Data files

Experimental data for Laurel and Hardy 2, in MATLAB binary format.

Model analysis results in binary Matlab format

Mean and SD data for metabolites and biomass, along with metadata used to simulate this experiment.

Complete excel spradsheets for Laurel and Hardy 2, including data for the pgm mutant that were not analysed in the Chew et al. 2017 preprint/publication. Data include fresh and dry biomass, gas exchange, leaf numbers and metabolites in Col0 (WT), prr7prr9, pgm and lsf1 plants. Metabolite data are from plants after 27 days of growth (end of night) and 28 days (end of day and end of night).

RNA levels for control amplicons and multiple clock genes in 2 WT (Col, Ws) and 5 clock mutants of Arabidopsis, in biological duplicates, from three conditions: Diurnal cycle (12L/12D), Extended night (DD), Extended light (LL), harvested every 2 hours. Numbers are in transcript copy per cell, obtained assuming 1 g FW contains 25000000 cells. Comments: Data from LD are concateneted with DD and LL for better visualization. Toc1-101 (col-0) gi-201 (col-0) prr7-3 prr9-1 (col-0) , lhy cca1 (ws) elf3-4 ...

for Chew, Seaton et al. paper Figure 1

For Chew, Seaton et al. Figure 1

Excel spreadsheet with data and simulations used to prepare figures for publication, see Metadata sheet for conditions. Data Fresh (not dry) rosette leaf biomass, measured in samples of 5 plants each on multiple days, as mean and SD; Simulation outputs from FMv2 for Col Wild Type plants, lsf1, and two simulations for prr7prr9 where the mutation affects only starch degradation or both starch degradation and malate/fumarate store mobilisation.

Starch levels in carbon units (not C6) measured on on ...

Experimental data, in MATLAB binary file format.

Model simulation data for Laurel and Hardy 1, in MATLAB binary format.

Biomass and metabolite data for Laurel and Hardy 1.

SD values of clock gene RNA data in absolute units of RNA copies per cell (calculated from copies per gFW, / 25 million cells/gFW) from TiMet WP1.1, RNA dataset ros (from rosettes). Note the Col data are from WP1.1, not substituted with Col from the LD12:12 of the WP1.2 photoperiod data set, as they were in Flis et al. 2015. Note also that cL_m in these data is taken from CCA1 only, not the average of CCA1 and LHY as in the data sets used for optimisation of P2011.2.1 in Flis et al. 2015.

The ...

Mean values of clock gene RNA data in absolute units of RNA copies per cell (calculated from copies per gFW, / 25 million cells/gFW) from TiMet WP1.1, RNA dataset ros (from rosettes). Note the Col data are from WP1.1, not substituted with Col from the LD12:12 of the WP1.2 photoperiod data set, as they were in Flis et al. 2015. Note also that cL_m in these data is taken from CCA1 only, not the average of CCA1 and LHY as in the data sets used for optimisation of P2011.2.1 in Flis et al. 2015.

The ...

Data for Figs. 2I, 2J, 2K in Chew et al. PNAS 2014 Fresh biomass, dry biomass (i.e. after baking out all water), SLA - specific leaf area (area per g)

The same data are available on the BioDare resource, with additional experimental meta data on growth conditions. BioDare ID 13790828881028, title "Physiology experiment using Col", the direct link is: https://www.biodare.ed.ac.uk/robust/ShowExperiment.action?experimentId=13790828881028

Data for Figs. 3D, 3E in Chew et al. PNAS 2014 Fresh biomass, dry biomass (i.e. after baking out all water), SLA - specific leaf area (area per g) Also FMv1 model simulation results.

The same data are available on the BioDare resource, with additional experimental meta data on growth conditions. BioDare ID 13790837647786, title "Physiology experiment using Fei", the direct link is: https://www.biodare.ed.ac.uk/robust/ShowExperiment.action?experimentId=13790837647786

Data for Figs. 3A, 3B in Chew et al. PNAS 2014 Fresh biomass, dry biomass (i.e. after baking out all water), SLA - specific leaf area (area per g)

Also contains model simulation data from the FMv1 The same data are available, with additional experimental meta data on growth conditions, from the BioDare resource: BioDare experiment 13790834110003; title "Physiology experiment using Ler", the direct link is: https://www.biodare.ed.ac.uk/robust/ShowExperiment.action?experimentId=13790834110003

Intact rosette is pictured, with plant number and genotype in handwritten labels, and ruler for scale. Then dissected leaves are organised in sequence of age, if necessary with small cuts to let them lie flat. Areas are then measured in image processing.

Data for Figs 3C, 3F and Supp 2 in Chew et al. PNAS 2014 Leaf number of the growing rosettes, from 4 to 37 days after sowing (DAS). Data and also results of FMv1 model simulations. Note that Fei-0 was previously tested by Mendez-Vigo et al, suggesting this line had a higher leaf appearance rate. We suggested that its larger final leaf number was more likely due to faster germination.

binary data file from "Hobo" environment multi-sensor + data logger, located next to the plants used in the experiment. Usually read in HOBOware software, free from Onsetcomp.com. Useful temperature record. Though light levels can usefully show changes they are not well calibrated.

Fig 5D

Figure 5D

Data for Fig. Supp 7B in Chew et al. PNAS 2014 Leaf number of the growing rosettes, from 5 to 37 days after sowing. Data and also results of three FMv1 model simulations, with default, fitted and linear (i.e. no juvenile-adult transition in phyllochron)

Data for Figs. 5D, 5E and Supp 7C in Chew et al. PNAS 2014 FW - fresh weight DW - dry weight (i.e. after baking out all water) SLA - specific leaf area (area per g mass), indicates leaf thickness Indiv, data for individual leaves rather than rosette

Experiment conducted in early April 2014 Intact rosette is pictured, with plant number and genotype in handwritten labels, and ruler for scale. Then dissected leaves are organised in sequence of age, if necessary with small cuts to let them lie flat.

Areas are then measured in image processing.

Supplementary information file from Chew et al. PNAS 2014, including full model description for Arabidopsis Framework Model v1, model simulations and experimental validations.

Microarray data at end of day (ED) and end of night (EN) in 4, 6, 8, 12, and 18h photoperiods.

Mean and standard deviation of protein abundances in 6h, 8h, 12h, and 18h photoperiods.

Results of the statistical analysis, identifying proteins that change in abundance significantly across photoperiods.