Transposable elements (TEs) constitute a substantial fraction of the human genome and contribute to gene regulatory programs. However, systematic analysis of TEs at the individual locus level remains technically challenging, particularly in single-cell contexts. While single-cell technologies have advanced the study of cellular heterogeneity, most analytical frameworks remain gene-centric. Existing TE-focused approaches are largely restricted to transcriptional profiling using scRNA-seq data, while analyses of single-cell chromatin accessibility have focused primarily on aggregate or family-level TE signals rather than individual loci. Consequently, no dedicated computational framework exists for quantifying chromatin accessibility at individual TE loci from scATAC-seq data, limiting investigation of locus-specific TE regulatory activity at single-cell resolution. scTELL (single-cell Transposable Element Locus-Level analysis) is a computational framework that quantifies TE accessibility at individual loci from scATAC-seq data using a distance-weighted scoring scheme. We applied scTELL to diverse biological systems, including healthy peripheral blood mononuclear cells (PBMCs), clear cell renal cell carcinoma (ccRCC), and breast cancer (BC). In PBMCs, scTELL identified distinct cell-type-specific TE accessibility patterns with clustering performance comparable to established gene activity scoring approaches, and validated key TE accessibility patterns using bulk ATAC-seq data from sorted immune cell populations. Motif enrichment analyses of TE-associated accessible regions revealed distinct TF motif landscapes, including family-level motif signatures, within-family locus heterogeneity across cell types, and motifs enriched in TE-associated regions relative to gene promoters. In cancer contexts, scTELL identified heterogeneity-associated TE loci and observed clinically associated accessibility patterns, including an L1PA2 locus in ccRCC associated with progression-free interval, and survival-associated TE loci in BC. scTELL provides a much-needed and robust tool to investigate the locus-specific regulatory landscape of TEs at single-cell resolution. Our findings demonstrate that this approach can uncover previously unrecognized cell-type-specific and disease-associated TE accessibility. The scTELL framework offers a new layer of biological insight, complementing existing single-cell analysis protocols and enabling the discovery of candidate biomarkers from a vast, understudied portion of the genome. While these associations are reproducible across datasets, prospective validation and functional studies will be required to establish clinical utility and to determine whether any locus has a causal role or therapeutic relevance.
Jeong et al. (Tue,) studied this question.