The Arabidopsis Framework Model version 2 predicts the organism-level effects of circadian clock gene mis-regulation

Yin Hoon Chew, Daniel D Seaton, Virginie Mengin, Anna Flis, Sam T Mugford, Gavin M George, Michael Moulin, Alastair Hume, Samuel C Zeeman, Teresa B. Fitzpatrick, Alison M. Smith, Mark Stitt, Andrew J Millar

Research output: Contribution to journalArticlepeer-review

Abstract

Predicting a multicellular organism’s phenotype quantitatively from its genotype is challenging, as genetic effects must propagate across scales. Circadian clocks are intracellular regulators that control temporal gene expression patterns and hence metabolism, physiology and behaviour. Here we explain and predict canonical phenotypes of circadian timing in a multicellular, model organism. We used diverse 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 the vegetative growth of Arabidopsis thaliana, sharing the model and data files in a structured, public resource. The calibrated model predicted the effect of altered circadian timing upon each particular phenotype in clock-mutant plants under standard laboratory conditions. Altered night-time metabolism of stored starch accounted for most of the decrease in whole-plant biomass, as previously proposed. Mobilisation of a secondary store of malate and fumarate was also mis-regulated, accounting for any remaining biomass defect. The three candidate mechanisms tested did not explain this organic acid accumulation. 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.
Original languageEnglish
Article numberdiac010
Number of pages15
JournalIn Silico Plants
Volume4
Issue number2
DOIs
Publication statusPublished - 30 May 2022

Keywords

  • photosynthesis
  • gene regulatory network
  • metabolism
  • genotype to phenotype
  • mathematical model
  • open research
  • data sharing

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