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2 Publications visible to you, out of a total of 2
Linking circadian time to growth rate quantitatively via carbon metabolism

Abstract (Expand)

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 …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.

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

Date Published: 6th Feb 2017

Publication Type: Tech report

Defining the robust behaviour of the plant clock gene circuit with absolute RNA timeseries and open infrastructure

Abstract (Expand)

Our understanding of the complex, transcriptional feedback loops in the circadian clock mechanism has depended upon quantitative, timeseries data from disparate sources. We measure clock gene RNA … profiles in Arabidopsis thaliana seedlings, grown with or without exogenous sucrose, or in soil-grown plants and in wild-type and mutant backgrounds. The RNA profiles were strikingly robust across the experimental conditions, so current mathematical models are likely to be broadly applicable in leaf tissue. In addition to providing reference data, unexpected behaviours included co-expression of PRR9 and ELF4, and regulation of PRR5 by GI. Absolute RNA quantification revealed low levels of PRR9 transcripts (peak approx. 50 copies cell(-1)) compared with other clock genes, and threefold higher levels of LHY RNA (more than 1500 copies cell(-1)) than of its close relative CCA1. The data are disseminated from BioDare, an online repository for focused timeseries data, which is expected to benefit mechanistic modelling. One data subset successfully constrained clock gene expression in a complex model, using publicly available software on parallel computers, without expert tuning or programming. We outline the empirical and mathematical justification for data aggregation in understanding highly interconnected, dynamic networks such as the clock, and the observed design constraints on the resources required to make this approach widely accessible.

Authors: A. Flis, A. P. Fernandez, T. Zielinski, V. Mengin, R. Sulpice, K. Stratford, A. Hume, A. Pokhilko, M. M. Southern, D. D. Seaton, H. G. McWatters, M. Stitt, K. J. Halliday, A. J. Millar

Date Published: 16th Oct 2015

Publication Type: Not specified

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