CRISPR artificial splicing factors

Menghan Du,Jacqueline Jufen Zhu,Sheng Li,Albert Wu Cheng,Nathaniel Jillette

doi:10.1038/s41467-020-16806-4

Abstract

Alternative splicing allows expression of mRNA isoforms from a single gene, expanding the diversity of the proteome. Its prevalence in normal biological and disease processes warrant precise tools for modulation. Here we report the engineering of CRISPR Artificial Splicing Factors (CASFx) based on RNA-targeting CRISPR-Cas systems. We show that simultaneous exon inclusion and exclusion can be induced at distinct targets by differential positioning of CASFx. We also create inducible CASFx (iCASFx) using the FKBP-FRB chemical-inducible dimerization domain, allowing small molecule control of alternative splicing. Finally, we demonstrate the activation of SMN2 exon 7 splicing in spinal muscular atrophy (SMA) patient fibroblasts, suggesting a potential application of the CASFx system.

Highlights

Alternative splicing allows expression of mRNA isoforms from a single gene, expanding the diversity of the proteome
In this study, we reported the development of CASFx, artificial splicing factors based on RNA-targeting CRISPR-Cas systems[30,31]
CASFx with RBFOX1 or RBM38 fusions can induce exon inclusion when targeted to bind at a downstream intron, and induce exon exclusion when guided to bind within a target exon

Summary

Introduction

Alternative splicing allows expression of mRNA isoforms from a single gene, expanding the diversity of the proteome. Alternative splicing is a phenomenon in which different exon segments of a gene are spliced together to form mature mRNA with varying sequences, greatly expanding the protein repertoire coded by a single gene. Tethering of serinerich or glycine-rich domains by engineered PUF domains to exons induce their inclusion or exclusion, respectively[12]. These artificial RNA effectors require either protein engineering or insertion of artificial tags to target RNA and depend on short recognition sequences which limits targeting flexibility and specificity

Methods

Results

Conclusion