The most widely used approach for defining gene function is to reduce or completely disrupt its normal expression. For over a decade, RNAi has ruled the lab, offering a magic bullet to disrupt gene expression in many organisms. However, new biotechnological tools--specifically CRISPR-based technologies--have become available and are squeezing out RNAi dominance in mammalian cell studies. These seemingly competing technologies leave research investigators with the question: "Which technology should I use in my experiment?" This review offers a practical resource to compare and contrast these technologies, guiding the investigator when and where to use this fantastic array of powerful tools.

Understanding the direction of information flow is essential for characterizing how genetic networks affect phenotypes. However, methods to find genetic interactions largely fail to reveal directional dependencies. We combine two orthogonal Cas9 proteins from Streptococcus pyogenes and Staphylococcus aureus to carry out a dual screen in which one gene is activated while a second gene is deleted in the same cell. We analyze the quantitative effects of activation and knockout to calculate genetic interaction and directionality scores for each gene pair. Based on the results from over 100,000 perturbed gene pairs, we reconstruct a directional dependency network for human K562 leukemia cells and demonstrate how our approach allows the determination of directionality in activating genetic interactions. Our interaction network connects previously uncharacterized genes to well-studied pathways and identifies targets relevant for therapeutic intervention.

Macrophages are critical effector cells of the immune system, and understanding genes involved in their viability and function is essential for gaining insights into immune system dysregulation during disease. We use a high-throughput, pooled-based CRISPR-Cas screening approach to identify essential genes required for macrophage viability. In addition, we target 3' UTRs to gain insights into previously unidentified cis-regulatory regions that control these essential genes. Next, using our recently generated nuclear factor κB (NF-κB) reporter line, we perform a fluorescence-activated cell sorting (FACS)-based high-throughput genetic screen and discover a number of previously unidentified positive and negative regulators of the NF-κB pathway. We unravel complexities of the TNF signaling cascade, showing that it can function in an autocrine manner in macrophages to negatively regulate the pathway. Utilizing a single complex library design, we are capable of interrogating various aspects of macrophage biology, thus generating a resource for future studies.