GWAS SNPs Research Articles

5154 Regulation Of T2D Genes In Human Adipocytes

Abstract Disclosure: Q. Zhang: None. Type 2 diabetes (T2D) is a chronic disease that affects 415 million people around the world and was the fourth leading cause of death (2015). Insulin resistance (IR), one of the major pathophysiological mechanisms that characterize T2D, is defined as the state in which cells, tissues, or organisms no longer respond appropriately to endogenous or exogenous insulin. We have generated detailed transcriptomes and chromatin state maps from the isolated adipocytes of insulin sensitive (IS) and insulin resistant (IR) human subjects. Mapping IR/IS differentially enriched H3K27ac peaks onto T2D GWAS SNPs suggested several loci as noncoding regulatory elements (REs) of human IR. We focused on the IRS1 gene, a known T2D related locus that encodes a critical protein in the insulin signaling cascade. We developed a CRISPRi-based assay that enabled us to determine which noncoding regulatory elements are required for normal IRS1 expression in human adipocytes. Our data indicate that many IR/IS differentially regulated H3K27ac peaks are critical regulatory elements for IRS1 transcription, although we did not observe that peaks that were increased in the IS state had a larger effect, as predicted. Overall, we have developed a CRISPRi-based screening system for noncoding elements in human adipocytes, which can be deployed to study many different loci related to metabolic disease. Presentation: 6/2/2024

A Comprehensive Genetic and Bioinformatic Analysis Provides Evidence for the Engagement of COVID-19 GWAS-Significant Loci in the Molecular Mechanisms of Coronary Artery Disease and Stroke

Cardiovascular diseases (CVDs) significantly exacerbate the severity and mortality of COVID-19. We aimed to investigate whether GWAS-significant SNPs correlate with CVDs in severe COVID-19 patients. DNA samples from 199 patients with severe COVID-19 hospitalized in intensive care units were genotyped using probe-based PCR for 10 GWAS SNPs previously implicated in severe COVID-19 outcomes. SNPs rs17713054 SLC6A20-LZTFL1 (risk allele A, OR = 2.14, 95% CI 1.06–4.36, p = 0.03), rs12610495 DPP9 (risk allele G, OR = 1.69, 95% CI 1.02–2.81, p = 0.04), and rs7949972 ELF5 (risk allele T, OR = 2.57, 95% CI 1.43–4.61, p = 0.0009) were associated with increased risk of coronary artery disease (CAD). SNPs rs7949972 ELF5 (OR = 2.67, 95% CI 1.38–5.19, p = 0.003) and rs61882275 ELF5 (risk allele A, OR = 1.98, 95% CI 1.14–3.45, p = 0.01) were linked to a higher risk of cerebral stroke (CS). No associations were observed with AH. Bioinformatics analysis revealed the involvement of GWAS-significant loci in atherosclerosis, inflammation, oxidative stress, angiogenesis, and apoptosis, which provides evidence of their role in the molecular mechanisms of CVDs. This study provides novel insights into the associations between GWAS-identified SNPs and the risk of CAD and CS.

438 DNA methylation patterns and transcriptional regulation during pig fetal skeletal muscle development

Abstract Fetal development is controlled by a complex cascade of highly regulated and coordinated gene expression patterns. Epigenetic mechanisms have important roles in regulating development and differentiation. Among such mechanisms, DNA methylation exhibits context-specific associations with gene expression and has been shown to be highly dynamic during developmental processes. We performed whole-genome bisulfite sequencing (WGBS) to assess DNA methylation in pig longissimus dorsi muscle at 41- and 70-d gestation (dg), as well as RNA- and small RNA-sequencing to identify coordinated changes in methylation and expression between myogenic stages. We identified 45,739 differentially methylated regions (DMRs) between stages, and the majority (n = 34,232) were hypomethylated at 70 vs. 41 dg. Developmental DMRs exhibited feature-specific enrichment in gene regulatory regions, as well as in regions proximal to micro-RNAs (miRNAs) that have known roles in myogenesis. Integration of methylation and transcriptomic data revealed strong associations between differential gene methylation and transcript abundance. We surveyed myogenic regulatory factor (MRF) genes to determine if differential methylation was present in expected genomic regions. Within the MYF5 and MYF6 locus, MYF5 was significantly promoter-hypermethylated at 70 dg, whereas MYF6 was significantly hypomethylated upstream of its transcription start site. MYF5 is the earliest MRF to be expressed and primarily functions in myoblast proliferation and determination, while MYF6 functions in muscle cell differentiation. Thus, these patterns were consistent with expected downregulation of MYF5 and upregulation of MYF6 as muscle development progresses and demonstrate that differential methylation is evident at myogenic transcription factors. Differential miRNA methylation was significantly negatively correlated with abundance, and dynamic expression of assayed miRNAs persisted postnatally. Motif analysis revealed significant enrichment of myogenic regulatory factor motifs among hypomethylated regions, suggesting that DNA hypomethylation may function to increase accessibility of muscle-specific transcription factors. We also show that developmental DMRs are enriched for GWAS SNPs associated with muscle physiology and meat quality traits, demonstrating the potential for epigenetic processes to influence phenotypic diversity. Our results enhance understanding of DNA methylation dynamics in pig fetal skeletal muscle and reveal putative cis-regulatory elements governed by epigenetic processes during porcine myogenesis.

Enhancing portability of trans-ancestral polygenic risk scores through tissue-specific functional genomic data integration.

Portability of trans-ancestral polygenic risk scores is often confounded by differences in linkage disequilibrium and genetic architecture between ancestries. Recent literature has shown that prioritizing GWAS SNPs with functional genomic evidence over strong association signals can improve model portability. We leveraged three RegulomeDB-derived functional regulatory annotations-SURF, TURF, and TLand-to construct polygenic risk models across a set of quantitative and binary traits highlighting functional mutations tagged by trait-associated tissue annotations. Tissue-specific prioritization by TURF and TLand provide a significant improvement in model accuracy over standard polygenic risk score (PRS) models across all traits. We developed the Trans-ancestral Iterative Tissue Refinement (TITR) algorithm to construct PRS models that prioritize functional mutations across multiple trait-implicated tissues. TITR-constructed PRS models show increased predictive accuracy over single tissue prioritization. This indicates our TITR approach captures a more comprehensive view of regulatory systems across implicated tissues that contribute to variance in trait expression.

ScaDA: A novel statistical method for differential analysis of single-cell chromatin accessibility sequencing data.

Single-cell ATAC-seq sequencing data (scATAC-seq) has been widely used to investigate chromatin accessibility on the single-cell level. One important application of scATAC-seq data analysis is differential chromatin accessibility (DA) analysis. However, the data characteristics of scATAC-seq such as excessive zeros and large variability of chromatin accessibility across cells impose a unique challenge for DA analysis. Existing statistical methods focus on detecting the mean difference of the chromatin accessible regions while overlooking the distribution difference. Motivated by real data exploration that distribution difference exists among cell types, we introduce a novel composite statistical test named "scaDA", which is based on zero-inflated negative binomial model (ZINB), for performing differential distribution analysis of chromatin accessibility by jointly testing the abundance, prevalence and dispersion simultaneously. Benefiting from both dispersion shrinkage and iterative refinement of mean and prevalence parameter estimates, scaDA demonstrates its superiority to both ZINB-based likelihood ratio tests and published methods by achieving the highest power and best FDR control in a comprehensive simulation study. In addition to demonstrating the highest power in three real sc-multiome data analyses, scaDA successfully identifies differentially accessible regions in microglia from sc-multiome data for an Alzheimer's disease (AD) study that are most enriched in GO terms related to neurogenesis and the clinical phenotype of AD, and AD-associated GWAS SNPs.

ChIP-Atlas 3.0: a data-mining suite to explore chromosome architecture together with large-scale regulome data.

ChIP-Atlas (https://chip-atlas.org/) presents a suite of data-mining tools for analyzing epigenomic landscapes, powered by the comprehensive integration of over 376000 public ChIP-seq, ATAC-seq, DNase-seqand Bisulfite-seq experiments from six representative model organisms. To unravel the intricacies of chromatin architecture that mediates the regulome-initiated generation of transcriptional and phenotypic diversity within cells, we report ChIP-Atlas 3.0 that enhances clarity by incorporating additional tracks for genomic and epigenomic features within a newly consolidated 'annotation track' section. The tracks include chromosomal conformation (Hi-C and eQTL datasets), transcriptional regulatory elements (ChromHMM and FANTOM5 enhancers), and genomic variants associated with diseases and phenotypes (GWAS SNPs and ClinVar variants). These annotation tracks are easily accessible alongside other experimental tracks, facilitating better elucidation of chromatin architecture underlying the diversification of transcriptional and phenotypic traits. Furthermore, 'Diff Analysis,' a new online tool, compares the query epigenome data to identify differentially bound, accessible, and methylated regions using ChIP-seq, ATAC-seq and DNase-seq, and Bisulfite-seq datasets, respectively. The integration of annotation tracks and the Diff Analysis tool, coupled with continuous data expansion, renders ChIP-Atlas 3.0 a robust resource for mining the landscape of transcriptional regulatory mechanisms, thereby offering valuable perspectives, particularly for genetic disease research and drug discovery.

Epigenetic profiling reveals key genes and cis-regulatory networks specific to human parathyroids

In all terrestrial vertebrates, the parathyroid glands are critical regulators of calcium homeostasis and the sole source of parathyroid hormone (PTH). Hyperparathyroidism and hypoparathyroidism are clinically important disorders affecting multiple organs. However, our knowledge regarding regulatory mechanisms governing the parathyroids has remained limited. Here, we present the comprehensive maps of the chromatin landscape of the human parathyroid glands, identifying active regulatory elements and chromatin interactions. These data allow us to define regulatory circuits and previously unidentified genes that play crucial roles in parathyroid biology. We experimentally validate candidate parathyroid-specific enhancers and demonstrate their integration with GWAS SNPs for parathyroid-related diseases and traits. For instance, we observe reduced activity of a parathyroid-specific enhancer of the Calcium Sensing Receptor gene, which contains a risk allele associated with higher PTH levels compared to the wildtype allele. Our datasets provide a valuable resource for unraveling the mechanisms governing parathyroid gland regulation in health and disease.

Identifying novel regulatory effects for clinically relevant genes through the study of the Greek population

BackgroundExpression quantitative trait loci (eQTL) studies provide insights into regulatory mechanisms underlying disease risk. Expanding studies of gene regulation to underexplored populations and to medically relevant tissues offers potential to reveal yet unknown regulatory variants and to better understand disease mechanisms. Here, we performed eQTL mapping in subcutaneous (S) and visceral (V) adipose tissue from 106 Greek individuals (Greek Metabolic study, GM) and compared our findings to those from the Genotype-Tissue Expression (GTEx) resource.ResultsWe identified 1,930 and 1,515 eGenes in S and V respectively, over 13% of which are not observed in GTEx adipose tissue, and that do not arise due to different ancestry. We report additional context-specific regulatory effects in genes of clinical interest (e.g. oncogene ST7) and in genes regulating responses to environmental stimuli (e.g. MIR21, SNX33). We suggest that a fraction of the reported differences across populations is due to environmental effects on gene expression, driving context-specific eQTLs, and suggest that environmental effects can determine the penetrance of disease variants thus shaping disease risk. We report that over half of GM eQTLs colocalize with GWAS SNPs and of these colocalizations 41% are not detected in GTEx. We also highlight the clinical relevance of S adipose tissue by revealing that inflammatory processes are upregulated in individuals with obesity, not only in V, but also in S tissue.ConclusionsBy focusing on an understudied population, our results provide further candidate genes for investigation regarding their role in adipose tissue biology and their contribution to disease risk and pathogenesis.

Abstract 5217: Genome-wide interactions of processed and red meat intake on colorectal cancer risk

Abstract Introduction: Colorectal cancer (CRC) is the third most common cancer, and second cause of cancer death worldwide. High red meat and/or processed meat consumption are established risk factors for CRC. Genome-wide association studies have identified over 200 genetic variants that explain ~20% of the variability in CRC risk. However, few large studies have evaluated genome-wide gene by environment (GxE) interactions with meat in CRC. Using the largest CRC pooled dataset available to date we conducted a genome-wide GxE analysis to identify possible interactions between common variants and red meat and/or processed meat intake and CRC risk. Methods: A pooled sample of 29,912 CRC cases and 39,704 unaffected controls of European (EUR) ancestry from 27 studies was analyzed. Sex- and study-specific quartiles for red meat and processed meat intake were constructed from harmonized questionnaire data on meat consumption. Genotyping arrays were imputated to the Haplotype Reference Consortium. To identify novel CRC interaction loci we used the two-step EDGE method, standard GxE analyses and a 1-3 degrees of freedom (DF) test. We removed previously known GWAS hits and SNPs in high linkage disequilibrium with them. Results: Our Meta-analyses confirmed a positive association between quartile consumption increase of red meat and processed meat with CRC risk (Red meat OR = 1.30; 95%CI = 1.21-1.41; Processed meat OR = 1.40; 95% CI = 1.20 -1.63). Greater magnitude in point estimates were observed for case-control studies compared to cohort studies, for processed meat consumption among men compared to women, and for red meat consumption and distal colon localization compared to proximal colon or rectum. Two DF GxE tests of red meat consumption revealed two SNPs in chromosome (Chr) 8 (rs4871179 & rs75212442) and a SNP in Chr10 (rs117674361) that map downstream HAS2, COLEC10 and downstream CCSER2. In addition, the two-step EDGE GxE method identified the rs35352860 SNP that maps to the SMAD7 gene in Chr18. Genotype-stratified analyses showed that the red meat and CRC risk association was restricted to homozygous carriers of major alleles for rs4871179, rs75212442 & rs117674361. Moreover, we observed dose-response increase in the red meat and CRC risk association with additional copies of the T allele of the SNP in Chr18, with homozygous carriers of the T allele having 46% higher chance of developing CRC associated with high red meat intake; this in contrast to homozygous carriers of the reference C allele, that had an 18% higher risk of developing CRC. No statistically significant GXE interactions with processed meat intake were found. Conclusion: In this large-scale genome-wide GxE analysis we identified interactions between 4 SNPs and red meat consumption affecting CRC risk. The interaction with the SMAD7 rs35352860 SNP provides supportive evidence for a role of heme iron in the carcinogenic pathway of red meat intake in CRC development. Citation Format: Joel Sanchez Mendez, Mariana C. Stern, Andre Kim, John Morrison, Juan P. Lewinger, Li Hsu, Eric Kawaguchi, Ulrike Peters, William J. Gauderman, on behalf of GECCO, CCFR and CORECT. Genome-wide interactions of processed and red meat intake on colorectal cancer risk. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5217.

Pig fetal skeletal muscle development is associated with genome-wide DNA hypomethylation and corresponding alterations in transcript and microRNA expression.

Fetal myogenesis represents a critical period of porcine skeletal muscle development and requires coordinated expression of thousands of genes. Epigenetic mechanisms, including DNA methylation, drive transcriptional regulation during development; however, these processes are understudied in developing porcine tissues. We performed bisulfite sequencing to assess DNA methylation in pig longissimus dorsi muscle at 41- and 70-days gestation (dg), as well as RNA- and small RNA-sequencing to identify coordinated changes in methylation and expression between myogenic stages. We identified 45 739 differentially methylated regions (DMRs) between stages, and the majority (N=34 232) were hypomethylated at 70versus 41 dg. Integration of methylation and transcriptomic data revealed strong associations between differential gene methylation and expression. Differential miRNA methylation was significantly negatively correlated with abundance, and dynamic expression of assayed miRNAs persisted postnatally. Motif analysis revealed significant enrichment of myogenic regulatory factor motifs among hypomethylated regions, suggesting that DNA hypomethylation may function to increase accessibility of muscle-specific transcription factors. We show that developmental DMRs are enriched for GWAS SNPs for muscle- and meat-related traits, demonstrating the potential for epigenetic processes to influence phenotypic diversity. Our results enhance understanding of DNA methylation dynamics of porcine myogenesis and reveal putative cis-regulatory elements governed by epigenetic processes.

A Comprehensive Investigation of Genomic Variants in Prostate Cancer Reveals 30 Putative Regulatory Variants.

Prostate cancer (PC) is the most frequently diagnosed non-skin cancer in the world. Previous studies have shown that genomic alterations represent the most common mechanism for molecular alterations responsible for the development and progression of PC. This highlights the importance of identifying functional genomic variants for early detection in high-risk PC individuals. Great efforts have been made to identify common protein-coding genetic variations; however, the impact of non-coding variations, including regulatory genetic variants, is not well understood. Identification of these variants and the underlying target genes will be a key step in improving the detection and treatment of PC. To gain an understanding of the functional impact of genetic variants, and in particular, regulatory variants in PC, we developed an integrative pipeline (AGV) that uses whole genome/exome sequences, GWAS SNPs, chromosome conformation capture data, and ChIP-Seq signals to investigate the potential impact of genomic variants on the underlying target genes in PC. We identified 646 putative regulatory variants, of which 30 significantly altered the expression of at least one protein-coding gene. Our analysis of chromatin interactions data (Hi-C) revealed that the 30 putative regulatory variants could affect 131 coding and non-coding genes. Interestingly, our study identified the 131 protein-coding genes that are involved in disease-related pathways, including Reactome and MSigDB, for most of which targeted treatment options are currently available. Notably, our analysis revealed several non-coding RNAs, including RP11-136K7.2 and RAMP2-AS1, as potential enhancer elements of the protein-coding genes CDH12 and EZH1, respectively. Our results provide a comprehensive map of genomic variants in PC and reveal their potential contribution to prostate cancer progression and development.

Lineage-selective super enhancers mediate core regulatory circuitry during adipogenic and osteogenic differentiation of human mesenchymal stem cells

Human mesenchymal stem cells (hMSCs) can be differentiated into osteoblasts and adipocytes. During these processes, super enhancers (SEs) play important roles. Here, we performed comprehensive characterization of the SEs changes associated with adipogenic and osteogenic differentiation of hMSCs, and revealed that SEs changed more dramatically compared with typical enhancers. We identified a set of lineage-selective SEs, whose target genes were enriched with cell type-specific functions. Functional experiments in lineage-selective SEs demonstrated their specific roles in directed differentiation of hMSCs. We also found that some key transcription factors regulated by lineage-selective SEs could form core regulatory circuitry (CRC) to regulate each other’s expression and control the hMSCs fate determination. In addition, we found that GWAS SNPs of osteoporosis and obesity were significantly enriched in osteoblasts-selective SEs or adipocytes-selective SEs, respectively. Taken together, our studies unveiled important roles of lineage-selective SEs in hMSCs differentiation into osteoblasts and adipocytes.

Genetically-estimated Telomere Length Weakly Associates With Body Composition And Metabolic Profiles But Not Cardiorespiratory Fitness

Telomere length is associated with many age-related diseases. However, its association with fitness-related traits and exercise responses are less understood. PURPOSE: To investigate the association of genetically estimated telomere length (gTL) with cardiorespiratory fitness (CRF) traits and metabolic traits before and after endurance exercise training in the HERITAGE Family Study. METHODS: gTL was calculated in Black and White adults from the HERITAGE Family Study (n=708) using 9 established telomere length GWAS SNPs. Race-stratified associations between gTL and baseline measures and changes in CRF traits, body composition, and the components of metabolic syndrome were determined using partial correlations controlling for age. RESULTS: Mean (±SE) gTL significantly (p<0.001) differed between Black (754.5±8.2 bp) and White subjects (603.1±5.98 bp). There were no associations between gTL and CRF traits at baseline or in response to training in Black or White subjects. Furthermore, there were no associations between gTL and body composition traits at baseline or in response to training in Black subjects. In White subjects, gTL was negatively, weakly correlated with baseline body composition measures including: BMI (r=-0.14), waist circumference (r=-0.12), visceral fat (r=-0.11), fat mass (r=-0.13), percent body fat (r=-0.11); all p<0.05. Only change in waist circumference was correlated with gTL in Whites subjects (r=-0.12, p=0.02). At baseline, Black (n=55) and White (n=97) subjects with metabolic syndrome had significantly shorter mean gTL compared to those without (p<0.05). Furthermore, gTL was negatively correlated with number of baseline metabolic syndrome components in Whites (r=-0.12, p=0.02), but not Blacks. In response to training, gTL was negatively correlated with change in number of metabolic syndrome components in Whites (r=-0.10, p=0.044), but positively correlated in Blacks (r=0.15, p=0.047). CONCLUSIONS: Baseline CRF traits and their response to training were not associated with gTL. Increased central adiposity and metabolic syndrome components are associated with shorter gTL in Whites. The gTL estimate used may not be optimized in Blacks and perhaps not sensitive enough to fully capture hypothesized associations with fitness traits or metabolic health.

Assessment of DNA methylation in porcine immune cells reveals novel regulatory elements associated with cell-specific gene expression and immune capacity traits

BackgroundGenetics studies in the porcine immune system have enhanced selection practices for disease resistance phenotypes and increased the efficacy of porcine models in biomedical research; however limited functional annotation of the porcine immunome has hindered progress on both fronts. Among epigenetic mechanisms that regulate gene expression, DNA methylation is the most ubiquitous modification made to the DNA molecule and influences transcription factor binding as well as gene and phenotype expression. Human and mouse DNA methylation studies have improved mapping of regulatory elements in these species, but comparable studies in the pig have been limited in scope.ResultsWe performed whole-genome bisulfite sequencing to assess DNA methylation patterns in nine pig immune cell populations: CD21+ and CD21− B cells, four T cell fractions (CD4+, CD8+, CD8+CD4+, and SWC6γδ+), natural killer and myeloid cells, and neutrophils. We identified 54,391 cell differentially methylated regions (cDMRs), and clustering by cDMR methylation rate grouped samples by cell lineage. 32,737 cDMRs were classified as cell lowly methylated regions (cLMRs) in at least one cell type, and cLMRs were broadly enriched in genes and regions of intermediate CpG density. We observed strong correlations between differential methylation and expression across immune cell populations, with cell-specific low methylation disproportionately impacting genes exhibiting enriched gene expression in the same cell type. Motif analysis of cLMRs revealed cell type-specific enrichment of transcription factor binding motifs, indicating that cell-specific methylation patterns may influence accessibility by trans-acting factors. Lastly, cDMRs were enriched for immune capacity GWAS SNPs, and many such overlaps occurred within genes known to influence immune cell development and function (CD8B, NDRG1).ConclusionOur DNA methylation data improve functional annotation of the porcine genome through characterization of epigenomic regulatory patterns that contribute to immune cell identity and function, and increase the potential for identifying mechanistic links between genotype and phenotype.

One step closer to linking GWAS SNPs with the right genes.

One step closer to linking GWAS SNPs with the right genes.

P508. Assessing Isoform Diversity in the Context of Psychiatric Disorders

The genetic architecture of schizophrenia is dominated by common variants of small effects, similar to most complex human traits. The majority of the schizophrenia GWAS SNPs reside in non-coding regions where they could act through a variety of regulatory mechanisms, such as alternative splicing to generate schizophrenia-associated isoforms. The brain expresses the most diverse repertoire of isoforms, yet our understanding of brain-specific isoform expression and the mechanisms of their regulation by RNA binding proteins (RBPs) are incomplete.

Approaching Genetics Through the MHC Lens: Tools and Methods for HLA Research.

The current SARS-CoV-2 pandemic era launched an immediate and broad response of the research community with studies both about the virus and host genetics. Research in genetics investigated HLA association with COVID-19 based on in silico, population, and individual data. However, they were conducted with variable scale and success; convincing results were mostly obtained with broader whole-genome association studies. Here, we propose a technical review of HLA analysis, including basic HLA knowledge as well as available tools and advice. We notably describe recent algorithms to infer and call HLA genotypes from GWAS SNPs and NGS data, respectively, which opens the possibility to investigate HLA from large datasets without a specific initial focus on this region. We thus hope this overview will empower geneticists who were unfamiliar with HLA to run MHC-focused analyses following the footsteps of the Covid-19|HLA & Immunogenetics Consortium.

Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits.

Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell–specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples. We capture type I and type II muscle fiber signatures, which are generally missed by existing single-cell RNA-seq methods. We perform cross-modality and cross-species integrative analyses on 33,862 nuclei and identify seven cell types ranging in abundance from 59.6% to 1.0% of all nuclei. We introduce a regression-based approach to infer cell types by comparing transcription start site–distal ATAC-seq peaks to reference enhancer maps and show consistency with RNA-based marker gene cell type assignments. We find heterogeneity in enrichment of genetic variants linked to complex phenotypes from the UK Biobank and diabetes genome-wide association studies in cell-specific ATAC-seq peaks, with the most striking enrichment patterns in muscle mesenchymal stem cells (∼3.5% of nuclei). Finally, we overlay these chromatin accessibility maps on GWAS data to nominate causal cell types, SNPs, transcription factor motifs, and target genes for type 2 diabetes signals. These chromatin accessibility profiles for human and rat skeletal muscle cell types are a useful resource for nominating causal GWAS SNPs and cell types.

Multi-omics colocalization with genome-wide association studies reveals a context-specific genetic mechanism at a childhood onset asthma risk locus

BackgroundGenome-wide association studies (GWASs) have identified thousands of variants associated with asthma and other complex diseases. However, the functional effects of most of these variants are unknown. Moreover, GWASs do not provide context-specific information on cell types or environmental factors that affect specific disease risks and outcomes. To address these limitations, we used an upper airway epithelial cell (AEC) culture model to assess transcriptional and epigenetic responses to rhinovirus (RV), an asthma-promoting pathogen, and provide context-specific functional annotations to variants discovered in GWASs of asthma.MethodsGenome-wide genetic, gene expression, and DNA methylation data in vehicle- and RV-treated upper AECs were collected from 104 individuals who had a diagnosis of airway disease (n=66) or were healthy participants (n=38). We mapped cis expression and methylation quantitative trait loci (cis-eQTLs and cis-meQTLs, respectively) in each treatment condition (RV and vehicle) in AECs from these individuals. A Bayesian test for colocalization between AEC molecular QTLs and adult onset asthma and childhood onset asthma GWAS SNPs, and a multi-ethnic GWAS of asthma, was used to assign the function to variants associated with asthma. We used Mendelian randomization to demonstrate DNA methylation effects on gene expression at asthma colocalized loci.ResultsAsthma and allergic disease-associated GWAS SNPs were specifically enriched among molecular QTLs in AECs, but not in GWASs from non-immune diseases, and in AEC eQTLs, but not among eQTLs from other tissues. Colocalization analyses of AEC QTLs with asthma GWAS variants revealed potential molecular mechanisms of asthma, including QTLs at the TSLP locus that were common to both the RV and vehicle treatments and to both childhood onset and adult onset asthma, as well as QTLs at the 17q12-21 asthma locus that were specific to RV exposure and childhood onset asthma, consistent with clinical and epidemiological studies of these loci.ConclusionsThis study provides evidence of functional effects for asthma risk variants in AECs and insight into RV-mediated transcriptional and epigenetic response mechanisms that modulate genetic effects in the airway and risk for asthma.

Integrative Epigenome Map of the Normal Human Prostate Provides Insights Into Prostate Cancer Predisposition.

Cells of all tissues in the human body share almost the exact same DNA sequence, but the epigenomic landscape can be drastically distinct. To improve our understanding of the epigenetic abnormalities in prostate-related diseases, it is important to use the epigenome of normal prostate as a reference. Although previous efforts have provided critical insights into the genetic and transcriptomic features of the normal prostate, a comprehensive epigenome map has been lacking. To address this need, we conducted a Roadmap Epigenomics legacy project integrating six histone marks (H3K4me1, H3K4me3, H3K9me3, H3K36me3, H3K27me3, and H3K27ac) with complete DNA methylome, transcriptome, and chromatin accessibility data to produce a comprehensive epigenome map of normal prostate tissue. Our epigenome map is composed of 18 chromatin states each with unique signatures of DNA methylation, chromatin accessibility, and gene expression. This map provides a high-resolution comprehensive annotation of regulatory regions of the prostate, including 105,593 enhancer and 70,481 promoter elements, which account for 5.3% of the genome. By comparing with other epigenomes, we identified 7,580 prostate-specific active enhancers associated with prostate development. Epigenomic annotation of GWAS SNPs associated with prostate cancers revealed that two out of nine SNPs within prostate enhancer regions destroyed putative androgen receptor (AR) binding motif. A notable SNP rs17694493, might decouple AR’s repressive effect on CDKN2B-AS1 and cell cycle regulation, thereby playing a causal role in predisposing cancer risk. The comprehensive epigenome map of the prostate is valuable for investigating prostate-related diseases.