Carbon Availability Transcriptomics
Chlamydomonas reinhardtii CC-1690 was grown in bioreactors. When the cells reached a non-stationary density, the acetate supply was stopped and the medium was kept at 25°C (control) or heated to 35 °C and 40 °C. Additionally to a preheat sample, four further samples were taken as triplicates after 2h, 4h, 8h, and 24h of heat treatment (nopump samples). The samples were analysed with NGS. In Zhang et al 2022 samples were taken at the same time points for 35°C and 40°C but with constant nutrient supply (TAP samples).
Table 1: Sampling schema for Transcriptomics analysis. Three biological replicates were measured. An x indicates triplicates measured at the respective time points.
condition | -18 h (preheat) | 2 h | 4 h | 8 h | 24 h | reference |
---|---|---|---|---|---|---|
25°C TAP | ||||||
35°C TAP | x | x | x | x | x | Zhang et al. 2022 |
40°C TAP | x | x | x | x | x | Zhang et al. 2022 |
25°C nopump | x | x | x | x | x | Zhang et al. 2023 |
35°C nopump | x | x | x | x | x | Zhang et al. 2023 |
40°C nopump | x | x | x | x | x | Zhang et al. 2023 |
Comparative analysis of both experiments were performed within this ARC. These include
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combined normalization
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statistical analysis
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enrichment studies
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visualization of all transcript signals and combined functional terms (Fig. 1)

Figure 1: Example of generated figures. (A) Exemplary visualization of the normalized counts of the HSP70C transcript. A clear separation of the different temperature kinetics is visible. While the initial level is comparable for all time courses after heat onset of 35°C transcript counts increase strongly while the 25°C signal seems constant. Transcript counts in both 40°C experiments decreased during the first 4 hours of treatment. After 8 hours of heat stress the behaviour of temperature-regulated signals change to medium specific effects. Cells living in low-acetate media show distinct reduction of HSP70C transcripts while TAP-samples settle approximately at prior-heat levels. (B) Heatmap representation of (A). (C) Transcript signals that belong to the functional term "intraflagellar transport.IFT particle protein.complex B" are visualized as z-scores. Since there was no measurement for TAP-25°C this panel remains empty (lower left). Because z-scores may distort signals that did not change at all, a ANOVA was performed to separate constant transcript from transcripts that showed differential expression within their time courses. Red shadings indicate a global change of the transcript counts. Blue/grey signals can be considered as constant and have less relevance for the shown kinetics. As seen most transcripts show no response at 25°C but show distinct patterns for 35°C and 40°C respectively. The response shape is solely dependent on the applied temperature and is not influenced by the media the cells are grown in. While for 35°C the transcripts show a strong decrease within the first two hours and a strong increase during the last period, for 40°C samples the transcripts remain constant for the first 2 hours and show no strong increase for the last time point.
References:
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Analysis:
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Benedikt Venn, Lukas Weil, Kevin Schneider, David Zimmer & Timo Mühlhaus. (2022). fslaborg/FSharp.Stats. Zenodo. https://doi.org/10.5281/zenodo.6337056
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Kevin Schneider, Lukas Weil, David Zimmer, Benedikt Venn & Timo Mühlhaus. (2022). CSBiology/BioFSharp. Zenodo. https://doi.org/10.5281/zenodo.6335372
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Love, M.I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15, 550 (2014). https://doi.org/10.1186/s13059-014-0550-8
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Andrews, S. (n.d.). FastQC A Quality Control tool for High Throughput Sequence Data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/
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Visualization:
- Schneider K, Venn B and Mühlhaus T. Plotly.NET: A fully featured charting library for .NET programming languages [version 1; peer review: awaiting peer review]. F1000Research 2022, 11:1094 (https://doi.org/10.12688/f1000research.123971.1
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Data and annotation:
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Merchant, S. S., Prochnik, S. E., Vallon, O., Harris, E. H., Karpowicz, S. J., Witman, G. B., … Grossman, A. R. (2007). The Chlamydomonas Genome Reveals the Evolution of Key Animal and Plant Functions. Science, 318(5848), 245–250. https://doi.org/10.1126/science.1143609
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Zhang, N., Mattoon, E.M., McHargue, W. et al. Systems-wide analysis revealed shared and unique responses to moderate and acute high temperatures in the green alga Chlamydomonas reinhardtii. Commun Biol 5, 460 (2022). https://doi.org/10.1038/s42003-022-03359-z
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