Mutualistic symbiosis relies on complex molecular communication processes between partners, influenced by genetics of both species. The evolutionary dynamics of this natural variation are not well understood, and many contributing genes remain unknown in part due to limitations in addressing natural variation in genes involved in these pathways and their function in partner quality. Combining transcriptomics to target candidate genes that are expressed during symbiosis with genomic analysis to identify causal variable regions (SNPs or presence-absence variation) can be useful to identify the natural variation that determines partner quality in mutualism. Particularly in well-studied models like Sinorhizobium, metabolic analysis and modeling can be used to quantify the differences in metabolite composition as a product of this genetic variation and model how this variation affects plant health and fitness. In this study, GEMS trainee Ivan Sosa Marquez aims to understand how previously described absence/presence patterns in important gene clusters of nodule-expressed genes influence intra-nodule metabolism and membrane transport systems and ultimately symbiotic quality.