Landscape of transcript isoforms in single T cells infiltrating in non-small-cell lung cancer

Abstract

Single-cell RNA sequencing (scRNA-seq) has enabled high-resolution characterization of molecular signatures of tumor-infiltrating lymphocytes. However, analyses at the transcript isoform level are rarely reported. As alternative splicing is critical to T-cell differentiation and activation, here, we proposed a computational method named IDEA (Isoform Detection, Enrichment, and functional Annotation) to comprehensively detect and annotate differentially used isoforms across cell subtypes. We applied IDEA on a scRNA-seq data set of 12,346 T cells from non-small-cell lung cancer (NSCLC). We found that most genes tend to dominantly express one isoform in single T cells, enabling typing T cells based on the isotypes, given a gene. Isotype analysis suggested that tumor-infiltrating T cells significantly preferred specific isotypes for 245 genes in CD8⁺ T cells and 456 genes in CD4⁺ T cells. Functional annotation suggests that the preferred isoforms involved in coding/noncoding switches, transcription start site changes, gains/losses of domains, and subcellular translocation. Clonal analysis revealed that isoform switching occurred during T-cell activation/differentiation. Our analysis provides precise characterization of the molecular events in tumor-infiltrating T cells and sheds new light on the regulatory mechanisms of tumor-infiltrating T cells.

Keywords: Alternative splicing; RNA-seq; Single-cell; T-cell subtypes.