An Analysis and Validation Pipeline for Large-Scale RNAi-Based Screens

Abstract

Large-scale RNAi-based screens are a major technology, but require adequate prioritization and validation of candidate genes from the primary screen. In this work, we performed a large-scale pooled shRNA screen in mouse embryonic stem cells (ESCs) to discover genes associated with oxidative stress resistance and found several candidates. We then developed a bioinformatics pipeline to prioritize these candidates incorporating effect sizes, functional enrichment analysis, interaction networks and gene expression information. To validate candidates, we mixed normal cells with cells expressing the shRNA coupled to a fluorescent protein, which allows control cells to be used as an internal standard, and thus we could detect shRNAs with subtle effects. Although we did not identify genes associated with oxidative stress resistance, as a proof-of-concept of our pipeline we demonstrate a detrimental role of Edd1 silencing in ESC growth. Our methods may be useful for candidate gene prioritization of large-scale RNAi-based screens.