scTraitReg: a single-cell multi-omic database of trait-relevant transcription factor eRegulons

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ID: 333197
2026
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Abstract
Abstract Genome-wide association studies (GWAS) identify loci associated with human diseases and disease-related traits, but the regulators and cellular contexts linked to these signals remain difficult to resolve. We present scTraitReg, a database of trait-relevant transcription factor (TF) eRegulons—TFs with their target genes and linked cis-regulatory regions—at single-cell resolution. scTraitReg integrates 655 sets of curated GWAS summary statistics covering 122 Medical Subject Headings (MeSH) disease terms with 111 human single-cell multi-omic datasets profiling RNA and chromatin accessibility in the same cells. The resource spans 34 tissues, 252 cell types, 2 081 538 cells, and 2208 curated GWAS—single-cell analysis pairs. Across these analyses, it contains 2 840 939 TF–cell-type records for 886 regulators; 67 666 records met all three criteria—cell-type specificity, genetic relevance, and the trait-associated regulon score—and were included as candidate trait-relevant eRegulon records. Each record links to the TF—target regulatory network with its cis-regulatory regions, cell-type-resolved evidence, per-cell regulon module scores, and target-gene enrichment, all available as downloadable tables. Users can search by disease, tissue, cell type, or regulator and examine these associations through interactive visualizations. scTraitReg thus provides a searchable and reusable resource linking genetic associations to cell-type-specific regulatory programs, and is freely available at https://www.sctraitreg.bio/.
Reference Key
openalex_W7223182884 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Haoran Chen, Yin Liu, Xue Rui, Shengxian Li, Lingna Sun, Guoli Xiao, Haozhe Tang, Yanqun Sun, Xiang Guan, Chen Cao
Journal Nucleic Acids Research
Year 2026
DOI
10.1093/nar/gkag1017
URL
https://doi.org/10.1093/nar/gkag1017
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