Identification and characterization of essential genes in the human genome

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Science  27 Nov 2015:
Vol. 350, Issue 6264, pp. 1096-1101
DOI: 10.1126/science.aac7041

Zeroing in on essential human genes

More powerful genetic techniques are helping to define the list of genes required for the life of a human cell. Two papers used the CRISPR genome editing system and a gene trap method in haploid human cells to screen for essential genes (see the Perspective by Boone and Andrews). Wang et al.'s analysis of multiple cell lines indicates that it may be possible to find tumor-specific dependencies on particular genes. Blomen et al. investigate the phenomenon in which nonessential genes are required for fitness in the absence of another gene. Hence, complexity rather than robustness is the human strategy.

Science, this issue p. 1096 and p. 1092; see also p. 1028


Large-scale genetic analysis of lethal phenotypes has elucidated the molecular underpinnings of many biological processes. Using the bacterial clustered regularly interspaced short palindromic repeats (CRISPR) system, we constructed a genome-wide single-guide RNA library to screen for genes required for proliferation and survival in a human cancer cell line. Our screen revealed the set of cell-essential genes, which was validated with an orthogonal gene-trap–based screen and comparison with yeast gene knockouts. This set is enriched for genes that encode components of fundamental pathways, are expressed at high levels, and contain few inactivating polymorphisms in the human population. We also uncovered a large group of uncharacterized genes involved in RNA processing, a number of whose products localize to the nucleolus. Last, screens in additional cell lines showed a high degree of overlap in gene essentiality but also revealed differences specific to each cell line and cancer type that reflect the developmental origin, oncogenic drivers, paralogous gene expression pattern, and chromosomal structure of each line. These results demonstrate the power of CRISPR-based screens and suggest a general strategy for identifying liabilities in cancer cells.

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