Background: Despite their widespread distribution and ecological importance, protists remain one of the least understood components of the soil and rhizosphere microbiome. Knowledge of the roles that protists play in stimulating organic matter decomposition and shaping microbiome dynamics continues to grow, but there remains a need to understand the extent to which biological and environmental factors mediate protist community assembly and dynamics. We hypothesize that protists communities are filtered by the influence of plants on their rhizosphere biological and physicochemical environment, resulting in patterns of protist diversity and composition that mirror previously observed diversity and successional dynamics in rhizosphere bacterial communities. Results: We analyzed protist communities associated with the rhizosphere and bulk soil of switchgrass (SG) plants (Panicum virgatum) at different phenological stages, grown in two marginal soils as part of a large-scale field experiment. Our results reveal that the diversity of protists is lower in rhizosphere than bulk soils, and that temporal variations depend on soil properties but are less pronounced in rhizosphere soil. Patterns of significantly prevalent protists groups in the rhizosphere suggest that most protists play varied ecological roles across plant growth stages and that some plant pathogenic protists and protists with omnivorous diets reoccur over time in the rhizosphere. We found that protist co-occurrence network dynamics are more complex in the rhizosphere compared to bulk soil. A phylogenetic bin-based null model analysis showed that protists’ community assembly in our study sites is mainly controlled by homogenous selection and dispersal limitation, with stronger selection in rhizosphere than bulk soil as SG grew and senesced. Conclusions: We demonstrate that environmental filtering is a dominant determinant of overall protist community properties and that at the rhizosphere level, plant control on the physical and biological environment is a critical driver of protist community composition and dynamics. Since protists are key contributors to plant nutrient availability and bacterial community composition and abundance, mapping and understanding their patterns in rhizosphere soil is foundational to understanding the ecology of the root-microbe-soil system.

Switchgrass (Panicum virgatum L.), is a warm season C₄ perennial grass, native to North American tall grass prairies. The high biomass production potential of switchgrass with low inputs makes it an excellent choice as a sustainable bioenergy crop. The objective of this study was to determine the genetic variability within and among 31 switchgrass populations obtained from Germplasm Resources Information Network (GRIN). Six plants from each population (186 genotypes) were characterized with 24 conserved grass expressed sequence tag-simple sequence repeats (EST-SSR) and 39 switchgrass EST-SSR markers. The partitioning of variance components based on the analysis of molecular variance (AMOVA) revealed that the variability within population was significantly higher (80%) than among populations (20%). Pair-wise genetic distance estimates based on SSR data revealed dissimilarity coefficients for genotypes ranging from 0.45 to 0.81. The uplands and lowlands were generally grouped in distinct sub-clusters. The genotypes were grouped into the different adaptive zones based on the geographical locations of the collections. Ploidy estimation showed that 20 of the accessions were tetraploid, four of them were octoploids and the remaining seven had mixed ploidy levels. Flow cytometry analysis of genotypes within cultivars collected from commercial seed sources did not always support the ploidy mixtures that were found in GRIN collections. Three genotypes of two accessions that clustered differently from other genotypes of the same accessions also had different ploidy levels.

Perennial bioenergy crops have been shown to increase soil organic carbon (SOC) stocks, potentially offsetting anthropogenic C emissions. The effects of perennial bioenergy crops on SOC are typically assessed at shallow depths (30 cm) SOC stocks would be greater under bioenergy crops relative to stocks under shallow‐rooted conventional crop cover. To test this, we sampled soils to between 1‐ and 3‐m depth at three sites in Oklahoma with 10‐ to 20‐year‐old switchgrass (Panicum virgatum) stands, and collected paired samples from nearby fields cultivated with shallow rooted annual crops. We measured root biomass, total organic C,¹⁴C,¹³C, and other soil properties in three replicate soil cores in each field and used a mixing model to estimate the proportion of recently fixed C under switchgrass based on¹⁴C. The subsoil C stock under switchgrass (defined over 500–1500 kg/m²equivalent soil mass, approximately 30–100 cm depth) exceeded the subsoil stock in neighboring fields by 1.5 kg C/m²at a sandy loam site, 0.6 kg C/m²at a site with loam soils, and showed no significant difference at a third site with clay soils. Using the mixing model, we estimated that additional SOC introduced after switchgrass cultivation comprised 31% of the subsoil C stock at the sandy loam site, 22% at the loam site, and 0% at the clay site. These results suggest that switchgrass can contribute significantly to subsoil organic C—but also indicated that this effect varies across sites. Our analysis shows that agricultural strategies that emphasize deep‐rooted grass cultivars can increase soil C relative to conventional crops while expanding energy biomass production on marginal lands.

Several fungal pathogens have been identified on ornamental and native stands of switchgrass (Panicum virgatum L.). Diseases of switchgrass, particularly rust, have been largely neglected and are likely to become the major limiting factor to biomass yield and quality, especially when monocultured over a large acreage. Based on teliospore morphology and internal transcribed spacer-based diagnostic primers, the rust pathogen collected from switchgrass research fields in Oklahoma was identified as Puccinia emaculata. Furthermore, to identify genetically diverse source(s) of rust resistance, several switchgrass genotypes from both upland (cv. ‘Summer’ and ‘Cave-in-Rock’) and lowland (cv. ‘Alamo’ and ‘Kanlow’) ecotypes were evaluated in Ardmore, Oklahoma during 2008 and 2009 and in growth chamber assays. Field and growth chamber evaluations revealed a high degree of genetic variation within and among switchgrass cultivars. In general, Alamo and Kanlow showed moderate resistance to P. emaculata, while Summer was highly susceptible. Distinct ecotypic variations for reactions to rust were also prevalent with the lowlands maintaining a high level of resistance. These results suggest the potential for improvement of rust resistance via the selection of resistant individuals from currently available cultivars. Further, the selection pressure on the pathogen would also be reduced by employing several rust resistant cultivars in production-scale situations.

Switchgrass (Panicum virgatum L.) biomass yield and feedstock quality improvement are priority research areas for bioenergy feedstock development. Identification of quantitative trait loci (QTL) underlying these traits and of trait-linked markers for application in marker-assisted selection (MAS) is of paramount importance in facilitating switchgrass breeding. Detection of QTL for biomass yield and plant height was conducted on parental linkage maps constructed using a heterozygous pseudo-F₁ population derived from a cross between lowland Alamo genotype AP13 and upland Summer genotype VS16. QTL analysis was performed with composite interval mapping. Four QTL for biomass yield and five QTL for plant height were identified using best linear unbiased predictors across ten and eight environments, respectively. The phenotypic variability explained (PVE) by QTL detected in the across environments analysis ranged from 4.9 to 12.4 % for biomass yield and 5.1 to 12.0 % for plant height. A total of 34 and 38 main effect QTL were detected for biomass yield and plant height, respectively, when data from each environment were analyzed separately. The PVE by individual environment QTL ranged from 3.3 to 15.3 % for biomass yield and from 4.3 to 17.4 % for plant height. In addition, 60 and 51 epistatic QTL were detected for biomass yield and plant height, respectively. Significant QTL by environment interactions were detected for QTL mapped in eight genomic regions for each of the two traits. Seven QTL affected both traits and may represent pleiotropic loci. Overall, 11 genomic regions were identified that were important in controlling biomass yield and/or plant height in switchgrass. The markers linked to the main effect and epistatic QTL may be used in MAS to maximize selection gain in switchgrass breeding, leading to a faster development of better biofuel cultivars.