Alleviation of off-target effects from vector-encoded shRNAs via codelivered RNA decoys

• Main Authors: Mockenhaupt, Stefan, Grosse, Stefanie, Rupp, Daniel, Bartenschlager, Ralf, Grimm, Dirk
• Other Authors: School of Biological Sciences
• Format: Article
• Language: English
• Published: 2015
• Subjects: Adeno-associated viral vector; AAV; RNA interference; Short hairpin RNA; Off-targeting
• Online Access: https://hdl.handle.net/10356/81167; http://hdl.handle.net/10220/39147
• Institution: Nanyang Technological University

Exogenous RNAi triggers such as shRNAs ideally exert their activities exclusively via the antisense strand that binds and silences designated target mRNAs. However, in principle, the sense strand also possesses silencing capacity that may contribute to adverse RNAi side effects including off-target gene regulation. Here, we address this concern with a novel strategy that reduces sense strand activity of vector-encoded shRNAs via codelivery of inhibitory tough decoy (TuD) RNAs. Using various shRNAs for proof of concept, we validate that coexpression of TuDs can sequester and inactivate shRNA sense strands in human cells selectively without affecting desired antisense activities from the same shRNAs. Moreover, we show how coexpressed TuDs can alleviate shRNA-mediated perturbation of global gene expression by specifically de-repressing off-target transcripts carrying seed matches to the shRNA sense strand. Our combination of shRNA and TuD in a single bicistronic gene transfer vector derived from Adeno-associated virus (AAV) enables a wide range of applications, including gene therapies. To this end, we engineered our constructs in a modular fashion and identified simple hairpin design rules permitting adaptation to preexisting or new shRNAs. Finally, we demonstrate the power of our vectors for combinatorial RNAi strategies by showing robust suppression of hepatitis C virus (HCV) with an AAV expressing a bifunctional TuD against an anti-HCV shRNA sense strand and an HCV-related cellular miRNA. The data and tools reported here represent an important step toward the next generation of RNAi triggers with increased specificity and thus ultimately safety in humans.