Composition of Framework Model FMv1.5
Millar group, Regulation of flowering time in natural conditions, PlaSMo model repository

Model files for FMv1.5. The model is based on FMv1 of Chew et al. PNAS 2014, which is also in FAIRDOMHub and linked to the Model record as an 'Attribution'. FMv1 was extended in this work by Hannah Kinmonth-Schultz and Daniel Seaton, in Matlab.

Submitter: Andrew Millar

Biological problem addressed: Model Analysis Type

Investigation: Temperature effects on Arabidopsis floral induc...

Study: Construction of the Framework Model v1.5

framework model v1_5
Regulation of flowering time in natural conditions

Model associated with the following:

Hannah A Kinmonth-Schultz, Melissa J S MacEwen, Daniel D Seaton, Andrew J Millar, Takato Imaizumi, Soo-Hyung Kim, An explanatory model of temperature influence on flowering through whole-plant accumulation of FLOWERING LOCUS T in Arabidopsis thaliana, in silico Plants, Volume 1, Issue 1, 2019, diz006, https://doi.org/10.1093/insilicoplants/diz006

Creator: Hannah Kinmonth-Schultz

Submitter: Hannah Kinmonth-Schultz

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Chew_et_al_2014_Framework_Model version 1, Matlab and Simile
Millar group

This record includes Matlab and Simile format versions of the Arabidopsis Framework Model version 1, FMv1 (Chew et al, PNAS 2014; http://www.pnas.org/content/early/2014/08/27/1410238111), copied from the PlaSMo resource (www.plasmo.ed.ac.uk), PLM_ID=76. The model description is in the Supplementary Materials of the publication, which should be uploaded somewhere here also but I don't see how to do it.

The FMv1 links the following sub-models: 1. Arabidopsis leaf carbohydrate model (Rasse and ...

Creators: Andrew Millar, Yin Hoon Chew

Submitter: Andrew Millar

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An explanatory model of temperature influence on flowering through whole-plant accumulation of FLOWERING LOCUS T in Arabidopsis thaliana
Regulation of flowering time in natural conditions

Abstract (Expand)

We assessed mechanistic temperature influence on flowering by incorporating temperature-responsive flowering mechanisms across developmental age into an existing model. Temperature influences the leaf … production rate as well as expression of FLOWERING LOCUS T (FT), a photoperiodic flowering regulator that is expressed in leaves. The Arabidopsis Framework Model incorporated temperature influence on leaf growth but ignored the consequences of leaf growth on and direct temperature influence of FT expression. We measured FT production in differently aged leaves and modified the model, adding mechanistic temperature influence on FT transcription, and causing whole-plant FT to accumulate with leaf growth. Our simulations suggest that in long days, the developmental stage (leaf number) at which the reproductive transition occurs is influenced by day length and temperature through FT, while temperature influences the rate of leaf production and the time (in days) the transition occurs. Further, we demonstrate that FT is mainly produced in the first 10 leaves in the Columbia (Col-0) accession, and that FT accumulation alone cannot explain flowering in conditions in which flowering is delayed. Our simulations supported our hypotheses that: (i) temperature regulation of FT, accumulated with leaf growth, is a component of thermal time, and (ii) incorporating mechanistic temperature regulation of FT can improve model predictions when temperatures change over time.

Authors: Hannah A Kinmonth-Schultz, Melissa J S MacEwen, Daniel D Seaton, Andrew J Millar, Takato Imaizumi, Soo-Hyung Kim

Date Published: 2019

Publication Type: Journal

Mechanistic model of temperature influence on flowering through whole-plant accumulation of FT
Regulation of flowering time in natural conditions

Abstract

BioRxiv preprint:

Authors: Hannah A Kinmonth-Schultz, Melissa J MacEwen, Daniel D Seaton, Andrew J Millar, Takato Imaizumi, Soo-Hyung Kim

Date Published: No date defined

Publication Type: Not specified

Linking circadian time to growth rate quantitatively via carbon metabolism
Millar group

Abstract (Expand)

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 plants1-3. Clock genes are rarely essential but appropriate alleles can confer a competitive advantage4,5 and have been repeatedly selected during crop domestication3,6. 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 thaliana7-9. 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 quantitatively 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: No date defined

Publication Type: Not specified

Multiscale digital Arabidopsis predicts individual organ and whole-organism growth
Millar group

Abstract (Expand)

Understanding how dynamic molecular networks affect whole-organism physiology, analogous to mapping genotype to phenotype, remains a key challenge in biology. Quantitative models that represent processes … at multiple scales and link understanding from several research domains can help to tackle this problem. Such integrated models are more common in crop science and ecophysiology than in the research communities that elucidate molecular networks. Several laboratories have modeled particular aspects of growth in Arabidopsis thaliana, but it was unclear whether these existing models could productively be combined. We test this approach by constructing a multiscale model of Arabidopsis rosette growth. Four existing models were integrated with minimal parameter modification (leaf water content and one flowering parameter used measured data). The resulting framework model links genetic regulation and biochemical dynamics to events at the organ and whole-plant levels, helping to understand the combined effects of endogenous and environmental regulators on Arabidopsis growth. The framework model was validated and tested with metabolic, physiological, and biomass data from two laboratories, for five photoperiods, three accessions, and a transgenic line, highlighting the plasticity of plant growth strategies. The model was extended to include stochastic development. Model simulations gave insight into the developmental control of leaf production and provided a quantitative explanation for the pleiotropic developmental phenotype caused by overexpression of miR156, which was an open question. Modular, multiscale models, assembling knowledge from systems biology to ecophysiology, will help to understand and to engineer plant behavior from the genome to the field.

Authors: Y. H. Chew, B. Wenden, A. Flis, V. Mengin, J. Taylor, C. L. Davey, C. Tindal, H. Thomas, H. J. Ougham, P. de Reffye, M. Stitt, M. Williams, R. Muetzelfeldt, K. J. Halliday, A. J. Millar

Date Published: 10th Sep 2014

Publication Type: Not specified

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