ABSTRACT: Identifying the molecular mechanisms by which genome-wide association study (GWAS) loci influence traits remains challenging. Chromatin accessibility quantitative trait loci (caQTL) help identify GWAS loci that may alter GWAS traits by modulating chromatin structure, but caQTL have been identified in a limited set of human tissues. Here we mapped caQTL in human liver tissue in 20 liver samples and identified 3,123 caQTL. 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 QTL. Using GWAS signals for 19 liver function and/or cardiometabolic traits, we identified 110 colocalized caQTL 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 caQTL contribute to the epigenomic characterization of human liver and help identify molecular mechanisms and genes at GWAS loci.
Project description:Identifying the molecular mechanisms by which genome-wide association study (GWAS) loci influence traits remains challenging. Chromatin accessibility quantitative trait loci (caQTL) help identify GWAS loci that may alter GWAS traits by modulating chromatin structure, but caQTL have been identified in a limited set of human tissues. Here we mapped caQTL in human liver tissue in 20 liver samples and identified 3,123 caQTL. 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 QTL. Using GWAS signals for 19 liver function and/or cardiometabolic traits, we identified 110 colocalized caQTL 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 caQTL contribute to the epigenomic characterization of human liver and help identify molecular mechanisms and genes at GWAS loci.
Project description:Identifying the molecular mechanisms by which genome-wide association study (GWAS) loci influence traits remains challenging. Chromatin accessibility quantitative trait loci (caQTL) help identify GWAS loci that may alter GWAS traits by modulating chromatin structure, but caQTL have been identified in a limited set of human tissues. Here we mapped caQTL in human liver tissue in 20 liver samples and identified 3,123 caQTL. 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 QTL. Using GWAS signals for 19 liver function and/or cardiometabolic traits, we identified 110 colocalized caQTL 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 caQTL contribute to the epigenomic characterization of human liver and help identify molecular mechanisms and genes at GWAS loci.
Project description:Chromatin accessibility quantitative trait locus (caQTL) studies have identified regulatory elements that may underlie genetic effects on gene expression and clinical quantitative traits. However, caQTL discovery has been limited by the sample sizes of previous studies. Here, we mapped caQTL in liver tissue from 138 human donors and identified caQTL for 35,361 regulatory elements. We identified 2,126 caQTL signals containing multiple regulatory elements, suggesting coordinated regulation of elements at these loci. CaQTL showed strong heritability enrichment and colocalization with genome-wide association study (GWAS) signals for traits relevant to liver function. We identified a colocalized caQTL at 667 GWAS signals for 17 traits, used multiple methods to predict target genes, and validated caQTL predictions at two loci using functional assays. These results demonstrate the power of caQTL to characterize gene regulation and predict regulatory mechanisms at GWAS loci.
Project description:Genome-wide association studies (GWAS) have identified thousands of genomic loci associated with a variety of common, complex human traits. The contribution of genetic variants to gene expression regulation has been well studied, supporting the idea that gene expression plays a causal role at some complex trait-associated loci. However, many current studies have not comprehensively investigated the impact of genetic variation on chromatin accessibility at a large scale within a single tissue. Genetic variants associated with differences in chromatin accessibility, known as chromatin accessibility quantitative trait loci (caQTLs), are major contributors to gene expression differences and GWAS signals. We assessed chromatin accessibility in 189 human liver tissue samples using ATAC-seq and identified over two million accessible chromatin regions enriched for gene regulatory characteristics. We integrated chromatin accessibility and genotype data from 175 samples and identified 14,076 caQTLs. Using publicly available blood lipid GWAS data, we found 157 loci where the colocalization of caQTLs, expression quantitative trait loci (eQTLs), and GWAS signals generated specific molecular hypotheses about causal regulatory elements, affected genes, and, in some cases, transcription factors, resolving these associations to single-nucleotide resolution. We performed a comprehensive analysis of the GWAS signals that remain without a proposed mechanism beyond liver caQTLs and eQTLs. After incorporating additional potential regulatory mechanism data, we found that approximately 26% of blood lipid GWAS signals remain without a proposed mechanism. Overall, our results demonstrate the benefits of integrating multiple datasets to improve our understanding of GWAS signals while emphasizing the need for additional experiments to fully characterize them.
Project description:Gene regulation is highly cell type-specific and understanding the function of non-coding genetic variants associated with complex traits requires molecular phenotyping at cell type resolution. In this study we performed single nucleus ATAC-seq (snATAC-seq) and genotyping in peripheral blood mononuclear cells from 13 individuals. Clustering chromatin accessibility profiles of 96,002 total nuclei identified 17 immune cell types and sub-types. We mapped chromatin accessibility QTLs (caQTLs) in each immune cell type and sub-type which identified ~6,000 total caQTL peaks, including those obscured from assays of bulk tissue such as with divergent effects on different cell types. For ~3,000 caQTLs we further annotated putative target genes of variant activity using single cell co-accessibility, and caQTL variants were significantly correlated with the accessibility level of linked gene promoters. We fine-mapped loci associated with 16 complex immune traits and identified immune cell caQTLs, including those with cell type-specific effects. At the 6q15 locus associated with type 1 diabetes, in line with previous reports, variant rs72928038 was a naïve CD4+ T cell caQTL linked to BACH2 and we validated the allelic effects of this variant on regulatory activity in Jurkat T cells. These results highlight the utility of snATAC-seq for mapping genetic effects on accessible chromatin in specific cell types and provide a resource for annotating complex immune trait loci.
Project description: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.
Project description:<p>Genome-wide association studies (GWAS) identified thousands of genetic loci associated with complex plant traits, including many traits of agronomical importance. However, functional interpretation of GWAS results remains challenging because of large candidate regions due to linkage disequilibrium. High-throughput omics technologies, such as genomics, transcriptomics, proteomics, and metabolomics open new avenues for integrative systems biological analyses and help to nominate systems information supported (prime) candidate genes. In the present study, we capitalize on a diverse canola population with spring-type 477 lines which was previously analysed by high-throughput phenotyping (Knoch et al., 2020), and by RNA sequencing and metabolite profiling for multi-omics-based hybrid performance prediction (Knoch et al., 2021). We deepened the phenotypic data analysis, now providing 123 time-resolved image-based traits, to gain insight into the complex relations during early vegetative growth and re-analysed the transcriptome data based on the latest Darmor-bzh v10 genome assembly (Rousseau-Gueutin et al., 2020). Genome-wide association testing revealed 61,298 robust quantitative trait loci (QTL) including 187 metabolite-QTL, 56,814 expression-QTL, and 4,297 phenotypic QTL, many clustered in pronounced hotspots. Combining information about QTL colocalisation across omics layers and correlations between omics features allowed us to discover prime candidate genes for metabolic and vegetative growth variation. Prioritized candidate genes for early biomass accumulation include A06p05760.1_BnaDAR (PIAL1), A10p16280.1_BnaDAR, C07p48260.1_BnaDAR (PRL1), and C07p48510.1_BnaDAR (CLPR4). Moreover, we observed unequal effects of the Brassica A and C subgenomes on early biomass production.</p><p><br></p>
Project description:Systematic characterization of how genetic variation modulates gene regulation in a cell type specific context is essential for understanding complex traits. To address this question, we profiled gene expression and chromatin state of cells from healthy retinae of 20 human donors with a single-cell multiomics approach, and performed genomic sequencing. sc-eQTLs, sc-caQTL, sc-ASCA and sc-ASE were mapped in major retinal cell types. By integrating these results, we identified and characterized regulatory elements and genetic variants effective on gene regulation in individual cell types. Most of the identified sc-eQTLs and sc-caQTLs exhibit cell type-specific effects. Interestingly, the cis-elements harboring genetic variants with cell type-specific effects tend to be accessible in multiple cell types. Lastly, we identified the enriched cell types, fine-mapped candidate causal variants and genes, and uncovered cell type-specific regulatory mechanism underlying GWAS loci.
Project description:GWAS have discovered thousands of genomic loci that are associated with disease risk and quantitative traits, but most of the variants responsible for risk remain uncharacterized. The vast majority of GWAS-identified loci contain non-coding SNPs and defining molecular mechanism of risk is challenging. Many non-coding causal SNPs are hypothesized to alter Transcription Factor (TF) binding sites as the mechanism by which they affect organismal phenotypes. We employed an integrative genomics approach to identify candidate TF binding motifs that confer breast cancer-specific phenotypes identified by GWAS. We performed de novo motif analysis of regulatory elements, analyzed evolutionary conservation of identified motifs, and assayed TF footprinting data to identify sequence elements that recruit TFs and maintain chromatin landscape in breast cancer-relevant tissue and cell lines. Regulatory elements for MCF10A were mapped with ATAC-seq.We identified top candidate causal SNPs that are predicted to alter TF binding, within breast cancer-relevant regulatory regions, and in strong linkage disequilibrium with the GWAS SNPs. This integrative analysis pipeline is a general framework to identify candidate causal variants within regulatory regions and TF binding sites that confer phenotypic variation and disease risk.
Project description:GWAS have identified hundreds of loci associated with height.However, determining causal mechanisms is challenging, especially since height-relevant tissues such as the growth plate are difficult to study. To discover mechanisms by which height GWAS variants function, we performed epigenetic profiling of murine femoral growth plates. The profiled open chromatin regions recapitulate known chondrocyte and skeletal biology and are enriched at height GWAS loci, particularly near differentially expressed growth plate genes. These regions are also enriched in binding motifs of transcription factors with known roles in chondrocyte biology. At specific loci, our analyses identified compelling mechanisms for GWAS variants. For example, at the CHYS1 locus, we identified a potentially causal variant overlapping an open chromatin region and predicted to alter binding of HOXD13, important for skeletal development. Thus, integrating biologically relevant epigenetic information (here, from mouse growth plate) with genetic association results can identify biological mechanisms important for human growth.