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

Author

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  • Grzegorczyk Marco

    (Johann Bernoulli Institute (JBI), Faculteit Wiskunde en Natuurwetenschappen (FWN), Groningen University, Nijenborgh 9, Postbus 407, 9747 AG Groningen 9700 AK, The Netherlands)

  • Aderhold Andrej

    (School of Mathematics and Statistics, University of Glasgow, 15 University Gardens, Glasgow G12 8QW, UK)

  • Husmeier Dirk

    (School of Mathematics and Statistics, University of Glasgow, 15 University Gardens, Glasgow G12 8QW, UK)

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.

Suggested Citation

  • Grzegorczyk Marco & Aderhold Andrej & Husmeier Dirk, 2015. "Inferring bi-directional interactions between circadian clock genes and metabolism with model ensembles," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(2), pages 143-167, April.
    • Handle: RePEc:bpj:sagmbi:v:14:y:2015:i:2:p:143-167:n:3
    DOI: 10.1515/sagmb-2014-0041
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    References listed on IDEAS

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    1. Michael J. Haydon & Olga Mielczarek & Fiona C. Robertson & Katharine E. Hubbard & Alex A. R. Webb, 2013. "Photosynthetic entrainment of the Arabidopsis thaliana circadian clock," Nature, Nature, vol. 502(7473), pages 689-692, October.
    2. Grzegorczyk Marco & Husmeier Dirk, 2012. "A Non-Homogeneous Dynamic Bayesian Network with Sequentially Coupled Interaction Parameters for Applications in Systems and Synthetic Biology," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(4), pages 1-62, July.
    3. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
    4. Schäfer Juliane & Strimmer Korbinian, 2005. "A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 4(1), pages 1-32, November.
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