Journal Article

The abundance of RNPS1, a protein component of the exon junction complex, can determine the variability in efficiency of the Nonsense Mediated Decay pathway

Marcelo H. Viegas, Niels H. Gehring, Stephen Breit, Matthias W. Hentze and Andreas E. Kulozik

in Nucleic Acids Research

Volume 35, issue 13, pages 4542-4551
Published in print July 2007 | ISSN: 0305-1048
Published online June 2007 | e-ISSN: 1362-4962 | DOI: http://dx.doi.org/10.1093/nar/gkm461
The abundance of RNPS1, a protein component of the exon junction complex, can determine the variability in efficiency of the Nonsense Mediated Decay pathway

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Nonsense-mediated mRNA decay (NMD) is a molecular pathway of mRNA surveillance that ensures rapid degradation of mRNAs containing premature translation termination codons (PTCs) in eukaryotes. NMD has been shown to also regulate normal gene expression and thus emerged as one of the key post-transcriptional mechanisms of gene regulation. Recently, NMD efficiency has been shown to vary between cell types and individuals thus implicating NMD as a modulator of genetic disease severity. We have now specifically analysed the molecular mechanism of variable NMD efficiency and first established an assay system for the quantification of NMD efficiency, which is based on carefully validated cellular NMD target transcripts. In a HeLa cell model system, NMD efficiency is shown to be remarkably variable and to represent a stable characteristic of different strains. In one of these strains, low NMD efficiency is shown to be functionally related to the reduced abundance of the exon junction component RNPS1. Furthermore, restoration of functional RNPS1 expression, but not of NMD-inactive mutant proteins, also restores efficient NMD in this model. We conclude that cellular concentrations of RNPS1 can modify NMD efficiency and propose that cell type specific co-factor availability represents a novel principle that controls NMD.

Journal Article.  5110 words.  Illustrated.

Subjects: Chemistry ; Biochemistry ; Bioinformatics and Computational Biology ; Genetics and Genomics ; Molecular and Cell Biology

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