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The poster and abstract below were presented at TIDES Europe: Oligonucleotide & Peptide Therapeutics 2019 (Amsterdam, The Netherlands)
RNAi-based library screens provide a powerful approach to identify novel therapeutic targets. These libraries target hundreds of candidate genes using multiple siRNAs (or shRNAs) per gene. Genes for which all (or the majority of) available siRNAs induce a phenotype of interest are considered as hits while individual siRNAs that induce the phenotype are considered to do so through off-target effects. Dozens of such individual siRNAs can be identified from a single screen. While they are typically ignored, they harbour an enormous untapped potential to identify novel candidate therapeutic targets. To reveal these off-target genes, we have applied HTTargetSeq, a novel cost-effective and high-throughput RNA-seq based platform to quantify gene expression directly from crude cell lysates. HTTargetSeq reproducibly detects 5,000-10,000 genes per sample at shallow sequencing depth and enables robust differential gene expression analysis between conditions (siRNA versus control treated cells). To demonstrate the potential of HTTargetSeq for siRNA off-target gene identification, we selected 90 siRNAs that induced the phenotype of interest through presumed off-target effects from an siRNA library screen experiment. Cells were treated with each of these siRNAs in quadruplicate flowed by cell lysis and shallow 3’ end mRNA sequencing. Genes that were significantly downregulated between siRNA and control treated cells were enriched for siRNA seed sequences in their 3’ UTR, confirming off-target behavior. Aggregating results from these 90 siRNAs revealed multiple off-target genes that were identified across 10 or more conditions. Several of these recurrent off-target genes were either known to induce the phenotype or were interaction partners of other genes known to induce the phenotype. Taken together, HTTargetSeq can be applied to repurpose off-target siRNA hits from library screens to reveal novel candidate therapeutic targets for drug development.