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.

The reproductive success of flowering plants with generalized pollination systems is influenced by the 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 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.

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 outcrossingBrassica rapaplants 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.

Summary: 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.

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 cyclingBrassica rapaplants 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.

Phytochemistry is a core player in shaping plant-pollinator networks and pollination services. Yet, little is known about the dynamic evolution of phytochemical traits in response to limited pollinator access, especially concerning chemical diversity. We combined an evolutionary experiment manipulating pollinator access with predictive metabolomics to uncover evolutionary changes in phytochemical traits of Brassica rapa . Our results unveiled chemical changes in both leaf and flower chemistry. Moreover, plants under selection by limited pollinator access showed a decreased chemical richness and diversity and a modulated primary and specialised metabolism, which could be used to predict pollinator access with 88% accuracy. Chemical indices and metabolites responding to pollinator access were associated with variation in flowering time and performance of outcrossing flowers. Our findings provide key insights into the influence of pollinator access on plant chemistry and indicate a risk of pollinator decline and losses of chemical diversity for plant-pollinator network structure and ecosystem dynamics.