Splicing-aware resolution of scRNA-Seq data

Abstract

Single-cell RNA sequencing (scRNA-Seq) provides invaluable insights in cell biology. Current scRNA-Seq analytic approaches do not distinguish between spliced and unspliced mRNA. RNA velocity paradigm suggests that the presence of unspliced mRNA reflects transitional cell states, informative for studies of dynamic processes such as embryogenesis or tissue regeneration. Alternatively, stable cell subsets may also maintain unspliced mRNA reservoirs for prompt initiation of transcription-independent expression. Based on the latter paradigm, we have developed a method called SANSARA (Splicing-Aware scrNa-Seq AppRoAch) for the splicing-aware analysis of scRNA-Seq data. We employed SANSARA to characterize peripheral blood regulatory T cell (Treg) subsets, revealing the complex interplay between FoxP3 and Helios master transcription factors and other unexpected splicing-informed features. For Th1 and cytotoxic CD4+T cell subsets, SANSARA also revealed substantial splicing heterogeneity across crucial subset-specific genes. SANSARA is straightforward to implement in current data analysis pipelines and opens new dimensions in scRNA-Seq-based discoveries.