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A systems biology approach to modelling tea (Camellia sinensis)
BMC Systems Biology volume 1, Article number: P13 (2007)
Tea manufacture induces a variety of stresses that affect tea quality. We are using microarray data to track transcriptional changes occurring during wounding and withering of the leaves to identify metabolic pathways that could influence tea aroma and flavour. Current transcriptomic approaches include the use of a partial, tea-specific array. In order to monitor a larger number of genes we have performed cross-species analyses using Affymetrix Arabidopsis genome arrays . Arabidopsis metabolic SBML  network data from AraCyc , KEGG and Reactome were collated and merged, then subsequently overlaid with the tea expression data. Subnetworks were constructed by connecting the shortest paths between the differentially expressed genes and the downstream aroma-related compounds, therefore identifying the pathways involved in aroma.
We present the initial output of this project and address how cross-species expression data can be used to colour a network and analysed using a variety of subgraph analyses.
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Many thanks to the NASC Arrays X-species Service, Peter Clarke, Shao Chih Kuo and Thomas Spriggs for their help throughout the project.
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Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Marshall, A., Gollapudi, S., de Silva, J. et al. A systems biology approach to modelling tea (Camellia sinensis). BMC Syst Biol 1 (Suppl 1), P13 (2007). https://doi.org/10.1186/1752-0509-1-S1-P13
- Short Path
- Expression Data
- Microarray Data
- System Biology
- Network Data