Abstract
Small interfering RNAs (siRNAs) exhibit strong off-target effects, which confound the gene-level interpretation of RNA interference screens and thus limit their utility for functional genomics studies. Here, we present gespeR, a statistical model for reconstructing individual, gene-specific phenotypes. Using 115,878 siRNAs, single and pooled, from three companies in three pathogen infection screens, we demonstrate that deconvolution of image-based phenotypes substantially improves the reproducibility between independent siRNA sets targeting the same genes. Genes selected and prioritized by gespeR are validated and shown to constitute biologically relevant components of pathogen entry mechanisms and TGF-β signaling. gespeR is available as a Bioconductor R-package.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0783-1) contains supplementary material, which is available to authorized users.
Highlights
The discovery of RNA interference (RNAi) brought the exciting prospect of targeted gene interventions for detailed characterization of biological processes to the functional genomics community
We focused on decreased Infectivity phenotypes, the phenotype of primary interest for follow-up studies indicating a repressive role in pathogen infection. gene-specific phenotype estimator (gespeR) identified 37 significantly enriched pathways in total for all studied pathogens, including a number of pathways exclusively enriched for gene-specific phenotype (GSP), which were previously reported to play a role in infection [23, 24], such as focal adhesion, integrin-signaling, and transforming growth factor (TGF)-β signaling
Despite substantial evidence of sequence-dependent, miRNA-like off-target silencing in RNAi screens [14], the problem has been widely ignored in the field of functional genomics for a long time
Summary
The discovery of RNA interference (RNAi) brought the exciting prospect of targeted gene interventions for detailed characterization of biological processes to the functional genomics community. Phenotypic readouts of RNAi knockdown experiments using distinct reagents targeting the same gene exhibit poor reproducibility [1,2,3]. For siRNAs, this lack of reproducibility is largely due to sequence-dependent off-target effects. The intended on-target gene is silenced through full complementarity of the siRNA to the open reading frame (ORF) of its transcript. Each siRNA, silences hundreds of additional off-target genes, which has been shown in vitro [4] and in silico (Additional file 1). Using the microRNA (miRNA) pathway, the set of off-target genes of an siRNA is mainly determined by
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