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RNAi (RNA Interference)


Figure 1. Harnessing the endogenous microRNA pathway to trigger RNAi

The endogenous mammalian microRNA pathway showing expression and processing of microRNA transcripts to induce gene knockdown. This occurs via (1) mRNA translational repression mediated by incomplete complementarity or (2) mRNA cleavage and degradation mediated by complete sequence complementarity. Green cartoons (on the right) show where siRNA, shRNA and shRNA-mir tools enter the endogenous microRNA pathway to trigger RNAi (Knott et al 2014, Castanotto 2011)

shERWOOD Algorithm and UltramiR microRNA scaffold for guaranteed potency

shERWOOD-UltramiR microRNA-adapted shRNA collections are based on the next generation shERWOOD algorithm for shRNA design developed by Dr. Greg Hannon and Dr. Simon Knott at Cold Spring Harbor Laboratory (CSHL). Data collected from the functional testing of  270,000 shRNA sequences was used to train the shERWOOD algorithm to design shRNA sequences optimized for increased potency even at single copy representation.  shERWOOD designs are expressed with an optimized microRNA scaffold.  The UltramiR scaffold has been optimized based on key determinants for primary microRNA biogenesis and results in more efficient small RNA processing through the microRNA pathway.  
 

shERWOOD Algorithm for shRNA design – Why is it important?

Increasing shRNA Knockdown Performance
Machine-learning-based applications trained on siRNA data sets have produced algorithms that facilitate prediction of potent siRNAs (Huesken et al 2005; Vert et al 2006). However, corresponding analysis had not been applied to the design of shRNAs, which rely on transcription and microRNA processing for the production of small RNA (Figure 1). siRNA algorithms are known to be inefficient for predicting potent shRNAs, leaving their identification to empirical testing (Bassik et al 2009; Li et al 2007) and existing shRNA collections have low percentages of potent RNAi triggers. 

Producing knockdown potency and specificity at low concentration
Exogenously delivered shRNAs act via the same cellular pathways as endogenous microRNAs (Figure 1), posing the risk of saturating essential components of the RNAi machinery. High intracellular levels of synthetic small RNAs can result in toxicities related to saturation of the RNAi machinery (Grimm et al 2006). Such effects can be reduced by the use of microRNA-adapted shRNA (Castanotto et al 2007; McBride et al 2008). Synthetic RNAi triggers can also evoke off-target effects by suppressing unintended transcripts due to sequence homologies of either the sense or the antisense strand. Identifying the most potent siRNA or shRNA designs that can be effective at the lowest possible concentration is therefore very important.

Providing tools for multiplexed RNAi screening and creation of animal models
Key RNAi applications such as pooled shRNA screening and creation of animal models require shRNAs that are effective even when expressed from a single genomic locus (‘‘single copy’’). Since most currently available shRNA reagents are not designed or tested to fulfill such stringent criteria, existing libraries contain many ineffective shRNAs that complicate the execution and interpretation of RNAi screens.