Arabidopsis thaliana

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

SMART Plants for Tomorrow’s Needs

Plants enable life on Earth through the conversion of solar energy into chemical energy. Beginning with the Neolithic Revolution, the domestication of plants provided the basis for human population growth and, subsequently, the evolution of highly developed civilizations. However, the growing food demands imposed by an increasing population and the effects of anthropogenic climate change pose huge challenges for sustainable food production and ecosystem maintenance. ...

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

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.

This projects seeks to uncover how phytochrome signalling modulates leaf architecture

How light control development

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.

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 ...

Research group of Guillaume Lobet

Andrew Millar's research group, University of Edinburgh

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 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 ...

Collection of clock models that rescale transcript variables to account for absolute units. The relationship between models is summarised in the attached 'model evolution' document and in more detail in the linked publications (preprint version linked in the Snapshot; publication Urquiza and Millar, In Silico Plants 2021 did not have a DOI when Snapshot was created).

Each model is presented three times, * - without a light:dark cycle, * - with an ISSF (Adams et al. JBR 2012) that is set up for ...

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.

Plant material The same plant material used for transcriptome analysis in (Flis et al., 2016) was the basis of our proteome study. Briefly, Arabidopsis thaliana Col-0 plants were grown on GS 90 soil mixed in a ratio 2:1 (v/v) with vermiculite. Plants were grown for 1 week in a 16 h light (250 μmol m−2 s−1, 20 °C)/8 h dark (6 °C) regime followed by an 8 h light (160 μmol m−2 s−1, 20 °C)/16 h dark (16 °C) regime for one week. Plants were then replanted with five seedlings per pot, transferred for ...

The models in this record were published in Flis et al. Royal Society Open Biology 2015. They will be submitted to Biomodels when we have a PubMed ID for the paper.

Original model: Arabidopsis clock model P2011.1.1 from Pokhilko et al. Mol Syst. Biol. 2012, http://dx.doi.org/10.1038/msb.2012.6

Published version is Biomodels ID 00412, http://www.ebi.ac.uk/compneur-srv/biomodels-main/BIOMD0000000412 Also public in Plasmo as PLM64, with several versions, http://www.plasmo.ed.ac.uk/plasmo/models/model.shtml?accession=PLM64 ...

The models in this record were published in Flis et al. Royal Society Open Biology 2015. They will be submitted to Biomodels when we have a PubMed ID for the paper.

Original model: Arabidopsis clock model P2011.1.1 from Pokhilko et al. Mol Syst. Biol. 2012, http://dx.doi.org/10.1038/msb.2012.6

Published version is Biomodels ID 00412, http://www.ebi.ac.uk/compneur-srv/biomodels-main/BIOMD0000000412 Also public in Plasmo as PLM64, with several versions, http://www.plasmo.ed.ac.uk/plasmo/models/model.shtml?accession=PLM64 ...

This model is termed P2011 and derives from the article: The clock gene circuit in Arabidopsis includes a repressilator with additional feedback loops. Alexandra Pokhilko, Aurora Piñas Fernández, Kieron D Edwards, Megan M Southern, Karen J Halliday & Andrew J Millar Mol. Syst. Biol. 2012; 8: 574, submitted 9 Aug 2011 and published 6 March 2012. Link Link to Supplementary Information, including equations. Minor errors in the published Supplementary Information are described in a file attached ...

Data for Figure 2I-2K in Chew et al. PNAS 2014. Experimental conditions: ∼21.3 °C; 12:12-h light/dark cycle; light intensity, 110 μmol·m−2·s−1;mean daytime CO2 level, 375 ppm. The error bars show the SEs of five plants Further detail on the experimental conditions is contained in the public record on the BioDare resource, link to follow

Data for Figure 3G and Supplementary Figure 4, including gas exchange measurements and photo of the experimental setup. The 'Summary' sheets in the XLSX files often include published graphs. Simulation data are included from FMv1.

These data were acquired in a separate experiment from the biomass, in March 2013. Replication of the earlier biomass study was imperfect, as some plants became a little dry when watering was controlled to reduce moss growth. Sufficient plants grew strongly to measure ...

Data for Figure 3G and Supplementary Figure 4, including gas exchange measurements and photo of the experimental setup. The 'Summary' sheets in the XLSX files often include published graphs. Simulation data are included from FMv1.

These data were acquired in a separate experiment from the biomass, in March 2013. Replication of the earlier biomass study was imperfect, as some plants became a little dry when watering was controlled to reduce moss growth. Sufficient plants grew strongly to measure ...

Data for Figure 3A-3F and Supplementary Figures 2, 3, and 6, including leaf number, biomass and leaf areas. Image data for leaf areas are included in a .ZIP archive. The 'Summary' sheets in the XLSX files often include published graphs. Simulation data are included from FMv1. These data were acquired in June 2012. Experimental conditions: ~22C constant temperature; 12:12-h light/dark cycle; light intensity = 130 μmol·m−2·s−1; average daytime CO2 concentration = 375 ppm. 10 plants per genotype per ...

Data for Figure 3A-3F and Supplementary Figures 2, 3, and 6, including leaf number, biomass and leaf areas. Image data for leaf areas are included in a .ZIP archive. The 'Summary' sheets in the XLSX files often include published graphs. Simulation data are included from FMv1. These data were acquired in June 2012. Experimental conditions: ~22C constant temperature; 12:12-h light/dark cycle; light intensity = 130 μmol·m−2·s−1; average daytime CO2 concentration = 375 ppm. 10 plants per genotype per ...

Data for Figures 5D-5F and Supplementary Figure 7B, 7C, including biomass and leaf areas. Image data for leaf areas are included in a .ZIP archive, with two samples as published in 5D. The 'Summary' sheets in the XLSX files include published graphs. Simulation data are included from FMv1. These data were acquired in April 2014, in a separate experiment from the La(er) and Fei-0. Experimental conditions: ∼20.7 °C constant temperature; 12h:12h light/dark cycle; light intensity = 100μmol·m−2·s−1; ...

Data for Figures 5D-5F and Supplementary Figure 7B, 7C, including biomass and leaf areas. Image data for leaf areas are included in a .ZIP archive, with two samples as published in 5D. The 'Summary' sheets in the XLSX files include published graphs. Simulation data are included from FMv1. These data were acquired in April 2014, in a separate experiment from the La(er) and Fei-0. Experimental conditions: ∼20.7 °C constant temperature; 12h:12h light/dark cycle; light intensity = 100μmol·m−2·s−1; ...

Data for Figure 4, from the prior publication of Sulpice et al. Mol. Plant 2014: Biomass, net growth and starch levels at end of day and end of night, under light:dark cycles of 4:20, 6:18, 8:16, 12:12 and 18:6 hours.

These Python scripts define and simulate the translational coincidence model. This model takes measured transcript dynamics (Blasing et al, 2005) in 12L:12D, measured synthesis rates of protein in light compared to dark (Pal et al, 2013), and outputs predicted changes in protein abundance between short (6h) and long (18h) photoperiods. These are compared to the photoperiod proteomics dataset we generated.

Transcript profiling by microarray in 4, 6, 8, 12 and 18 h photoperiods, originally published in Flis et al, 2016, Photoperiod-dependent changes in the phase of core clock transcripts and global transcriptional outputs at dawn and dusk in Arabidopsis. doi: 10.1111/pce.12754.

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 ...

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

U2019.3 that simulates light condition with ISSF

U2020.2 that simulates light condition with ISSF

U2019.1 that simulates light condition with ISSF

U2019.3 that simulates light condition with ISSF

U2019.2 that simulates light condition with ISSF

U2019.1 that simulates light condition with ISSF