Genetic effects on liver chromatin accessibility identify disease regulatory variants

Abstract

Identifying the molecular mechanisms by which genome-wide association study (GWAS) loci influence traits remains challenging. Chromatin accessibility quantitative trait loci (caQTLs) help identify GWAS loci that may alter GWAS traits by modulating chromatin structure, but caQTLs have been identified in a limited set of human tissues. Here we mapped caQTLs in human liver tissue in 20 liver samples and identified 3,123 caQTLs. The caQTL variants are enriched in liver tissue promoter and enhancer states and frequently disrupt binding motifs of transcription factors expressed in liver. We predicted target genes for 861 caQTL peaks using proximity, chromatin interactions, correlation with promoter accessibility or gene expression, and colocalization with expression QTLs. Using GWAS signals for 19 liver function and/or cardiometabolic traits, we identified 110 colocalized caQTLs and GWAS signals, 56 of which contained a predicted caPeak target gene. At the LITAF LDL-cholesterol GWAS locus, we validated that a caQTL variant showed allelic differences in protein binding and transcriptional activity. These caQTLs contribute to the epigenomic characterization of human liver and help identify molecular mechanisms and genes at GWAS loci.

Cell-specific chromatin landscape of human coronary artery resolves regulatory mechanisms of disease risk

“…Chromatin accessibility quantitative trait locus (caQTL) mapping is a powerful association analysis to resolve candidate GWAS regulatory mechanisms 67–72 . We thus calculated caQTLs in our dataset in four major coronary cell types (SMC, macrophages, fibroblasts, and endothelial cells).…”

From Reads to Insights: Integrative Pipelines for Biological Interpretation of ATAC-Seq Data

“…For example, the integration of genotype and ATAC-seq modalities to identify quantitative trait loci for chromatin accessibility (caQTLs) has been recently used to evaluate genetic effects on chromatin accessibility [20] . caQTLs have been applied to the fine mapping of causal variants in noncoding chromatin accessible regions in multiple cell lines and tissues, such as blood [21] , liver [22] , and brain [23] , furthering our understanding of regulatory mechanisms in human diseases at the tissue or cell type-specific levels. We expect more ATAC-seq-specific analytic tools to be developed in the future.…”

Systematic analysis of the effects of genetic variants on chromatin accessibility to decipher functional variants in non-coding regions

“…We then investigated whether TFs are more likely to bind the more accessible allele. TFs are theoretically more likely to bind the alleles with higher accessibility ( 31 ). In our results, more than half of the 406 motifs of 377 expressed TFs (59.9%) bind the alleles with more accessibility better.…”

“…Only the most significant match per allele and the match that overlapped with the caQTL position was retained. The log ratio of p -values defined as lg(p_weak) - lg(p_strong) was used for quantifying the difference in motif match between alleles ( 31 ), where the p_weak and the p_strong stand for the p -values for the alleles with the weaker and stronger match, separately.…”