Inferring bi-directional interactions between circadian clock genes and metabolism with model ensembles

Marco Grzegorczyk*, Andrej Aderhold, Dirk Husmeier

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)

Abstract

There has been much interest in reconstructing bi-directional regulatory networks linking the circadian clock to metabolism in plants. A variety of reverse engineering methods from machine learning and computational statistics have been proposed and evaluated. The emphasis of the present paper is on combining models in a model ensemble to boost the network reconstruction accuracy, and to explore various model combination strategies to maximize the improvement. Our results demonstrate that a rich ensemble of predictors outperforms the best individual model, even if the ensemble includes poor predictors with inferior individual reconstruction accuracy. For our application to metabolomic and transcriptomic time series from various mutagenesis plants grown in different light-dark cycles we also show how to determine the optimal time lag between interactions, and we identify significant interactions with a randomization test. Our study predicts new statistically significant interactions between circadian clock genes and metabolites in Arabidopsis thaliana, and thus provides independent statistical evidence that the regulation of metabolism by the circadian clock is not uni-directional, but that there is a statistically significant feedback mechanism aiming from metabolism back to the circadian clock.

Original languageEnglish
Pages (from-to)143-167
Number of pages25
JournalStatistical applications in genetics and molecular biology
Volume14
Issue number2
DOIs
Publication statusPublished - Apr-2015

Keywords

  • circadian clock
  • determination of time delays
  • model ensembles
  • plant metabolism
  • regulatory network inference
  • REGULATORY NETWORKS
  • ARABIDOPSIS-THALIANA
  • BAYESIAN NETWORKS
  • EXPRESSION DATA
  • INFERENCE
  • COMPONENTS
  • SHRINKAGE
  • ELF4
  • LOOP

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