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.

Uncovering genes involved in pollinator-driven mating system shifts and selfing syndrome evolution in Brassica rapa.

Shifts in pollinator occurrence and their pollen transport effectiveness drive the evolution of mating systems in flowering plants. Understanding the genomic basis of these changes is essential for predicting the persistence of a species under environmental changes. We investigated the genomic changes in Brassica rapa over nine generations of pollination by hoverflies associated with rapid morphological evolution toward the selfing syndrome. We combined a genotyping-by-sequencing (GBS) approach with a genome-wide association study (GWAS) to identify candidate genes, and assessed their functional role in the observed morphological changes by studying mutations of orthologous genes in the model plant Arabidopsis thaliana. We found 31 candidate genes involved in a wide range of functions from DNA/RNA binding to transport. Our functional assessment of orthologous genes in A. thaliana revealed that two of the identified genes in B. rapa are involved in regulating the size of floral organs. We found a protein kinase superfamily protein involved in petal width, an important trait in plant attractiveness to pollinators. Moreover, we found a histone lysine methyltransferase (HKMT) associated with stamen length. Altogether, our study shows that hoverfly pollination leads to rapid evolution toward the selfing syndrome mediated by polygenic changes.

Rapid genomic evolution in Brassica rapa with bumblebee selection in experimental evolution.

BACKGROUND: Insect pollinators shape rapid phenotypic evolution of traits related to floral attractiveness and plant reproductive success. However, the underlying genomic changes remain largely unknown despite their importance in predicting adaptive responses to natural or to artificial selection. Based on a nine-generation experimental evolution study with fast cycling Brassica rapa plants adapting to bumblebees, we investigate the genomic evolution associated with the previously observed parallel phenotypic evolution. In this current evolve and resequencing (E&R) study, we conduct a genomic scan of the allele frequency changes along the genome in bumblebee-pollinated and hand-pollinated plants and perform a genomic principal component analysis (PCA). RESULTS: We highlight rapid genomic evolution associated with the observed phenotypic evolution mediated by bumblebees. Controlling for genetic drift, we observe significant changes in allelic frequencies at multiple loci. However, this pattern differs according to the replicate of bumblebee-pollinated plants, suggesting putative non-parallel genomic evolution. Finally, our study underlines an increase in genomic variance implying the putative involvement of multiple loci in short-term pollinator adaptation. CONCLUSIONS: Overall, our study enhances our understanding of the complex interactions between pollinator and plants, providing a stepping stone towards unravelling the genetic basis of plant genomic adaptation to biotic factors in the environment.

The Genetic Architecture of Adaptation to Leaf and Root Bacterial Microbiota in Arabidopsis thaliana.

Understanding the role of the host genome in modulating microbiota variation is a need to shed light on the holobiont theory and overcome the current limits on the description of host-microbiota interactions at the genomic and molecular levels. However, the host genetic architecture structuring microbiota is only partly described in plants. In addition, most association genetic studies on microbiota are often carried out outside the native habitats where the host evolves and the identification of signatures of local adaptation on the candidate genes has been overlooked. To fill these gaps and dissect the genetic architecture driving adaptive plant-microbiota interactions, we adopted a genome-environment association (GEA) analysis on 141 whole-genome sequenced natural populations of Arabidopsis thaliana characterized in situ for their leaf and root bacterial communities in fall and spring, and a large range of nonmicrobial ecological factors (i.e., climate, soil, and plant communities). A much higher fraction of among-population microbiota variance was explained by the host genetics than by nonmicrobial ecological factors. Importantly, the relative importance of host genetics and nonmicrobial ecological factors in explaining the presence of particular operational taxonomic units (OTUs) differs between bacterial families and genera. In addition, the polygenic architecture of adaptation to bacterial communities was highly flexible between plant compartments and seasons. Relatedly, signatures of local adaptation were stronger on quantitative trait loci (QTLs) of the root microbiota in spring. Finally, plant immunity appears as a major source of adaptive genetic variation structuring bacterial assemblages in A. thaliana.

Putative Signals of Generalist Plant Species Adaptation to Local Pollinator Communities and Abiotic Factors.

The reproductive success of flowering plants with generalized pollination systems is influenced by interactions with a diverse pollinator community and abiotic factors. However, knowledge about the adaptative potential of plants to complex ecological networks and the underlying genetic mechanisms is still limited. Based on a pool-sequencing approach of 21 natural populations of Brassica incana in Southern Italy, we combined a genome-environmental association analysis with a genome scan for signals of population genomic differentiation to discover genetic variants associated with the ecological variation. We identified genomic regions putatively involved in the adaptation of B. incana to the identity of local pollinator functional categories and pollinator community composition. Interestingly, we observed several shared candidate genes associated with long-tongue bees, soil texture, and temperature variation. We established a genomic map of potential generalist flowering plant local adaptation to complex biotic interactions, and the importance of considering multiple environmental factors to describe the adaptive landscape of plant populations.

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.

Low-Input High-Molecular-Weight DNA Extraction for Long-Read Sequencing From Plants of Diverse Families.

Long-read DNA sequencing technologies require high molecular weight (HMW) DNA of adequate purity and integrity, which can be difficult to isolate from plant material. Plant leaves usually contain high levels of carbohydrates and secondary metabolites that can impact DNA purity, affecting downstream applications. Several protocols and kits are available for HMW DNA extraction, but they usually require a high amount of input material and often lead to substantial DNA fragmentation, making sequencing suboptimal in terms of read length and data yield. We here describe a protocol for plant HMW DNA extraction from low input material (0.1 g) which is easy to follow and quick (2.5 h). This method successfully enabled us to extract HMW from four species from different families (Orchidaceae, Poaceae, Brassicaceae, Asteraceae). In the case of recalcitrant species, we show that an additional purification step is sufficient to deliver a clean DNA sample. We demonstrate the suitability of our protocol for long-read sequencing on the Oxford Nanopore Technologies PromethION® platform, with and without the use of a short fragment depletion kit.

Combining biotechnology and evolution for understanding the mechanisms of pollinator attraction.

Many flowering plants rely on pollinators for their reproductive success. Plant-pollinator interactions usually depend on a complex combination of traits based on a fine-tuned biosynthetic machinery, with many structural and regulatory genes involved. Yet, the physiological mechanisms in plants are the product of evolutionary processes. While evolution has been modifying flowers through millions of years, it is also a rapid process that can change plant traits within few generations. Here we discuss both mechanistic and evolutionary aspects of pollinator attraction. We also propose how latest advances in biotechnology and evolutionary studies, and their combination, will improve the elucidation of molecular mechanisms and evolutionary dynamics of pollinator attraction in changing environments.

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.

A Genomic Map of Climate Adaptation in Arabidopsis thaliana at a Micro-Geographic Scale.

Understanding the genetic bases underlying climate adaptation is a key element to predict the potential of species to face climate warming. Although substantial climate variation is observed at a micro-geographic scale, most genomic maps of climate adaptation have been established at broader geographical scales. Here, by using a Pool-Seq approach combined with a Bayesian hierarchical model that control for confounding by population structure, we performed a genome-environment association (GEA) analysis to investigate the genetic basis of adaptation to six climate variables in 168 natural populations of Arabidopsis thaliana distributed in south-west of France. Climate variation among the 168 populations represented up to 24% of climate variation among 521 European locations where A. thaliana inhabits. We identified neat and strong peaks of association, with most of the associated SNPs being significantly enriched in likely functional variants and/or in the extreme tail of genetic differentiation among populations. Furthermore, genes involved in transcriptional mechanisms appear predominant in plant functions associated with local climate adaptation. Globally, our results suggest that climate adaptation is an important driver of genomic variation in A. thaliana at a small spatial scale and mainly involves genome-wide changes in fundamental mechanisms of gene regulation. The identification of climate-adaptive genetic loci at a micro-geographic scale also highlights the importance to include within-species genetic diversity in ecological niche models for projecting potential species distributional shifts over short geographic distances.

In situ relationships between microbiota and potential pathobiota in Arabidopsis thaliana.

A current challenge in microbial pathogenesis is to identify biological control agents that may prevent and/or limit host invasion by microbial pathogens. In natura, hosts are often infected by multiple pathogens. However, most of the current studies have been performed under laboratory controlled conditions and by taking into account the interaction between a single commensal species and a single pathogenic species. The next step is therefore to explore the relationships between host-microbial communities (microbiota) and microbial members with potential pathogenic behavior (pathobiota) in a realistic ecological context. In the present study, we investigated such relationships within root-associated and leaf-associated bacterial communities of 163 ecologically contrasted Arabidopsis thaliana populations sampled across two seasons in southwest of France. In agreement with the theory of the invasion paradox, we observed a significant humped-back relationship between microbiota and pathobiota α-diversity that was robust between both seasons and plant organs. In most populations, we also observed a strong dynamics of microbiota composition between seasons. Accordingly, the potential pathobiota composition was explained by combinations of season-specific microbiota operational taxonomic units. This result suggests that the potential biomarkers controlling pathogen's invasion are highly dynamic.

Author Correction: Intermediate degrees of synergistic pleiotropy drive adaptive evolution in ecological time.

In the version of this Article previously published, there was a typographical error ('4' instead of '2') in the equations relating F ST and effective population size (N e) in the Methods section 'Genome-wide scan for selection based on temporal differentiation'. The correct equations are given below.[Formula: see text] [Formula: see text].

Intermediate degrees of synergistic pleiotropy drive adaptive evolution in ecological time.

Rapid phenotypic evolution of quantitative traits can occur within years, but its underlying genetic architecture remains uncharacterized. Here we test the theoretical prediction that genes with intermediate pleiotropy drive adaptive evolution in nature. Through a resurrection experiment, we grew Arabidopsis thaliana accessions collected across an 8-year period in six micro-habitats representative of that local population. We then used genome-wide association mapping to identify the single-nucleotide polymorphisms (SNPs) associated with evolved and unevolved traits in each micro-habitat. Finally, we performed a selection scan by testing for temporal differentiation in these SNPs. Phenotypic evolution was consistent across micro-habitats, but its associated genetic bases were largely distinct. Adaptive evolutionary change was most strongly driven by a small number of quantitative trait loci (QTLs) with intermediate degrees of pleiotropy; this pleiotropy was synergistic with the per-trait effect size of the SNPs, increasing with the degree of pleiotropy. In addition, weak selection was detected for frequent micro-habitat-specific QTLs that shape single traits. In this population, A. thaliana probably responded to local warming and increased competition, in part mediated by central regulators of flowering time. This genetic architecture, which includes both synergistic pleiotropic QTLs and distinct QTLs within particular micro-habitats, enables rapid phenotypic evolution while still maintaining genetic variation in wild populations.

Biological invasion and biological control select for different life histories.

Biological invaders have long been hypothesized to exhibit the fast end of the life-history spectrum, with early reproduction and a short lifespan. Here, we examine the rapid evolution of life history within the harlequin ladybird Harmonia axyridis. The species, once used as a biological control agent, is now a worldwide invader. We show that biocontrol populations have evolved a classic fast life history during their maintenance in laboratories. Invasive populations also reproduce earlier than native populations, but later than biocontrol ones. Invaders allocate more resources to reproduction than native and biocontrol individuals, and their reproduction is spread over a longer lifespan. This life history is best described as a bet-hedging strategy. We assert that invasiveness cannot be explained only by invoking faster life histories. Instead, the evolution of life history within invasive populations can progress rapidly and converge to a fine-tuned evolutionary match between the invaded environment and the invader.