Cells from different tissues have different genetic dependencies, but all share a common set of "core fitness genes" that are required for proliferation. We use this difference between core and context essentials to guide our estimates of screen quality and gene classification, and to identify tumor-specific pathways and targets

New CRISPR technologies enable precise multiplex genetic perturbations, allowing us to go beyond simple single-gene knockouts. We can now begin to explore genetic interaction networks in mammalian cells, as has been done in yeast, and decipher cellular organization as well as discover synthetic lethals.

Genes with correlated knock-out fitness profiles across a diverse set of screens operate in the same biological process or biochemical pathway. But there are many ways to construct these functional interaction networks. Which is best?

See the paper (Gheorghe & Hart) here

Correlation networks integrate functional interactions across all cell states represented in the underlying data. But sometimes those interactions vary across cell states. This variation can give insight into cellular organization and information flow.

We use approaches like these to ask fundamental biological questions about the hierarchical organization of the cell, and to guide the development of new technologies to address the blind spots in our data.

See the paper (Kim et al.) here

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One such blind spot is functional buffering by paralogs, where a single gene knockout shows no phenotype in a CRISPR/Cas9 screen because a closely related gene shoulders the burden.

We used the enCas12a system to perform targeted double knockouts of selected paralogs. By measuring genetic interaction between the gene pairs, we were able to identify dozens of synthetic lethals. For example, in the Cop9 signalosome complex, most subunits are essential but the COPS7A/B genes encode proteins that can substitute for each other.

See the paper (Dede, McLaughlin, et al.) here