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A systems biology approach to modelling tea (Camellia sinensis)

Abstract

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 [1]. Arabidopsis metabolic SBML [2] network data from AraCyc [3], 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.

Conclusion

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.

Figure 1
figure 1

This figure shows Cytoscape [4] layouts of (a) the merged AraCyc, KEGG and Reactome network, (b) the AraCyc metabolic network with gene identifiers, (c) the subgraph extracted based on the tea wounding and withering expression data [identified by green nodes] connected to tea aroma related compounds [identified by red nodes].

References

  1. Hammond JP, Broadley MR, Craigon DJ, Higgins J, Emmerson ZF, Townsend HJ, White PJ, May ST: Using genomic DNA-based probe-selection to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species. Plant Methods. 2005, 1:

    Google Scholar 

  2. Hucka M, Finney A, Sauro HM, Bolouri H, Doyle JC, Kitano H, Arkin AP, Bornstein BJ, Bray D, Cornish-Bowden A: The Systems Biology Markup Language (SBML): A medium for the representation and exchange of biochemical network models. Bioinformatics. 2003, 19: 524-531. 10.1093/bioinformatics/btg015.

    Article  PubMed  CAS  Google Scholar 

  3. Mueller LA, Zhang P, Rhee SY: AraCyc: A Biochemical Pathway Database for Arabidopsis. Plant Physiology. 2003, 132: 453-460. 10.1104/pp.102.017236.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  4. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T: Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks. Genome Research. 2003, 13: 2498-2504. 10.1101/gr.1239303.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

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Acknowledgements

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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Correspondence to Alex Marshall.

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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

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  • DOI: https://doi.org/10.1186/1752-0509-1-S1-P13

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