Arabidopsis thaliana

What is PlaSMo? PlaSMo stands for Plant Systems-biology Modelling Ensuring the achievements of yesterday's Mathematical Modellers will be available for the Systems Biologists of tomorrow.

Our aims

To identify plant mathematical models useful to the UK plant systems biology community, which are currently in a variety of legacy formats and in danger of being lost To represent these models in a declarative XML-based format, which is closer to the systems biology standard SBML To evaluate the behaviour ...

Data project within the CropXR program

Research programme in the Takato Imaizumi lab, with multiple collaborators. Published in Song et al. Nature Plants 2018; Kinmonth-Schultz et al., in silico Plant 2019.

The workshop focuses on the publication, curation, retrieval, and usage of kinetic data from the reaction kinetics database SABIO-RK and on the use of data in modeling. There will be experience reports from scientists who successfully used experimental data to formulate or verify biological hypotheses with the computer, and you will experience how experimental data can be used with computational models.

ZucAt - Sucrose (from german Zucker) translocation in Arabidopsis thaliana. Sucrose translocation between plant tissues is crucial for growth, development and reproduction of plants. Systemic analysis of this metabolic process and underlying regulatory processes can help to achieve better understanding of carbon distribution within the plant and the formation of phenotypic traits. Sucrose translocation from ‘source’ tissues (e.g. mesophyll) to ‘sink’ tissues (e.g. root) is tightly bound to the ...

Andrew Millar's research group, University of Edinburgh

For plants, light is a signal that carries information about the environment, and a source of energy for photosynthesis. PHYTOCAL focuses on the interaction between phytochrome signalling and photosynthesis, and seeks to understand fundamental processes that make carbon (C) and nitrogen (N) resources available for plant growth. These unexplored connections underlie biomass production and plasticity, which contribute significantly to yield variability in the field.

optogenetic control of plant signaling

Collaboration with Miltos Tsiantis for reconstructing RCO transcriptional regulation

improvement of PULSE, derivation of tools for ontogenetic control of interesting pathways

Modulation of light, temperature and time networks using prime editing and mathematical modelling

generation of a toggle switch based on a non-cooperative network

This projects seeks to uncover how phytochrome signalling modulates leaf architecture

How light control development

Research group of Guillaume Lobet

EPSRC project with Exeter, SynthSys and EPCC

EU FP7 collaborative project TiMet, award number 245143. Funded 2010-2015. "TiMet assembles world leaders in experimental and theoretical plant systems biology to advance understanding of the regulatory interactions between the circadian clock and plant metabolism, and their emergent effects on whole-plant growth and productivity."

The multi-compartmental metabolic network of Arabidopsis thaliana was reconstructed and optimized in order to explain growth stoichiometry of the plant both in light and in dark conditions. Balances and turnover of energy (ATP/ADP) and redox (NAD(P)H/NAD(P)) metabolites as well as proton in different compartments were estimated. The model showed that in light conditions, the plastid ATP balance depended on the relationship between fluxes through photorespiration and photosynthesis including both ...

Metabolite analysis in clock mutants: Col-0 parent and mutants gi-201, toc1-101 and prr7prr9; WS parent and lhy/cca1 double mutant. Plants grown in Golm and harvested at End of Day and End of Night, , assays 22 major metabolites. More detail on TiMet wiki if required. Heteroscedastic t-tests to highlight most significant changes, without multiple-testing correction.

Metabolite analysis in clock mutants: Col-0 parent and mutants gi-201, toc1-101 and prr7prr9; WS parent and lhy/cca1 double mutant. Plants grown in Golm and harvested at End of Day and End of Night, , assays 22 major metabolites. More detail on TiMet wiki if required. Heteroscedastic t-tests to highlight most significant changes, without multiple-testing correction.

Metabolite analysis in clock mutants: Col-0 parent and mutants gi-201, toc1-101 and prr7prr9; WS parent and lhy/cca1 double mutant. Plants grown in Golm and harvested at End of Day and End of Night, , assays 22 major metabolites. More detail on TiMet wiki if required. Heteroscedastic t-tests to highlight most significant changes, without multiple-testing correction.

Leaf number at flowering data from literature for prr7 prr9 and Col wild-type plants under long photoperiods and short photoperiods

Leaf number at flowering data from literature for prr7 prr9 and Col wild-type plants under long photoperiods and short photoperiods

Seedling hypocotyl data from literature for prr7 prr9 and Col wild-type plants under various photoperiods

Seedling hypocotyl data from literature for prr7 prr9 and Col wild-type plants under various photoperiods

RNA timeseries data from TiMet for clock genes in prr7 prr9 and Col wild-type plants under 12L:12D cycle and LL

RNA timeseries data from TiMet for clock genes in prr7 prr9 and Col wild-type plants under 12L:12D cycle and LL

RNA timeseries data from TiMet for clock genes in prr7 prr9 and Col wild-type plants under 12L:12D cycle and LL

effects of 1% increase in each parameter, more detailed analysis of water content

correlations of starch mobilisation and fresh weight under single parameter changes

Combination of multiple sub-models to form Framework Model version 2

Comparison of simulated wild-type and prr7prr9 double mutant under 12L:12D cycles. Simulation with CVODE simulator via SBSI v1.5 framework.

Comparison of simulated wild-type and prr7prr9 double mutant under 12L:12D cycles. Simulation with CVODE simulator via SBSI v1.5 framework.

Biomass, leaf number and metabolites in Col0 (WT), prr7, prr7prr9, and lsf1. Metabolite data from plants after 28 days of growth were analysed most (27 days 'end of night', 28 days 'end of day' and 'end of night'). The data file also includes data from 21 days of growth ('end of day' and 'end of night'), which is useful for comparison to early-flowering plants not tested here, such as the lhycca1 double mutant, that flower before 28 days, altering their physiology.

Biomass, leaf number and metabolites in Col0 (WT), prr7, prr7prr9, and lsf1. Metabolite data from plants after 28 days of growth were analysed most (27 days 'end of night', 28 days 'end of day' and 'end of night'). The data file also includes data from 21 days of growth ('end of day' and 'end of night'), which is useful for comparison to early-flowering plants not tested here, such as the lhycca1 double mutant, that flower before 28 days, altering their physiology.

Biomass, leaf number and metabolites in Col0 (WT), prr7, prr7prr9, and lsf1. Metabolite data from plants after 28 days of growth were analysed most (27 days 'end of night', 28 days 'end of day' and 'end of night'). The data file also includes data from 21 days of growth ('end of day' and 'end of night'), which is useful for comparison to early-flowering plants not tested here, such as the lhycca1 double mutant, that flower before 28 days, altering their physiology.

Biomass, leaf number and metabolites in Col0 (WT), prr7, prr7prr9, and lsf1. Metabolite data from plants after 28 days of growth were analysed most (27 days 'end of night', 28 days 'end of day' and 'end of night'). The data file also includes data from 21 days of growth ('end of day' and 'end of night'), which is useful for comparison to early-flowering plants not tested here, such as the lhycca1 double mutant, that flower before 28 days, altering their physiology.

Parameters rescaled and scaling factors set to 1

This is the scaled version of U2020.4 in sbml file. It already contains the scaling factors

Paramters rescaled and scaling factors set to 1

Parameters rescaled and scaling factors set to 1

Derived from U2019.3 from Testing the inferred rate of dynamic, gene regulatory network in absolute units

Sbml version of U2019.4 with reacaling factors values already incoporated in the model. This was generated autmatically using tellurium python package

This file was derived from U2020.3 by introducing the scalig factors in the required locations in the model. This files is used then for numerically rescaling the model for matching synthetic protein data.

A model of the circadian regulation of starch turnover, as published in Seaton, Ebenhoeh, Millar, Pokhilko, "Regulatory principles and experimental approaches to the circadian control of starch turnover", J. Roy. Soc. Interface, 2013. This model is referred to as "Model Variant 2". The other model variants are all available from www.plasmo.ed.ac.uk as stated in the publication. Note that the 'P2011' circadian clock model was modified for this publication (as described), in order to replicate the ...

Matlab model (could not be represented in SBML) from publication with abstract: Clock-regulated pathways coordinate the response of many developmental processes to changes in photoperiod and temperature. We model two of the best-understood clock output pathways in Arabidopsis, which control key regulators of flowering and elongation growth. In flowering, the model predicted regulatory links from the clock to CYCLING DOF FACTOR 1 (CDF1) and FLAVIN-BINDING, KELCH REPEAT, F-BOX 1 (FKF1) transcription. ...

Originally submitted model file for PLaSMo accession ID PLM_1030, version 1

Model derived from U2019.1 in which the transcription rates were rescaled to match the scale of TiMet data set for absolute units of RNA concentration. The gmX scaling parameters in the model were fitted numerically. This model has equivalent dynamics to P2011.1.2.

Model derived from U2020.2, fitted to the TiMet RNA data for wild-type and clock mutants. Fixed parameters are scaling factors, COP1 and cP parameters. The rest of the parameters were left optimisable. The networks used in the fitting include WT, lhycca1, prr79, toc1, gi and ztl. The ztl network was only used for fixing the period in this mutant. Then final parameter values for transcription rates were obtained by taking the product of scaling factor and either transcription or translation, the ...

Model derived from U2020.1 by fitting the scaling factors for matching TiMet data set for wild-type and clock mutants, in absolute units.

Model derived from U2019.1, in which the way the PRR genes are regulated is modified. Repression mechanism introduced Instead of activation between the PRRs for producing the wave of expression. This is inspired in the result of three models P2012, F2014 and F2016. P2012 introduced TOC1 repression in earlier genes relative to its expression. F2014 introduced also the backward repression of PRR9 |-- PRR7 |--- PRR5, TOC1. However little attention was given to why there is a sharper expression ...

Model written in Antimony human-readable language and then translate into SBML using Tellurium

Model written in Antimony human-readable language, Model used in Pokhilko et al 2012

autogenerated equation listing from the SBML of U2020.3, as a .PDF file

autogenerated equation listing from the SBML of U2019.3, as a .PDF file