Disentangling leaf-microbiome interactions in Arabidopsis thaliana by network mapping

The leaf microbiota plays a key role in plant development, but a detailed mechanism of microbe-plant relationships remains elusive. Many genome-wide association studies (GWAS) have begun to map leaf microbes, but few have systematically characterized the genetics of how microbes act and interact. Previously, we integrated behavioral ecology and game theory to define four types of microbial interactions - mutualism, antagonism, aggression, and altruism, in a microbial community assembly. Here, we apply network mapping to identify specific plant genes that mediate the topological architecture of microbial networks. Analyzing leaf microbiome data from an Arabidopsis GWAS, we identify several heritable hub microbes for leaf microbial communities and detect 140-728 SNPs (Single nucleotide polymorphisms) responsible for emergent properties of microbial network. We reconstruct Bayesian genetic networks from which to identify 22-43 hub genes found to code molecular pathways related to leaf growth, abiotic stress responses, disease resistance and nutrition uptake. A further path analysis visualizes how genetic variants of Arabidopsis affect its fecundity through the internal workings of the leaf microbiome. We find that microbial networks and their genetic control vary along spatiotemporal gradients. Our study provides a new avenue to reveal the endophenotype role of microbial networks in linking genotype to end-point phenotypes in plants. Our integrative theory model provides a powerful tool to understand the mechanistic basis of structural-functional relationships within the leaf microbiome and supports the need for future research on plant breeding and synthetic microbial consortia with a specific function.

Automated summary

The leaf microbiota plays a crucial role in plant development, yet the detailed mechanisms behind microbe-plant relationships remain unclear. In this study, network mapping and genetic analysis were used to identify plant genes that mediate the topological architecture of microbial networks and uncover their molecular pathways related to leaf growth, stress responses, disease resistance, and nutrition uptake. Path analysis also revealed how genetic variants in Arabidopsis affect its fecundity through the leaf microbiome. This study provides new insights into the role of microbial networks in connecting plant genotype to end-point phenotypes, and highlights the importance of further research in plant breeding and synthetic microbial consortia.