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ShRNA Sensor Analysis of 5' U converted shRNAs reveals 3' target bias exists in addition to 5' guide bias

ABSTRACT: 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,

ORGANISM(S): synthetic construct

SUBMITTER: Simon Knott

PROVIDER: E-GEOD-62186 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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shRNA Sensor Analysis of 5' U converted shRNAs reveals 3' target bias exists in addition to 5' guide bias

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.

2014-11-24 | GSE62186 | GEO

shRNA Sensor Analysis of DSIR Selected shRNAs

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.

2014-11-24 | E-GEOD-62183 | biostudies-arrayexpress

synthetic construct

Project description:shRNA Sensor Analysis of DSIR Selected shRNAs

| PRJNA263390 | ENA

synthetic construct

Project description:shRNA Sensor Analysis of 5' U converted shRNAs reveals 3' target bias exists in addition to 5' guide bias

| PRJNA263391 | ENA

shRNA off target analysis via RNAseq

Project description:shRNAs were assessed for off-target effects by comparing the gene expression profiles of cells that they had been infected into. shRNAs designed with the shERWOOD algorithm and house in the ultramir microRNA scafold were found to have very little off targeting. Purpose: A major detriment to RNAi is off-targeting. We wished to assess the level of off targeting of microRNA (ultramiR) housed shERWOOD shRNAs as compared to similar shRNAs in the TRC collection. Methods: 5 shRNAs targeting each of two genes were infected into the 4T1 cell line. For each gene one shRNA was selected from the TRC collection and one based on the shERWOOD algorithm. For each gene, the exrpession profiles of the corresponding shRNA infected cells were compared using RNAseq. Conclusions: Highly similar profiles were observed between shERWOOD selected shRNAs. TRC shRNAs produced profiles indicative of off-targeting.

2014-11-24 | E-GEOD-62184 | biostudies-arrayexpress

Sub-genomewide shRNAs constructed using an optimized selection algorithm and microRNA backbone provide stronger evidence for follow-up studies

Project description:Sub-genomewide shRNA libraries were constructed using the current RNAi consortium constructs as well as using the DSIR (siRNA algoirthm) and a novel shRNA specific algorithm (shERWOOD). All libraries were placed into mir30 expression vectors. The shERWOOD libraries were also placed in a vector harboring an optimized mir cassette (ultramir). Each library was screened using the pancreatic cell line A385. A concensus set of essential genes identified as the set for which two shRNAs depleted in each of the libries. For these genes, a great percentage of shERWOOD seletected shRNA depleted. In addition the placement of shERWOOD selected constructs into ultramir scaffoled increased the rate of shRNA depletion for essential genes further. Purpose: shRNA screens were carried out using various library construction strategies to identify the strategy that provides the best shRNA screening results. Method: Libraries were constructed using the TRC shRNA set as well as shRNAs identified using the DSIR and shERWOOD algorithms. shRNA libraries were cloned into mir30 expression vectors. shERWOOD shRNAs were also cloned into an expression vector harboring an optimized microRNA scaffold termed ultramir. Each resultant library was screened using the pancreatic cell line A385. Each library was analyzed separately to identify a set of genes where at least two shRNAs depleted. These gene sets were intersected to develop a set of essential genes. Results: The shERWOOD shRNA libraries provided the highest number depleting shRNAs for each essential gene. Further these shRNAs depleted to a greater extent than did the shRNAs from the other libraries. When shERWOOD libraries were placed into the ultramir cassette a greater number of shRNAs per essential gene depleted.

2014-11-24 | E-GEOD-62185 | biostudies-arrayexpress

Identification of Zdhhc20 knock-down cell palmitome

Project description:An shRNA screen to search for the mediators of pancreatic cancer metastasis identified palmitoyl transferase ZDHHC20 as a protein that mediates this process by promoting the outgrowth of metastatic cells in vivo. We sought to identify the changes in the palmitome of the cells expessing scrambled shRNA or shRNAs targeting Zdhhc20.

2023-02-09 | PXD038048 | Pride

Small RNA sequencing of mouse muscle and heart samples after small hairpin RNA delivery

Project description:RNA interference (RNAi) is a promising gene therapy strategy for targeting dominant mutations. This therapy leverages small hairpin RNAs (shRNAs) to knock down gene expression; however, delivery of too much shRNA can disrupt the processing of endogenous microRNAs (miRNAs), and lead to toxicity. In this study, we sought to understand the effect that excessive shRNAs have on muscle miRNAs by transducing several constructs in mice and performing small RNA sequencing on their muscle and liver tissues. We found that shRNA expression was highest in the heart, and that when shRNAs accumulated to about 27% of total small RNAs, mice experienced substantial cardiomyopathy. At this level in the heart, shRNAs in other muscle tissues were only ~1.8-7.6% of total miRNAs. Regardless of treatment, the predominant heart microRNAs remained stable across samples, while the lower-expressed miR-451 – one of the only microRNAs processed in a Dicer-independent manner – changed in direct correlation with shRNA level and toxicity. Our data suggest that certain muscle miRNAs compete with exogenous shRNAs, leading to the observed cardiomyopathy, and that the mechanism of cardiotoxicity in these mice in response shRNA treatment was in contrast to what has been previously shown in the liver. Quantifying microRNA profiles after excessive shRNA delivery illuminates the host response to rAAV-shRNA, allowing for safer and more robust therapeutic gene knockdown, and gives us insight into the basic functions of muscle microRNAs.

2019-12-30 | GSE129896 | GEO

Sub-genomewide shRNAs constructed using an optimized selection algorithm and microRNA backbone provide stronger evidence for follow-up studies

2014-11-24 | GSE62185 | GEO

The loop position of shRNAs and pre-miRNAs is critical for the accuracy of Dicer processing in vivo

Project description:Short-hairpin RNA (shRNA)-induced RNAi is used for biological discovery and therapeutics. Dicer, whose normal role is to liberate endogenous miRNAs from their precursors, processes shRNAs into different biologically active siRNAs, affecting their efficacy and potential for off-targeting. We found that in cells, Dicer induced imprecise cleavage events around the expected sites based on the previously described 5'/3'-counting rules. These promiscuous non-canonical cleavages were abrogated when the cleavage site was positioned 2 nt from a bulge or loop. Interestingly, we observed that the ~1/3 of mammalian endogenous pre-miRNAs that contained such structures were more precisely processed by Dicer. Implementing a new "loop-counting rule", we designed potent anti-HCV shRNAs with substantially reduced off-target effects. Our results suggest that Dicer recognizes the loop/bulge structure in addition to the ends of shRNAs/pre-miRNAs for accurate processing. This has important implications for both miRNA processing and future design of shRNAs for RNAi-based genetic screens and therapies.

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