ArticleAmerican journal of human genetics2025
Characterization of non-coding variants associated with transcription-factor binding through ATAC-seq-defined footprint QTLs in liver.
Article in American journal of human genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- ceQTL: a co-expression QTL model to detect a variant that affects transcription factor binding and its target regulation.Briefings in bioinformatics · 2026Article
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Abstract
Non-coding variants discovered by genome-wide association studies (GWASs) are enriched in regulatory elements harboring transcription factor (TF) binding motifs, strongly suggesting a connection between disease association and the disruption of cis-regulatory sequences. Occupancy of a TF inside a region of open chromatin can be detected in ATAC-seq where bound TFs block the transposase Tn5, leaving a pattern of relatively depleted Tn5 insertions known as a "footprint." Here, we sought to identify variants associated with TF binding, or "footprint quantitative trait loci" (fpQTLs), in ATAC-seq data generated from 170 human liver samples. We used computational tools to scan the ATAC-seq reads to quantify TF binding likelihood as "footprint scores" at variants derived from whole-genome sequencing generated in the same samples. We tested for association between genotype and footprint score and observed 809 fpQTLs associated with footprint-inferred TF binding (FDR < 5%). Given that Tn5 insertion sites are measured with base-pair resolution, we show that fpQTLs can aid GWAS and QTL fine-mapping by precisely pinpointing TF activity within broad trait-associated loci where the underlying causal variant is unknown. Liver fpQTLs were strongly enriched across ChIP-seq peaks, liver expression QTLs (eQTLs), and liver-related GWAS loci, and their inferred effect on TF binding was concordant with their effect on underlying sequence motifs in 78% of cases. We conclude that fpQTLs can reveal causal GWAS variants, define the role of TF binding-site disruption in complex traits, and provide functional insights into non-coding variants, ultimately informing novel treatments for common diseases.
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