Improved discovery of genetic interactions using CRISPRiSeq across multiple environments
- Mia Jaffe1,
- Adam Dziulko2,3,4,
- Justin D. Smith5,6,
- Robert P. St.Onge5,6,
- Sasha F. Levy1,2,3,4,7 and
- Gavin Sherlock1
- 1Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA;
- 2Joint Initiative for Metrology in Biology, Stanford, California 94305, USA;
- 3SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA;
- 4Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, USA;
- 5Stanford Genome Technology Center, Stanford University, Palo Alto, California 94305, USA;
- 6Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305, USA;
- 7National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
Abstract
Large-scale genetic interaction (GI) screens in yeast have been invaluable for our understanding of molecular systems biology and for characterizing novel gene function. Owing in part to the high costs and long experiment times required, a preponderance of GI data has been generated in a single environmental condition. However, an unknown fraction of GIs may be specific to other conditions. Here, we developed a pooled-growth CRISPRi-based sequencing assay for GIs, CRISPRiSeq, which increases throughput such that GIs can be easily assayed across multiple growth conditions. We assayed the fitness of approximately 17,000 strains encompassing approximately 7700 pairwise interactions in five conditions and found that the additional conditions increased the number of GIs detected nearly threefold over the number detected in rich media alone. In addition, we found that condition-specific GIs are prevalent and improved the power to functionally classify genes. Finally, we found new links during respiratory growth between members of the Ras nutrient–sensing pathway and both the COG complex and a gene of unknown function. Our results highlight the potential of conditional GI screens to improve our understanding of cellular genetic networks.
Footnotes
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.246603.118.
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Freely available online through the Genome Research Open Access option.
- Received November 19, 2018.
- Accepted February 13, 2019.
This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.
