期刊
GENOME BIOLOGY
卷 14, 期 11, 页码 -出版社
BMC
DOI: 10.1186/gb-2013-14-11-r133
关键词
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资金
- FEBS
- Austrian Science Fund FWF (Fonds zur Forderung der wissenschaftlichen Forschung) Chromosome Dynamics [SFB-F3402]
- European Commission
- Austrian Academy of Sciences
- Austrian Science Fund FWF [P20547-B09, Z153-B09, I552-B19]
- European Research Council
- Austrian Science Fund (FWF) [Z 153] Funding Source: researchfish
- Austrian Science Fund (FWF) [P20547, Z153] Funding Source: Austrian Science Fund (FWF)
Background: 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. Results: 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. Conclusions: 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.
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