Nature Communications · 2018 · 111 citations · 50 references
Life SciencesDevelopmental BiologySystems BiologyGene ExpressionProteomicsTranscriptomicsDevelopmental TranscriptomicsGene Expression DynamicsGene Expression RegulationPost-translational RegulationProtein SynthesisRna-protein InteractionsDevelopmental Time Course AnalysisMrna Degradation DynamicsPost-transcriptional Gene RegulationPost-transcriptional RegulationPost-transcriptional Regulation In DevelopmentTime-course TranscriptomicsTime-resolved ProteomicsTime-resolved Transcriptomics
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 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 postulate that the RNA-binding protein Hrb98DE is involved in post-transcriptional control of sugar metabolism in early embryogenesis and partially validate this hypothesis using Hrb98DE knockdown. In summary, we present a systems biology framework for the identification of post-transcriptional gene regulation from large-scale, time-resolved transcriptome and proteome data.
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