@article {Hart015412, author = {Traver Hart and Megha Chandrashekhar and Michael Aregger and Zachary Steinhart and Kevin R. Brown and Stephane Angers and Jason Moffat}, title = {Systematic discovery and classification of human cell line essential genes}, elocation-id = {015412}, year = {2015}, doi = {10.1101/015412}, publisher = {Cold Spring Harbor Laboratory}, abstract = {The study of gene essentiality in human cells is crucial for elucidating gene function and holds great potential for finding therapeutic targets for diseases such as cancer. Technological advances in genome editing using clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 systems have set the stage for identifying human cell line core and context-dependent essential genes. However, first generation negative selection screens using CRISPR technology demonstrate extreme variability across different cell lines. To advance the development of the catalogue of human core and context-dependent essential genes, we have developed an optimized, ultracomplex, genome-scale gRNA library of 176,500 guide RNAs targeting 17,661 genes and have applied it to negative and positive selection screens in a human cell line. Using an improved Bayesian analytical approach, we find CRISPR-based screens yield double to triple the number of essential genes than were previously observed using systematic RNA interference, including many genes at moderate expression levels that are largely refractory to RNAi methods. We further characterized four essential genes of unknown significance and found that they all likely exist in protein complexes with other essential genes. For example, RBM48 and ARMC7 are both essential nuclear proteins, strongly interact and are commonly amplified across major cancers. Our findings suggest the CRISPR-Cas9 system fundamentally alters the landscape for systematic reverse genetics in human cells for elucidating gene function, identifying disease genes, and uncovering therapeutic targets.}, URL = {https://www.biorxiv.org/content/early/2015/02/18/015412}, eprint = {https://www.biorxiv.org/content/early/2015/02/18/015412.full.pdf}, journal = {bioRxiv} }