Dana-Farber Cancer Institute, Department of Medical Oncology, Boston, MA 02215, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02215, USA.
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Cell Syst. 2022 Apr 20;13(4):286-303.e10. doi: 10.1016/j.cels.2021.12.005. Epub 2022 Jan 31.
In high-throughput functional genomic screens, each gene product is commonly assumed to exhibit a singular biological function within a defined protein complex or pathway. In practice, a single gene perturbation may induce multiple cascading functional outcomes, a genetic principle known as pleiotropy. Here, we model pleiotropy in fitness screen collections by representing each gene perturbation as the sum of multiple perturbations of biological functions, each harboring independent fitness effects inferred empirically from the data. Our approach (Webster) recovered pleiotropic functions for DNA damage proteins from genotoxic fitness screens, untangled distinct signaling pathways upstream of shared effector proteins from cancer cell fitness screens, and predicted the stoichiometry of an unknown protein complex subunit from fitness data alone. Modeling compound sensitivity profiles in terms of genetic functions recovered compound mechanisms of action. Our approach establishes a sparse approximation mechanism for unraveling complex genetic architectures underlying high-dimensional gene perturbation readouts.
在高通量功能基因组筛选中，通常假设每个基因产物在定义明确的蛋白质复合物或途径中表现出单一的生物学功能。实际上，单个基因扰动可能会引发多个级联的功能后果，这是一个被称为多效性的遗传原理。在这里，我们通过将每个基因扰动表示为多个生物功能扰动的总和来模拟适应性筛选集中的多效性，每个功能扰动都具有从数据中经验推断出的独立适应性效应。我们的方法（Webster）从遗传毒性适应性筛选中恢复了 DNA 损伤蛋白的多效性功能，从癌症细胞适应性筛选中分离了共享效应蛋白上游的不同信号通路，并仅从适应性数据预测了未知蛋白质复合物亚基的化学计量比。根据遗传功能对化合物敏感性谱进行建模，恢复了化合物的作用机制。我们的方法建立了一种稀疏逼近机制，用于揭示高维基因扰动读数背后复杂的遗传结构。
