UC Berkeley

Recent work suggests that plants have a plethora of previously underappreciated microbial allies that help them during their growth and development. The close interactions between plants and their complex microbial communities, otherwise known as the plant microbiome, play essential roles in plant health and productivity (Turner, James and Poole, 2013). Recent studies in various plant species have discovered multiple factors that shape the plant root microbiome, including geographical location, soil source, host genotype, and cultivation practice (Peiffer et al., 2013; Edwards et al., 2015; Naylor et al., 2017; Xu et al., 2018). Accumulating evidence suggests an interaction between host genetics and plant microbiome composition (Horton et al., 2014; Naylor et al., 2017; Fitzpatrick et al., 2018; Walters et al., 2018). However, identifying specific mechanisms driving microbiome acquisition and assembly, as well as the host genetic variants involved in these processes, has proved challenging. A few groups have delved into the impact of individual genes on microbiome composition (Lebeis et al., 2015; Castrillo et al., 2017). However, these studies were guided by a priori hypotheses of gene involvement. We believe that additional research is needed to better understand the host genetic regulation of plant-associated microbes within a naturally occurring ecological context.

Here I describe how we utilize recent advances in sequencing technology, quantitative genetics, statistical models, and data mining in conjunction with a successful sorghum diversity panel (Casa et al., 2008) to perform a population-level microbiome study using large scale genetic approaches. In this experiment, we used 200 diverse sorghum ecotypes and planted them in a replicated field trial. Our experimental design allowed us to control the environmental effect on associated microbiome composition in order to better resolve the impacts of host genetics. After examining multiple sample types, including the leaf, root, and rhizosphere, we first demonstrated that for sorghum plants, the rhizosphere represents the most suitable fraction of the plant microbiome for studying the host genetic effect, as compared to the root and leaf. We calculated broad sense heritability scores of the rhizosphere-associated microbial partners across all of the 200 sorghum diverse lines. We then identified which rhizosphere microbes exhibit reproducible associations with specific sorghum genotypes; these included members of the microbial orders Verrucomicrobiales, Flavobacteriales, Planctomycetales, and Burkholderiales. We also demonstrated that the heritable taxa in sorghum show a strong degree of overlap with heritable lineages previously identified in maize. To gain further insight into the host genetic regulation that is responsible for determining root microbiome variation, we employed a Genome-Wide Association Study (GWAS) approach, which allows us to rapidly scan genetic markers across the complete sets of DNA of many sorghum germplasm to find genetic variation associated with particular microbiome-related traits. We identified multiple plant loci that are associated with variation in the sorghum root microbiome. Furthermore, we demonstrated that GWAS could be used as a non-candidate approach to predict microbiome structure based solely on host genetic information. Collectively, this work demonstrates the utility of GWAS for analysis of host-mediated control of rhizosphere microbiome phenotypes and advances our knowledge of the relationship between the plant microbiome and host genetics control.

Finally, I describe our work on testing the effect of a commercially available soil amendment on agricultural soil and strawberry root bacterial microbiome. This final study highlights the main overarching significance of the above mentioned studies: understanding host genetic regulation of the plant root microbiome can provide insights into how to develop new and improved microbial formulations that are able to enhance crop productivity under a range of biotic and abiotic factors.