Endogenous spacing enables co-processing of microRNAs and efficient combinatorial RNAi.

We present Multi-miR, a microRNA-embedded shRNA system modeled after endogenous microRNA clusters that enables simultaneous expression of up to three or four short hairpin RNAs (shRNAs) from a single promoter without loss of activity, enabling robust combinatorial RNA interference (RNAi). We further developed complementary all-in-one vectors that are over one log-scale more sensitive to doxycycline-mediated activation in vitro than previous methods and resistant to shRNA inactivation in vivo. We demonstrate the utility of this system for intracranial expression of shRNAs in a glioblastoma model. Additionally, we leverage this platform to target the redundant RAF signaling node in a mouse model of KRAS-mutant cancer and show that robust combinatorial synthetic lethality efficiently abolishes tumor growth.

Prediction of potent shRNAs with a sequential classification algorithm.

We present SplashRNA, a sequential classifier to predict potent microRNA-based short hairpin RNAs (shRNAs). Trained on published and novel data sets, SplashRNA outperforms previous algorithms and reliably predicts the most efficient shRNAs for a given gene. Combined with an optimized miR-E backbone, >90% of high-scoring SplashRNA predictions trigger >85% protein knockdown when expressed from a single genomic integration. SplashRNA can significantly improve the accuracy of loss-of-function genetics studies and facilitates the generation of compact shRNA libraries.

An optimized microRNA backbone for effective single-copy RNAi.

Short hairpin RNA (shRNA) technology enables stable and regulated gene repression. For establishing experimentally versatile RNAi tools and minimizing toxicities, synthetic shRNAs can be embedded into endogenous microRNA contexts. However, due to our incomplete understanding of microRNA biogenesis, such "shRNAmirs" often fail to trigger potent knockdown, especially when expressed from a single genomic copy. Following recent advances in design of synthetic shRNAmir stems, here we take a systematic approach to optimize the experimental miR-30 backbone. Among several favorable features, we identify a conserved element 3' of the basal stem as critically required for optimal shRNAmir processing and implement it in an optimized backbone termed "miR-E", which strongly increases mature shRNA levels and knockdown efficacy. Existing miR-30 reagents can be easily converted to miR-E, and its combination with up-to-date design rules establishes a validated and accessible platform for generating effective single-copy shRNA libraries that will facilitate the functional annotation of the genome.