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Transcriptome and proteome quantification of a tumor model provides novel insights into post‐transcriptional gene regulation

Christoph Jüschke1, Ilse Dohnal2, Peter Pichler23, Heike Harzer1, Remco Swart4, Gustav Ammerer2, Karl Mechtler13 and Juergen A Knoblich1*

Author Affiliations

1 Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Dr Bohr‐Gasse 3, 1030 Vienna, Austria

2 Christian Doppler Laboratory for Proteome Analysis, Dr Bohr‐Gasse 9, 1030 Vienna, Austria

3 Research Institute of Molecular Pathology (IMP), Dr Bohr‐Gasse 7, 1030 Vienna, Austria

4 Thermo Fisher Scientific, Abberdaan 114, 1046 AA Amsterdam, Netherlands

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Genome Biology 2013, 14:r133  doi:10.1186/gb-2013-14-11-r133

Published: 30 November 2013

Additional files

Additional file 1:

Figure S1. iTRAQ reproducibility. (A) Technical reproducibility of iTRAQ protein quantification. (B) Technical reproducibility between iTRAQ and label‐free SRM protein quantification. Error bars indicate standard deviations. (C) Reproducibility of protein level changes between biological replicates measured with SRM and iTRAQ. Error bars indicate standard deviations. (D) Venn diagram showing the number of quantified unique peptides in the trypsin‐ and LysC‐digested samples. The samples were largely complementary: only 16% of the quantified peptides were identical. (E) Venn diagram showing the number of quantified proteins from the trypsin and LysC samples. This shows that 75% of the proteins were quantified in both samples. (F) Correlation of iTRAQ protein quantification using either trypsin‐ or LysC‐digested samples.

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Additional file 2:

Figure S2. Analysis of proteome coverage. For each bin the number of annotated (dark gray), expressed (light gray) and quantified proteins (white) are shown together with the percentage of quantified proteins (red). (A) Proteome coverage is higher for proteins predicted by the codon adaptation index to be more abundant. The blue line indicates the percentage of quantified proteins from all annotated protein. (B) Proteome coverage is higher for larger proteins. (C) Proteome coverage is lower for very hydrophobic proteins. (D) Proteome coverage is higher than 60% for all isoelectric points.

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Additional file 3:

Figure S3. Correlation of protein level change with transcript abundance. Correlation of protein level change with transcript abundance in (A) wild‐type and (B) brat samples.

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Additional file 4:

Cytoscape protein interaction network. Cytoscape file containing log2‐fold expression changes on mRNA and protein levels combined with DPiM protein interaction data. The centers of the nodes indicate protein expression changes and the borders of the nodes mRNA expression changes. Blue represents downregulation, red represents upregulation and the color intensity is proportional to the level of regulation. Transcripts and proteins not quantified are shown in gray. Protein interactions are depicted as light green lines and their thickness is proportional to the interaction strength.

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Additional file 5:

Figure S5. Complex co‐regulation. Protein‐complex co‐regulation on the mRNA level. Transcripts encoding subunits of annotated protein complexes (red) are significantly more co‐regulated than random pairs (green).

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Additional file 6:

Data set of transcriptome and proteome changes. Complete data set of transcript and protein quantification data, containing FlyBase gene number, gene name, protein level change (log2‐fold change), standard deviation of log2 protein level change, number of quantified spectra, transcript level change (log2‐fold change), brat FPKM, control FPKM, standard deviation of brat FPKM and standard deviation of control FPKM. Since a double‐labeling approach was performed, each quantified spectrum contains two reporter ions from both brat and control samples.

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