Crossfit analysis: a novel method to characterize the dynamics of induced plant responses

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• 作者：Jeroen J Jansen (1)
  Nicole M van Dam (2)
  Huub CJ Hoefsloot (1)
  Age K Smilde (1)
  
• 刊名：BMC Bioinformatics
• 出版年：2009
• 出版时间：December 2009
• 年：2009
• 卷：10
• 期：1
• 全文大小：1226KB
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• 作者单位：Jeroen J Jansen (1)
  Nicole M van Dam (2)
  Huub CJ Hoefsloot (1)
  Age K Smilde (1)
  
  1. Biosystems Data Analysis, Swammerdam Institute for Life Sciences, Faculty of Sciences, Universiteit van Amsterdam, Nieuwe Achtergracht 166, 1018 WV, Amsterdam, The Netherlands
  2. Department of Multitrophic Interactions, Centre for Terrestrial Ecology, Netherlands Institute for Ecology, P.O. Box 40, 6666 ZG, Heteren, The Netherlands
  
• ISSN：1471-2105

文摘

Background Many plant species show induced responses that protect them against exogenous attacks. These responses involve the production of many different bioactive compounds. Plant species belonging to the Brassicaceae family produce defensive glucosinolates, which may greatly influence their favorable nutritional properties for humans. Each responding compound may have its own dynamic profile and metabolic relationships with other compounds. The chemical background of the induced response is therefore highly complex and may therefore not reveal all the properties of the response in any single model. Results This study therefore aims to describe the dynamics of the glucosinolate response, measured at three time points after induction in a feral Brassica, by a three-faceted approach, based on Principal Component Analysis. First the large-scale aspects of the response are described in a 'global model' and then each time-point in the experiment is individually described in 'local models' that focus on phenomena that occur at specific moments in time. Although each local model describes the variation among the plants at one time-point as well as possible, the response dynamics are lost. Therefore a novel method called the 'Crossfit' is described that links the local models of different time-points to each other. Conclusions Each element of the described analysis approach reveals different aspects of the response. The crossfit shows that smaller dynamic changes may occur in the response that are overlooked by global models, as illustrated by the analysis of a metabolic profiling dataset of the same samples.