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

Abstract

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 formore » 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.« less

Authors:
 [1]; ORCiD logo [2]; ORCiD logo [2];  [1];  [3];  [3];  [1]
  1. Univ. of Texas, Austin, TX (United States). Department of Integrative Biology
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States). National Bioenergy Center
  3. USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); HudsonAlpha Institute for Biotechnology, Huntsville, AL (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1424901
Report Number(s):
NREL/JA-2700-71057
Journal ID: ISSN 1754-6834
Grant/Contract Number:
AC36-08GO28308; SC0008451
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Biotechnology for Biofuels
Additional Journal Information:
Journal Volume: 11; Journal Issue: 1; Journal ID: ISSN 1754-6834
Publisher:
BioMed Central
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; Panicum hallii; cell wall composition; QTL; NIRS; lignocellulosic biomass; bioenergy feedstock

Citation Formats

Milano, Elizabeth R., Payne, Courtney E., Wolfrum, Edward J., Lovell, John, Jenkins, Jerry, Schmutz, Jeremy, and Juenger, Thomas E. Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii. United States: N. p., 2018. Web. doi:10.1186/s13068-018-1033-z.
Milano, Elizabeth R., Payne, Courtney E., Wolfrum, Edward J., Lovell, John, Jenkins, Jerry, Schmutz, Jeremy, & Juenger, Thomas E. Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii. United States. doi:10.1186/s13068-018-1033-z.
Milano, Elizabeth R., Payne, Courtney E., Wolfrum, Edward J., Lovell, John, Jenkins, Jerry, Schmutz, Jeremy, and Juenger, Thomas E. Sat . "Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii". United States. doi:10.1186/s13068-018-1033-z. https://www.osti.gov/servlets/purl/1424901.
@article{osti_1424901,
title = {Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii},
author = {Milano, Elizabeth R. and Payne, Courtney E. and Wolfrum, Edward J. and Lovell, John and Jenkins, Jerry and Schmutz, Jeremy and Juenger, Thomas E.},
abstractNote = {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.},
doi = {10.1186/s13068-018-1033-z},
journal = {Biotechnology for Biofuels},
number = 1,
volume = 11,
place = {United States},
year = {Sat Feb 03 00:00:00 EST 2018},
month = {Sat Feb 03 00:00:00 EST 2018}
}

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