1] Department of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, San Francisco, California, USA. [2] Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, California, USA. [3].
1] Department of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research, University of California, San Francisco, San Francisco, California, USA. [2] Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, California, USA. [3] [4].
Nat Protoc. 2014 Aug;9(8):1825-47. doi: 10.1038/nprot.2014.103. Epub 2014 Jul 3.
Systematic genetic interaction maps in microorganisms are powerful tools for identifying functional relationships between genes and for defining the function of uncharacterized genes. We have recently implemented this strategy in mammalian cells as a two-stage approach. First, genes of interest are robustly identified in a pooled genome-wide screen using complex shRNA libraries. Second, phenotypes for all pairwise combinations of 'hit' genes are measured in a double-shRNA screen and used to construct a genetic interaction map. Our protocol allows for rapid pooled screening under various conditions without a requirement for robotics, in contrast to arrayed approaches. Each round of screening can be implemented in ∼2 weeks, with additional time for analysis and generation of reagents. We discuss considerations for screen design, and we present complete experimental procedures, as well as a full computational analysis suite for the identification of hits in pooled screens and generation of genetic interaction maps. Although the protocol outlined here was developed for our original shRNA-based approach, it can be applied more generally, including to CRISPR-based approaches.
系统遗传学相互作用图谱在微生物中是一种强大的工具，可用于鉴定基因之间的功能关系，并定义未鉴定基因的功能。我们最近在哺乳动物细胞中实现了这一策略，采用两阶段方法。首先，使用复杂的 shRNA 文库在全基因组筛选中稳健地鉴定感兴趣的基因。其次，在双 shRNA 筛选中测量所有“命中”基因的成对组合的表型，并用于构建遗传相互作用图谱。与阵列方法不同，我们的方案允许在无需机器人的情况下在各种条件下快速进行 pooled 筛选。每轮筛选可在大约 2 周内完成，另外还需要时间进行分析和生成试剂。我们讨论了筛选设计的注意事项，并提供了完整的实验程序，以及用于鉴定 pooled 筛选中的命中和生成遗传相互作用图谱的完整计算分析套件。虽然这里概述的方案是为我们最初的基于 shRNA 的方法开发的，但它可以更普遍地应用，包括基于 CRISPR 的方法。
