Linking the gene regulatory network with the functional physical structure of whole-genome engineered Arabidopsis mutants : an HR-MAS NMR-based metabolomics approach

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Linking the gene regulatory network with the functional physical structure of whole-genome engineered Arabidopsis mutants : an HR-MAS NMR-based metabolomics approach

Type: Doctoral Thesis
Title: Linking the gene regulatory network with the functional physical structure of whole-genome engineered Arabidopsis mutants : an HR-MAS NMR-based metabolomics approach
Author: Augustijn, D.
Issue Date: 2018-12-04
Keywords: Arabidopsis thaliana
HR-MAS_NMR
Metabolomics
Systems biology
Abstract: Climate change is a challenge for both current and future generations. New biological resources have to be developed in order to meet the demand for energy as well as the demand for food. One way of doing this is to make use of so-called smart crops, as they have improved yields and a small environmental footprint. Model plant organisms, such as Arabidopsis thaliana, can contribute to the development of smart crops as they have been studied extensively by the research community. The purpose of this research is to unravel the pathways leading to the enhanced growth characteristics phenotype of two phenotypically engineered Arabidopsis mutants from a systems biology perspective, by using metabolomics. In metabolomics, metabolites are studied both qualitatively and quantitively under specific growth conditions. Since metabolites are the end products of cellular processes, the metabolome is most closely related to the phenotype of plants. To obtain the metabolic profile directly from the leaves of Arabidopsis, high-resolution magic angle spinning (HR-MAS) NMR is used. Combined with multivariate analysis, biomarkers, related to the mutant phenotype, are determined. The biological interpretation of the biomarkers will be performed in a systems biology approach to obtain a model to explain the mutant phenotype.
Promotor: Supervisor: Groot H.J.M. de, Alia A.
Faculty: Science
University: Leiden
Uri: urn:isbn:9789463324076
Handle: http://hdl.handle.net/1887/67093
 

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