Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii
Abstract 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...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2018-02-01
|
| Series: | Biotechnology for Biofuels |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13068-018-1033-z |
| _version_ | 1818534783335006208 |
|---|---|
| author | Elizabeth R. Milano Courtney E. Payne Ed Wolfrum John Lovell Jerry Jenkins Jeremy Schmutz Thomas E. Juenger |
| author_facet | Elizabeth R. Milano Courtney E. Payne Ed Wolfrum John Lovell Jerry Jenkins Jeremy Schmutz Thomas E. Juenger |
| author_sort | Elizabeth R. Milano |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-11T18:16:04Z |
| format | Article |
| id | doaj.art-381b44e711294de4a9f3233bc38b1385 |
| institution | Directory Open Access Journal |
| issn | 1754-6834 |
| language | English |
| last_indexed | 2024-12-11T18:16:04Z |
| publishDate | 2018-02-01 |
| publisher | BMC |
| record_format | Article |
| series | Biotechnology for Biofuels |
| spelling | doaj.art-381b44e711294de4a9f3233bc38b13852022-12-22T00:55:25ZengBMCBiotechnology for Biofuels1754-68342018-02-0111111110.1186/s13068-018-1033-zQuantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum halliiElizabeth R. Milano0Courtney E. Payne1Ed Wolfrum2John Lovell3Jerry Jenkins4Jeremy Schmutz5Thomas E. Juenger6Department of Integrative Biology, The University of Texas at AustinNational Bioenergy Center, National Renewable Energy LaboratoryNational Bioenergy Center, National Renewable Energy LaboratoryDepartment of Integrative Biology, The University of Texas at AustinDepartment of Energy Joint Genome InstituteDepartment of Energy Joint Genome InstituteDepartment of Integrative Biology, The University of Texas at AustinAbstract 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.http://link.springer.com/article/10.1186/s13068-018-1033-zPanicum halliiCell wall compositionQTLNIRSLignocellulosic biomassBioenergy feedstock |
| spellingShingle | Elizabeth R. Milano Courtney E. Payne Ed Wolfrum John Lovell Jerry Jenkins Jeremy Schmutz Thomas E. Juenger Quantitative trait loci for cell wall composition traits measured using near-infrared spectroscopy in the model C4 perennial grass Panicum hallii Biotechnology for Biofuels Panicum hallii Cell wall composition QTL NIRS Lignocellulosic biomass Bioenergy feedstock |
| 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 | Panicum hallii Cell wall composition QTL NIRS Lignocellulosic biomass Bioenergy feedstock |
| url | http://link.springer.com/article/10.1186/s13068-018-1033-z |
| work_keys_str_mv | AT elizabethrmilano quantitativetraitlociforcellwallcompositiontraitsmeasuredusingnearinfraredspectroscopyinthemodelc4perennialgrasspanicumhallii AT courtneyepayne quantitativetraitlociforcellwallcompositiontraitsmeasuredusingnearinfraredspectroscopyinthemodelc4perennialgrasspanicumhallii AT edwolfrum quantitativetraitlociforcellwallcompositiontraitsmeasuredusingnearinfraredspectroscopyinthemodelc4perennialgrasspanicumhallii AT johnlovell quantitativetraitlociforcellwallcompositiontraitsmeasuredusingnearinfraredspectroscopyinthemodelc4perennialgrasspanicumhallii AT jerryjenkins quantitativetraitlociforcellwallcompositiontraitsmeasuredusingnearinfraredspectroscopyinthemodelc4perennialgrasspanicumhallii AT jeremyschmutz quantitativetraitlociforcellwallcompositiontraitsmeasuredusingnearinfraredspectroscopyinthemodelc4perennialgrasspanicumhallii AT thomasejuenger quantitativetraitlociforcellwallcompositiontraitsmeasuredusingnearinfraredspectroscopyinthemodelc4perennialgrasspanicumhallii |