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

Jüschke et al. Genome Biology 2013, 14:r133 http://genomebiology.com/2013/14/11/r133 R ESEA R CH Open Access Transcriptome and proteome quantification of a tumor model provides novel insights into post-transcriptional gene regulation Christoph Jüschke1 , Ilse Dohnal2 , Peter Pichler2,3 , Heike Harzer1 , Remco Swart4 , Gustav Ammerer2 , Karl Mechtler1,3 and Juergen A Knoblich1* Abstract 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. Background Eukaryotic gene expression involves transcription, mRNA processing and decay, translation, and protein modification and degradation. Each of these steps is tightly regulated to ensure the proper function and stability of the biological system [1]. While genome and transcriptome data have accumulated rapidly since the advent of microarray and deep-sequencing technologies, the limited depth of quantitative proteomics has inhibited similar progress in post-transcriptional gene regulation. Therefore, transcript levels are still routinely used as the only measure for gene expression in high-throughput approaches. Several studies, however, have reported a low *Correspondence: 1 Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Dr Bohr-Gasse 3, 1030 Vienna, Austria Full list of author information is available at the end of the article correlation between transcript and protein levels [2-6], highlighting the importance of post-transcriptional processes as well as the limited predictive value of transcripts for protein expression. Hence, a better understanding of genetic information processing requires consideration of quantitative information at every step of gene expression control. Recently, studies have begun to address this problem systematically by acquiring large-scale quantitative mRNA and protein data from bacteria [7,8], yeasts [9-11] and cell lines [12,13]. For complex tissues of higher organisms, however, such information is still rare. Quantitative analyses are either restricted to a few hundred genes due to limited proteome coverage [5,14] or they focus on cultured cell lines that might have lost properties of their tissue of origin over time [12,13,15-17]. We therefore set out to address this problem using a complex neural tissue in wild-type state and tumor state. © 2013 Jüschke et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Jüschke et al. Genome Biology 2013, 14:r133 http://genomebiology.com/2013/14/11/r133 The Drosophila brain arises from neural stem cells called neuroblasts that undergo repeated rounds of asymmetric cell division giving rise to self-renewing neuroblasts and terminally differentiating neurons [18-20]. In homozygous brain tumor (brat) mutants, some neuroblast divisions become symmetric leading to the formation of excess neuroblasts at the expense of neurons. This causes an uncontrolled expansion of the neuroblast pool and results in the formation of a large brain tumor [21-23]. These tumors can be transplanted into host flies, where they become aneuploid and undergo metastasis [24]. Normally, tumor formation is lethal during larval development, but hypomorphic mutants can survive until adulthood, and the flies harbor large proliferating neuroblast tumors in their brains. The simple cytology of the developing Drosophila brain and the reproducibility of tumor formation have made brat mutants a well-studied example for stem-cellderived tumor formation. Here, we performed an in-depth integrative analysis of transcript and protein expression data from a complex metazoan tissue, comparing Drosophila brain tumor (brat) versus wild-type heads. Using relative protein quantification with mass spectrometry (isobaric tag for relative and absolute quantification (iTRAQ)) [25], we determined relative expression levels for more than 6,200 proteins, corresponding to about 70% of all transcribed protein coding genes. By investigating transcript–protein correlations, namely the change of correlation between the normal and tumorous state, we identify biological processes that are strongly regulated by post-transcriptional mechanisms. Furthermore, we demonstrate that the stoichiometric expression of protein-complex subunits is controlled by a two-tiered mechanism involving co-expression on the mRNA level followed by post-transcriptional fine-tuning. Surprisingly, our data suggest that co-regulation of protein-complex subunits is the exception and not the rule. Finally, our comprehensive data set provides a valuable resource for quantitative systems-level analyses. Results and discussion About 60% of protein-coding transcripts are expressed in wild-type and brat fly heads To obtain sufficient amounts of material for transcriptome and proteome analyses we established a workflow to collect large numbers of homozygous brat mutant fly heads (Figure 1A). Homozygous mutant female flies exhibited a tumor penetrance of 100%, and the median adult survival time was reduced to 10 days (Figure 1B). For transcriptome analysis, total RNA samples from brat and wild-type female fly heads were prepared in biological triplicates, analyzed by strand-specific paired-end mRNA sequencing and quantified by mapping the reads to the Drosophila genome. The averag (...truncated)