Intermediate degrees of synergistic pleiotropy drive adaptive evolution in ecological time

36-year study reveals stability of a wild wheat population across microhabitats

Long-term genetic studies of wild populations are very scarce, but are essential for connecting ecological and population genetics models, and for understanding the dynamics of biodiversity. We present a study of a wild wheat population sampled over a 36-year period at high spatial resolution. We genotyped 832 individuals from regular sampling along transects during the course of the experiment. Genotypes were clustered into ecological microhabitats over scales of tens of metres, and this clustering was remarkably stable over the 36 generations of the study. Simulations show that it is difficult to determine whether this spatial and temporal stability reflects extremely limited dispersal or fine-scale local adaptation to ecological parameters. Using a common-garden experiment, we showed that the genotypes found in distinct microhabitats differ phenotypically. Our results provide a rare insight into the population genetics of a natural population over a long monitoring period.

The genetic architecture of repeated local adaptation to climate in distantly related plants

Closely related species often use the same genes to adapt to similar environments. However, we know little about why such genes possess increased adaptive potential and whether this is conserved across deeper evolutionary lineages. Adaptation to climate presents a natural laboratory to test these ideas, as even distantly related species must contend with similar stresses. Here, we re-analyse genomic data from thousands of individuals from 25 plant species as diverged as lodgepole pine and Arabidopsis (~300 Myr). We test for genetic repeatability based on within-species associations between allele frequencies in genes and variation in 21 climate variables. Our results demonstrate significant statistical evidence for genetic repeatability across deep time that is not expected under randomness, identifying a suite of 108 gene families (orthogroups) and gene functions that repeatedly drive local adaptation to climate. This set includes many orthogroups with well-known functions in abiotic stress response. Using gene co-expression networks to quantify pleiotropy, we find that orthogroups with stronger evidence for repeatability exhibit greater network centrality and broader expression across tissues (higher pleiotropy), contrary to the 'cost of complexity' theory. These gene families may be important in helping wild and crop species cope with future climate change, representing important candidates for future study.

Temporal genomics help in deciphering neutral and adaptive patterns in the contemporary evolution of kelp populations

The impact of climate change on populations will be contingent upon their contemporary adaptive evolution. In this study, we investigated the contemporary evolution of 4 populations of the cold-water kelp Laminaria digitata by analyzing their spatial and temporal genomic variations using ddRAD-sequencing. These populations were sampled from the center to the southern margin of its north-eastern Atlantic distribution at 2 time points, spanning at least 2 generations. Through genome scans for local adaptation at a single time point, we identified candidate loci that showed clinal variation correlated with changes in sea surface temperature (SST) along latitudinal gradients. This finding suggests that SST may drive the adaptive response of these kelp populations, although factors such as species' demographic history should also be considered. Additionally, we performed a simulation approach to distinguish the effect of selection from genetic drift in allele frequency changes over time. This enabled the detection of loci in the southernmost population that exhibited temporal differentiation beyond what would be expected from genetic drift alone: these are candidate loci which could have evolved under selection over time. In contrast, we did not detect any outlier locus based on temporal differentiation in the population from the North Sea, which also displayed low and decreasing levels of genetic diversity. The diverse evolutionary scenarios observed among populations can be attributed to variations in the prevalence of selection relative to genetic drift across different environments. Therefore, our study highlights the potential of temporal genomics to offer valuable insights into the contemporary evolution of marine foundation species facing climate change.

Biotic interactions promote local adaptation to soil in plants

Although different ecological factors shape adaptative evolution in natural habitats, we know little about how their interactions impact local adaptation. Here we used eight generations of experimental evolution with outcrossing Brassica rapa plants as a model system, in eight treatment groups that varied in soil type, herbivory (with/without aphids), and pollination mode (hand- or bumblebee-pollination), to study how biotic interactions affect local adaptation to soil. First, we show that several plant traits evolved in response to biotic interactions in a soil-specific way. Second, using a reciprocal transplant experiment, we demonstrate that significant local adaptation to soil-type evolved in the "number of open flowers", a trait used as a fitness proxy, but only in plants that evolved with herbivory and bee pollination. Whole genome re-sequencing of experimental lines revealed that biotic interactions caused a 10-fold increase in the number of SNPs across the genome with significant allele frequency change, and that alleles with opposite allele frequency change in different soil types (antagonistic pleiotropy) were most common in plants with an evolutionary history of herbivory and bee pollination. Our results demonstrate that the interaction with mutualists and antagonists can facilitate local adaptation to soil type through antagonistic pleiotropy.

Natural genetic variation underlying the negative effect of elevated CO2 on ionome composition in Arabidopsis thaliana

The elevation of atmospheric CO2 leads to a decline in plant mineral content, which might pose a significant threat to food security in coming decades. Although few genes have been identified for the negative effect of elevated CO2 on plant mineral composition, several studies suggest the existence of genetic factors. Here, we performed a large-scale study to explore genetic diversity of plant ionome responses to elevated CO2, using six hundred Arabidopsis thaliana accessions, representing geographical distributions ranging from worldwide to regional and local environments. We show that growth under elevated CO2 leads to a global decrease of ionome content, whatever the geographic distribution of the population. We observed a high range of genetic diversity, ranging from the most negative effect to resilience or even to a benefit in response to elevated CO2. Using genome-wide association mapping, we identified a large set of genes associated with this response, and we demonstrated that the function of one of these genes is involved in the negative effect of elevated CO2 on plant mineral composition. This resource will contribute to understand the mechanisms underlying the effect of elevated CO2 on plant mineral nutrition, and could help towards the development of crops adapted to a high-CO2 world.

Variation and plasticity in life-history traits and fitness of wild Arabidopsis thaliana populations are not related to their genotypic and ecological diversity

BACKGROUND

Despite its implications for population dynamics and evolution, the relationship between genetic and phenotypic variation in wild populations remains unclear. Here, we estimated variation and plasticity in life-history traits and fitness of the annual plant Arabidopsis thaliana in two common garden experiments that differed in environmental conditions. We used up to 306 maternal inbred lines from six Iberian populations characterized by low and high genotypic (based on whole-genome sequences) and ecological (vegetation type) diversity.

RESULTS

Low and high genotypic and ecological diversity was found in edge and core Iberian environments, respectively. Given that selection is expected to be stronger in edge environments and that ecological diversity may enhance both phenotypic variation and plasticity, we expected genotypic diversity to be positively associated with phenotypic variation and plasticity. However, maternal lines, irrespective of the genotypic and ecological diversity of their population of origin, exhibited a substantial amount of phenotypic variation and plasticity for all traits. Furthermore, all populations harbored maternal lines with canalization (robustness) or sensitivity in response to harsher environmental conditions in one of the two experiments.

CONCLUSIONS

Overall, we conclude that the environmental attributes of each population probably determine their genotypic diversity, but all populations maintain substantial phenotypic variation and plasticity for all traits, which represents an asset to endure in changing environments.

A pan-genome of 69 Arabidopsis thaliana accessions reveals a conserved genome structure throughout the global species range

Although originally primarily a system for functional biology, Arabidopsis thaliana has, owing to its broad geographical distribution and adaptation to diverse environments, developed into a powerful model in population genomics. Here we present chromosome-level genome assemblies of 69 accessions from a global species range. We found that genomic colinearity is very conserved, even among geographically and genetically distant accessions. Along chromosome arms, megabase-scale rearrangements are rare and typically present only in a single accession. This indicates that the karyotype is quasi-fixed and that rearrangements in chromosome arms are counter-selected. Centromeric regions display higher structural dynamics, and divergences in core centromeres account for most of the genome size variations. Pan-genome analyses uncovered 32,986 distinct gene families, 60% being present in all accessions and 40% appearing to be dispensable, including 18% private to a single accession, indicating unexplored genic diversity. These 69 new Arabidopsis thaliana genome assemblies will empower future genetic research.

Strategies for breeding crops for future environments

The green revolution successfully increased agricultural output in the early 1960s by relying primarily on three pillars: plant breeding, irrigation, and chemical fertilization. Today, the need to reduce the use of chemical fertilizers, water scarcity, and future environmental changes, together with a growing population, requires innovative strategies to adapt to a new context and prevent food shortages. Therefore, scientists from around the world are directing their efforts to breed crops for future environments to sustainably produce more nutritious food. Herein, we propose scientific avenues to be reinforced in selecting varieties, including crop wild relatives, either for monoculture or mixed cropping systems, taking advantage of plant-microbial interactions, while considering the diversity of organisms associated with crops and unlocking combinatorial nutritional stresses.

Pervasive G × E interactions shape adaptive trajectories and the exploration of the phenotypic space in artificial selection experiments

Quantitative genetics models have shown that long-term selection responses depend on initial variance and mutational influx. Understanding limits of selection requires quantifying the role of mutational variance. However, correlative responses to selection on nonfocal traits can perturb the selection response on the focal trait; and generations are often confounded with selection environments so that genotype by environment (G×E) interactions are ignored. The Saclay divergent selection experiments (DSEs) on maize flowering time were used to track the fate of individual mutations combining genotyping data and phenotyping data from yearly measurements (DSEYM) and common garden experiments (DSECG) with four objectives: (1) to quantify the relative contribution of standing and mutational variance to the selection response, (2) to estimate genotypic mutation effects, (3) to study the impact of G×E interactions in the selection response, and (4) to analyze how trait correlations modulate the exploration of the phenotypic space. We validated experimentally the expected enrichment of fixed beneficial mutations with an average effect of +0.278 and +0.299 days to flowering, depending on the genetic background. Fixation of unfavorable mutations reached up to 25% of incoming mutations, a genetic load possibly due to antagonistic pleiotropy, whereby mutations fixed in the selection environment (DSEYM) turned to be unfavorable in the evaluation environment (DSECG). Global patterns of trait correlations were conserved across genetic backgrounds but exhibited temporal patterns. Traits weakly or uncorrelated with flowering time triggered stochastic exploration of the phenotypic space, owing to microenvironment-specific fixation of standing variants and pleiotropic mutational input.

Genetic architecture of the response of Arabidopsis thaliana to a native plant-growth-promoting bacterial strain

By improving plant nutrition and alleviating abiotic and biotic stresses, plant growth-promoting bacteria (PGPB) can help to develop eco-friendly and sustainable agricultural practices. Besides climatic conditions, soil conditions, and microbe-microbe interactions, the host genotype influences the effectiveness of PGPB. Yet, most GWAS conducted to characterize the genetic architecture of response to PGPB are based on non-native interactions between a host plant and PGPB strains isolated from the belowground compartment of other plants. In this study, a GWAS was set up under in vitro conditions to describe the genetic architecture of the response of Arabidopsis thaliana to the PGPB Pseudomonas siliginis, by inoculating seeds of 162 natural accessions from the southwest of France with one strain isolated from the leaf compartment in the same geographical region. Strong genetic variation of plant growth response to this native PGPB was observed at a regional scale, with the strain having a positive effect on the vegetative growth of small plants and a negative effect on the vegetative growth of large plants. The polygenic genetic architecture underlying this negative trade-off showed suggestive signatures of local adaptation. The main eco-evolutionary relevant candidate genes are involved in seed and root development.

Patterns and evolutionary consequences of pleiotropy

Pleiotropy refers to the phenomenon of one gene or one mutation affecting multiple phenotypic traits. While the concept of pleiotropy is as old as Mendelian genetics, functional genomics has finally allowed the first glimpses of the extent of pleiotropy for a large fraction of genes in a genome. After describing conceptual and operational difficulties in quantifying pleiotropy and the pros and cons of various methods for measuring pleiotropy, I review empirical data on pleiotropy, which generally show an L-shaped distribution of the degree of pleiotropy (i.e., the number of traits affected) with most genes having low pleiotropy. I then review the current understanding of the molecular basis of pleiotropy. The rest of the review discusses evolutionary consequences of pleiotropy, focusing on advances in topics including the cost of complexity, regulatory vs. coding evolution, environmental pleiotropy and adaptation, evolution of ageing and other seemingly harmful traits, and evolutionary resolution of pleiotropy.

Immigration and seasonal bottlenecks: high inbreeding despite high genetic diversity in an oscillating population of Culicoides sonorensis (Diptera: Ceratopogonidae)

Most population genetic studies concern spatial genetic differentiation, but far fewer aim at analyzing the temporal genetic changes that occur within populations. Vector species, including mosquitoes and biting midges, are often characterized by oscillating adult population densities, which may affect their dispersal, selection, and genetic diversity over time. Here, we used a population of Culicoides sonorensis from a single site in California to investigate short-term (intra-annual) and long-term (inter-annual) temporal variation in genetic diversity over a 3 yr period. This biting midge species is the primary vector of several viruses affecting both wildlife and livestock, thus a better understanding of the population dynamics of this species can help inform epidemiological studies. We found no significant genetic differentiation between months or years, and no correlation between adult populations and the inbreeding coefficient (FIS). However, we show that repeated periods of low adult abundance during cooler winter months resulted in recurring bottleneck events. Interestingly, we also found a high number of private and rare alleles, which suggests both a large, stable population, as well as a constant influx of migrants from nearby populations. Overall, we showed that the high number of migrants maintains a high level of genetic diversity by introducing new alleles, while this increased diversity is counterbalanced by recurrent bottleneck events potentially purging unfit alleles each year. These results highlight the temporal influences on population structure and genetic diversity in C. sonorensis and provide insight into factors effecting genetic variation that may occur in other vector species with fluctuating populations.

An atypical NLR gene confers bacterial wilt susceptibility in Arabidopsis

Quantitative disease resistance (QDR) remains the most prevalent form of plant resistance in crop fields and wild habitats. Genome-wide association studies (GWAS) have proved to be successful in deciphering the quantitative genetic basis of complex traits such as QDR. To unravel the genetics of QDR to the devastating worldwide bacterial pathogen Ralstonia solanacearum, we performed a GWAS by challenging a highly polymorphic local mapping population of Arabidopsis thaliana with four R. solanacearum type III effector (T3E) mutants, identified as key pathogenicity determinants after a first screen on an A. thaliana core collection of 25 accessions. Although most quantitative trait loci (QTLs) were highly specific to the identity of the T3E mutant (ripAC, ripAG, ripAQ, and ripU), we finely mapped a common QTL located on a cluster of nucleotide-binding domain and leucine-rich repeat (NLR) genes that exhibited structural variation. We functionally validated one of these NLRs as a susceptibility factor in response to R. solanacearum, named it Bacterial Wilt Susceptibility 1 (BWS1), and cloned two alleles that conferred contrasting levels of QDR. Further characterization indicated that expression of BWS1 leads to suppression of immunity triggered by different R. solanacearum effectors. In addition, we showed a direct interaction between BWS1 and RipAC T3E, and BWS1 and SUPPRESSOR OF G2 ALLELE OF skp1 (SGT1b), the latter interaction being suppressed by RipAC. Together, our results highlight a putative role for BWS1 as a quantitative susceptibility factor directly targeted by the T3E RipAC, mediating negative regulation of the SGT1-dependent immune response.

Rapid and biased evolution of canalization during adaptive divergence revealed by dominance in gene expression variability during Arctic charr early development

Adaptive evolution may be influenced by canalization, the buffering of developmental processes from environmental and genetic perturbations, but how this occurs is poorly understood. Here, we explore how gene expression variability evolves in diverging and hybridizing populations, by focusing on the Arctic charr (Salvelinus alpinus) of Thingvallavatn, a classic case of divergence between feeding habitats. We report distinct profiles of gene expression variance for both coding RNAs and microRNAs between the offspring of two contrasting morphs (benthic/limnetic) and their hybrids reared in common conditions and sampled at two key points of cranial development. Gene expression variance in the hybrids is substantially affected by maternal effects, and many genes show biased expression variance toward the limnetic morph. This suggests that canalization, as inferred by gene expression variance, can rapidly diverge in sympatry through multiple gene pathways, which are associated with dominance patterns possibly biasing evolutionary trajectories and mitigating the effects of hybridization on adaptive evolution.

The design of mapping populations: Impacts of geographic scale on genetic architecture and mapping efficacy for defense and immunity

Genome-wide association studies (GWAS) have yielded tremendous insight into the genetic architecture of trait variation. However, the collections of loci they uncover are far from exhaustive. As many of the complicating factors that confound or limit the efficacy of GWAS are exaggerated over broad geographic scales, a shift toward more analyses using mapping panels sampled from narrow geographic localities ("local" populations) could provide novel, complementary insights. Here, we present an overview of the major complicating factors, review mounting evidence from genomic analyses that these factors are pervasive, and synthesize theoretical and empirical evidence for the power of GWAS in local populations.

Genome-wide association studies in plant pathosystems: success or failure?

Harnessing natural genetic variation is an established alternative to artificial genetic variation for investigating the molecular dialog between partners in plant pathosystems. Herein, we review the successes of genome-wide association studies (GWAS) in both plants and pathogens. While GWAS in plants confirmed that the genetic architecture of disease resistance is polygenic, dynamic during the infection kinetics, and dependent on the environment, GWAS shortened the time of identification of quantitative trait loci (QTLs) and revealed both complex epistatic networks and a genetic architecture dependent upon the geographical scale. A similar picture emerges from the few GWAS in pathogens. In addition, the ever-increasing number of functionally validated QTLs has revealed new molecular plant defense mechanisms and pathogenicity determinants. Finally, we propose recommendations to better decode the disease triangle.

The ecologically relevant genetics of plant-plant interactions

Interactions among plants have been long recognized as a major force driving plant community dynamics and crop yield. Surprisingly, our knowledge of the ecological genetics associated with variation of plant-plant interactions remains limited. In this opinion article by scientists from complementary disciplines, the international PLANTCOM network identified four timely questions to foster a better understanding of the mechanisms mediating plant assemblages. We propose that by identifying the key relationships among phenotypic traits involved in plant-plant interactions and the underlying adaptive genetic and molecular pathways, while considering environmental fluctuations at diverse spatial and time scales, we can improve predictions of genotype-by-genotype-by-environment interactions and modeling of productive and stable plant assemblages in wild habitats and crop fields.

A Genome-Wide Association study in Arabidopsis thaliana to decipher the adaptive genetics of quantitative disease resistance in a native heterogeneous environment

Pathogens are often the main selective agents acting in plant communities, thereby influencing the distribution of polymorphism at loci affecting resistance within and among natural plant populations. In addition, the outcome of plant-pathogen interactions can be drastically affected by abiotic and biotic factors at different spatial and temporal grains. The characterization of the adaptive genetic architecture of disease resistance in native heterogeneous environments is however still missing. In this study, we conducted an in situ Genome-Wide Association study in the spatially heterogeneous native habitat of a highly genetically polymorphic local mapping population of Arabidopsis thaliana, to unravel the adaptive genetic architecture of quantitative disease resistance. Disease resistance largely differed among three native soils and was affected by the presence of the grass Poa annua. The observation of strong crossing reactions norms among the 195 A. thaliana genotypes for disease resistance among micro-habitats, combined with a negative fecundity-disease resistance relationship in each micro-habitat, suggest that alternative local genotypes of A. thaliana are favored under contrasting environmental conditions at the scale of few meters. A complex genetic architecture was detected for disease resistance and fecundity. However, only few QTLs were common between these two traits. Heterogeneous selection in this local population should therefore promote the maintenance of polymorphism at only few candidate resistance genes.

Differential environmental and genomic architectures shape the natural diversity for trichome patterning and morphology in different Arabidopsis organs

Despite the adaptive and taxonomic relevance of the natural diversity for trichome patterning and morphology, the molecular and evolutionary mechanisms underlying these traits remain mostly unknown, particularly in organs other than leaves. In this study, we address the ecological, genetic and molecular bases of the natural variation for trichome patterning and branching in multiple organs of Arabidopsis (Arabidopsis thaliana). To this end, we characterized a collection of 191 accessions and carried out environmental and genome-wide association (GWA) analyses. Trichome amount in different organs correlated negatively with precipitation in distinct seasons, thus suggesting a precise fit between trichome patterning and climate throughout the Arabidopsis life cycle. In addition, GWA analyses showed small overlapping between the genes associated with different organs, indicating partly independent genetic bases for vegetative and reproductive phases. These analyses identified a complex locus on chromosome 2, where two adjacent MYB genes (ETC2 and TCL1) displayed differential effects on trichome patterning in several organs. Furthermore, analyses of transgenic lines carrying different natural alleles demonstrated that TCL1 accounts for the variation for trichome patterning in all organs, and for stem trichome branching. By contrast, two other MYB genes (TRY and GL1), mainly showed effects on trichome patterning or branching, respectively.

Signatures of polygenic adaptation align with genome-wide methylation patterns in wild strawberry plants

Epigenetic inheritance can drive adaptive evolution independently of DNA sequence variation. However, to what extent epigenetic variation represents an autonomous evolutionary force remains largely elusive. Through gene ontology and comparative analyses of genomic and epigenomic variation of wild strawberry plants raised in distinct drought settings, we characterised genome-wide covariation between single nucleotide polymorphisms (SNPs) and differentially methylated cytosines (DMCs). Covariation between SNPs and DMCs was independent of genomic proximity, but instead associated with fitness-related processes such as stress responses, genome regulation and reproduction. We expected this functional SNP-DMC covariation to be driven by adaptive evolution canalising SNP and DMC variation, but instead observed significantly lower covariation with DMCs for adaptive rather than for neutral SNPs. Drought-induced DMCs frequently co-varied with tens of SNPs, suggesting high genomic redundancy as a broad potential basis for polygenic adaptation of gene expression. Our findings suggest that stress-responsive DMCs initially co-vary with many SNPs under increased environmental stress, and that natural selection acting upon several of these SNPs subsequently reduces standing covariation with stress-responsive DMCs. Our study supports DNA methylation profiles that represent complex quantitative traits rather than autonomous evolutionary forces. We provide a conceptual framework for polygenic regulation and adaptation shaping genome-wide methylation patterns in plants.

Genetics of adaptation

The rediscovery of Mendel’s work showing that the heredity of phenotypes is controlled by discrete genes was followed by the reconciliation of Mendelian genetics with evolution by natural selection in the middle of the last century with the Modern Synthesis. In the past two decades, dramatic advances in genomic methods have facilitated the identification of the loci, genes, and even individual mutations that underlie phenotypic variants that are the putative targets of natural selection. Moreover, these methods have also changed how we can study adaptation by flipping the problem around, allowing us to first examine what loci show evidence of having been under selection, and then connecting these genetic variants to phenotypic variation. As a result, we now have an expanding list of actual genetic changes that underlie potentially adaptive phenotypic variation. Here, we synthesize how considering the effects of these adaptive loci in the context of cellular environments, genomes, organisms, and populations has provided new insights to the genetic architecture of adaptation.

Genome-wide association mapping within a local Arabidopsis thaliana population more fully reveals the genetic architecture for defensive metabolite diversity

A paradoxical finding from genome-wide association studies (GWAS) in plants is that variation in metabolite profiles typically maps to a small number of loci, despite the complexity of underlying biosynthetic pathways. This discrepancy may partially arise from limitations presented by geographically diverse mapping panels. Properties of metabolic pathways that impede GWAS by diluting the additive effect of a causal variant, such as allelic and genetic heterogeneity and epistasis, would be expected to increase in severity with the geographical range of the mapping panel. We hypothesized that a population from a single locality would reveal an expanded set of associated loci. We tested this in a French Arabidopsis thaliana population (less than 1 km transect) by profiling and conducting GWAS for glucosinolates, a suite of defensive metabolites that have been studied in depth through functional and genetic mapping approaches. For two distinct classes of glucosinolates, we discovered more associations at biosynthetic loci than the previous GWAS with continental-scale mapping panels. Candidate genes underlying novel associations were supported by concordance between their observed effects in the TOU-A population and previous functional genetic and biochemical characterization. Local populations complement geographically diverse mapping panels to reveal a more complete genetic architecture for metabolic traits. This article is part of the theme issue 'Genetic basis of adaptation and speciation: from loci to causative mutations'.

Gene copy number variations at the within-host population level modulate gene expression in a multipartite virus

Multipartite viruses have a segmented genome, with each segment encapsidated separately. In all multipartite virus species for which the question has been addressed, the distinct segments reproducibly accumulate at a specific and host-dependent relative frequency, defined as the 'genome formula'. Here, we test the hypothesis that the multipartite genome organization facilitates the regulation of gene expression via changes of the genome formula and thus via gene copy number variations. In a first experiment, the faba bean necrotic stunt virus (FBNSV), whose genome is composed of eight DNA segments each encoding a single gene, was inoculated into faba bean or alfalfa host plants, and the relative concentrations of the DNA segments and their corresponding messenger RNAs (mRNAs) were monitored. In each of the two host species, our analysis consistently showed that the genome formula variations modulate gene expression, the concentration of each genome segment linearly and positively correlating to that of its cognate mRNA but not of the others. In a second experiment, twenty parallel FBNSV lines were transferred from faba bean to alfalfa plants. Upon host switching, the transcription rate of some genome segments changes, but the genome formula is modified in a way that compensates for these changes and maintains a similar ratio between the various viral mRNAs. Interestingly, a deep-sequencing analysis of these twenty FBNSV lineages demonstrated that the host-related genome formula shift operates independently of DNA-segment sequence mutation. Together, our results indicate that nanoviruses are plastic genetic systems, able to transiently adjust gene expression at the population level in changing environments, by modulating the copy number but not the sequence of each of their genes.

Natural variation in Drosophila shows weak pleiotropic effects

Background

Pleiotropy describes the phenomenon in which a gene affects multiple phenotypes. The extent of pleiotropy is still disputed, mainly because of issues of inadequate power of analyses. A further challenge is that empirical tests of pleiotropy are restricted to a small subset of all possible phenotypes. To overcome these limitations, we propose a new measurement of pleiotropy that integrates across many phenotypes and multiple generations to improve power.

Results

We infer pleiotropy from the fitness cost imposed by frequency changes of pleiotropic loci. Mixing Drosophila simulans populations, which adapted independently to the same new environment using different sets of genes, we show that the adaptive frequency changes have been accompanied by measurable fitness costs.

Conclusions

Unlike previous studies characterizing the molecular basis of pleiotropy, we show that many loci, each of weak effect, contribute to genome-wide pleiotropy. We propose that the costs of pleiotropy are reduced by the modular architecture of gene expression, which facilitates adaptive gene expression changes with low impact on other functions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02680-4.

Class III Peroxidases in Response to Multiple Abiotic Stresses in Arabidopsis thaliana Pyrenean Populations

Class III peroxidases constitute a plant-specific multigene family, where 73 genes have been identified in Arabidopsis thaliana. These genes are members of the reactive oxygen species (ROS) regulatory network in the whole plant, but more importantly, at the root level. In response to abiotic stresses such as cold, heat, and salinity, their expression is significantly modified. To learn more about their transcriptional regulation, an integrative phenotypic, genomic, and transcriptomic study was executed on the roots of A. thaliana Pyrenean populations. Initially, the root phenotyping highlighted 3 Pyrenean populations to be tolerant to cold (Eaux), heat (Herr), and salt (Grip) stresses. Then, the RNA-seq analyses on these three populations, in addition to Col-0, displayed variations in CIII Prxs expression under stressful treatments and between different genotypes. Consequently, several CIII Prxs were particularly upregulated in the tolerant populations, suggesting novel and specific roles of these genes in plant tolerance against abiotic stresses.

Study of natural diversity in response to a key pathogenicity regulator of Ralstonia solanacearum reveals new susceptibility genes in Arabidopsis thaliana

Ralstonia solanacearum gram-negative phytopathogenic bacterium exerts its virulence through a type III secretion system (T3SS) that translocates type III effectors (T3Es) directly into the host cells. T3E secretion is finely controlled at the posttranslational level by helper proteins, T3SS control proteins, and type III chaperones. The HpaP protein, one of the type III secretion substrate specificity switch (T3S4) proteins, was previously highlighted as a virulence factor on Arabidopsis thaliana Col-0 accession. In this study, we set up a genome-wide association analysis to explore the natural diversity of response to the hpaP mutant of two A. thaliana mapping populations: a worldwide collection and a local population. Quantitative genetic variation revealed different genetic architectures in both mapping populations, with a global delayed response to the hpaP mutant compared to the GMI1000 wild-type strain. We have identified several quantitative trait loci (QTLs) associated with the hpaP mutant inoculation. The genes underlying these QTLs are involved in different and specific biological processes, some of which were demonstrated important for R. solanacearum virulence. We focused our study on four candidate genes, RKL1, IRE3, RACK1B, and PEX3, identified using the worldwide collection, and validated three of them as susceptibility factors. Our findings demonstrate that the study of the natural diversity of plant response to a R. solanacearum mutant in a key regulator of virulence is an original and powerful strategy to identify genes directly or indirectly targeted by the pathogen.

Evolution of flowering time in a selfing annual plant: Roles of adaptation and genetic drift

Resurrection studies are a useful tool to measure how phenotypic traits have changed in populations through time. If these trait modifications correlate with the environmental changes that occurred during the time period, it suggests that the phenotypic changes could be a response to selection. Selfing, through its reduction of effective size, could challenge the ability of a population to adapt to environmental changes. Here, we used a resurrection study to test for adaptation in a selfing population of Medicago truncatula, by comparing the genetic composition and flowering times across 22 generations. We found evidence for evolution toward earlier flowering times by about two days and a peculiar genetic structure, typical of highly selfing populations, where some multilocus genotypes (MLGs) are persistent through time. We used the change in frequency of the MLGs through time as a multilocus fitness measure and built a selection gradient that suggests evolution toward earlier flowering times. Yet, a simulation model revealed that the observed change in flowering time could be explained by drift alone, provided the effective size of the population is small enough (<150). These analyses suffer from the difficulty to estimate the effective size in a highly selfing population, where effective recombination is severely reduced.

The Genomic Architecture of Competitive Response of Arabidopsis thaliana Is Highly Flexible Among Plurispecific Neighborhoods

Plants are daily challenged by multiple abiotic and biotic stresses. A major biotic constraint corresponds to competition with other plant species. Although plants simultaneously interact with multiple neighboring species throughout their life cycle, there is still very limited information about the genetics of the competitive response in the context of plurispecific interactions. Using a local mapping population of Arabidopsis thaliana, we set up a genome wide association study (GWAS) to estimate the extent of genetic variation of competitive response in 12 plant species assemblages, based on three competitor species (Poa annua, Stellaria media, and Veronica arvensis). Based on five phenotypic traits, we detected strong crossing reaction norms not only between the three bispecific neighborhoods but also among the plurispecific neighborhoods. The genetic architecture of competitive response was highly dependent on the identity and the relative abundance of the neighboring species. In addition, most of the enriched biological processes underlying competitive responses largely differ among neighborhoods. While the RNA related processes might confer a broad range response toolkit for multiple traits in diverse neighborhoods, some processes, such as signaling and transport, might play a specific role in particular assemblages. Altogether, our results suggest that plants can integrate and respond to different species assemblages depending on the identity and number of each neighboring species, through a large range of candidate genes associated with diverse and unexpected processes leading to developmental and stress responses.

Allogenous Selection of Mutational Collateral Resistance: Old Drugs Select for New Resistance Within Antibiotic Families

Allogeneous selection occurs when an antibiotic selects for resistance to more advanced members of the same family. The mechanisms of allogenous selection are (a) collateral expansion, when the antibiotic expands the gene and gene-containing bacterial populations favoring the emergence of other mutations, inactivating the more advanced antibiotics; (b) collateral selection, when the old antibiotic selects its own resistance but also resistance to more modern drugs; (c) collateral hyper-resistance, when resistance to the old antibiotic selects in higher degree for populations resistant to other antibiotics of the family than to itself; and (d) collateral evolution, when the simultaneous or sequential use of antibiotics of the same family selects for new mutational combinations with novel phenotypes in this family, generally with higher activity (higher inactivation of the antibiotic substrates) or broader spectrum (more antibiotics of the family are inactivated). Note that in some cases, collateral selection derives from collateral evolution. In this article, examples of allogenous selection are provided for the major families of antibiotics. Improvements in minimal inhibitory concentrations with the newest drugs do not necessarily exclude “old” antibiotics of the same family of retaining some selective power for resistance to the newest agents. If this were true, the use of older members of the same drug family would facilitate the emergence of mutational resistance to the younger drugs of the family, which is frequently based on previously established resistance traits. The extensive use of old drugs (particularly in low-income countries and in farming) might be significant for the emergence and selection of resistance to the novel members of the family, becoming a growing source of variation and selection of resistance to the whole family. In terms of future research, it could be advisable to focus antimicrobial drug discovery more on the identification of new targets and new (unique) classes of antimicrobial agents, than on the perpetual chemical exploitation of classic existing ones.

Deciphering the Genetic Architecture of Plant Virus Resistance by GWAS, State of the Art and Potential Advances

Growing virus resistant varieties is a highly effective means to avoid yield loss due to infection by many types of virus. The challenge is to be able to detect resistance donors within plant species diversity and then quickly introduce alleles conferring resistance into elite genetic backgrounds. Until now, mainly monogenic forms of resistance with major effects have been introduced in crops. Polygenic resistance is harder to map and introduce in susceptible genetic backgrounds, but it is likely more durable. Genome wide association studies (GWAS) offer an opportunity to accelerate mapping of both monogenic and polygenic resistance, but have seldom been implemented and described in the plant-virus interaction context. Yet, all of the 48 plant-virus GWAS published so far have successfully mapped QTLs involved in plant virus resistance. In this review, we analyzed general and specific GWAS issues regarding plant virus resistance. We have identified and described several key steps throughout the GWAS pipeline, from diversity panel assembly to GWAS result analyses. Based on the 48 published articles, we analyzed the impact of each key step on the GWAS power and showcase several GWAS methods tailored to all types of viruses.

Depicting the phenotypic space of the annual plant Diplotaxis acris in hyperarid deserts

The phenotypic space encompasses the assemblage of trait combinations yielding well-suited integrated phenotypes. At the population level, understanding the phenotypic space structure requires the quantification of among- and within-population variations in traits and the correlation pattern among them. Here, we studied the phenotypic space of the annual plant Diplotaxis acris occurring in hyperarid deserts. Given the advance of warming and aridity in vast regions occupied by drylands, D. acris can indicate the successful evolutionary trajectory that many other annual plant species may follow in expanding drylands. To this end, we conducted a greenhouse experiment with 176 D. acris individuals from five Saudi populations to quantify the genetic component of variation in architectural and life history traits. We found low among-population divergence but high among-individual variation in all traits. In addition, all traits showed a high degree of genetic determination in our study experimental conditions. We did not find significant effects of recruitment and fecundity on fitness. Finally, all architectural traits exhibited a strong correlation pattern among them, whereas for life history traits, only higher seed germination implied earlier flowering. Seed weight appeared to be an important trait in D. acris as individuals with heavier seeds tended to advance flowering and have a more vigorous branching pattern, which led to higher fecundity. Population divergence in D. acris might be constrained by the severity of the hyperarid environment, but populations maintain high among-individual genetic variation in all traits. Furthermore, D. acris showed phenotypic integration for architectural traits and, to a lesser extent, for life history traits. Overall, we hypothesize that D. acris may be fine-tuned to its demanding extreme environments. Evolutionary speaking, annual plants facing increasing warming, aridity, and environmental seasonality might modify their phenotypic spaces toward new phenotypic configurations strongly dominated by correlated architectural traits enhancing fecundity and seed-related traits advancing flowering time.

A neglected conceptual problem regarding phenotypic plasticity's role in adaptive evolution: The importance of genetic covariance and social drive

There is tantalizing evidence that phenotypic plasticity can buffer novel, adaptive genetic variants long enough to permit their evolutionary spread, and this process is often invoked in explanations for rapid adaptive evolution. However, the strength and generality of evidence for it is controversial. We identify a conceptual problem affecting this debate: recombination, segregation, and independent assortment are expected to quickly sever associations between genes controlling novel adaptations and genes contributing to trait plasticity that facilitates the novel adaptations by reducing their indirect fitness costs. To make clearer predictions about this role of plasticity in facilitating genetic adaptation, we describe a testable genetic mechanism that resolves the problem: genetic covariance between new adaptive variants and trait plasticity that facilitates their persistence within populations. We identify genetic architectures that might lead to such a covariance, including genetic coupling via physical linkage and pleiotropy, and illustrate the consequences for adaptation rates using numerical simulations. Such genetic covariances may also arise from the social environment, and we suggest the indirect genetic effects that result could further accentuate the process of adaptation. We call the latter mechanism of adaptation social drive, and identify methods to test it. We suggest that genetic coupling of plasticity and adaptations could promote unusually rapid ‘runaway’ evolution of novel adaptations. The resultant dynamics could facilitate evolutionary rescue, adaptive radiations, the origin of novelties, and other commonly studied processes.

Rapid divergent evolution of an annual plant across a latitudinal gradient revealed by seed resurrection

Global change is expected to drive short-term evolution of natural populations. However, it remains unclear whether different populations are changing in unison. Here, we study contemporary evolution of growth-related and reproductive traits of three populations of Cyanus segetum facing warming and pollinator decline across a latitudinal gradient in France. We resurrected stored seeds sampled up to 24 years apart from northern, central-western, and southern populations and conducted an in situ common-garden experiment. To disentangle neutral from selection-driven differentiation, we calculated neutral genetic differentiation (F_ST ) and quantitative trait differentiation (Q_ST ) between temporal samples. We found that phenotypic evolution was divergent across populations exhibiting different trends for rosette size, date of flowering, and capitula size. By measuring seed set as a proxy of fitness, we showed that samples with larger mean capitula size outperformed samples with smaller mean capitula size in the western and southern populations. Regression of traits on seed set showed that flowering date and capitula size are the primary determinants of fitness, and Q_ST -F_ST comparisons indicated that natural selection has likely contributed to the shifts in flowering phenology and rosette size. These findings outline the potential for rescue of natural populations through contemporary evolution and emphasize the complex interplay between spatial and temporal variation in species' responses to global change.

Toward Unifying Evolutionary Ecology and Genomics to Understand Positive Plant-Plant Interactions Within Wild Species

In a local environment, plant networks include interactions among individuals of different species and among genotypes of the same species. While interspecific interactions are recognized as main drivers of plant community patterns, intraspecific interactions have recently gained attention in explaining plant community dynamics. However, an overview of intraspecific genotype-by-genotype interaction patterns within wild plant species is still missing. From the literature, we identified 91 experiments that were mainly designed to investigate the presence of positive interactions based on two contrasting hypotheses. Kin selection theory predicts partisan help given to a genealogical relative. The rationale behind this hypothesis relies on kin/non-kin recognition, with the positive outcome of kin cooperation substantiating it. On the other hand, the elbow-room hypothesis supports intraspecific niche partitioning leading to positive outcome when genetically distant genotypes interact. Positive diversity-productivity relationship rationalizes this hypothesis, notably with the outcome of overyielding. We found that both these hypotheses have been highly supported in experimental studies despite their opposite predictions between the extent of genetic relatedness among neighbors and the level of positive interactions. Interestingly, we identified a highly significant effect of breeding system, with a high proportion of selfing species associated with the presence of kin cooperation. Nonetheless, we identified several shortcomings regardless of the species considered, such as the lack of a reliable estimate of genetic relatedness among genotypes and ecological characterization of the natural habitats from which genotypes were collected, thereby impeding the identification of selective drivers of positive interactions. We therefore propose a framework combining evolutionary ecology and genomics to establish the eco-genomic landscape of positive GxG interactions in wild plant species.

Functional biology in its natural context: A search for emergent simplicity

The immeasurable complexity at every level of biological organization creates a daunting task for understanding biological function. Here, we highlight the risks of stripping it away at the outset and discuss a possible path toward arriving at emergent simplicity of understanding while still embracing the ever-changing complexity of biotic interactions that we see in nature.

LEA 3: Factor models in population genetics and ecological genomics with R

A major objective of evolutionary biology is to understand the processes by which organisms have adapted to various environments, and to predict the response of organisms to new or future conditions. The availability of large genomic and environmental data sets provides an opportunity to address those questions, and the R package LEA has been introduced to facilitate population and ecological genomic analyses in this context. By using latent factor models, the program computes ancestry coefficients from population genetic data and performs genotype-environment association analyses with correction for unobserved confounding variables. In this study, we present new functionalities of LEA, which include imputation of missing genotypes, fast algorithms for latent factor mixed models using multivariate predictors for genotype-environment association studies, population differentiation tests for admixed or continuous populations, and estimation of genetic offset based on climate models. The new functionalities are implemented in version 3.1 and higher releases of the package. Using simulated and real data sets, our study provides evaluations and examples of applications, outlining important practical considerations when analysing ecological genomic data in R.

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.

A complex network of additive and epistatic quantitative trait loci underlies natural variation of Arabidopsis thaliana quantitative disease resistance to Ralstonia solanacearum under heat stress

Plant immunity is often negatively impacted by heat stress. However, the underlying molecular mechanisms remain poorly characterized. Based on a genome-wide association mapping approach, this study aims to identify in Arabidopsis thaliana the genetic bases of robust resistance mechanisms to the devastating pathogen Ralstonia solanacearum under heat stress. A local mapping population was phenotyped against the R. solanacearum GMI1000 strain at 27 and 30 °C. To obtain a precise description of the genetic architecture underlying natural variation of quantitative disease resistance (QDR), we applied a genome-wide local score analysis. Alongside an extensive genetic variation found in this local population at both temperatures, we observed a playful dynamics of quantitative trait loci along the infection stages. In addition, a complex genetic network of interacting loci could be detected at 30 °C. As a first step to investigate the underlying molecular mechanisms, the atypical meiotic cyclin SOLO DANCERS gene was validated by a reverse genetic approach as involved in QDR to R. solanacearum at 30 °C. In the context of climate change, the complex genetic architecture underlying QDR under heat stress in a local mapping population revealed candidate genes with diverse molecular functions.

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.

FLOWERING LOCUS M (FLM) is known as a repressor of Arabidopsis flowering. Here, the authors show that a single intronic substitution of FLM modulates leaf color and plant growth strategy along the leaf economics spectrum, as well as plays a role in plant adaptation.

Temporal migration rates affect the genetic structure of populations in the biennial Erysimum mediohispanicum with reproductive asynchrony

Migration is a process with important implications for the genetic structure of populations. However, there is an aspect of migration seldom investigated in plants: migration between temporally isolated groups of individuals within the same geographic population. The genetic implications of temporal migration can be particularly relevant for semelparous organisms, which are those that reproduce only once in a lifetime after a certain period of growth. In this case, reproductive asynchrony in individuals of the same population generates demes of individuals differing in their developmental stage (non-reproductive and reproductive). These demes are connected by temporal migrants, that is, individuals that become annually asynchronous with respect to the rest of individuals of their same deme. Here, we investigated the extent of temporal migration and its effects on temporal genetic structure in the biennial plant Erysimum mediohispanicum. To this end, we conducted two independent complementary approaches. First, we empirically estimated temporal migration rates and temporal genetic structure in four populations of E. mediohispanicum during three consecutive years using nuclear microsatellites markers. Second, we developed a demographic genetic simulation model to assess genetic structure for different migration scenarios differing in temporal migration rates and their occurrence probabilities. We hypothesized that genetic structure decreased with increasing temporal migration rates due to the homogenizing effect of migration. Empirical and modelling results were consistent and indicated a U-shape relationship between genetic structure and temporal migration rates. Overall, they indicated the existence of temporal genetic structure and that such genetic structure indeed decreased with increasing temporal migration rates. However, genetic structure increased again at high temporal migration rates. The results shed light into the effects of reproductive asynchrony on important population genetic parameters. Our study contributes to unravel the complexity of some processes that may account for genetic diversity and genetic structure of natural populations.

Ecological, genetic and evolutionary drivers of regional genetic differentiation in Arabidopsis thaliana

BACKGROUND

Disentangling the drivers of genetic differentiation is one of the cornerstones in evolution. This is because genetic diversity, and the way in which it is partitioned within and among populations across space, is an important asset for the ability of populations to adapt and persist in changing environments. We tested three major hypotheses accounting for genetic differentiation-isolation-by-distance (IBD), isolation-by-environment (IBE) and isolation-by-resistance (IBR)-in the annual plant Arabidopsis thaliana across the Iberian Peninsula, the region with the largest genomic diversity. To that end, we sampled, genotyped with genome-wide SNPs, and analyzed 1772 individuals from 278 populations distributed across the Iberian Peninsula.

RESULTS

IBD, and to a lesser extent IBE, were the most important drivers of genetic differentiation in A. thaliana. In other words, dispersal limitation, genetic drift, and to a lesser extent local adaptation to environmental gradients, accounted for the within- and among-population distribution of genetic diversity. Analyses applied to the four Iberian genetic clusters, which represent the joint outcome of the long demographic and adaptive history of the species in the region, showed similar results except for one cluster, in which IBR (a function of landscape heterogeneity) was the most important driver of genetic differentiation. Using spatial hierarchical Bayesian models, we found that precipitation seasonality and topsoil pH chiefly accounted for the geographic distribution of genetic diversity in Iberian A. thaliana.

CONCLUSIONS

Overall, the interplay between the influence of precipitation seasonality on genetic diversity and the effect of restricted dispersal and genetic drift on genetic differentiation emerges as the major forces underlying the evolutionary trajectory of Iberian A. thaliana.

The evolution of competitive ability for essential resources

Competition for limiting resources is among the most fundamental ecological interactions and has long been considered a key driver of species coexistence and biodiversity. Species' minimum resource requirements, their R*s, are key traits that link individual physiological demands to the outcome of competition. However, a major question remains unanswered-to what extent are species' competitive traits able to evolve in response to resource limitation? To address this knowledge gap, we performed an evolution experiment in which we exposed Chlamydomonas reinhardtii for approximately 285 generations to seven environments in chemostats that differed in resource supply ratios (including nitrogen, phosphorus and light limitation) and salt stress. We then grew the ancestors and descendants in a common garden and quantified their competitive abilities for essential resources. We investigated constraints on trait evolution by testing whether changes in resource requirements for different resources were correlated. Competitive abilities for phosphorus improved in all populations, while competitive abilities for nitrogen and light increased in some populations and decreased in others. In contrast to the common assumption that there are trade-offs between competitive abilities for different resources, we found that improvements in competitive ability for a resource came at no detectable cost. Instead, improvements in competitive ability for multiple resources were either positively correlated or not significantly correlated. Using resource competition theory, we then demonstrated that rapid adaptation in competitive traits altered the predicted outcomes of competition. These results highlight the need to incorporate contemporary evolutionary change into predictions of competitive community dynamics over environmental gradients. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

Pleiotropy facilitates local adaptation to distant optima in common ragweed (Ambrosia artemisiifolia)

Pleiotropy, the control of multiple phenotypes by a single locus, is expected to slow the rate of adaptation by increasing the chance that beneficial alleles also have deleterious effects. However, a prediction arising from classical theory of quantitative trait evolution states that pleiotropic alleles may have a selective advantage when phenotypes are distant from their selective optima. We examine the role of pleiotropy in regulating adaptive differentiation among populations of common ragweed (Ambrosia artemisiifolia); a species that has recently expanded its North American range due to human-mediated habitat change. We employ a phenotype-free approach by using connectivity in gene networks as a proxy for pleiotropy. First, we identify loci bearing footprints of local adaptation, and then use genotype-expression mapping and co-expression networks to infer the connectivity of the genes. Our results indicate that the putatively adaptive loci are highly pleiotropic, as they are more likely than expected to affect the expression of other genes, and they reside in central positions within the gene networks. We propose that the conditionally advantageous alleles at these loci avoid the cost of pleiotropy by having large phenotypic effects that are beneficial when populations are far from their selective optima. We further use evolutionary simulations to show that these patterns are in agreement with a model where populations face novel selective pressures, as expected during a range expansion. Overall, our results suggest that highly connected genes may be targets of positive selection during environmental change, even though they likely experience strong purifying selection in stable selective environments.

Evolutionary processes from the perspective of flowering time diversity

Although it is well appreciated that genetic studies of flowering time regulation have led to fundamental advances in the fields of molecular and developmental biology, the ways in which genetic studies of flowering time diversity have enriched the field of evolutionary biology have received less attention despite often being equally profound. Because flowering time is a complex, environmentally responsive trait that has critical impacts on plant fitness, crop yield, and reproductive isolation, research into the genetic architecture and molecular basis of its evolution continues to yield novel insights into our understanding of domestication, adaptation, and speciation. For instance, recent studies of flowering time variation have reconstructed how, when, and where polygenic evolution of phenotypic plasticity proceeded from standing variation and de novo mutations; shown how antagonistic pleiotropy and temporally varying selection maintain polymorphisms in natural populations; and provided important case studies of how assortative mating can evolve and facilitate speciation with gene flow. In addition, functional studies have built detailed regulatory networks for this trait in diverse taxa, leading to new knowledge about how and why developmental pathways are rewired and elaborated through evolutionary time.

HpaP Sequesters HrpJ, an Essential Component of Ralstonia solanacearum Virulence That Triggers Necrosis in Arabidopsis

The Gram-negative bacterium Ralstonia solanacearum, the causal agent of bacterial wilt, is a worldwide major crop pathogen whose virulence strongly relies on a type III secretion system (T3SS). This extracellular apparatus allows the translocation of proteins, called type III effectors (T3Es), directly into the host cells. To date, very few data are available in plant-pathogenic bacteria concerning the role played by type III secretion (T3S) regulators at the posttranslational level. We have demonstrated that HpaP, a putative T3S substrate specificity switch protein of R. solanacearum, controls T3E secretion. To better understand the role of HpaP on T3S control, we analyzed the secretomes of the GMI1000 wild-type strain as well as the hpaP mutant using a mass spectrometry experiment (liquid chromatography tandem mass spectrometry). The secretomes of both strains appeared to be very similar and highlighted the modulation of the secretion of few type III substrates. Interestingly, only one type III-associated protein, HrpJ, was identified as specifically secreted by the hpaP mutant. HrpJ appeared to be an essential component of the T3SS, essential for T3S and pathogenicity. We further showed that HrpJ is specifically translocated in planta by the hpaP mutant and that HrpJ can physically interact with HpaP. Moreover, confocal microscopy experiments demonstrated a cytoplasmic localization for HrpJ once in planta. When injected into Arabidopsis thaliana leaves, HrpJ is able to trigger a necrosis on 16 natural accessions. A genome-wide association mapping revealed a major association peak with 12 highly significant single-nucleotide polymorphisms located on a plant acyl-transferase.

Adaptation to Plant Communities across the Genome of Arabidopsis thaliana

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

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.

PIF transcription factors link a neighbor threat cue to accelerated reproduction in Arabidopsis

Changes in light quality indicative of competition for this essential resource influence plant growth and developmental transitions; however, little is known about neighbor proximity-induced acceleration of reproduction. Phytochrome B (phyB) senses light cues from plant competitors, ultimately leading to the expression of the floral inducers FLOWERING LOCUS T (FT) and TWIN SISTER of FT (TSF). Here we show that PHYTOCHROME INTERACTING FACTORs 4, 5 and 7 (PIF4, PIF5 and PIF7) mediate neighbor proximity-induced flowering, with PIF7 playing a prominent role. These transcriptional regulators act directly downstream of phyB to promote expression of FT and TSF. Neighbor proximity enhances PIF accumulation towards the end of the day, coinciding with enhanced floral inducer expression. We present evidence supporting direct PIF-regulated TSF expression. The relevance of our findings is illustrated by the prior identification of FT, TSF and PIF4 as loci underlying flowering time regulation in natural conditions.