Technological advancement has opened the door to systematic genetics in mammalian cells. Genome‐scale loss‐of‐function screens can assay fitness defects induced by partial gene knockdown, using RNA interference, or complete gene knockout, using new CRISPR techniques. These screens can reveal the basic blueprint required for cellular proliferation. Moreover, comparing healthy to cancerous tissue can uncover genes that are essential only in the tumor; these genes are targets for the development of specific anticancer therapies. Unfortunately, progress in this field has been hampered by off‐target effects of perturbation reagents and poorly quantified error rates in large‐scale screens. To improve the quality of information derived from these screens, and to provide a framework for understanding the capabilities and limitations of CRISPR technology, we derive gold‐standard reference sets of essential and nonessential genes, and provide a Bayesian classifier of gene essentiality that outperforms current methods on both RNAi and CRISPR screens. Our results indicate that CRISPR technology is more sensitive than RNAi and that both techniques have nontrivial false discovery rates that can be mitigated by rigorous analytical methods.

Mutations at the mouse W/c-kit locus lead to intrinsic defects in stem cells of the melanocytic, hematopoietic, and germ cell lineages. W alleles vary in the overall severity of phenotype that they confer, and some alleles exhibit an independence of pleiotropic effects. To elucidate the molecular basis for these biological differences, we analyzed the c-kit locus and the c-kit-associated autophosphorylation activities in five different W mutants representative of a range of W phenotypes. Mast cell cultures derived from mice or embryos homozygous for each W allele were deficient in c-kit autophosphorylation activity, the extent of which paralleled the severity of phenotype conferred by a given W allele both in vivo and in an in vitro mast cell coculture assay. The mildly dominant, homozygous viable alleles W44 and W57 were found to express reduced levels of an apparently normal c-kit protein. In contrast, c-kit kinase defects conferred by the moderately dominant, homozygous viable alleles W41 or W55 or the homozygous lethal allele, W37, were attributed to single-point mutations within the kinase domain of the c-kit polypeptide, which result in point substitutions of amino acid residues highly conserved in the family of protein tyrosine kinases. The nature and location of these amino acid substitutions account for the relative severity of phenotypes conferred by these W alleles and demonstrate that the pleiotropic developmental defects associated with the W/c-kit locus arise as the result of dominant loss-of-function mutations in a transmembrane receptor tyrosine kinase.

Genomic analyses are yielding a host of new information on the multiple genetic abnormalities associated with specific types of cancer. A comprehensive description of cancer-associated genetic abnormalities can improve our ability to classify tumors into clinically relevant subgroups and, on occasion, identify mutant genes that drive the cancer phenotype (“drivers”). More often, though, the functional significance of cancer-associated mutations is difficult to discern. Genome-wide pooled short hairpin RNA (shRNA) screens enable global identification of the genes essential for cancer cell survival and proliferation, providing a “functional genomic” map of human cancer to complement genomic studies. Using a lentiviral shRNA library targeting ∼16,000 genes and a newly developed, dynamic scoring approach, we identified essential gene profiles in 72 breast, pancreatic, and ovarian cancer cell lines. Integrating our results with current and future genomic data should facilitate the systematic identification of drivers, unanticipated synthetic lethal relationships, and functional vulnerabilities of these tumor types. Significance: This study presents a resource of genome-scale, pooled shRNA screens for 72 breast, pancreatic, and ovarian cancer cell lines that will serve as a functional complement to genomics data, facilitate construction of essential gene profiles, help uncover synthetic lethal relationships, and identify uncharacterized genetic vulnerabilities in these tumor types. Cancer Discovery; 2(2); 172–89. © 2011 AACR. This article is highlighted in the In This Issue feature, p. 95.