Mapping context-dependent genetic interaction networks and the impact of functional variation with CRISPR-based platforms

Abstract

CRISPR-based technologies allow systematic interrogation of biological systems. By perturbing genetic sequences or modulating the expression of a gene and then observing the resulting effects, we can gain an understanding of the function of those elements. In this work, I use two CRISPR-based platforms, dual delivery of CRISPRi sgRNAs and prime editing, to systematically interrogate genetic interactions and the effects of genetic variation on cell fitness. My first section considers how genetic interaction measurements contribute to an overall understanding of biological pathways. Genetic interactions are a quantitative measurement that define how genes relate to each other within a biological context, and measuring a large set of interaction measurements for a single gene can act as a quantitative profile of that gene’s function. I used a dual-sgRNA CRISPRi-based platform to measure nearly 150,000 genetic interactions involving 543 genes across two conditions, with and without the presence of a DNA damaging agent (a chemotherapeutic called a PARP inhibitor, or PARPi). This work identified previously unknown roles for genes across many subnetworks in the DNA damage response pathway and revealed the specific architecture of cellular response to PARP inhibitors. In my second section, I design and test a new high-efficiency prime editing platform for generalized applications. Genetic variation plays a large role in disease risk and phenotypic heterogeneity, but our understanding of the functional consequences of individual variants, and our ability to experimentally assess them, is limited. Prime editing, a recently developed gene editing tool, allows the precise manipulation of genomic DNA, but to date its adaptation has been hindered by low editing efficiencies. Here, I present a new prime editing platform capable of generally high efficiency editing across genomic loci, enabling large-scale systematic interrogation of genetic variation. Using this platform, I interrogate the phenotypic consequences of more than 30,000 genetic variants and define features that influence prime editing efficiencies. The new platform described here can be used for widespread applications to assess genetic variants, biological processes, factors modulating prime editing efficiencies, and genomic DNA more generally.