Nuclear envelope budding is a non-canonical mechanism to export large transcripts in muscle cells
Zaganelli, S.; Meehl, J.; Abrisch, R. G.; Voeltz, G. K.
Show abstract
In recent years, nuclear envelope budding (NEB) has emerged as an alternative route for nuclear export of viral particles that are too large to pass through the nuclear pore complex. Yet, the significance of this unconventional export pathway for large endogenous cargoes in mammalian cells has remained largely unexplored. Here, we use a combination of electron and fluorescence microscopy to demonstrate that NEB events occur following myoblast differentiation into myotubes and concomitant with the expression of extremely long muscle-specific transcripts. We show that NE buds are derived from the inner nuclear membrane, contain internal vesicles, and are specifically enriched with long sarcomeric transcripts. We identify a role for the protein UIF in regulating mRNA cargo targeting into NE buds and show that this pathway requires the ESCRT-III membrane remodeling machinery. Our findings uncover a non-canonical pathway for large transcript nuclear export in muscle cells and provide insight into its mechanism.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Single-nuclei sequencing of skeletal muscle reveals subsynaptic-specific transcripts involved in neuromuscular junction maintenance 95%
- The Flemmingsome reveals an ESCRT-to-membrane coupling required for completion of cytokinesis 95%
- Single-nucleus RNA-seq and FISH reveal coordinated transcriptional activity in mammalian myofibers 94%
Similar papers in this journal
- Caveolae and Bin1 form ring-shaped platforms for T-tubule initiation 96%
- RNA-Binding Proteins Direct Myogenic Cell Fate Decisions 95%
- C-terminal tagging, transmembrane domain hydrophobicity, and an ER retention motif influence the secretory trafficking of the inner nuclear membrane protein emerin 95%
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.