Understanding the variability in nonsense-mediated RNA decay

University Of Colorado Denver, Aurora CO

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Abstract

PROJECT SUMMARY Predicting functional consequences of genomic variation remains the biggest barrier to precision medicine. While nonsense variants are considered the best understood of all genetic variants, our work has revealed significant gaps in our knowledge base for their functional interpretation. My group studies how variability in mRNA surveillance impacts the functional consequence of human genetic variants. Protein-truncating genetic variants often cause loss of gene function because their encoding transcripts are subject to degradation by an RNA quality control process called nonsense-mediated RNA decay (NMD). NMD senses transcripts with a premature stop codon and triggers their degradation to prevent the production of truncated proteins. However, the efficiency with which NMD acts on a target transcript is variable across genes, tissues, and even individuals. We have shown that non-canonical translation events such as stop codon readthrough and translation reinitiation can cause NMD evasion by a nonsense-containing transcript, though the rules governing such events are unknown. My research program builds on these discoveries to systematically investigate factors that cause variable NMD efficiency. Specifically, we combine massively parallel reporter assays with targeted gene editing to identify and validate sequence features that permit NMD escape. Through this work, we aspire to build new rules for the functional classification of variants and use such rubrics to build more accurate and predictive models for phenotypic consequence of nonsense variants. Such a model will allow us to identify variants that are likely to cause disease and to develop novel therapeutic approaches to counter genetic disorders.