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Dataset results
27 results for “Panicum virgatum”
Data from: Relative performance of non-local cultivars and local, wild populations of switchgrass (Panicum virgatum) in competition experiments
The possibility of increased invasiveness in cultivated varieties of native perennial species is a question of interest in biofuel risk assessment. Competitive success is a key factor in the fitness and invasive potential of perennial plants, and thus the large-scale release of high-yielding biomass cultivars warrants empirical comparisons with local conspecifics in the presence of competitors. We evaluated the performance of non-local cultivars and local wild biotypes of the tallgrass species Panicum virgatum L. (switchgrass) in competition experiments during two growing seasons in Ohio and Iowa. At each location, we measured growth and reproductive traits (plant height, tiller number, flowering time, aboveground biomass, and seed production) of four non-locally sourced cultivars and two locally collected wild biotypes. Plants were grown in common garden experiments under three types of competition, referred to as none, moderate (with Schizachyrium scoparium), and high (with Bromus inermis). In both states, the two "lowland" cultivars grew taller, flowered later, and produced between 2x and 7.5x more biomass and between 3x and 34x more seeds per plant than local wild biotypes, while the other two cultivars were comparable to wild biotypes in these traits. Competition did not affect relative differences among biotypes, with the exception of shoot number, which was more similar among biotypes under high competition. Insights into functional differences between cultivars and wild biotypes are crucial for developing biomass crops while mitigating the potential for invasiveness. Here, two of the four cultivars generally performed better than wild biotypes, indicating that these biotypes may pose more of a risk in terms of their ability to establish vigorous feral populations in new regions outside of their area of origin. Our results support an ongoing assessment of switchgrass cultivars developed for large-scale planting for biofuels.
Data from: Relative performance of non-local cultivars and local, wild populations of switchgrass (Panicum virgatum) in competition experiments
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Data from: Nucleotide polymorphism and copy number variant detection using exome capture and next generation sequencing in the polyploid grass 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
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Profiling changes in gene expression by RNA-Seq during drought and recovery in switchgrass (Panicum virgatum Alamo AP13)
GEO Series GSE57887. Panicum virgatum. 119 samples. Type: Expression profiling by high throughput sequencing.
High-throughput sequencing of small RNAs in Panicum virgatum
GEO Series GSE28980. Panicum virgatum. 3 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Transcriptional, Metabolic, Physiological and Developmental Responses to Nitrogen Limitation in Switchgrass (Panicum virgatum)
GEO Series GSE237286. Panicum virgatum. 18 samples. Type: Expression profiling by high throughput sequencing.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.