RNAMolecular BiologyPeer-reviewed journal article
Comparative analyses of disease-linked missense mutations in the RNA exosome modeled in budding yeast reveal distinct functional consequences in translation
Maria C. SterrettiD, Lauryn A. CuretoniD, Lauren N. CoheniD, Ambro van HoofiD, Sohail KhoshnevisiD, Milo B. FaskeniD, Anita H. CorbettiD, Homa GhaleiiD
Abstract
The RNA exosome is a multi-subunit, evolutionarily conserved ribonuclease complex that is essential for processing, decay and surveillance of many cellular RNAs. Missense mutations in genes encoding the structural subunits of the RNA exosome complex cause a diverse range of diseases, collectively known as RNA exosomopathies, often involving neurological and developmental defects. The varied symptoms suggest that different mutations lead to distinct in vivo consequences. To investigate these functional consequences and distinguish whether they are unique to each RNA exosomopathy mutation, we generated a collection of in vivo models by introducing pathogenic missense mutations in orthologous S. cerevisiae genes. Comparative RNA-seq analysis assessing broad transcriptomic changes in each mutant model revealed that three yeast mutant models, rrp4-G226D, rrp40-W195R and rrp46-L191H, which model mutations in the genes encoding EXOSC2, EXOSC3 and EXOSC5, respectively, had the largest transcriptomic differences. While some transcriptomic changes, particularly in transcripts related to ribosome biogenesis, were shared among mutant models, each mutation also induced unique transcriptomic changes. Thus, our data suggests that while there are some shared consequences, there are also distinct differences in RNA exosome function by each variant. Assessment of ribosome biogenesis and translation defects in the three models revealed distinct differences in polysome profiles. Collectively, our results provide the first comparative analyses of RNA exosomopathy mutant models and suggest that different RNA exosome gene mutations result in in vivo consequences that are both unique and shared across each variant, providing further insight into the biology underlying each distinct pathology.
- organism: yeast
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 9
- FWCI
- 2.10
- Field percentile
- top 13%
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