Switchgrass (Panicum virgatum L.) is a potential source for producing bioenergy from lignocellulosic biomass. Many breeding programs focus on the genetic improvement of switchgrass for increasing bioenergy traits. Significant genetic variation for bioenergy traits was observed in lowland switchgrass hybrids (P<0.05). Due to the quantitative inheritance of bioenergy traits, varietal improvement for the trait through conventional methods is slow and challenging. 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 eight hybrid populations (30 to 96 F1s) developed by crossing lowland cultivars, Alamo and Kanlow. The populations were evaluated in a simulated-sward plot with two replications at two locations in Tennessee in 2020 and 2021. The crosses were genotyped using 17,251 single nucleotide polymorphisms generated through genotyping-by-sequencing. QTL mapping was performed across populations using R-QTL. The study identified ten QTL for predicted ethanol, four for cellulose, and three hemicellulose on chromosomes 1K, 1N, 2N, 4N, 5K, 5N, 7K, 8K, 8N, and 9N, respectively, with phenotypic variability ranged from 2.1 to 7.4%.The dataset contains two comma-separated files (CSV) describing the phenotype of each individual used in the quantitative trait loci (QTL) analysis. The genotype data, including the number of SNPs and thier chromosomal locations, progeny file and linkage map, are provided in Shrestha et al. (2023).‘File1.Phenotype_traits.csv’ contains bioenergy traits analyzed using Near-Infrared Reflectance Spectroscopy (NIRS) technique after plants reached to the physiological maturity. The traits include predicted ethanol (ETOH), cellulose, hemicellulose, glucose (GLC), sugar (SUG), klason lignin (KL), ash, p-coumarate esters (PCA), esterified ferulates (FEST), etherified ferulates (FETH), pentose sugars released per gram of dry forage (PENT), the proportion of hexoses that are non-structural or soluble (PSOL), pentose proportion of total carbohydrates (PPEN), theoretical ethanol from hexoses (HEXE), estimated ethanol from non-structural carbohydrates (NSCE), and cell wall ethanol (CWE) data for each genotype. The genotypes were evaluated in two replications at two locations in Tennessee; the Plateau Research and Education Center (PREC), Crossville and East Tennessee Research and Education Center (ETREC), Knoxville in 2020 and 2021. ETOH, cellulose, hemicellulose, GLC, SUG, KL, ash, PCA, FEST, FETH, PENT, HEXE, NSCE, and CWE were measured in mg/g and PSOL and PPEN were measured in %.‘File 2.QTL_phenotype.csv’ provides averaged phenotype information for each genotype derived through the statistical analysis and was used as phenotype data in QTL mapping.

Switchgrass (Panicum virgatum L.) is a potential source for producing bioenergy from lignocellulosic biomass. Many breeding programs focus on the genetic improvement of switchgrass for increasing bioenergy traits. Significant genetic variation for bioenergy traits was observed in lowland switchgrass hybrids (P<0.05). Due to the quantitative inheritance of bioenergy traits, varietal improvement for the trait through conventional methods is slow and challenging. 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 eight hybrid populations (30 to 96 F1s) developed by crossing lowland cultivars, Alamo and Kanlow. The populations were evaluated in a simulated-sward plot with two replications at two locations in Tennessee in 2020 and 2021. The crosses were genotyped using 17,251 single nucleotide polymorphisms generated through genotyping-by-sequencing. QTL mapping was performed across populations using R-QTL. The study identified ten QTL for predicted ethanol, four for cellulose, and three hemicellulose on chromosomes 1K, 1N, 2N, 4N, 5K, 5N, 7K, 8K, 8N, and 9N, respectively, with phenotypic variability ranged from 2.1 to 7.4%.The dataset contains two comma-separated files (CSV) describing the phenotype of each individual used in the quantitative trait loci (QTL) analysis. The genotype data, including the number of SNPs and thier chromosomal locations, progeny file and linkage map, are provided in Shrestha et al. (2023).‘File1.Phenotype_traits.csv’ contains bioenergy traits analyzed using Near-Infrared Reflectance Spectroscopy (NIRS) technique after plants reached to the physiological maturity. The traits include predicted ethanol (ETOH), cellulose, hemicellulose, glucose (GLC), sugar (SUG), klason lignin (KL), ash, p-coumarate esters (PCA), esterified ferulates (FEST), etherified ferulates (FETH), pentose sugars released per gram of dry forage (PENT), the proportion of hexoses that are non-structural or soluble (PSOL), pentose proportion of total carbohydrates (PPEN), theoretical ethanol from hexoses (HEXE), estimated ethanol from non-structural carbohydrates (NSCE), and cell wall ethanol (CWE) data for each genotype. The genotypes were evaluated in two replications at two locations in Tennessee; the Plateau Research and Education Center (PREC), Crossville and East Tennessee Research and Education Center (ETREC), Knoxville in 2020 and 2021. ETOH, cellulose, hemicellulose, GLC, SUG, KL, ash, PCA, FEST, FETH, PENT, HEXE, NSCE, and CWE were measured in mg/g and PSOL and PPEN were measured in %.‘File 2.QTL_phenotype.csv’ provides averaged phenotype information for each genotype derived through the statistical analysis and was used as phenotype data in QTL mapping.

Switchgrass (Panicum virgatum 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. The dataset contains five files describing the phenotype and genotype of each individual used in the quantitative trait loci (QTL) analysis. ‘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. ‘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’. 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’). The progeny file (‘File 4’) contains the name of the parents used for making crosses and their progenies. 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.