Systematic Single Cell Pathway Analysis (SCPA) reveals novel pathways engaged during early T cell activation

Abstract

Next generation sequencing technologies have revolutionized the study of T cell biology, capturing previously unrecognized diversity in cellular states and functions. Pathway analysis is a key analytical stage in the interpretation of such transcriptomic data, providing a powerful method for detecting alterations in important biological processes. Current pathway analysis tools are built on models developed for bulk-RNA sequencing, limiting their effectiveness when applied to more complex single cell RNA-sequencing (scRNA-seq) datasets. We recently developed a sensitive and distribution-free statistical framework for multisample distribution testing, which we implement here in the open-source R package Single Cell Pathway Analysis (SCPA). After demonstrating the effectiveness of SCPA over commonly used methods, we generate a scRNA-seq T cell dataset and characterize pathway activity over early cellular activation and between T cell populations. This revealed unexpected regulatory pathways in T cells, such as an intrinsic type I interferon system regulating T cell survival and a reliance on arachidonic acid metabolism throughout T cell activation. A systems level characterization of pathway activity in T cells across multiple human tissues also revealed alpha defensin expression as a hallmark of bone marrow derived T cells. Overall, our work here provides a widely applicable tool for single cell pathway analysis, and highlights unexpected regulatory mechanisms of T cells using a novel T cell dataset.