Genetic determinants of switchgrass-root-associated microbiota in field sites spanning its natural range.

A fundamental goal in plant microbiome research is to determine the relative impacts of host and environmental effects on root microbiota composition, particularly how host genotype impacts bacterial community composition. Most studies characterizing the effect of plant genotype on root microbiota undersample host genetic diversity and grow plants outside of their native ranges, making the associations between host and microbes difficult to interpret. Here, we characterized the root microbiota of a large diversity panel of switchgrass, a North American native C4 bioenergy crop, in three field locations spanning its native range. Our data, composed of 1,961 samples, suggest that field location is the primary determinant of microbiome composition; however, substantial heritable variation is widespread across bacterial taxa, especially those in the Sphingomonadaceae family. Despite diverse compositions, relatively few highly prevalent taxa make up the majority of the switchgrass root microbiota, a large fraction of which is shared across sites. Local genotypes preferentially recruit/filter for local microbes, supporting the idea of affinity between local plants and their microbiota. Using genome-wide association, we identified loci impacting the abundance of >400 microbial strains and found an enrichment of genes involved in immune responses, signaling pathways, and secondary metabolism. We found loci associated with over half of the core microbiota (i.e., microbes in >80% of samples), regardless of field location. Finally, we show a genetic relationship between a basal plant immunity pathway and relative abundances of root microbiota. This study brings us closer to harnessing and manipulating beneficial microbial associations via host genetics.

Artificial Selection on Microbiomes To Breed Microbiomes That Confer Salt Tolerance to Plants.

We develop a method to artificially select for rhizosphere microbiomes that confer salt tolerance to the model grass Brachypodium distachyon grown under sodium salt stress or aluminum salt stress. In a controlled greenhouse environment, we differentially propagated rhizosphere microbiomes between plants of a nonevolving, highly inbred plant population; therefore, only microbiomes evolved in our experiment, but the plants did not evolve in parallel. To maximize microbiome perpetuation when transplanting microbiomes between plants and, thus, maximize response to microbiome selection, we improved earlier methods by (i) controlling microbiome assembly when inoculating seeds at the beginning of each selection cycle; (ii) fractionating microbiomes before transfer between plants to harvest, perpetuate, and select on only bacterial and viral microbiome components; (iii) ramping of salt stress gradually from minor to extreme salt stress with each selection cycle to minimize the chance of overstressing plants; (iv) using two nonselection control treatments (e.g., nonselection microbial enrichment and null inoculation) that permit comparison to the improving fitness benefits that selected microbiomes impart on plants. Unlike previous methods, our selection protocol generated microbiomes that enhance plant fitness after only 1 to 3 rounds of microbiome selection. After nine rounds of microbiome selection, the effect of microbiomes selected to confer tolerance to aluminum salt stress was nonspecific (these artificially selected microbiomes equally ameliorate sodium and aluminum salt stresses), but the effect of microbiomes selected to confer tolerance to sodium salt stress was specific (these artificially selected microbiomes do not confer tolerance to aluminum salt stress). Plants with artificially selected microbiomes had 55 to 205% greater seed production than plants with unselected control microbiomes. IMPORTANCE We developed an experimental protocol that improves earlier methods of artificial selection on microbiomes and then tested the efficacy of our protocol to breed root-associated bacterial microbiomes that confer salt tolerance to a plant. Salt stress limits growth and seed production of crop plants, and artificially selected microbiomes conferring salt tolerance may ultimately help improve agricultural productivity. Unlike previous experiments of microbiome selection, our selection protocol generated microbiomes that enhance plant productivity after only 1 to 3 rounds of artificial selection on root-associated microbiomes, increasing seed production under extreme salt stress by 55 to 205% after nine rounds of microbiome selection. Although we artificially selected microbiomes under controlled greenhouse conditions that differ from outdoor conditions, increasing seed production by 55 to 205% under extreme salt stress is a remarkable enhancement of plant productivity compared to traditional plant breeding. We describe a series of additional experimental protocols that will advance insights into key parameters that determine efficacy and response to microbiome selection.

Compositional shifts in root-associated bacterial and archaeal microbiota track the plant life cycle in field-grown rice.

Bacterial communities associated with roots impact the health and nutrition of the host plant. The dynamics of these microbial assemblies over the plant life cycle are, however, not well understood. Here, we use dense temporal sampling of 1,510 samples from root spatial compartments to characterize the bacterial and archaeal components of the root-associated microbiota of field grown rice (Oryza sativa) over the course of 3 consecutive growing seasons, as well as 2 sites in diverse geographic regions. The root microbiota was found to be highly dynamic during the vegetative phase of plant growth and then stabilized compositionally for the remainder of the life cycle. Bacterial and archaeal taxa conserved between field sites were defined as predictive features of rice plant age by modeling using a random forest approach. The age-prediction models revealed that drought-stressed plants have developmentally immature microbiota compared to unstressed plants. Further, by using genotypes with varying developmental rates, we show that shifts in the microbiome are correlated with rates of developmental transitions rather than age alone, such that different microbiota compositions reflect juvenile and adult life stages. These results suggest a model for successional dynamics of the root-associated microbiota over the plant life cycle.