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

Chew, Y. H., Seaton, D. D., Mengin, V., Flis, A., Mugford, S. T., George, G. M., et al. (2022). The Arabidopsis Framework Model version 2 predicts the organism-level effects of circadian clock gene mis-regulation. in silico Plants, 4(2): diac010. doi:10.1093/insilicoplants/diac010.

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 Creators:
Chew, Yin Hoon1, Author
Seaton, Daniel D1, Author
Mengin, V.2, Author              
Flis, A.2, Author              
Mugford, Sam T1, Author
George, Gavin M1, Author
Moulin, Michael1, Author
Hume, Alastair1, Author
Zeeman, Samuel C1, Author
Fitzpatrick, Teresa B1, Author
Smith, Alison M1, Author
Stitt, M.2, Author              
Millar, Andrew J1, Author
Affiliations:
1external, ou_persistent22              
2System Regulation, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753327              

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 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.

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Language(s): eng - English
 Dates: 2022-05-302022-07-22
 Publication Status: Published in print
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 Identifiers: DOI: 10.1093/insilicoplants/diac010
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Title: in silico Plants
  Alternative Title : in silico Plants
Source Genre: Journal
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Pages: - Volume / Issue: 4 (2) Sequence Number: diac010 Start / End Page: - Identifier: ISBN: 2517-5025