Department of Microbiology and Immunology, University of California San Francisco Diabetes Center, WM Keck Center for Noncoding RNAs, University of California, San Francisco, San Francisco, California, USA.
Institute for Neurodegenerative Diseases, Department of Biochemistry and Biophysics, University of California, San Francisco and Chan Zuckerberg Biohub, San Francisco, California, USA.
Nat Biotechnol. 2018 Feb;36(2):170-178. doi: 10.1038/nbt.4062. Epub 2018 Jan 15.
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.
理解信息流的方向对于描述基因网络如何影响表型至关重要。然而,寻找遗传相互作用的方法在很大程度上未能揭示方向依赖性。我们结合了来自酿脓链球菌和金黄色葡萄球菌的两种正交 Cas9 蛋白,以进行双重筛选,其中一个基因被激活,而第二个基因在同一个细胞中被删除。我们分析激活和敲除的定量影响,以计算每个基因对的遗传相互作用和方向性得分。基于超过 100,000 个受干扰的基因对的结果,我们为人类 K562 白血病细胞重建了一个有向依赖网络,并展示了我们的方法如何能够确定激活遗传相互作用的方向。我们的相互作用网络将以前未表征的基因与研究充分的途径联系起来,并确定了与治疗干预相关的靶标。