Characterizing genetic interactions in humans, including synthetic lethal interactions, can provide fundamental insight into protein functions and pathway interactions. However, it can also assist in the development of innovative therapeutic strategies by uncovering novel drug targets used to combat diseases like cancer. To expedite the discovery of novel synthetic lethal interactions in humans, cross-species candidate gene approaches rely on the evolutionary conservation of genetic interactions between organisms. Here, we provide a guide that couples bioinformatic approaches and publicly available datasets from model organisms with cross-species approaches to expedite the identification of candidate synthetic lethal interactions to test in humans. First, we detail a method to identify relevant genetic interactions in budding yeast and subsequently provide a prioritization scheme to identify the most promising yeast interactions to pursue. Finally, we provide details on the tools and approaches used to identify the corresponding human orthologs to ultimately generate a testable network of candidate human synthetic lethal interactions. In summary, this approach leverages publicly available resources and datasets to expedite the identification of conserved synthetic lethal interactions in humans.

• PMID: 34590273
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Journal Article | Research Support, Non-U.S. Gov't

Authors

Jeusset LM, McManus KJ

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