IRescue: uncertainty-aware quantification of transposable elements expression at single cell level

Abstract

Abstract Transposable elements (TEs) are mobile DNA repeats known to shape the evolution of eukaryotic genomes. In complex organisms, they exhibit tissue-specific transcription. However, understanding their role in cellular diversity across most tissues remains a challenge, when employing single-cell RNA sequencing (scRNA-seq), due to their widespread presence and genetic similarity. To address this, we present IRescue (Interspersed Repeats single-cell quantifier), a software capable of estimating the expression of TE subfamilies at the single-cell level. IRescue incorporates a unique UMI deduplication algorithm to rectify sequencing errors and employs an Expectation-Maximization procedure to effectively redistribute the counts of multi-mapping reads. Our study showcases the precision of IRescue through analysis of both simulated and real single cell and nuclei RNA-seq data from human colorectal cancer, brain, skin aging, and PBMCs during SARS-CoV-2 infection and recovery. By linking the expression patterns of TE signatures to specific conditions and biological contexts, we unveil insights into their potential roles in cellular heterogeneity and disease progression.