Direct measurement of engineered cancer mutations and their transcriptional phenotypes in single cells.
Heon Seok KimSusan M GrimesTianqi ChenAnuja SatheBilly T LauGue-Ho HwangSangsu BaeHanlee P JiPublished in: Nature biotechnology (2023)
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.
Keyphrases
- single cell
- rna seq
- gene expression
- high throughput
- induced apoptosis
- genome wide
- cell cycle arrest
- dna methylation
- squamous cell carcinoma
- transcription factor
- crispr cas
- oxidative stress
- endoplasmic reticulum stress
- cell death
- single molecule
- poor prognosis
- signaling pathway
- long non coding rna
- genome editing
- squamous cell
- pi k akt
- case control
- heat stress