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ShareScore release 0.9.0
Dataset results
11 results for “Panicum virgatum L.”
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>.
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>
Alamo x Kanlow genotypic and phenotypic data for biomass yield and yield-related traits in lowland switchgrass (Panicum virgatum L.) crosses
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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: 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.
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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