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Chromatin accessibility and gene expression in relevant cell contexts can guide identification of regulatory elements and mechanisms at genome-wide association study (GWAS) loci. To identify regulatory elements that display differential activity across adipocyte differentiation, we performed ATAC-seq and RNA-seq in a human cell model of preadipocytes and adipocytes at days 4 and 14 of differentiation. For comparison, we created a consensus map of ATAC-seq peaks in 11 human subcutaneous adipose tissue samples. We identified 58,387 context-dependent chromatin accessibility peaks and 3,090 context-dependent genes between all timepoint comparisons (log2 fold change>1, FDR<5%) with 15,919 adipocyte- and 18,244 preadipocyte-dependent peaks. Adipocyte-dependent peaks showed increased overlap (60.1%) with Roadmap Epigenomics adipocyte nuclei enhancers compared to preadipocyte-dependent peaks (11.5%). We linked context-dependent peaks to genes based on adipocyte promoter capture Hi-C data, overlap with adipose eQTL variants, and context-dependent gene expression. Of 16,167 context-dependent peaks linked to a gene, 5,145 were linked by two or more strategies to 1,670 genes. Among GWAS loci for cardiometabolic traits, adipocyte-dependent peaks, but not preadipocyte-dependent peaks, showed significant enrichment (LD score regression P<0.005) for waist-to-hip ratio and modest enrichment (P < 0.05) for HDL-cholesterol. We identified 659 peaks linked to 503 genes by two or more approaches and overlapping a GWAS signal, suggesting a regulatory mechanism at these loci. To identify variants that may alter chromatin accessibility between timepoints, we identified 582 variants in 454 context-dependent peaks that demonstrated allelic imbalance in accessibility (FDR<5%), of which 55 peaks also overlapped GWAS variants. At one GWAS locus for palmitoleic acid, rs603424 was located in an adipocyte-dependent peak linked to SCD and exhibited allelic differences in transcriptional activity in adipocytes (P = 0.003) but not preadipocytes (P = 0.09). These results demonstrate that context-dependent peaks and genes can guide discovery of regulatory variants at GWAS loci and aid identification of regulatory mechanisms., Competing Interests: The authors have declared that no competing interests exist.

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., (Copyright © 2021 American Society of Human Genetics. All rights reserved.)

Identifying the regulatory mechanisms of genome-wide association study (GWAS) loci affecting adipose tissue has been restricted due to limited characterization of adipose transcriptional regulatory elements. We profiled chromatin accessibility in three frozen human subcutaneous adipose tissue needle biopsies and preadipocytes and adipocytes from the Simpson Golabi-Behmel Syndrome (SGBS) cell strain using an assay for transposase-accessible chromatin (ATAC-seq). We identified 68,571 representative accessible chromatin regions (peaks) across adipose tissue samples (FDR < 5%). GWAS loci for eight cardiometabolic traits were enriched in these peaks ( P < 0.005), with the strongest enrichment for waist-hip ratio. Of 110 recently described cardiometabolic GWAS loci colocalized with adipose tissue eQTLs, 59 loci had one or more variants overlapping an adipose tissue peak. Annotated variants at the SNX10 waist-hip ratio locus and the ATP2A1-SH2B1 body mass index locus showed allelic differences in regulatory assays. These adipose tissue accessible chromatin regions elucidate genetic variants that may alter adipose tissue function to impact cardiometabolic traits., (Copyright © 2019 Cannon et al.)

Translation of noncoding common variant association signals into meaningful molecular and biological mechanisms explaining disease susceptibility remains challenging. For the type 2 diabetes association signal in JAZF1 intron 1, we hypothesized that the underlying risk variants have cis-regulatory effects in islets or other type 2 diabetes-relevant cell types. We used maps of experimentally predicted open chromatin regions to prioritize variants for functional follow-up studies of transcriptional activity. Twelve regions containing type 2 diabetes-associated variants were tested for enhancer activity in 832/13 and MIN6 insulinoma cells. Three regions exhibited enhancer activity and only rs1635852 displayed allelic differences in enhancer activity; the type 2 diabetes risk allele T showed lower transcriptional activity than the nonrisk allele C. This risk allele showed increased binding to protein complexes, suggesting that it functions as part of a transcriptional repressor complex. We applied DNA affinity capture to identify factors in the complex and determined that the risk allele preferentially binds the pancreatic master regulator PDX1. These data suggest that the rs1635852 region in JAZF1 intron 1 is part of a cis-regulatory complex and that maps of open chromatin are useful to guide identification of variants with allelic differences in regulatory activity at type 2 diabetes loci.

Genome-wide association studies (GWASs) have identified more than 150 loci associated with blood lipid and cholesterol levels; however, the functional and molecular mechanisms for many associations are unknown. We examined the functional regulatory effects of candidate variants at the GALNT2 locus associated with high-density lipoprotein cholesterol (HDL-C). Fine-mapping and conditional analyses in the METSIM study identified a single locus harboring 25 noncoding variants (r(2) > 0.7 with the lead GWAS variants) strongly associated with total cholesterol in medium-sized HDL (e.g., rs17315646, p = 3.5 × 10(-12)). We used luciferase reporter assays in HepG2 cells to test all 25 variants for allelic differences in regulatory enhancer activity. rs2281721 showed allelic differences in transcriptional activity (75-fold [T] versus 27-fold [C] more than the empty-vector control), as did a separate 780-bp segment containing rs4846913, rs2144300, and rs6143660 (49-fold [AT(-) haplotype] versus 16-fold [CC(+) haplotype] more). Using electrophoretic mobility shift assays, we observed differential CEBPB binding to rs4846913, and we confirmed this binding in a native chromatin context by performing chromatin-immunoprecipitation (ChIP) assays in HepG2 and Huh-7 cell lines of differing genotypes. Additionally, sequence reads in HepG2 DNase-I-hypersensitivity and CEBPB ChIP-seq signals spanning rs4846913 showed significant allelic imbalance. Allelic-expression-imbalance assays performed with RNA from primary human hepatocyte samples and expression-quantitative-trait-locus (eQTL) data in human subcutaneous adipose tissue samples confirmed that alleles associated with increased HDL-C are associated with a modest increase in GALNT2 expression. Together, these data suggest that at least rs4846913 and rs2281721 play key roles in influencing GALNT2 expression at this HDL-C locus.

Genome-wide association studies (GWAS) have identified >100 independent SNPs that modulate the risk of type 2 diabetes (T2D) and related traits. However, the pathogenic mechanisms of most of these SNPs remain elusive. Here, we examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to understand the links between genetic variation, chromatin landscape, and gene expression in the context of T2D. We first integrated genome and transcriptome variation across 112 islet samples to produce dense cis-expression quantitative trait loci (cis-eQTL) maps. Additional integration with chromatin-state maps for islets and other diverse tissue types revealed that cis-eQTLs for islet-specific genes are specifically and significantly enriched in islet stretch enhancers. High-resolution chromatin accessibility profiling using assay for transposase-accessible chromatin sequencing (ATAC-seq) in two islet samples enabled us to identify specific transcription factor (TF) footprints embedded in active regulatory elements, which are highly enriched for islet cis-eQTL. Aggregate allelic bias signatures in TF footprints enabled us de novo to reconstruct TF binding affinities genetically, which support the high-quality nature of the TF footprint predictions. Interestingly, we found that T2D GWAS loci were strikingly and specifically enriched in islet Regulatory Factor X (RFX) footprints. Remarkably, within and across independent loci, T2D risk alleles that overlap with RFX footprints uniformly disrupt the RFX motifs at high-information content positions. Together, these results suggest that common regulatory variations have shaped islet TF footprints and the transcriptome and that a confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition. [ABSTRACT FROM AUTHOR]