Genome editing has revolutionized our ability to manipulate the properties of the human cell and interrogate its mechanisms. However, to match the complexity of the cellular ecosystem, this interrogation needs to be done at scale. Here, we will present our approaches to optimize the throughput of genome editing for the fluorescent tagging of endogenous proteins, and introduce our OpenCell collection of >1,200 GFP-tagged HEK293T cell lines combining live-cell imaging and interaction proteomics. But while knock-in of new functions into the genome by homology-directed repair (HDR) is powerful, our lack of precise understanding of what governs the efficiency and precision of HDR hinders its scalability. To address this limitation, we carried out a systematic and quantitative profiling of the knock-in integration landscape by combining long-read sequencing with a novel computational pipeline (knock-knock). Our data uncover complex repair profiles, with perfect HDR often accounting for a minority of payload integration events, and distinct mis-integration patterns between cell-types or HDR donor-types. Altogether, this comprehensive framework paves the way for investigating repair mechanisms, monitoring accuracy, and optimizing the precision of genome engineering.
Deep Profiling of Repair Outcomes in CRISPR Knock-In:
A Gateway to High-Throughput Cell Biology
Dr. Manuel Leonetti (left)
Group Leader, Cell Atlas Initiative
Chan Zuckerberg Biohub
Dr. Jeff Hussmann (right)
Postdoctoral Scholar, Microbiology and Immunology
UCSF School of Medicine
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