Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Department of Life Science, College of Natural Sciences, Hanyang University, Seoul, Republic of Korea.
Nat Biotechnol. 2024 Aug;42(8):1254-1262. doi: 10.1038/s41587-023-01949-8. Epub 2023 Sep 11.
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.
基因组测序研究在广泛的肿瘤类型中鉴定了许多癌症突变,但确定这些突变的表型后果仍然是一个挑战。在这里,我们开发了一种称为 TISCC-seq 的高通量、多重化的单细胞技术,使用 CRISPR 碱基编辑器在细胞中设计预定的突变,直接在单个细胞中描绘它们的基因型,并确定每个突变的转录表型。目标基因转录本的长读测序鉴定出工程化的突变,并且同一组细胞的转录组谱同时通过短读测序进行分析。通过整合,我们以单细胞分辨率确定突变的基因型和表达表型。我们使用细胞系设计和评估了 >100 个 TP53 突变对基因表达的影响。基于单细胞基因表达,我们将突变分类为具有功能显著表型。