Splicing-aware scRNA-Seq resolution reveals execution-ready programs in effector Tregs

TL;DR

A new method called SANSARA improves scRNA-Seq analysis by considering spliced and unspliced mRNA, revealing hidden features in immune cells like Tregs.

Contribution

SANSARA introduces splicing-aware analysis to scRNA-Seq, uncovering new insights into cell states and functions.

Findings

Effector Tregs have high levels of spliced mRNAs for genes like IL10RA, CD38, and LFA-1, indicating readiness for function.

FOXP3 and Helios show complementary splicing patterns in Tregs, suggesting coordinated regulation.

SANSARA reveals splicing heterogeneity in Th1 and cytotoxic CD4+ T cell subsets.

Abstract

Single-cell RNA sequencing (scRNA-Seq) provides valuable insights into cell biology. However, current scRNA-Seq analytic approaches do not distinguish between spliced and unspliced mRNA at the level of dimensionality reduction. 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 translationally repressed spliced mRNA (e.g., in P-bodies) and/or unspliced mRNA reservoirs for prompt initiation of transcription-independent expression. Thus, functional cell subsets may differ not only in the current levels of actively produced mRNAs, but also in which mRNAs and in what forms are stored in the nucleus and cytoplasm. To enable splicing-aware analysis of scRNA-Seq data, we developed a method called SANSARA (Splicing-Aware scrNa-Seq AppRoAch). We employed SANSARA to characterize peripheral blood regulatory T cell (Treg) subsets, revealing a complementary interplay between the FOXP3 and Helios master transcription factors and high levels of spliced IL10RA, LGALS3, FCRL3, CD38, ITGAL, and LEF1 mRNAs in effector Tregs. Among Th1 and cytotoxic CD4+ T cell subsets, SANSARA also revealed substantial splicing heterogeneity across subset-specific genes. SANSARA is straightforward to implement in current data analysis pipelines and opens new dimensions for scRNA-Seq-based discoveries.

Single-cell transcriptomics classifies cells by the patterns of genes they express. Most methods, however, treat every RNA message in the same way, even though cells produce RNA in two stages: unspliced (nascent) and spliced (mature and ready to make protein). To provide additional resolution, we developed SANSARA, a splicing-aware analysis that uses this extra layer of information to sharpen how we read cellular states.

We applied SANSARA to human regulatory T cells (Tregs) – immune cells that prevent harmful inflammation – which uncovered features that were missed by splicing-unaware analysis. SANSARA revealed unexpectedly complementary splicing behavior of genes encoding FOXP3 and Helios, the two major Treg transcription factors. Effector Tregs were enriched for mature, translation-ready transcripts encoding key functionality, including MHC-II – antigen-presentation machinery, CD39 and CD38 – contributing to the generation of immunosuppressive adenosine, LFA-1 – stabilizes Treg interactions with dendritic cells, LEF1 – transcription factor that cooperates with FOXP3, and IL10RA – receptor that forms a feed-forward loop with IL-10, also produced by Tregs.

This splicing-aware view provides a clearer picture of immune function and uncovers mechanisms that standard approaches often overlook. SANSARA transforms the interpretation of single-cell transcriptomics data and can be broadly applied to other cell types and diseases to deepen biological insight and guide target discovery.

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