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27 results for “Panicum virgatum”
Panicum virgatum L. (BR0000011819400)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Panicum virgatum L. (BR0000005558940)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Panicum virgatum L. (BR0000010773802)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Panicum virgatum L. (BR0000012503278)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Data from: Associative nitrogen fixation (ANF) in switchgrass (Panicum virgatum) across a nitrogen input gradient
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Data from: Plant community response to switchgrass (Panicum virgatum) population source in establishing prairies
Ecological restoration and revegetation efforts entail the translocation of native plant populations. Risks associated with these efforts include failure of translocated populations to establish or, conversely, such strong establishment that they excessively dominate the recipient community. The role that selective breeding plays in mediating these risks is unclear but of increasing importance as efforts to restore and establish multifunctional grasslands also increase. In a three-year, spatially replicated study, we seeded experimental prairie communities with either domesticated (cultivar) or undomesticated strains of Panicum virgatum (switchgrass), a North American C4 species under development as a biomass crop. We evaluated the composition, performance, and diversity of the recipient plant communities and compared the performance of cultivar and undomesticated switchgrass in those communities. We found little evidence that switchgrass population source affected community response. Switchgrass cultivars modestly exceeded undomesticated strains with respect to stand establishment, third-year stand density, and aboveground biomass; effect size and significance differed among sites. Our results suggest that including cultivars in ecological restorations and multifunctional grasslands may enhance success of switchgrass establishment with little risk of impairing the composition or diversity of plant communities for up to three years, as reflected in the measures used here. However, the incorporation of undomesticated switchgrass into multifunctional grasslands may enhance landscape-scale genetic variation and mitigate risks associated with gene flow between translocated and local wild switchgrass populations; more research on these dynamics is needed.
Plant biomass, not plant economics traits, determines responses of soil CO2 efflux to precipitation in the C4 grass Panicum virgatum
<p>1. Plant responses to major environmental drivers like precipitation can influence important aspects of carbon (C) cycling like soil CO<sub>2</sub> efflux (J<sub>CO2</sub>). These responses may be predicted by two independent classes of drivers: plant size—larger plants respire more and produce a larger quantity of labile C, and plant economics—plants possessing more acquisitive plant economics strategies (i.e., high metabolic rate and tissue nutrient content) produce higher-quality tissue that respires rapidly and decomposes quickly.</p> <p>2. At two sites in central Texas, USA with similar climates and differing soil characteristics, we examined the response of eight <i>Panicum virgatum</i> genotypes to three annual precipitation levels defined by the driest, average, and wettest years from each site's precipitation history. We evaluated the individual and joint influence of plant genotypes and precipitation on J<sub>CO2</sub> and traits related to plant economics and plant size. We then used confirmatory path analysis to evaluate whether effects of precipitation on J<sub>CO2</sub> were in part related to effects of precipitation on plant economics traits or size ('mediated' effects).</p> <p>3. These genotypes exhibited variation in plant economics traits and aboveground net primary productivity (ANPP), an aboveground measure of plant size. Increasing precipitation increased J<sub>CO2</sub> and ANPP more than plant economics traits. At both sites, ANPP was the single best predictor of J<sub>CO2</sub>. Moreover, the sites differed in the ways that plant size and plant economics traits combined with precipitation to influence J<sub>CO2</sub>. At the Austin site, the positive effect of precipitation on J<sub>CO2</sub> was mediated primarily by ANPP, offset by a smaller effect of leaf nitrogen content; no direct precipitation effect was detected. At the Temple site, increasing precipitation had positive direct and ANPP-mediated effects on J<sub>CO2</sub>. This suggests that greater water limitation at Austin may strengthen the links between plant size and J<sub>CO2</sub>.</p> <p>4. Synthesis Estimates of C cycling can be improved by accounting for mediation of precipitation effects on J<sub>CO2</sub> by plant economics traits and plant size in resource-limited environments.</p>
Alamo x Kanlow genotypic and phenotypic data for biomass yield and yield-related traits in lowland switchgrass (Panicum virgatum L.) crosses
<p>Switchgrass (<em>Panicum virgatum</em> L.) is a model herbaceous bioenergy crop in the USA. It is a native, perennial, warm-season grass, and has broad adaptability. Many breeding programs focus on the genetic improvement of switchgrass for increasing biomass yield. Significant genetic variation for biomass yield observed in lowland switchgrass hybrids. Due to the quantitative inheritance of biomass yield, varietal improvement for the trait through conventional breeding is slow. Therefore, quantitative trait loci (QTL) mapping is used to discover marker-trait associations and accelerate the breeding process through marker-assisted selection. To identify significant QTL, this study mapped seven biparental crosses and one combined cross of two biparental crosses (30 to 96 F1s) between lowland Alamo and Kanlow genotypes. The crosses were evaluated for biomass yield, plant height, and clonal mass scores in a simulated-sward plot with two replications at two locations in Tennessee from 2019 to 2021. The crosses were genotyped using 17,251 single nucleotide polymorphisms generated through genotyping-by-sequencing. QTL mapping was performed using a single-QTL model in R-QTL. The study identified major QTL for biomass yield, plant height, and clonal mass scores resided on chromosomes 7K, 4K, and 3K and had 0.47, 0.63, and 0.62 heritability, respectively.</p> <p>The dataset contains five files describing the phenotype and genotype of each individual used in the quantitative trait loci (QTL) analysis.</p> <ul> <li>'File 1' contains biomass yield, plant height, and clonal mass data for each genotype and parents evaluated at two locations in Tennessee; the Plateau Research and Education Center (PREC), Crossville and East Tennessee Research and Education Center (ETREC), Knoxville from 2019 to 2021. Plant height and biomass yield were measured at maturity, and clonal mass scores were evaluated after harvesting biomass.</li> <li>'File 2' has the genotype name, library, index, total reads, bases, and the Phred quality score (Q30). Young leaf tissue was collected from each F1 progeny and parent, and DNA was extracted using the cetyltrimethylammonium bromide (CTAB) procedure. The extracted DNA was genotyped at the USDA-ARS Western Regional Research Center laboratory in Albany, CA. Genotyping by sequencing (GBS) was performed on 951 lines (F1s and their parents) using the PstI-MspI GBS protocol. The quality of these sequences showed that 94.4% of the bases were at or above Q30. Reads were mapped to version 5.0 of the switchgrass reference genome. Single nucleotide polymorphism (SNP) calling was performed, and redundant markers were filtered out for linkage map construction. 'File 3' has SNP ID numbers, SNP locations on chromosomes, map positions, and SNP scores. The cross was used as a four-way cross for QTL analysis, where the male parent Kanlow (K) was assigned as '1', and the female parent Alamo (A) was assigned as '2'.</li> <li>The phased output data from the four-way cross, i.e., 11, 12, 21, and 22, were represented by AC, BC, AD, and BD, respectively ('File 3').</li> <li>The progeny file ('File 4') contains the name of the parents used for making crosses and their progenies.</li> <li>A consensus linkage map ('File 5') was produced with Lep-Map3 software. The linkage map contains 18 linkage groups associated with 18 switchgrass chromosomes, marker size (bp), map position (cM) based on male and female maps, and map order.</li> </ul>
Data from: Identification of anti-fungal bioactive terpenoids from the bioenergy crop switchgrass (Panicum virgatum)
<p>Plant derived bioactive small molecules have attracted attention of scientists across fundamental and applied scientific disciplines. We seek to understand the influence of these phytochemicals on functional phytobiomes. Increased knowledge of specialized metabolite bioactivities could inform strategies for sustainable crop production. We hypothesized that – consistent with accumulating evidence that switchgrass genotype impacts microbiome assembly – differential terpenoid accumulation contributes to switchgrass ecotype-specific microbiome composition. An initial in vitro plate-based disc diffusion screen of 18 switchgrass root derived fungal isolates revealed differential responses to upland- and lowland-isolated metabolites. To identify specific fungal growth-modulating metabolites, we tested fractions from root extracts on three ecologically important fungal isolates – <em>Linnemania elongata</em>, <em>Trichoderma</em> sp. and <em>Fusarium</em> sp. Saponins and diterpenoids were identified as the most prominent antifungal metabolites. Finally, analysis of liquid chromatography-purified terpenoids revealed fungal inhibition structure – activity relationships (SAR). Saponin antifungal activity was primarily determined by the number of sugar moieties – saponins glycosylated at a single core position were inhibitory whereas saponins glycosylated at two core positions were inactive. Saponin core hydroxylation and acetylation were also associated with reduced activity. Diterpenoid activity required the presence of an intact furan ring for strong fungal growth inhibition.</p>
Data from: Inorganic N addition replaces N supplied to switchgrass (Panicum virgatum) by arbuscular mycorrhizal fungi
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Alamo x Kanlow genotypic and phenotypic data for biomass yield and yield-related traits in lowland switchgrass (Panicum virgatum L.) crosses
Open the record for dataset details and reuse information.
Data from: Plant community response to switchgrass (Panicum virgatum) population source in establishing prairies
Open the record for dataset details and reuse information.
Data from: Identification of anti-fungal bioactive terpenoids from the bioenergy crop switchgrass (Panicum virgatum)
Open the record for dataset details and reuse information.
Data from: Plant biomass, not plant economics traits, determines responses of soil CO2 efflux to precipitation in the C4 grass Panicum virgatum
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Data from: Adaptations between ecotypes and along environmental gradients in Panicum virgatum
Determining the patterns and mechanisms of natural selection in the wild is of fundamental importance to understanding the differentiation of populations and the evolution of new species. However, it is often unknown the extent to which adaptive genetic variation is distributed among ecotypes between distinct habitats versus along large-scale geographic environmental gradients, such as those that track latitude. Classic selection in the wild experiments in switchgrass, Panicum virgatum, tested for adaptation at both of these levels of natural variation. Here we review what these field experiments, as well as modern agronomic field trials, have taught us about natural variation and selection at both the ecotype and environmental gradient level in P. virgatum. With the recent genome sequencing efforts of P. virgatum, it is poised to become an excellent system for understanding the adaptation of grassland species across the eastern half of North America. The identification of genetic loci involved in different types of adaptations will help to understand the evolutionary mechanisms of diversification within P. virgatum and provide useful information for the breeding of high yielding cultivars for different ecoregions.
Surveying Grassland Islands: the genetics and performance of Appalachian switchgrass (Panicum virgatum L.) collections
<p>The interior Southeastern United States could contain novel germplasm for the bioenergy crop switchgrass due to its diverse habitats and geographic location between genetic subpopulations (Atlantic, Midwest, and Gulf). Collections from this region could accelerate breeding progress, contribute to conservation efforts, and improve understanding of isolated grasslands in the region. This study located 22 sites in the Midsouth region and obtained 1,521,210 single nucleotide polymorphism markers of 202 individuals through genotype-by-sequencing. Individuals were evaluated for flowering time, winter survival and tiller number. Comparison to a national diversity panel revealed that branches of two major subpopulations occur in the region with two levels of polyploidy: Atlantic tetraploids and Midwest octoploids. Two locations contained admixed octoploid individuals with Midwest and Gulf genetics. Field performance of the Midwest octoploids conformed with prior reported performance of the Midwest subpopulation, although three sites contained promising late flowering traits. The Atlantic tetraploids had moderate winter survival, short stature, and anomalously early flowering. Atlantic populations mostly occurred in marginal sites and their morphological and flowering time adaptations may be a resource conservation strategy. Demographic inference of historical effective population size variation in a subset of tetraploid locations indicated a widespread recent decline in effective population size. This pattern is consistent with isolation of these switchgrass communities from larger populations and is further supported by evidence of inbreeding within the populations (F<sub>I</sub> = 0.18). The populations documented in this study contain novel genetic diversity and adaptations to a range of marginal habitats. Therefore, this study provides a new source of germplasm for future breeding and conservation programs.</p>
Data from: Integrating transcriptional, metabolomic, and physiological responses to drought stress and recovery in switchgrass (Panicum virgatum L.)
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Surveying Grassland Islands: the genetics and performance of Appalachian switchgrass (Panicum virgatum L.) collections
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Data from: Adaptations between ecotypes and along environmental gradients in Panicum virgatum
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Data from: Candidate variants for additive and interactive effects on bioenergy traits in switchgrass (Panicum virgatum L.) identified by genome-wide association analyses
Switchgrass is a promising herbaceous energy crop, but further gains in biomass yield and quality must be achieved to enable a viable bioenergy industry. Developing DNA markers can contribute to such progress, but depiction of genetic bases should be reliable, involving not only simple additive marker effects but also interactions with genetic backgrounds, e.g., ecotypes, or synergies with other markers. We analyzed plant height, carbon content, nitrogen content, and mineral concentration in a diverse panel consisting of 512 genotypes of upland and lowland ecotype. We performed association analyses based on exome capture sequencing and tested 439,170 markers for marginal effects, but also 83,290 markers for marker-by-ecotype interactions and up to 311,445 marker pairs for pairwise interactions. Analyses of pairwise interactions focused on subsets of marker pairs preselected based on marginal marker effects, gene ontology annotation, and pairwise marker associations. Our tests identified 12 significant effects. Homology and gene expression information corroborated seven effects and indicated plausible causal pathways: flowering time and lignin synthesis for plant height; plant growth and senescence for carbon content and mineral concentration. Four pairwise interactions were detected, including three interactions preselected based on pairwise marker correlations. Furthermore, one marker-by-ecotype interaction and one pairwise interaction were confirmed in an independent switchgrass panel. Our analyses identified reliable candidate variants for important bioenergy traits in switchgrass. Moreover, they exemplified the importance of interactive effects for the depiction of genetic bases, and illustrated the usefulness of preselection of marker pairs for identifying pairwise marker interactions in association testing.
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