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Plant–microbe symbioses such as the legume–rhizobium mutualism are vital in the web of ecological relationships within both natural and managed ecosystems, influencing primary productivity, crop yield, and ecosystem services. The outcome of these interactions for plant hosts varies quantitatively and can range from highly beneficial to even detrimental depending on natural genetic variation in microbial symbionts. Here, we take a systems genetics approach, harnessing the genetic diversity present in wild rhizobial populations to predict genes and molecular pathways crucial in determining partner quality, i.e., the benefits of symbiosis for legume hosts. We combine traits, dual-RNAseq of both partners from active nodules, pangenomics/pantranscriptomics, and Weighted Gene Co-expression Network Analysis (WGCNA) for a panel of 20Sinorhizobium melilotistrains that vary in symbiotic partner quality. We find that genetic variation in the nodule transcriptome predicts host plant biomass, and WGCNA reveals networks of genes in plants and rhizobia that are coexpressed and associated with high-quality symbiosis. Presence–absence variation of gene clusters on the symbiosis plasmid (pSymA), validated in planta, is associated with high or low-quality symbiosis and is found within important coexpression modules. Functionally our results point to management of oxidative stress, amino acid and carbohydrate transport, and NCR peptide signaling mechanisms in driving symbiotic outcomes. Our integrative approach highlights the complex genetic architecture of microbial partner quality and raises hypotheses about the genetic mechanisms and evolutionary dynamics of symbiosis. 

ABSTRACT A goal of modern biology is to develop the genotype-phenotype (G→P) map, a predictive understanding of how genomic information generates trait variation that forms the basis of both natural and managed communities. As microbiome research advances, however, it has become clear that many of these traits are symbiotic extended phenotypes , being governed by genetic variation encoded not only by the host’s own genome, but also by the genomes of myriad cryptic symbionts. Building a reliable G→P map therefore requires accounting for the multitude of interacting genes and even genomes involved in symbiosis. Here, we use naturally occurring genetic variation in 191 strains of the model microbial symbiont Sinorhizobium meliloti paired with two genotypes of the host Medicago truncatula in four genome-wide association studies (GWAS) to determine the genomic architecture of a key symbiotic extended phenotype— partner quality , or the fitness benefit conferred to a host by a particular symbiont genotype, within and across environmental contexts and host genotypes. We define three novel categories of loci in rhizobium genomes that must be accounted for if we want to build a reliable G→P map of partner quality; namely, (i) loci whose identities depend on the environment, (ii) those that depend on the host genotype with which rhizobia interact, and (iii) universal loci that are likely important in all or most environments. IMPORTANCE Given the rapid rise of research on how microbiomes can be harnessed to improve host health, understanding the contribution of microbial genetic variation to host phenotypic variation is pressing, and will better enable us to predict the evolution of (and select more precisely for) symbiotic extended phenotypes that impact host health. We uncover extensive context-dependency in both the identity and functions of symbiont loci that control host growth, which makes predicting the genes and pathways important for determining symbiotic outcomes under different conditions more challenging. Despite this context-dependency, we also resolve a core set of universal loci that are likely important in all or most environments, and thus, serve as excellent targets both for genetic engineering and future coevolutionary studies of symbiosis.