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Transcript and Metabolite Profiling for the Evaluation of Tobacco Tree and Poplar as Feedstock for the Bio-based Industry
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2014 (English)In: Journal of Visualized Experiments, ISSN 1940-087X, E-ISSN 1940-087X, no 87, e51393- p.Article in journal (Refereed) Published
Abstract [en]

The global demand for food, feed, energy and water poses extraordinary challenges for future generations. It is evident that robust platforms for the exploration of renewable resources are necessary to overcome these challenges. Within the multinational framework MultiBioPro we are developing biorefinery pipelines to maximize the use of plant biomass. More specifically, we use poplar and tobacco tree (Nicotiana glauca) as target crop species for improving saccharification, isoprenoid, long chain hydrocarbon contents, fiber quality, and suberin and lignin contents. The methods used to obtain these outputs include GC-MS, LC-MS and RNA sequencing platforms. The metabolite pipelines are well established tools to generate these types of data, but also have the limitations in that only well characterized metabolites can be used. The deep sequencing will allow us to include all transcripts present during the developmental stages of the tobacco tree leaf, but has to be mapped back to the sequence of Nicotiana tabacum. With these set-ups, we aim at a basic understanding for underlying processes and at establishing an industrial framework to exploit the outcomes. In a more long term perspective, we believe that data generated here will provide means for a sustainable biorefinery process using poplar and tobacco tree as raw material. To date the basal level of metabolites in the samples have been analyzed and the protocols utilized are provided in this article.

Place, publisher, year, edition, pages
2014. no 87, e51393- p.
Keyword [en]
Environmental Sciences, Issue 87, botany, plants, Biorefining, Poplar, Tobacco tree, Arabidopsis, suberin, lignin, cell walls, biomass, long-chain hydrocarbons, isoprenoids, Nicotiana glauca, systems biology
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:kth:diva-160772DOI: 10.3791/51393ISI: 000348905400043OAI: oai:DiVA.org:kth-160772DiVA: diva2:792142
Funder
EU, FP7, Seventh Framework Programme, 311804
Note

QC 20150303

Available from: 2015-03-03 Created: 2015-02-27 Last updated: 2017-12-04Bibliographically approved

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