Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii

Milano, Elizabeth R.; Payne, Courtney E.; Wolfrum, Ed; Lovell, John; Jenkins, Jerry; Schmutz, Jeremy; Juenger, Thomas E.

doi:10.1186/s13068-018-1033-z

Title: Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii

Journal Article · Sat Feb 03 00:00:00 EST 2018 · Biotechnology for Biofuels

DOI:https://doi.org/10.1186/s13068-018-1033-z· OSTI ID:1618732

Milano, Elizabeth R.; Payne, Courtney E.; Wolfrum, Ed; Lovell, John; Jenkins, Jerry; Schmutz, Jeremy; Juenger, Thomas E.

Biofuels derived from lignocellulosic plant material are an important component of current renewable energy strategies. Improvement efforts in biofuel feedstock crops have been primarily focused on increasing biomass yield with less consideration for tissue quality or composition. Four primary components found in the plant cell wall contribute to the overall quality of plant tissue and conversion characteristics, cellulose and hemicellulose polysaccharides are the primary targets for fuel conversion, while lignin and ash provide structure and defense. We explore the genetic architecture of tissue characteristics using a quantitative trait loci (QTL) mapping approach in Panicum hallii, a model lignocellulosic grass system. Diversity in the mapping population was generated by crossing xeric and mesic varietals, comparative to northern upland and southern lowland ecotypes in switchgrass. We use near-infrared spectroscopy with a primary analytical method to create a P. hallii specific calibration model to quickly quantify cell wall components.Ash, lignin, glucan, and xylan comprise 68% of total dry biomass in P. hallii: comparable to other feedstocks. We identified 14 QTL and one epistatic interaction across these four cell wall traits and found almost half of the QTL to localize to a single linkage group.Panicum hallii serves as the genomic model for its close relative and emerging biofuel crop, switchgrass (P. virgatum). We used high throughput phenotyping to map genomic regions that impact natural variation in leaf tissue composition. Understanding the genetic architecture of tissue traits in a tractable model grass system will lead to a better understanding of cell wall structure as well as provide genomic resources for bioenergy crop breeding programs.

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Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC0008451; AC02-05CH11231; AC36-08GO28308

OSTI ID:: 1618732

Alternate ID(s):: OSTI ID: 1424901; OSTI ID: 1616056

Report Number(s):: NREL/JA-2700-71057; 25; PII: 1033

Journal Information:: Biotechnology for Biofuels, Journal Name: Biotechnology for Biofuels Vol. 11 Journal Issue: 1; ISSN 1754-6834

Publisher:: BioMed CentralCopyright Statement

Country of Publication:: Netherlands

Language:: English

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Cited by: 7 works

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