Drosophila melanogaster
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: PXD000478
PROVIDER: PRJNA222987 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Proteome and transcriptome often show poor correlation, hindering the system-wide analysis of post-transcriptional regulation. Here, the authors study proteome and transcriptome dynamics during Drosophila embryogenesis and present basic mathematical models describing the temporal regulation of most protein-RNA pairs.
2018-10-13 | GSE121161 | GEO
Project description:Proteome and transcriptome often show poor correlation, hindering the system-wide analysis of post-transcriptional regulation. Here, the authors study proteome and transcriptome dynamics during Drosophila embryogenesis and present basic mathematical models describing the temporal regulation of most protein-RNA pairs.
2018-10-13 | GSE121160 | GEO
Project description:A Novel Role of Polycomb in Positive Transcription Regulation by Modulating H4K20me1
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Project description:Even though proteins are produced from mRNA, the correlation between mRNA levels and protein abundances is moderate in most studies, occasionally attributed to complex post-transcriptional regulation. To address this, we generated a paired transcriptome/proteome time course dataset with 14 time points during Drosophila embryogenesis. Despite a limited mRNA-protein correlation (ρ = 0.54), mathematical models describing protein translation and degradation explain 84% of protein time-courses based on the measured mRNA dynamics without assuming complex post-transcriptional regulation, and allow for classification of most proteins into four distinct regulatory scenarios. By performing an in-depth characterization of the putatively post-transcriptionally regulated genes, we postulated that the RNA-binding protein Hrb98DE is involved in post-transcriptional control of sugar metabolism in early embryogenesis and partially validated this hypothesis using Hrb98DE knockdown. In summary, we present a systems biology framework for the identification of post-transcriptional gene regulation for large-scale time-resolved transcriptome and proteome data.
2018-10-26 | PXD011238 | Pride
Project description:Genome-wide transcriptome analyses have allowed for 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 iTRAQ technology to determine transcript and protein expression changes of a Drosophila brain tumour 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 analysing the co-regulation of potential subunits. Our comprehensive transcriptome and proteome data provide a rich resource for quantitative biology and offer novel insights into understanding post- transcriptional gene regulation in a tumour model. Transcriptomes of 1-3 day old adult female Drosophila melanogaster heads of control and brat mutant were generated by deep sequencing, in triplicate, using Illumina GAIIx.
2013-11-11 | E-GEOD-51412 | biostudies-arrayexpress
Project description:Quantification of RNA editing in the Drosophila Genetic Reference Panel
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Project description:The mRNA-bound proteome of the early fly embryo
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Project description:Genome-wide transcriptome analyses have allowed for 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 iTRAQ technology to determine transcript and protein expression changes of a Drosophila brain tumour 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 analysing the co-regulation of potential subunits. Our comprehensive transcriptome and proteome data provide a rich resource for quantitative biology and offer novel insights into understanding post- transcriptional gene regulation in a tumour model.
2013-11-11 | GSE51412 | GEO
Project description:A systematic search for transgenerational effect of drug exposure to adult males using a novel Drosophila model
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