bioRxivMolecular BiologyPreprint
Isoform-Specific Localization Diversifies Human MSI2 Function
Kathryn WaltersiD, Nadine KörteliD, Amber BaldwiniD, Marcin Piotr SajekiD, Neelanjan MukherjeeiD
Abstract
Musashi-2 (MSI2) is an RNA-binding protein implicated in stem cell regulation and cancer, yet reports of its regulatory activity span translational activation, repression, and effects on mRNA stability, sometimes within the same cellular context. The basis for this diversity has remained unclear. Here, we identify alternative splicing as a determinant of MSI2 regulatory activity, acting through isoform-specific subcellular localization. Using a tethered reporter assay, we show that the canonical MSI2-328 isoform promotes translation without changing mRNA abundance. Truncation and mutation analysis identify a 40-amino-acid region (residues 194-234) as necessary and sufficient for cytoplasmic localization and necessary for translational activation. In contrast, the alternatively spliced MSI2-324 isoform localizes predominantly to the nucleus and fails to promote translation. We map this difference to an 18-amino-acid sequence introduced by an alternative 3 splice acceptor in exon 12; this sequence is sufficient to direct nuclear localization, and its removal restores MSI2-328-like cytoplasmic localization and translational activation. Consistent with these compartmental differences, the two isoforms associate with distinct protein networks, MSI2-328 with translation factors and ribosomal proteins, and MSI2-324 with chromatin and pre-mRNA processing factors. These isoform-specific activities are conserved across cell types, and the relative abundance of MSI2 isoforms shifts toward MSI2-324 in several cancers. Altogether, alternative splicing controls MSI2 subcellular localization, interaction networks, and regulatory output, providing a mechanistic framework for the context-dependent roles of MSI2 in gene regulation.
- organism: human
- assay: protein sequence
- research focus: cell type annotation
- research focus: differential expression
- research focus: protein structure prediction
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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