QTL mapping identifies significant bioenergy trait variation in lowland switchgrass hybrids, suggesting future breeding strategies.
Switchgrass ( Panicum virgatum L.) is a potential source of producing bioenergy from lignocellulosic biomass. Bioenergy traits are quantitatively inherited. This study localized variation in bioenergy traits estimated via near infrared spectroscopy using quantitative trait loci (QTL) mapping. Eight hybrid populations (30 to 96 F1s) developed by crossing lowland cultivars, Alamo and Kanlow, were evaluated in two environments in Tennessee using a randomized complete block design with two replications per location in 2020 and 2021. The hybrid populations exhibited significant variation for all the studied traits ( p ≤ 0.05). A linkage map including 17,251 single nucleotide polymorphisms (SNPs) generated through genotype‐by‐sequencing was used for the QTL mapping. The QTL analyses were performed on the traits across populations in each and across environments (years and locations) and detected a total of 74 significant QTL peaks with the logarithm of odds (LOD) scores ranging from 3.0 to 6.9. Phenotypic variability explained (PVE) by QTL varied from 2.1% to 7.4%. Ten QTL for predicted ethanol yield were identified on chromosomes 4N, 5K, 5N, 8K, 8N, and 9N, respectively, in which the major QTL resided on chromosome 5N with the highest PVE value (7.4%). Four cellulose and three hemicellulose QTL were identified on chromosomes 1K, 1N, 2N, 5K, 5N, 7K, and 8N, with PVE ranging from 2.1% to 5.8%. The chromosomal regions of 1N, 4K, 5N, and 7K had pleiotropic effects affecting multiple bioenergy traits. SNPs linked to QTL will be useful for improving bioenergy traits through marker‐assisted breeding.
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Shrestha et al. (2025) studied this question.
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