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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



Genome‐wide transcriptome analyses have given systems‐level insights into gene regulatory networks. Due to the limited depth of quantitative proteomics, however, our understanding of post‐transcriptional gene regulation and its effects on protein‐complex stoichiometry are lagging behind.


Here, we employ deep sequencing and the isobaric tag for relative and absolute quantification (iTRAQ) technology to determine transcript and protein expression changes of a Drosophila brain tumor model at near genome‐wide resolution. In total, we quantify more than 6,200 tissue‐specific proteins, corresponding to about 70% of all transcribed protein‐coding genes. Using our integrated data set, we demonstrate that post‐transcriptional gene regulation varies considerably with biological function and is surprisingly high for genes regulating transcription. We combine our quantitative data with protein‐protein interaction data and show that post‐transcriptional mechanisms significantly enhance co‐regulation of protein‐complex subunits beyond transcriptional co‐regulation. Interestingly, our results suggest that only about 11% of the annotated Drosophila protein complexes are co‐regulated in the brain. Finally, we refine the composition of some of these core protein complexes by analyzing the co‐regulation of potential subunits.


Our comprehensive transcriptome and proteome data provide a valuable resource for quantitative biology and offer novel insights into understanding post‐transcriptional gene regulation in a tumor model.