studied the genetic variability and relationships between decomposability, plant traits typically related to decomposability at species level (morphophysiological traits), and leaf metabolites among a set of genotypes of Arabidopsis thaliana grown under controlled conditions. We also investigated correlations between decomposability and environmental variables at genotypes collection site. We investigated the genetic architecture of decomposability with genome-wide association studies (GWAS). There was large genetic variability in decomposability that was correlated with precipitation. Morphophysiological traits had a minor effect, while secondary metabolites, especially glucosinolates, were correlated with decomposability. Consistently, GWAS suggested that genes and metabolites related to the composition of cell membranes and envelopes control the variation of decomposability across genotypes. Our study suggests that decomposability varies within species as a result of metabolic adaptation to climate. Our findings highlight that subtle variations of defence-related metabolites like glucosinolates may strongly influence after-life processes such as decomposability.

Nonlinear phenotypic variation uncovers the emergence of heterosis in Arabidopsis thaliana.

Heterosis describes the phenotypic superiority of hybrids over their parents in traits related to agronomic performance and fitness. Understanding and predicting nonadditive inheritance such as heterosis is crucial for evolutionary biology as well as for plant and animal breeding. However, the physiological bases of heterosis remain debated. Moreover, empirical data in various species have shown that diverse genetic and molecular mechanisms are likely to explain heterosis, making it difficult to predict its emergence and amplitude from parental genotypes alone. In this study, we examined a model of physiological dominance initially proposed by Sewall Wright to explain the nonadditive inheritance of traits like metabolic fluxes at the cellular level. We evaluated Wright's model for two fitness-related traits at the whole-plant level, growth rate and fruit number, using 450 hybrids derived from crosses among natural accessions of A. thaliana. We found that allometric relationships between traits constrain phenotypic variation in a nonlinear and similar manner in hybrids and accessions. These allometric relationships behave predictably, explaining up to 75% of heterosis amplitude, while genetic distance among parents at best explains 7%. Thus, our findings are consistent with Wright's model of physiological dominance and suggest that the emergence of heterosis on plant performance is an intrinsic property of nonlinear relationships between traits. Furthermore, our study highlights the potential of a geometric approach of phenotypic relationships for predicting heterosis of major components of crop productivity and yield.

Climate as a driver of adaptive variations in ecological strategies in Arabidopsis thaliana.

Background and aims: The CSR classification categorizes plants as stress tolerators (S), ruderals (R) and competitors (C). Initially proposed as a general framework to describe ecological strategies across species, this scheme has recently been used to investigate the variation of strategies within species. For instance, ample variation along the S-R axis was found in Arabidopsis thaliana, with stress-tolerator accessions predominating in hot and dry regions, which was interpreted as a sign of functional adaptation to climate within the species. Methods: In this study the range of CSR strategies within A. thaliana was evaluated across 426 accessions originating from North Africa to Scandinavia. A position in the CSR strategy space was allocated for every accession based on three functional traits: leaf area, leaf dry matter content (LDMC) and specific leaf area (SLA). Results were related to climate at origin and compared with a previous study performed on the same species. Furthermore, the role of natural selection in phenotypic differentiation between lineages was investigated with QST-FST comparisons, using the large amount of genetic information available for this species. Key Results: Substantial variation in ecological strategies along the S-R axis was found in A. thaliana. By contrast with previous findings, stress-tolerator accessions predominated in cold climates, notably Scandinavia, where late flowering was associated with traits related to resource conservation, such as high LDMC and low SLA. Because of trait plasticity, variations in CSR classification in relation to growth conditions were also observed for the same genotypes. Conclusions: There is a latitudinal gradient of ecological strategies in A. thaliana as a result of within-species adaptation to climate. Our study also underlines the importance of growth conditions and of the methodology used for trait measurement, notably age versus stage measurement, to infer the strength and direction of trait-environment relationships. This highlights the potential and limitations of the CSR classification in explaining functional adaptation to the environment.

Image-based methods for phenotyping growth dynamics and fitness components in Arabidopsis thaliana.

BACKGROUND: The model species Arabidopsis thaliana has extensive resources to investigate intraspecific trait variability and the genetic bases of ecologically relevant traits. However, the cost of equipment and software required for high-throughput phenotyping is often a bottleneck for large-scale studies, such as mutant screening or quantitative genetics analyses. Simple tools are needed for the measurement of fitness-related traits, like relative growth rate and fruit production, without investment in expensive infrastructures. Here, we describe methods that enable the estimation of biomass accumulation and fruit number from the analysis of rosette and inflorescence images taken with a regular camera. RESULTS: We developed two models to predict plant dry mass and fruit number from the parameters extracted with the analysis of rosette and inflorescence images. Predictive models were trained by sacrificing growing individuals for dry mass estimation, and manually measuring a fraction of individuals for fruit number at maturity. Using a cross-validation approach, we showed that quantitative parameters extracted from image analysis predicts more 90% of both plant dry mass and fruit number. When used on 451 natural accessions, the method allowed modeling growth dynamics, including relative growth rate, throughout the life cycle of various ecotypes. Estimated growth-related traits had high heritability (0.65 < H2 < 0.93), as well as estimated fruit number (H2 = 0.68). In addition, we validated the method for estimating fruit number with rev5, a mutant with increased flower abortion. CONCLUSIONS: The method we propose here is an application of automated computerization of plant images with ImageJ, and subsequent statistical modeling in R. It allows plant biologists to measure growth dynamics and fruit number in hundreds of individuals with simple computing steps that can be repeated and adjusted to a wide range of laboratory conditions. It is thus a flexible toolkit for the measurement of fitness-related traits in large populations of a model species.

Adaptive diversification of growth allometry in the plant Arabidopsis thaliana.

Seed plants vary tremendously in size and morphology; however, variation and covariation in plant traits may be governed, at least in part, by universal biophysical laws and biological constants. Metabolic scaling theory (MST) posits that whole-organismal metabolism and growth rate are under stabilizing selection that minimizes the scaling of hydrodynamic resistance and maximizes the scaling of resource uptake. This constrains variation in physiological traits and in the rate of biomass accumulation, so that they can be expressed as mathematical functions of plant size with near-constant allometric scaling exponents across species. However, the observed variation in scaling exponents calls into question the evolutionary drivers and the universality of allometric equations. We have measured growth scaling and fitness traits of 451 Arabidopsis thaliana accessions with sequenced genomes. Variation among accessions around the scaling exponent predicted by MST was correlated with relative growth rate, seed production, and stress resistance. Genomic analyses indicate that growth allometry is affected by many genes associated with local climate and abiotic stress response. The gene with the strongest effect, PUB4, has molecular signatures of balancing selection, suggesting that intraspecific variation in growth scaling is maintained by opposing selection on the trade-off between seed production and abiotic stress resistance. Our findings suggest that variation in allometry contributes to local adaptation to contrasting environments. Our results help reconcile past debates on the origin of allometric scaling in biology and begin to link adaptive variation in allometric scaling to specific genes.

Genomic basis and evolutionary potential for extreme drought adaptation in Arabidopsis thaliana.

As Earth is currently experiencing dramatic climate change, it is of critical interest to understand how species will respond to it. The chance of a species withstanding climate change is likely to depend on the diversity within the species and, particularly, whether there are sub-populations that are already adapted to extreme environments. However, most predictive studies ignore that species comprise genetically diverse individuals. We have identified genetic variants in Arabidopsis thaliana that are associated with survival of an extreme drought event-a major consequence of global warming. Subsequently, we determined how these variants are distributed across the native range of the species. Genetic alleles conferring higher drought survival showed signatures of polygenic adaptation and were more frequently found in Mediterranean and Scandinavian regions. Using geo-environmental models, we predicted that Central European, but not Mediterranean, populations might lag behind in adaptation by the end of the twenty-first century. Further analyses showed that a population decline could nevertheless be compensated by natural selection acting efficiently over standing variation or by migration of adapted individuals from populations at the margins of the species' distribution. These findings highlight the importance of within-species genetic heterogeneity in facilitating an evolutionary response to a changing climate.

Genetic architecture of nonadditive inheritance in Arabidopsis thaliana hybrids.

The ubiquity of nonparental hybrid phenotypes, such as hybrid vigor and hybrid inferiority, has interested biologists for over a century and is of considerable agricultural importance. Although examples of both phenomena have been subject to intense investigation, no general model for the molecular basis of nonadditive genetic variance has emerged, and prediction of hybrid phenotypes from parental information continues to be a challenge. Here we explore the genetics of hybrid phenotype in 435 Arabidopsis thaliana individuals derived from intercrosses of 30 parents in a half diallel mating scheme. We find that nonadditive genetic effects are a major component of genetic variation in this population and that the genetic basis of hybrid phenotype can be mapped using genome-wide association (GWA) techniques. Significant loci together can explain as much as 20% of phenotypic variation in the surveyed population and include examples that have both classical dominant and overdominant effects. One candidate region inherited dominantly in the half diallel contains the gene for the MADS-box transcription factor AGAMOUS-LIKE 50 (AGL50), which we show directly to alter flowering time in the predicted manner. Our study not only illustrates the promise of GWA approaches to dissect the genetic architecture underpinning hybrid performance but also demonstrates the contribution of classical dominance to genetic variance.