INVESTIGATORS: Bartley, L.E., Wu, Y., Brummer, E.C., Saha, M.
INSTITUTIONS: University of Oklahoma, Oklahoma State University, Samuel Roberts Noble Foundation
NON-TECHNICAL SUMMARY: The goal of this project is to identify natural switchgrass genetic variation that correlates with extreme lignocellulose qualities. Lignocellulose is the material the makes up most of the dry mass of plant leaves, stems, and roots. Such material is being targeted for conversion into biofuel due to its abundance and potential for sustainable production. Switchgrass is an attractive species for development as a biofuel crop as it can grow to a large size and tolerate drought and other stresses. Lignocellulose qualities critically impact the efficiency of conversion of lignocellulose into biofuels, both through so-called biological conversion processes and, to an extent, through thermochemical conversion processes.
OBJECTIVES: (1) Identify grass genes that may control lignocellulose-to-biofuel conversion quality and variants (so-called single nucleotide polymorphisms or SNPs) in those genes within 36 diverse, lowland switchgrass accessions, or families. (2) Measure the association between the identified SNPs and lignocellulose quality in a larger collection made from the 36 accessions. (3) Determine if the identified significant SNP-biomass quality associations also hold in two additional, independent switchgrass populations, representing 110 accessions. This will lead to the identification of switchgrass plants with superior lignocellulose quality for immediate use in breeding programs and SNP markers that may be used to rapidly screen other grass populations for similar traits. (4) Test the functions of selected genes to obtain insight into the genetic control of lignocellulose composition for further biomass improvement.
APPROACH: The objectives will be accomplished through an innovative combination of gene network analysis and advanced breeding techniques, as follows: (1) Gene networks from the reference grass, rice, and other data will be used to identify candidate control genes. The DNA for these genes will be captured from diverse switchgrass plants and sequenced to identify SNPs. (2 and 3) In the larger populations, lignocellulose quality will be rapidly determined based on light absorption (NIRS) and wet lab analyses. Selected SNPs will be detected with a method that handles the genomic complexity of switchgrass. These data sets will be subject to statistical association analysis. (4) The functions of possible lignocellulose control genes will be tested in reference grasses with mutants with increased and decreased gene expression.
Name: Bartley, L.E.
Related BER Research Highlights