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Batch process strategy for analysing metabolic variation controlling the growth process of hybrid aspen
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Science and Technology, Department of Chemistry.
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2005 (English)Conference proceedings (editor) (Other (popular science, discussion, etc.))
Abstract [en]

High resolution magic angle spinning proton nuclear magnetic resonance spectroscopy, {1}H HR/MAS NMR, and multivariate data analysis using batch processing, BP, was applied for the analysis of two different genotypes of poplar tree (Populus tremula L. x tremuloides Michx.), containing an antisense construct of PttMYB76 and control (wild type). A gene encoding a MYB transcription factor, with unknown function, PttMYB76, was selected from a cambial EST library of poplar tree (Populus tremula L. x remuloides Michx.) for metabonomic characterisation. The PttMYB76 gene is believed to affect different paths of the phenyl propanoid synthetic pathway. This pathway leads to the formation of S- and G-lignin, flavonoids and sinapate esters. Milled poplar samples collected at the internodes of the tree were analysed using {1}H high resolution magic angle spinning NMR spectroscopy. The application of multivariate batch processing of the NMR results revealed a growth-related gradient in the plant internode direction as well as the discrimination between the trees with down regulated PttMYB76 expression and wild type populations. This paper is focused on the potential of a new analytical multivariate approach for analysing time-related plant metabonomic data. The techniques used could, with the aid of suitable model compounds, be of high relevance to the detection and understanding of the different lignification processes within the two types of poplar tree. Additionally, the findings are highlighting the importance of applying robust and organised multivariate data analysis approaches to facilitate modelling and interpretation of complex biological data sets.

Place, publisher, year, edition, pages
2005. , 8 p.
National Category
Chemical Sciences
URN: urn:nbn:se:umu:diva-20680ISBN: 0958554897OAI: diva2:209301

59th Appita Annual Conference and Exhibition: Incorporating the 13th ISWFPC (International Symposium on Wood, Fibre and Pulping Chemistry), Auckland, New Zealand, 16-19 May 2005: Proceedings; volume 2, sid 195-202

Available from: 2009-03-24 Created: 2009-03-24 Last updated: 2016-08-15Bibliographically approved

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Edlund, UlfWiklund, SusanneAntti, Henrik
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