Home-field advantage affects the local adaptive interaction between Andropogon gerardii ecotypes and root-associated bacterial communities.

Due to climate change, drought frequencies and severities are predicted to increase across the United States. Plant responses and adaptation to stresses depend on plant genetic and environmental factors. Understanding the effect of those factors on plant performance is required to predict species' responses to environmental change. We used reciprocal gardens planted with distinct regional ecotypes of the perennial grass Andropogon gerardii adapted to dry, mesic, and wet environments to characterize their rhizosphere communities using 16S rRNA metabarcode sequencing. Even though the local microbial pool was the main driver of these rhizosphere communities, the significant plant ecotypic effect highlighted active microbial recruitment in the rhizosphere, driven by ecotype or plant genetic background. Our data also suggest that ecotypes planted at their homesites were more successful in recruiting rhizosphere community members that were unique to the location. The link between the plants' homesite and the specific local microbes supported the "home field advantage" hypothesis. The unique homesite microbes may represent microbial specialists that are linked to plant stress responses. Furthermore, our data support ecotypic variation in the recruitment of congeneric but distinct bacterial variants, highlighting the nuanced plant ecotype effects on rhizosphere microbiome recruitment. These results improve our understanding of the complex plant host-soil microbe interactions and should facilitate further studies focused on exploring the functional potential of recruited microbes. Our study has the potential to aid in predicting grassland ecosystem responses to climate change and impact restoration management practices to promote grassland sustainability. IMPORTANCE In this study, we used reciprocal gardens located across a steep precipitation gradient to characterize rhizosphere communities of distinct dry, mesic, and wet regional ecotypes of the perennial grass Andropogon gerardii. We used 16S rRNA amplicon sequencing and focused oligotyping analysis and showed that even though location was the main driver of the microbial communities, ecotypes could potentially recruit distinct bacterial populations. We showed that different A. gerardii ecotypes were more successful in overall community recruitment and recruitment of microbes unique to the "home" environment, when growing at their "home site." We found evidence for "home-field advantage" interactions between the host and host-root-associated bacterial communities, and the capability of ecotypes to recruit specialized microbes that were potentially linked to plant stress responses. Our study aids in a better understanding of the factors that affect plant adaptation, improve management strategies, and predict grassland function under the changing climate.

Pseudomonas cultivated from Andropogon gerardii rhizosphere show functional potential for promoting plant host growth and drought resilience.

BACKGROUND: Climate change will result in more frequent droughts that can impact soil-inhabiting microbiomes (rhizobiomes) in the agriculturally vital North American perennial grasslands. Rhizobiomes have contributed to enhancing drought resilience and stress resistance properties in plant hosts. In the predicted events of more future droughts, how the changing rhizobiome under environmental stress can impact the plant host resilience needs to be deciphered. There is also an urgent need to identify and recover candidate microorganisms along with their functions, involved in enhancing plant resilience, enabling the successful development of synthetic communities. RESULTS: In this study, we used the combination of cultivation and high-resolution genomic sequencing of bacterial communities recovered from the rhizosphere of a tallgrass prairie foundation grass, Andropogon gerardii. We cultivated the plant host-associated microbes under artificial drought-induced conditions and identified the microbe(s) that might play a significant role in the rhizobiome of Andropogon gerardii under drought conditions. Phylogenetic analysis of the non-redundant metagenome-assembled genomes (MAGs) identified a bacterial genome of interest - MAG-Pseudomonas. Further metabolic pathway and pangenome analyses recovered genes and pathways related to stress responses including ACC deaminase; nitrogen transformation including assimilatory nitrate reductase in MAG-Pseudomonas, which might be associated with enhanced drought tolerance and growth for Andropogon gerardii. CONCLUSIONS: Our data indicated that the metagenome-assembled MAG-Pseudomonas has the functional potential to contribute to the plant host's growth during stressful conditions. Our study also suggested the nitrogen transformation potential of MAG-Pseudomonas that could impact Andropogon gerardii growth in a positive way. The cultivation of MAG-Pseudomonas sets the foundation to construct a successful synthetic community for Andropogon gerardii. To conclude, stress resilience mediated through genes ACC deaminase, nitrogen transformation potential through assimilatory nitrate reductase in MAG-Pseudomonas could place this microorganism as an important candidate of the rhizobiome aiding the plant host resilience under environmental stress. This study, therefore, provided insights into the MAG-Pseudomonas and its potential to optimize plant productivity under ever-changing climatic patterns, especially in frequent drought conditions.

Bacterial but Not Fungal Rhizosphere Community Composition Differ among Perennial Grass Ecotypes under Abiotic Environmental Stress.

Environmental change, especially frequent droughts, is predicted to detrimentally impact the North American perennial grasslands. Consistent dry spells will affect plant communities as well as their associated rhizobiomes, possibly altering the plant host performance under environmental stress. Therefore, there is a need to understand the impact of drought on the rhizobiome, and how the rhizobiome may modulate host performance and ameliorate its response to drought stress. In this study, we analyzed bacterial and fungal communities in the rhizospheres of three ecotypes (dry, mesic, and wet) of dominant prairie grass, Andropogon gerardii. The ecotypes were established in 2010 in a common garden design and grown for a decade under persistent dry conditions at the arid margin of the species' range in Colby, Kansas. The experiment aimed to answer whether and to what extent do the different ecotypes maintain or recruit distinct rhizobiomes after 10 years in an arid climate. In order to answer this question, we screened the bacterial and fungal rhizobiome profiles of the ecotypes under the arid conditions of western Kansas as a surrogate for future climate environmental stress using 16S rRNA and ITS2 metabarcoding sequencing. Under these conditions, bacterial communities differed compositionally among the A. gerardii ecotypes, whereas the fungal communities did not. The ecotypes were instrumental in driving the differences among bacterial rhizobiomes, as the ecotypes maintained distinct bacterial rhizobiomes even after 10 years at the edge of the host species range. This study will aid us to optimize plant productivity through the use of different ecotypes under future abiotic environmental stress, especially drought. IMPORTANCE In this study, we used a 10-year long reciprocal garden system, and reports that different ecotypes (dry, mesic, and wet) of dominant prairie grass, Andropogon gerardii can maintain or recruit distinct bacterial but not fungal rhizobiomes after 10 years in an arid environment. We used both 16S rRNA and ITS2 amplicons to analyze the bacterial and fungal communities in the rhizospheres of the respective ecotypes. We showed that A. gerardii might regulate the bacterial community to adapt to the arid environment, in which some ecotypes were not adapted to. Our study also suggested a possible tradeoff between the generalist and the specialist bacterial communities in specific environments, which could benefit the plant host. Our study will provide insights into the plant host regulation of the rhizosphere bacterial and fungal communities, especially during frequent drought conditions anticipated in the future.

Adaptive genetic potential and plasticity of trait variation in the foundation prairie grass Andropogon gerardii across the US Great Plains' climate gradient: Implications for climate change and restoration.

Plant response to climate depends on a species' adaptive potential. To address this, we used reciprocal gardens to detect genetic and environmental plasticity effects on phenotypic variation and combined with genetic analyses. Four reciprocal garden sites were planted with three regional ecotypes of Andropogon gerardii, a dominant Great Plains prairie grass, using dry, mesic, and wet ecotypes originating from western KS to Illinois that span 500-1,200 mm rainfall/year. We aimed to answer: (a) What is the relative role of genetic constraints and phenotypic plasticity in controlling phenotypes? (b) When planted in the homesite, is there a trait syndrome for each ecotype? (c) How are genotypes and phenotypes structured by climate? and (d) What are implications of these results for response to climate change and use of ecotypes for restoration? Surprisingly, we did not detect consistent local adaptation. Rather, we detected co-gradient variation primarily for most vegetative responses. All ecotypes were stunted in western KS. Eastward, the wet ecotype was increasingly robust relative to other ecotypes. In contrast, fitness showed evidence for local adaptation in wet and dry ecotypes with wet and mesic ecotypes producing little seed in western KS. Earlier flowering time in the dry ecotype suggests adaptation to end of season drought. Considering ecotype traits in homesite, the dry ecotype was characterized by reduced canopy area and diameter, short plants, and low vegetative biomass and putatively adapted to water limitation. The wet ecotype was robust, tall with high biomass, and wide leaves putatively adapted for the highly competitive, light-limited Eastern Great Plains. Ecotype differentiation was supported by random forest classification and PCA. We detected genetic differentiation and outlier genes associated with primarily precipitation. We identified candidate gene GA1 for which allele frequency associated with plant height. Sourcing of climate adapted ecotypes should be considered for restoration.

Local adaptation, genetic divergence, and experimental selection in a foundation grass across the US Great Plains' climate gradient.

Many prior studies have uncovered evidence for local adaptation using reciprocal transplant experiments. However, these studies are rarely conducted for a long enough time to observe succession and competitive dynamics in a community context, limiting inferences for long-lived species. Furthermore, the genetic basis of local adaptation and genetic associations with climate has rarely been identified. Here, we report on a long-term (6-year) experiment conducted under natural conditions focused on Andropogon gerardii, the dominant grass of the North American Great Plains tallgrass ecosystem. We focus on this foundation grass that comprises 80% of tallgrass prairie biomass and is widely used in 20,000 km2 of restoration. Specifically, we asked the following questions: (a) Whether ecotypes are locally adapted to regional climate in realistic ecological communities. (b) Does adaptive genetic variation underpin divergent phenotypes across the climate gradient? (c) Is there evidence of local adaptation if the plants are exposed to competition among ecotypes in mixed ecotype plots? Finally, (d) are local adaptation and genetic divergence related to climate? Reciprocal gardens were planted with 3 regional ecotypes (originating from dry, mesic, wet climate sources) of Andropogon gerardii across a precipitation gradient (500-1,200 mm/year) in the US Great Plains. We demonstrate local adaptation and differentiation of ecotypes in wet and dry environments. Surprisingly, the apparent generalist mesic ecotype performed comparably under all rainfall conditions. Ecotype performance was underpinned by differences in neutral diversity and candidate genes corroborating strong differences among ecotypes. Ecotype differentiation was related to climate, primarily rainfall. Without long-term studies, wrong conclusions would have been reached based on the first two years. Further, restoring prairies with climate-matched ecotypes is critical to future ecology, conservation, and sustainability under climate change.

Inferential considerations for low-count RNA-seq transcripts: a case study on the dominant prairie grass Andropogon gerardii.

BACKGROUND: Differential expression (DE) analysis of RNA-seq data still poses inferential challenges, such as handling of transcripts characterized by low expression levels. In this study, we use a plasmode-based approach to assess the relative performance of alternative inferential strategies on RNA-seq transcripts, with special emphasis on transcripts characterized by a small number of read counts, so-called low-count transcripts, as motivated by an ecological application in prairie grasses. Big bluestem (Andropogon gerardii) is a wide-ranging dominant prairie grass of ecological and agricultural importance to the US Midwest while edaphic subspecies sand bluestem (A. gerardii ssp. Hallii) grows exclusively on sand dunes. Relative to big bluestem, sand bluestem exhibits qualitative phenotypic divergence consistent with enhanced drought tolerance, plausibly associated with transcripts of low expression levels. Our dataset consists of RNA-seq read counts for 25,582 transcripts (60% of which are classified as low-count) collected from leaf tissue of individual plants of big bluestem (n = 4) and sand bluestem (n = 4). Focused on low-count transcripts, we compare alternative ad-hoc data filtering techniques commonly used in RNA-seq pipelines and assess the inferential performance of recently developed statistical methods for DE analysis, namely DESeq2 and edgeR robust. These methods attempt to overcome the inherently noisy behavior of low-count transcripts by either shrinkage or differential weighting of observations, respectively. RESULTS: Both DE methods seemed to properly control family-wise type 1 error on low-count transcripts, whereas edgeR robust showed greater power and DESeq2 showed greater precision and accuracy. However, specification of the degree of freedom parameter under edgeR robust had a non-trivial impact on inference and should be handled carefully. When properly specified, both DE methods showed overall promising inferential performance on low-count transcripts, suggesting that ad-hoc data filtering steps at arbitrary expression thresholds may be unnecessary. A note of caution is in order regarding the approximate nature of DE tests under both methods. CONCLUSIONS: Practical recommendations for DE inference are provided when low-count RNA-seq transcripts are of interest, as is the case in the comparison of subspecies of bluestem grasses. Insights from this study may also be relevant to other applications focused on transcripts of low expression levels.

Ecotypes of an ecologically dominant prairie grass (Andropogon gerardii) exhibit genetic divergence across the U.S. Midwest grasslands' environmental gradient.

Big bluestem (Andropogon gerardii) is an ecologically dominant grass with wide distribution across the environmental gradient of U.S. Midwest grasslands. This system offers an ideal natural laboratory to study population divergence and adaptation in spatially varying climates. Objectives were to: (i) characterize neutral genetic diversity and structure within and among three regional ecotypes derived from 11 prairies across the U.S. Midwest environmental gradient, (ii) distinguish between the relative roles of isolation by distance (IBD) vs. isolation by environment (IBE) on ecotype divergence, (iii) identify outlier loci under selection and (iv) assess the association between outlier loci and climate. Using two primer sets, we genotyped 378 plants at 384 polymorphic AFLP loci across regional ecotypes from central and eastern Kansas and Illinois. Neighbour-joining tree and PCoA revealed strong genetic differentiation between Kansas and Illinois ecotypes, which was better explained by IBE than IBD. We found high genetic variability within prairies (80%) and even fragmented Illinois prairies, surprisingly, contained high within-prairie genetic diversity (92%). Using Bayenv2, 14 top-ranked outlier loci among ecotypes were associated with temperature and precipitation variables. Six of seven BayeScanFST outliers were in common with Bayenv2 outliers. High genetic diversity may enable big bluestem populations to better withstand changing climates; however, population divergence supports the use of local ecotypes in grassland restoration. Knowledge of genetic variation in this ecological dominant and other grassland species will be critical to understanding grassland response and restoration challenges in the face of a changing climate.