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Nonsense‐mediated mRNA decay: The challenge of telling right from wrong in a complex transcriptome

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Abstract The nonsense‐mediated mRNA decay pathway selects and degrades its targets using a dense network of RNA‐protein and protein–protein interactions. Together, these interactions allow the pathway to collect copious information about the translating mRNA, including translation termination status, splice junction positions, mRNP composition, and 3′UTR length and structure. The core NMD machinery, centered on the RNA helicase UPF1, integrates this information to determine the efficiency of decay. A picture of NMD is emerging in which many factors contribute to the dynamics of decay complex assembly and disassembly, thereby influencing the probability of decay. The ability of the NMD pathway to recognize mRNP features of diverse potential substrates allows it to simultaneously perform quality control and regulatory functions. In vertebrates, increased transcriptome complexity requires balance between these two functions since high NMD efficiency is desirable for maintenance of quality control fidelity but may impair expression of normal mRNAs. NMD has adapted to this challenge by employing mechanisms to enhance identification of certain potential substrates, while using sequence‐specific RNA‐binding proteins to shield others from detection. These elaborations on the conserved NMD mechanism permit more sensitive post‐transcriptional gene regulation but can have severe deleterious consequences, including the failure to degrade pathogenic aberrant mRNAs in many B cell lymphomas. This article is categorized under: RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution RNA Interactions with Proteins and Other Molecules > Protein–RNA Interactions: Functional Implications RNA Turnover and Surveillance > Turnover/Surveillance Mechanisms
The ribonucleoprotein (RNP) configuration of the 3′UTR of a message influences substrate selection for NMD. Transcripts identified as decay substrates by the NMD machinery may contain errors or may be a part of a cellular regulatory program. The trigger for decay, however, is not determined by the process that generates a transcript but rather its 3′UTR RNP composition. Left, colored boxes indicate exons where narrow sections represent the 5′ and 3′UTRs, while wide sections represent the coding sequence (CDS). Typical termination codons are at the point where a wide box transitions to a narrow box. Chevrons indicate introns. Right, various input transcripts have been distilled to the common RNP elements directing decay. Transcripts that have exon junction complexes (EJCs) downstream of a termination codon are efficiently degraded by NMD. This configuration may arise when the termination codon is positioned upstream (asterisk) from the typical termination codon or is in its native position but is still upstream of an EJC. A second signal that could activate the machinery is a long 3′UTR. The 3′UTR could be defined by a termination codon in its typical position, or a premature termination codon (PTC) in the last exon. In either case, UPF1 molecules accumulate downstream of the terminating ribosome in a length‐dependent manner, enhancing the probability of decay. Specific molecules are labeled in the figure key
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Reversible RNP assembly and modification states may determine the probability of NMD. NMD requires concurrent translation termination (the left side of figure indicates the state of the terminating ribosome, and the bracket represents the critical window of opportunity for NMD activation) and occupancy of NMD proteins on the transcript. Assembly of these components, however, does not have to be a linear process. Instead, many binding events may be reversible, and modifications such as UPF1 phosphorylation may be undone by the activity of phosphatases. This model highlights the heterogeneity of possible RNP configurations that may ultimately lead to decay. Specific molecules in the figure are labeled in the figure key
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Peripheral EJC factors influence NMD substrate selection. ICE1‐mediated assembly of the EJC with UPF3B leads to transcripts that are more likely to be targeted for decay. EJC‐enhanced decay can be disrupted by UPF3A, which effectively competes with UPF3B for UPF2 binding. Additionally, replacement of RNPS1 with CASC3 may reduce the likelihood of NMD targeting, through a mechanism that remains to be elucidated but may involve altered association of NMD factors. Transcripts more likely to be degraded are over a red background while transcripts less likely to be degraded are over a green background
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UPF1 integrates information about mRNP configuration to define NMD substrates. UPF1 occupies a central position in the NMD pathway due to its role in directly or indirectly sensing features of the mRNP. These signals include the length of the 3′UTR, the positions of EJCs, the presence of protective or recruitment factors, and the timing of translation termination. Integration of these signals will influence UPF1 phosphorylation, an important mark for recruitment and activation of decay factors. UPF1 molecules persistently associated with mRNPs are more likely to be highly phosphorylated. Specific molecules in the figure are labeled in the figure key
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In order to simultaneously regulate and safeguard the transcriptome, NMD pathway functionality must balance multiple parameters. As NMD efficiency increases, the protein products from PTC‐containing and other NMD‐regulated mRNAs will be strongly down‐regulated, but mRNAs that are not normally NMD targets may also become susceptible to decay. Thus, aggressive clearance of aberrant transcripts may come at the cost of sacrificing beneficial mRNAs. Conversely, increased specificity could prevent targeting of all but mRNAs with the strongest NMD‐promoting features. Further, an intermediate level of NMD efficiency may be optimal to simultaneously influence the function of multiple cellular pathways, as illustrated by hypothetical values of “regulatory flexibility” across the spectrum of NMD efficiency. Optimal NMD efficiencies to maintain regulatory flexibility are expected to vary according to cell type and physiological conditions
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RNA Interactions with Proteins and Other Molecules > Protein–RNA Interactions: Functional Implications
RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution
RNA Turnover and Surveillance > Turnover/Surveillance Mechanisms

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