Millar group

Click on Snapshot 2 to download data, models and analysis for Daniel Seaton et al.
biorXiv 2017 https://doi.org/10.1101/182071 and
Molecular Systems Biology, accepted Jan 2018, https://doi.org/10.15252/msb.20177962.
Note that the published paper cannot be fully linked into this record as the DOI above was not live when we made the Research Object from this Investigation on FAIRDOMHub.

Data, models and simulations for the Chew et al. 2014 paper (PNAS, https://doi.org/10.1073/pnas.1410238111), using wild-type Arabidopsis ecotype Col-0 in standard 12hL:12hD growth conditions, compared to La(er) or Fei-0 accessions, or to plants overexpressing a micro RNA (miR156).

Data, models and simulations for the Chew et al. 2017 paper (bioRxiv https://doi.org/10.1101/105437 ), mostly on the prr7 prr9 double mutant, with controls in lsf1 and prr7 single mutants.

Altering the light:dark cycle of standard growth conditions and standard 'wild-type' Arabidopsis accession, with sucrose, starch and biomass data for whole rosettes

Standard growth conditions and standard 'wild-type' Arabidopsis accession, with biomass data for whole rosettes, and in some cases, individual leaf area and leaf biomass data

Standard growth conditions and 'wild-type' Arabidopsis accessions other than Col-0 and the 35S:miR156 transgenics, with biomass data for whole rosettes, and in some cases, individual leaf area and leaf biomass data

The FMv1 was constructed from 4 existing models, with Matlab and Simile versions.

Literature data used in the Seaton et al. 2017 study; data processing by Daniel Seaton.

Experimental data reported in the Seaton et al. 2017 study; data processing by Alex Graf. Part of the EU FP7 TiMet project.

Literature data and associated scripts analysed in the Seaton et al. 2017 study; data processing by Daniel Seaton.

Data analysis and modelling scripts and results for the Seaton et al. 2017 study, from Daniel Seaton.

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
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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
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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;
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In future we should split these versions into separate Assays, and link to the four, original component models, when they are imported with the PlaSMo resource into FairdomHub (expected late 2018)

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.

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
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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

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
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Framework Model for Arabidopsis vegetative growth, version 2 (FMv2), as described in Chew et al. bioRxiv 2017 (https://doi.org/10.1101/105437; please see linked Article file).

The FMv2 model record on FAIRDOMHub has the following versions, which represent the same FMv2 model:
Version 1 is an archive of the github repository of MATLAB code for the Framework Model v2, downloaded from https://github.com/danielseaton/frameworkmodel on 06/02/17. This version was not licensed for further use and was
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Exactly the same as model 243, but uploaded as a file rather than copied from PlaSMo.

This version is P2011.1.2, model ID PLM_71 version 1. Dynamics identical to P2011.1.1 of the Pokhilko et al. 2012 publication.

http://www.plasmo.ed.ac.uk/plasmo/models/download.shtml?accession=PLM_71&version=1

Python scripts to run the analysis estimating rates of protein synthesis in the light and dark, and overall rates of protein turnover, in Cyanothece and Ostrecoccus tauri.

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Outline report of joint research conducted during MSBnet-funded visit of Sanu Shameer to Millar lab