Heon Seok Kim 1,2,3, Susan M. Grimes 1, Tianqi Chen 1, Anuja Sathe 1, Billy T. Lau 1, Gue-Ho Hwang 4, Sangsu Bae 4,5 & Hanlee P. Ji 1,6,*
1Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
2Department of Life Science, College of Natural Sciences, Hanyang University, Seoul, Republic of Korea.
3Hanyang Institute of Bioscience and Biotechnology, Hanyang University, Seoul, Republic of Korea.
4Medical Research Center of Genomic Medicine Institute, Seoul National University College of Medicine, Seoul, Republic of Korea.
5Department of Biochemistry and Molecular Biology, Seoul National University College of Medicine, Seoul, Republic of Korea.
6Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
*Corresponding author: correspondence to Hanlee P. Ji
Genome sequencing studies have identified numerous cancer mutations across a wide spectrum of tumor types, but determining the phenotypic consequence of these mutations remains a challenge. Here, we developed a high-throughput, multiplexed single-cell technology called TISCC-seq to engineer predesignated mutations in cells using CRISPR base editors, directly delineate their genotype among individual cells and determine each mutation’s transcriptional phenotype. Long-read sequencing of the target gene’s transcript identifies the engineered mutations, and the transcriptome profile from the same set of cells is simultaneously analyzed by short-read sequencing. Through integration, we determine the mutations’ genotype and expression phenotype at single-cell resolution. Using cell lines, we engineer and evaluate the impact of >100 TP53 mutations on gene expression. Based on the single-cell gene expression, we classify the mutations as having a functionally significant phenotype.