Linking circadian time to growth rate quantitatively via carbon metabolism

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Abstract:

      Summary paragraph
      
        Predicting a multicellular organism’s phenotype quantitatively from its genotype is challenging, as genetic effects must propagate up time and length scales. Circadian clocks are intracellular regulators that control temporal gene expression patterns and hence metabolism, physiology and behaviour, from sleep/wake cycles in mammals to flowering in plants
        1–3
        . Clock genes are rarely essential but appropriate alleles can confer a competitive advantage
        4,5
        and have been repeatedly selected during crop domestication
        3,6
        . Here we quantitatively explain and predict canonical phenotypes of circadian timing in a multicellular, model organism. We used metabolic and physiological data to combine and extend mathematical models of rhythmic gene expression, photoperiod-dependent flowering, elongation growth and starch metabolism within a Framework Model for growth of
        Arabidopsis thaliana
        7–9
        . The model predicted the effect of altered circadian timing upon each particular phenotype in clock-mutant plants. Altered night-time metabolism of stored starch accounted for most but not all of the decrease in whole-plant growth rate. Altered mobilisation of a secondary store of organic acids explained the remaining defect. Our results link genotype through specific processes to higher-level phenotypes, formalising our understanding of a subtle, pleiotropic syndrome at the whole-organism level, and validating the systems approach to understand complex traits starting from intracellular circuits.

SEEK ID: https://fairdomhub.org/publications/345

DOI: 10.1101/105437

Projects: Millar group

Publication type: Tech report

Citation: biorxiv;105437v1,[Preprint]

Date Published: 6th Feb 2017

Registered Mode: Not specified

Authors: Yin Hoon Chew, Daniel D. Seaton, Virginie Mengin, Anna Flis, Sam T. Mugford, Alison M. Smith, Mark Stitt, Andrew J Millar

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Andrew Millar

Citation

Chew, Y. H., Seaton, D. D., Mengin, V., Flis, A., Mugford, S. T., George, G. M., Moulin, M., Hume, A., Zeeman, S. C., Fitzpatrick, T. B., Smith, A. M., Stitt, M., & Millar, A. J. (2017). The Arabidopsis Framework Model version 2 predicts the organism-level effects of circadian clock gene mis-regulation. In []. Cold Spring Harbor Laboratory. https://doi.org/10.1101/105437

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Created: 4th Sep 2017 at 11:53

Last updated: 8th Dec 2022 at 17:26

Linking circadian time to growth rate quantitatively via carbon metabolism

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