alexa Dissecting the expression dynamics of RNA-binding proteins in posttranscriptional regulatory networks.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Computer Science & Systems Biology

Author(s): Mittal N, Roy N, Babu MM, Janga SC

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Abstract In eukaryotic organisms, gene expression requires an additional level of coordination that links transcriptional and posttranslational processes. Messenger RNAs have traditionally been viewed as passive molecules in the pathway from transcription to translation. However, it is now clear that RNA-binding proteins (RBPs) play an important role in cellular homeostasis by controlling gene expression at the posttranscriptional level. Here, we show that RBPs, as a class of proteins, show distinct gene expression dynamics compared to other protein coding genes in the eukaryote Sacchoromyces cerevisiae. We find that RBPs generally exhibit high protein stability, translational efficiency, and protein abundance but their encoding transcripts tend to have a low half-life. We show that RBPs are also most often posttranslationally modified, indicating their potential for regulation at the protein level to control diverse cellular processes. Further analysis of the RBP-RNA interaction network showed that the number of distinct targets bound by an RBP (connectivity) is strongly correlated with its protein stability, translational efficiency, and abundance. We also note that RBPs show less noise in their expression in a population of cells, with highly connected RBPs showing significantly lower noise. Our results indicate that highly connected RBPs are likely to be tightly regulated at the protein level as significant changes in their expression may bring about large-scale changes in global expression levels by affecting their targets. These observations might explain the molecular basis behind the cause of a number of disorders associated with misexpression or mutation in RBPs. Future studies uncovering the posttranscriptional networks in higher eukaryotes can help our understanding of the link between different levels of regulation and their role in pathological conditions.
This article was published in Proc Natl Acad Sci U S A and referenced in Journal of Computer Science & Systems Biology

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