Dual gene activation and knockout screen reveals directional dependencies in genetic networks

• Type of Material: Article
• Authors: Michael Boettcher, University of California San Francisco; Ruilin Tian, University of California San Francisco; James A. Blau, University of California San Francisco; Evan Markegard, University of California San Francisco; Ryan T. Wagner, University of California San Francisco; David Wu, University of California San Francisco; Xiulei Mo, Emory University; Anne Biton, University of California San Francisco; Noah Zaitlen, University of California San Francisco; Haian Fu, Emory University; Frank McCormick, University of California San Francisco; Martin Kampmann, University of California San Francisco; Michael T. McManus, University of California San Francisco
• Language: English
• Date: 2018-02-01
• Publisher: Nature Research (part of Springer Nature)
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2018 Nature America, Inc., part of Springer Nature. All rights reserved.
• Final Published Version (URL): http://dx.doi.org/10.1038/nbt.4062
• Title of Journal or Parent Work: Nature Biotechnology
• ISSN: 1087-0156
• Volume: 36
• Issue: 2
• Start Page: 170
• End Page: +
• Grant/Funding Information: J.B. was supported by NIH Training grant T32 GM00715 and an AFPE Predoctoral Fellowship.; M.T.M. was supported by NIH/CTD2 (U01CA168370) and IDG (1U01MH105028).; M.K. was supported by NIH/NIGMS New Innovator Award DP2 GM119139, NIH/NCI K99/R00 CA181494, a Stand Up to Cancer Innovative Research Grant and the Chan Zuckerberg Biohub.; H.F. was supported by NIH/CTD2 (U01CA168449).
• Keywords: Life Sciences & Biomedicine; CANCER; CRISPR; CHRONIC MYELOID-LEUKEMIA; MAMMALIAN-CELLS; Science & Technology; IN-VIVO; INTERACTION MAP; Biotechnology & Applied Microbiology; KINASE; PROTEIN-TYROSINE-PHOSPHATASE; IMATINIB; BCR-ABL
• Research Categories: Health Sciences, Pharmacology; Biology, Microbiology

Abstract

Understanding the direction of information flow is essential for characterizing how genetic networks affect phenotypes. However, methods to find genetic interactions largely fail to reveal directional dependencies. We combine two orthogonal Cas9 proteins from Streptococcus pyogenes and Staphylococcus aureus to carry out a dual screen in which one gene is activated while a second gene is deleted in the same cell. We analyze the quantitative effects of activation and knockout to calculate genetic interaction and directionality scores for each gene pair. Based on the results from over 100,000 perturbed gene pairs, we reconstruct a directional dependency network for human K562 leukemia cells and demonstrate how our approach allows the determination of directionality in activating genetic interactions. Our interaction network connects previously uncharacterized genes to well-studied pathways and identifies targets relevant for therapeutic intervention.