Early divergence of Th1 and Th2 transcriptomes involves a small core response and sets of transiently expressed genes
Article first published online: 4 MAR 2013
© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
European Journal of Immunology
Volume 43, Issue 4, pages 1074–1084, April 2013
How to Cite
van den Ham, H.-J., de Waal, L., Zaaraoui-Boutahar, F., Bijl, M., van IJcken, W. F. J., Osterhaus, A. D.M.E., de Boer, R. J. and Andeweg, A. C. (2013), Early divergence of Th1 and Th2 transcriptomes involves a small core response and sets of transiently expressed genes. Eur. J. Immunol., 43: 1074–1084. doi: 10.1002/eji.201242979
- Issue published online: 16 APR 2013
- Article first published online: 4 MAR 2013
- Accepted manuscript online: 22 FEB 2013 03:59AM EST
- Manuscript Accepted: 28 JAN 2013
- Manuscript Revised: 3 DEC 2012
- Manuscript Received: 11 SEP 2012
- VIRGO consortium
- Netherlands Genomics Initiative
- Dutch Government. Grant Number: FES0908
- Netherlands Organisation for Scientific Research (NWO) VICI. Grant Number: 016.048.603
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Supporting Table 1: Differential KEGG & MSigDB pathways for differential gene expression in time or skewing treatment. Global test was used to assess the differential regulation of KEGG and MSigDB pathways in time by using neutral treatment on day 1–4 versus naive T cells (i.e. D1 versus D0, D2 versus D0, D3 versus D0 and D4 versus D0). Differential pathways in response to skewing were assessed by the Th1–Th2 within day contrast on all days (i.e. D1.Th2 versus D1.Th1, D2.Th2 versus D2.Th1, etc.). All pathways shown have a comparative p-value < 0:01 in all contrasts.
Supporting Table 2: Experimental setup for microarray experiments.
Supporting Figure 1: Comparing qRT-PCR and microarray results. Validation of canonical cytokine expression by qRT-PCR for (a) IFN (Th1) and (b) IL4 (Th2). (c) Regression analysis of canonical Th1 and Th2 gene expression with 45 – # qRT-PCR cycles versus log2 transformed microarray gene intensity. Pearson's correlation was calculated for each gene separately.
Supporting Figure 2: Differential gene expression as assessed by limma, depicted as four-set Venn diagrams. Panels a, c and e shown all statistically significant probesets (i.e. genes), panels b, d and f additionally require gene expression levels to be at least twofold different. Panels a and b show overlap in differential genes for neutral stimulation (i.e. no skewing cytokine added) for 1 to 4 days versus naive (D0) cells. Panels c and d show overlap in differential genes between the Th1 and Th2 treatment on day 1 to 4. Panels e and f show the overlap in differential genes between Th1 and Th2. All arrays were VSN normalised, FDR p-value < 0:05.
Supporting Figure 3: Polar score analysis. (a) Polar scores per cluster. (b) Correlation tree of skewed cluster genes. The clusters are indicated by red boxes. (c) Gene expression trajectories for cluster 1.
Supporting Figure 4: Gene expression value trajectories of skewed clusters 2 (a), 4 (b) and 10 (c).
Supporting Figure 5: Gene expression value trajectories of skewed clusters 11 (a), 24 (b) and 27 (c).
Supporting Figure 6: Microarray quality control. Boxplots and density plots show the raw probe intensity distribution for all arrays.
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