Project description:shRNAs selected with the shERWOOD algorithm were converted to have a U at the 5' end of their guide. When endogenous 1U shRNAs were compared to artificial shRNA via the sensor algorithm, the endogenous shRNAs were found to be more efficacious.
Project description:shRNAs selected with the shERWOOD algorithm were converted to have a U at the 5' end of their guide. When endogenous 1U shRNAs were compared to artificial shRNA via the sensor algorithm, the endogenous shRNAs were found to be more efficacious. Purpose: Structural studies have hinted that the 5' end of shRNA guides is engulfed in the RISC complex. It has also been reported that shRNAs with a 5' U are more efficacious than those with other 5' caps. We wished to determine whether replacement of shRNA guide 5' nucleotides with a U, regardless of the corresponding target base, would increase their efficacy. Method: For each gene in the "druggable genome" 10 shRNAs were selected with the shERWOOD algorithm. In each case the score was assessed as if the guide had a 5' U. Sensor constructs were designed pairing 1U-guide shRNAs with their endogenous target. shRNAs were assessed for efficacy via the shRNA sensor assay (Fellmann et al. Mol Cell 2011). Results: shRNAs with artificial 5' Us were found to be less efficacious than those with an endogenous 5' U,
Project description:Sub-genomewide shRNAs constructed using an optimized selection algorithm and microRNA backbone provide stronger evidence for follow-up studies
Project description:Purpose: Generate a large, high quality database of paired shRNA efficacy/sequence datapoints. Methods:Twelve shRNAs for each Refseq annotated human gene were selected based on the DSIR algorithm. Twelve batches of ~22K shRNAs (corresponding to 12 agilent chips) were then assessed for efficacy via the sensor method outlined in Fellmann et al, Mol Cell, 2011. Conclusions: Neighboring nucleotide combinations are best at predicting shRNA efficacy.
