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/.
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Authors Haoran Chen, Yin Liu, Xue Rui, Shengxian Li, Lingna Sun, Guoli Xiao, Haozhe Tang, Yanqun Sun, Xiang Guan, Chen Cao
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Journal Nucleic Acids Research
Year 2026
DOI
10.1093/nar/gkag1017
URL
https://doi.org/10.1093/nar/gkag1017
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