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

BACKGROUND: 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 p...

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Autores principales: Milano, Elizabeth R., Payne, Courtney E., Wolfrum, Ed, Lovell, John, Jenkins, Jerry, Schmutz, Jeremy, Juenger, Thomas E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797396/
https://www.ncbi.nlm.nih.gov/pubmed/29434668
http://dx.doi.org/10.1186/s13068-018-1033-z
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author Milano, Elizabeth R.
Payne, Courtney E.
Wolfrum, Ed
Lovell, John
Jenkins, Jerry
Schmutz, Jeremy
Juenger, Thomas E.
author_facet Milano, Elizabeth R.
Payne, Courtney E.
Wolfrum, Ed
Lovell, John
Jenkins, Jerry
Schmutz, Jeremy
Juenger, Thomas E.
author_sort Milano, Elizabeth R.
collection PubMed
description BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13068-018-1033-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-57973962018-02-12 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. Biotechnol Biofuels Research BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13068-018-1033-z) contains supplementary material, which is available to authorized users. BioMed Central 2018-02-03 /pmc/articles/PMC5797396/ /pubmed/29434668 http://dx.doi.org/10.1186/s13068-018-1033-z Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Milano, Elizabeth R.
Payne, Courtney E.
Wolfrum, Ed
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
title Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii
title_full Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii
title_fullStr Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii
title_full_unstemmed Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii
title_short Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii
title_sort quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model c4 perennial grass panicum hallii
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5797396/
https://www.ncbi.nlm.nih.gov/pubmed/29434668
http://dx.doi.org/10.1186/s13068-018-1033-z
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