ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2013
Identification of bioconversion quantitative trait loci in the interspecific cross Sorghum bicolor × Sorghum propinquum.
Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 14 citations in OpenAlex.
- Crop growth model-enabled genetic mapping of biomass accumulation dynamics in photoperiod-sensitive sorghum.The plant genome · 2025Article
- Genotyping by Sequencing of 393G3 (Bethesda, Md.) · 2018Article
- Genetic complexity of miscanthus cell wall composition and biomass quality for biofuels.BMC genomics · 2017Article
- Redefining Agricultural Residues as Bioenergy Feedstocks.Materials (Basel, Switzerland) · 2016Review
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Authors and funding
6 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
For lignocellulosic bioenergy to be economically viable, genetic improvements must be made in feedstock quality including both biomass total yield and conversion efficiency. Toward this goal, multiple studies have considered candidate genes and discovered quantitative trait loci (QTL) associated with total biomass accumulation and/or grain production in bioenergy grass species including maize and sorghum. However, very little research has been focused on genes associated with increased biomass conversion efficiency. In this study, Trichoderma viride fungal cellulase hydrolysis activity was measured for lignocellulosic biomass (leaf and stem tissue) obtained from individuals in a F5 recombinant inbred Sorghum bicolor × Sorghum propinquum mapping population. A total of 49 QTLs (20 leaf, 29 stem) were associated with enzymatic conversion efficiency. Interestingly, six high-density QTL regions were identified in which four or more QTLs overlapped. In addition to enzymatic conversion efficiency QTLs, two QTLs were identified for biomass crystallinity index, a trait which has been shown to be inversely correlated with conversion efficiency in bioenergy grasses. The identification of these QTLs provides an important step toward identifying specific genes relevant to increasing conversion efficiency of bioenergy feedstocks. DNA markers linked to these QTLs could be useful in marker-assisted breeding programs aimed at increasing overall bioenergy yields concomitant with selection of high total biomass genotypes.
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