Project description:We developed SCAN-seq2, a high-throughput and highly sensitive single-cell RNA sequencing method based on the TGS platform. Our study demonstrated that SCAN-seq2 improves upon the previous method, SCAN-seq, in terms of sensitivity and throughput. By using reference-guided assembly of single-cell data, we were able to identify thousands of novel full-length RNA isoforms, including cell type-specific expression patterns of pseudogenes. We also accurately determined V(D)J rearrangement events in T and B cells. Lastly, we found that treatment of HepG2 and Hela cells with the spliceosome inhibitor Isoginkgetin (IGG) resulted in a subpopulation of cells with distinct apoptosis features. Our study provides a promising new tool for single-cell transcriptome research. The source code for SCAN-seq2 data analysis pipelines is available at https://github.com/liuzhenyu-yyy/SCAN-seq2 .
Project description:Transcription profiling of human MOLT4 cell lines before and after inhibition of gamma secretase to investigate NOTCH signaling in T-cell acute lymphoblastic leukemia cell lines