The degree to which plant genetics regulate microbial communities is of interest to crop breeders, evolutionary biologists, and ecologists. Plant genetics have been shown to play a significant role in shaping the microbiota, yet little work has been done to identify specific loci driving the structure and function of the rhizosphere microbiome. Identifying host genetic elements influencing assembly or function of the host-associated microbiome could provide us with a novel method to manage and understand our root-associated soils. Here we use the genetic variability that exists within the Zea genus, which comprises an ecologically diverse collection of plant species including domesticated maize and its closest wild relative, teosinte, to understand the relationship between host genetics and structure and function of the rhizosphere microbiome. We have previously found that maize and teosinte assemble their below-ground rhizosphere communities very differently. These microbiome differences manifest themselves in changes in diversity, composition, and rates of microbial N-cycling metabolism. To further dissect the genetic basis of these ancestral microbiome traits, we used newly developed teosinte-maize near-isogenic lines (NILs). Using NIL populations allows for the fine-mapping of traits to specific genetic loci in the plant genome. NILs were grown in the field setting in a randomized complete block design, and microbiomes were characterized though Amplicon sequencing and potential nitrogen cycling assays.
Results/Conclusions
From this Maize-Teosinte NIL experimental population, we identified 13 candidate NILs that altered the composition of the microbiome in the root zone. These candidate NILs vary in their degree of influence on the microbial community. Three of these introgressions strongly altered the rhizosphere microbial community composition. In total, 23% of the Zea genome mapped to change in the microbiome. Functionally, we identified five NILs that altered the microbial communities N-cycling activity. Two of these NILs were shown to have 40% lower potential nitrification rates (t-test P<0.05). Three of these NILs were shown to have 35% lower potential denitrification rates (t-test P<0.05). These findings begin to shed light on how specific plant genetic loci in the host influence their associated microbiota's structure and function. This type of understanding could provide us with a novel biological method by which to manage our agricultural ecosystems and global nitrogen cycle.