Proteomics

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Quantifying post-transcriptional regulation in the development of Drosophila melanogaster


ABSTRACT: 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.

OTHER RELATED OMICS DATASETS IN: GSE121167

INSTRUMENT(S): Q Exactive

ORGANISM(S): Drosophila Melanogaster (fruit Fly)

SUBMITTER: F Butter  

LAB HEAD: Falk Butter

PROVIDER: PXD011238 | Pride | 2018-10-26

REPOSITORIES: Pride

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Publications

Quantifying post-transcriptional regulation in the development of Drosophila melanogaster.

Becker Kolja K   Bluhm Alina A   Casas-Vila Nuria N   Dinges Nadja N   Dejung Mario M   Sayols Sergi S   Kreutz Clemens C   Roignant Jean-Yves JY   Butter Falk F   Legewie Stefan S  

Nature communications 20181126 1


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 generate 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 o  ...[more]

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