ArticleMobile DNA2026
scTELL: a single-cell ATAC-seq tool for locus-specific transposable element identification in chromatin accessibility.
Article in Mobile DNA, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTransposable 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.
resultsscTELL (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.
conclusionsscTELL 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.