Datasets Used in Evaluation Of RNAi And CRISPR Technologies By Large Scale Gene Expression Profiling In The Connectivity Map

This GEO Series contains datasets used in the paper "Evaluation Of RNAi And CRISPR Technologies By Large Scale Gene Expression Profiling In The Connectivity Map". The application of RNA interference (RNAi) to mammalian cells has provided the means to perform phenotypic screens to determine the functions of genes. Although RNAi has revolutionized loss of function genetic experiments, it has been difficult to systematically assess the prevalence and consequences of off-target effects. The Connectivity Map (CMAP) represents an unprecedented resource to study the gene expression consequences of expressing short hairpin RNAs (shRNAs). Analysis of signatures for over 13,000 shRNAs applied in 9 cell lines revealed that miRNA-like off-target effects of RNAi are far stronger and more pervasive than generally appreciated. We show that mitigating off-target effects is feasible in these datasets via computational methodologies to produce a Consensus Gene Signature (CGS). In addition, we compared RNAi technology to clustered regularly interspaced short palindromic repeat (CRISPR)-based knockout by analysis of 373 sgRNAs in 6 cells lines, and show that the on-target efficacies are comparable, but CRISPR technology is far less susceptible to systematic off-target effects. These results will help guide the proper use and analysis of loss-of-function reagents for the determination of gene function. Note: Related GEO projects include a large corpus of additional L1000 data, available at GSE92742. The Platform is GPL20573: Broad Institute Human L1000 epsilon https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL20573 For questions or assistance with this dataset, please email the CMap support team at: [e-mail] The datasets in this Series were generated as part of the LINCS project, which aims to enable a functional understanding of biology by cataloging changes in gene expression and other cellular processes that occur when cells are exposed to a variety of perturbing agents. The Broad Institute LINCS Center for Transcriptomics contributes to this collaborative effort by application of the Connectivity Map concept. In brief, the study design involves the generation of a compendium of transcriptional expression data from cultured human cells treated with small-molecule and genetic loss/gain of function perturbagens. These measurements are made using the L1000 high-throughput gene-expression assay that enables data generation at an unprecedented scale. The data provided here include Levels 4 and 5, as well as additional data described in the README: Level 4 (Z-SCORES) - signatures with differentially expressed genes computed by robust z-scores for each profile relative to control (PC relative to plate population as control; VC relative to vehicle control). Level 5 (SIG) consists of the replicates, usually 3 per treatment, aggregated into a single differential expression vector derived from the weighted averages of the individual replicates. For more data levels and their descriptions, please consult GSE92742.