A promoter interaction map for cardiovascular disease genetics

Investigation of inherited noncoding genetic variation impacting the pharmacogenomics of childhood acute lymphoblastic leukemia treatment

Defining genetic factors impacting chemotherapy failure can help to better predict response and identify drug resistance mechanisms. However, there is limited understanding of the contribution of inherited noncoding genetic variation on inter-individual differences in chemotherapy response in childhood acute lymphoblastic leukemia (ALL). Here we map inherited noncoding variants associated with treatment outcome and/or chemotherapeutic drug resistance to ALL cis-regulatory elements and investigate their gene regulatory potential and target gene connectivity using massively parallel reporter assays and three-dimensional chromatin looping assays, respectively. We identify 54 variants with transcriptional effects and high-confidence gene connectivity. Additionally, functional interrogation of the top variant, rs1247117, reveals changes in chromatin accessibility, PU.1 binding affinity and gene expression, and deletion of the genomic interval containing rs1247117 sensitizes cells to vincristine. Together, these data demonstrate that noncoding regulatory variants associated with diverse pharmacological traits harbor significant effects on allele-specific transcriptional activity and impact sensitivity to antileukemic agents.

Mechanosensitive super-enhancers regulate genes linked to atherosclerosis in endothelial cells

Vascular homeostasis and pathophysiology are tightly regulated by mechanical forces generated by hemodynamics. Vascular disorders such as atherosclerotic diseases largely occur at curvatures and bifurcations where disturbed blood flow activates endothelial cells while unidirectional flow at the straight part of vessels promotes endothelial health. Integrated analysis of the endothelial transcriptome, the 3D epigenome, and human genetics systematically identified the SNP-enriched cistrome in vascular endothelium subjected to well-defined atherosclerosis-prone disturbed flow or atherosclerosis-protective unidirectional flow. Our results characterized the endothelial typical- and super-enhancers and underscored the critical regulatory role of flow-sensitive endothelial super-enhancers. CRISPR interference and activation validated the function of a previously unrecognized unidirectional flow-induced super-enhancer that upregulates antioxidant genes NQO1, CYB5B, and WWP2, and a disturbed flow-induced super-enhancer in endothelium which drives prothrombotic genes EDN1 and HIVEP in vascular endothelium. Our results employing multiomics identify the cis-regulatory architecture of the flow-sensitive endothelial epigenome related to atherosclerosis and highlight the regulatory role of super-enhancers in mechanotransduction mechanisms.

Genome-wide enhancer-associated tandem repeats are expanded in cardiomyopathy

BACKGROUND

Cardiomyopathy is a clinically and genetically heterogeneous heart condition that can lead to heart failure and sudden cardiac death in childhood. While it has a strong genetic basis, the genetic aetiology for over 50% of cardiomyopathy cases remains unknown.

METHODS

In this study, we analyse the characteristics of tandem repeats from genome sequence data of unrelated individuals diagnosed with cardiomyopathy from Canada and the United Kingdom (n = 1216) and compare them to those found in the general population. We perform burden analysis to identify genomic and epigenomic features that are impacted by rare tandem repeat expansions (TREs), and enrichment analysis to identify functional pathways that are involved in the TRE-associated genes in cardiomyopathy. We use Oxford Nanopore targeted long-read sequencing to validate repeat size and methylation status of one of the most recurrent TREs. We also compare the TRE-associated genes to those that are dysregulated in the heart tissues of individuals with cardiomyopathy.

FINDINGS

We demonstrate that tandem repeats that are rarely expanded in the general population are predominantly expanded in cardiomyopathy. We find that rare TREs are disproportionately present in constrained genes near transcriptional start sites, have high GC content, and frequently overlap active enhancer H3K27ac marks, where expansion-related DNA methylation may reduce gene expression. We demonstrate the gene silencing effect of expanded CGG tandem repeats in DIP2B through promoter hypermethylation. We show that the enhancer-associated loci are found in genes that are highly expressed in human cardiomyocytes and are differentially expressed in the left ventricle of the heart in individuals with cardiomyopathy.

INTERPRETATION

Our findings highlight the underrecognized contribution of rare tandem repeat expansions to the risk of cardiomyopathy and suggest that rare TREs contribute to ∼4% of cardiomyopathy risk.

FUNDING

Government of Ontario (RKCY), The Canadian Institutes of Health Research PJT 175329 (RKCY), The Azrieli Foundation (RKCY), SickKids Catalyst Scholar in Genetics (RKCY), The University of Toronto McLaughlin Centre (RKCY, SM), Ted Rogers Centre for Heart Research (SM), Data Sciences Institute at the University of Toronto (SM), The Canadian Institutes of Health Research PJT 175034 (SM), The Canadian Institutes of Health Research ENP 161429 under the frame of ERA PerMed (SM, RL), Heart and Stroke Foundation of Ontario & Robert M Freedom Chair in Cardiovascular Science (SM), Bitove Family Professorship of Adult Congenital Heart Disease (EO), Canada Foundation for Innovation (SWS, JR), Canada Research Chair (PS), Genome Canada (PS, JR), The Canadian Institutes of Health Research (PS).

Functional dissection of human cardiac enhancers and noncoding de novo variants in congenital heart disease

Rare coding mutations cause ∼45% of congenital heart disease (CHD). Noncoding mutations that perturb cis-regulatory elements (CREs) likely contribute to the remaining cases, but their identification has been problematic. Using a lentiviral massively parallel reporter assay (lentiMPRA) in human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), we functionally evaluated 6,590 noncoding de novo variants (ncDNVs) prioritized from the whole-genome sequencing of 750 CHD trios. A total of 403 ncDNVs substantially affected cardiac CRE activity. A majority increased enhancer activity, often at regions with undetectable reference sequence activity. Of ten DNVs tested by introduction into their native genomic context, four altered the expression of neighboring genes and iPSC-CM transcriptional state. To prioritize future DNVs for functional testing, we used the MPRA data to develop a regression model, EpiCard. Analysis of an independent CHD cohort by EpiCard found enrichment of DNVs. Together, we developed a scalable system to measure the effect of ncDNVs on CRE activity and deployed it to systematically assess the contribution of ncDNVs to CHD.

Mapping the functional impact of non-coding regulatory elements in primary T cells through single-cell CRISPR screens

BACKGROUND

Drug targets with genetic evidence are expected to increase clinical success by at least twofold. Yet, translating disease-associated genetic variants into functional knowledge remains a fundamental challenge of drug discovery. A key issue is that the vast majority of complex disease associations cannot be cleanly mapped to a gene. Immune disease-associated variants are enriched within regulatory elements found in T-cell-specific open chromatin regions.

RESULTS

To identify genes and molecular programs modulated by these regulatory elements, we develop a CRISPRi-based single-cell functional screening approach in primary human T cells. Our pipeline enables the interrogation of transcriptomic changes induced by the perturbation of regulatory elements at scale. We first optimize an efficient CRISPRi protocol in primary CD4+ T cells via CROPseq vectors. Subsequently, we perform a screen targeting 45 non-coding regulatory elements and 35 transcription start sites and profile approximately 250,000 T -cell single-cell transcriptomes. We develop a bespoke analytical pipeline for element-to-gene (E2G) mapping and demonstrate that our method can identify both previously annotated and novel E2G links. Lastly, we integrate genetic association data for immune-related traits and demonstrate how our platform can aid in the identification of effector genes for GWAS loci.

CONCLUSIONS

We describe "primary T cell crisprQTL" - a scalable, single-cell functional genomics approach for mapping regulatory elements to genes in primary human T cells. We show how this framework can facilitate the interrogation of immune disease GWAS hits and propose that the combination of experimental and QTL-based techniques is likely to address the variant-to-function problem.

Cardiac Aging Is Promoted by Pseudohypoxia Increasing p300-Induced Glycolysis

BACKGROUND

Heart failure is typical in the elderly. Metabolic remodeling of cardiomyocytes underlies inexorable deterioration of cardiac function with aging: glycolysis increases at the expense of oxidative phosphorylation, causing an energy deficit contributing to impaired contractility. Better understanding of the mechanisms of this metabolic switching could be critical for reversing the condition.

METHODS

To investigate the role of 3 histone modifications (H3K27ac, H3K27me3, and H3K4me1) in the metabolic remodeling occurring in the aging heart, we cross-compared epigenomic, transcriptomic, and metabolomic data from mice of different ages. In addition, the role of the transcriptional coactivator p300 (E1A-associated binding protein p300)/CBP (CREB binding protein) in cardiac aging was investigated using a specific inhibitor of this histone acetyltransferase enzyme.

RESULTS

We report a set of species-conserved enhancers associated with transcriptional changes underlying age-related metabolic remodeling in cardiomyocytes. Activation of the enhancer region of Hk2-a key glycolysis pathway gene-was fostered in old age-onset mouse heart by pseudohypoxia, wherein hypoxia-related genes are expressed under normal O2 levels, via increased activity of P300/CBP. Pharmacological inhibition of this transcriptional coactivator before the onset of cardiac aging led to a more aerobic, less glycolytic, metabolic state, improved heart contractility, and overall blunting of cardiac decline.

CONCLUSIONS

Taken together, our results suggest how epigenetic dysregulation of glycolysis pathway enhancers could potentially be targeted to treat heart failure in the elderly.

Insight into the regulatory mechanism of dynamic chromatin 3D interactions during cardiomyocyte differentiation in human

Cardiogenesis is an extremely complicated process involved with DNA regulatory elements, and trans factors regulate gene expression pattern spatiotemporally. Enhancers, as the well-known DNA elements, activate target gene expression by transcription factors (TFs) occupied to organize dynamic three-dimensional (3D) interactions, which when affected or interrupted might cause heart defects or diseases. In this study, we integrated transcriptome, 3D genome, and regulatome to reorganize the global 3D genome in cardiomyogenesis, showing a gradually decreased trend of both chromatin interactions and topological associating domains (TADs) during cardiomyocyte differentiation. And almost all of the chromatin interactions occurred within the same or between adjacent TADs involved with enhancers, indicating that dynamical rewiring of enhancer-related chromatin interactions in the continuous expansive TADs is closely correlated to cardiogenesis. Moreover, we found stage-specific interactions activate stage-specific expression to be involved within corresponding biological functions, and the stage-specific combined regulations of enhancers and binding TFs form connected networks to control stage-specific expression and biological processes, which promote cardiomyocyte differentiation. Finally, we identified markers based on regulatory networks, which might drive cardiac development. This study demonstrates the power of enhancer interactome combined with active TFs to reveal insights into transcriptional regulatory networks during cardiomyogenesis.

Single-cell genomics improves the discovery of risk variants and genes of atrial fibrillation

Genome-wide association studies (GWAS) have linked hundreds of loci to cardiac diseases. However, in most loci the causal variants and their target genes remain unknown. We developed a combined experimental and analytical approach that integrates single cell epigenomics with GWAS to prioritize risk variants and genes. We profiled accessible chromatin in single cells obtained from human hearts and leveraged the data to study genetics of Atrial Fibrillation (AF), the most common cardiac arrhythmia. Enrichment analysis of AF risk variants using cell-type-resolved open chromatin regions (OCRs) implicated cardiomyocytes as the main mediator of AF risk. We then performed statistical fine-mapping, leveraging the information in OCRs, and identified putative causal variants in 122 AF-associated loci. Taking advantage of the fine-mapping results, our novel statistical procedure for gene discovery prioritized 46 high-confidence risk genes, highlighting transcription factors and signal transduction pathways important for heart development. In summary, our analysis provides a comprehensive map of AF risk variants and genes, and a general framework to integrate single-cell genomics with genetic studies of complex traits.

Three-dimensional genome structure and function

Linear DNA undergoes a series of compression and folding events, forming various three-dimensional (3D) structural units in mammalian cells, including chromosomal territory, compartment, topologically associating domain, and chromatin loop. These structures play crucial roles in regulating gene expression, cell differentiation, and disease progression. Deciphering the principles underlying 3D genome folding and the molecular mechanisms governing cell fate determination remains a challenge. With advancements in high-throughput sequencing and imaging techniques, the hierarchical organization and functional roles of higher-order chromatin structures have been gradually illuminated. This review systematically discussed the structural hierarchy of the 3D genome, the effects and mechanisms of cis-regulatory elements interaction in the 3D genome for regulating spatiotemporally specific gene expression, the roles and mechanisms of dynamic changes in 3D chromatin conformation during embryonic development, and the pathological mechanisms of diseases such as congenital developmental abnormalities and cancer, which are attributed to alterations in 3D genome organization and aberrations in key structural proteins. Finally, prospects were made for the research about 3D genome structure, function, and genetic intervention, and the roles in disease development, prevention, and treatment, which may offer some clues for precise diagnosis and treatment of related diseases.

In Vivo Dissection of Chamber-Selective Enhancers Reveals Estrogen-Related Receptor as a Regulator of Ventricular Cardiomyocyte Identity

BACKGROUND

Cardiac chamber-selective transcriptional programs underpin the structural and functional differences between atrial and ventricular cardiomyocytes (aCMs and vCMs). The mechanisms responsible for these chamber-selective transcriptional programs remain largely undefined.

METHODS

We nominated candidate chamber-selective enhancers (CSEs) by determining the genome-wide occupancy of 7 key cardiac transcription factors (GATA4, MEF2A, MEF2C, NKX2-5, SRF, TBX5, TEAD1) and transcriptional coactivator P300 in atria and ventricles. Candidate enhancers were tested using an adeno-associated virus-mediated massively parallel reporter assay. Chromatin features of CSEs were evaluated by performing assay of transposase accessible chromatin sequencing and acetylation of histone H3 at lysine 27-HiChIP on aCMs and vCMs. CSE sequence requirements were determined by systematic tiling mutagenesis of 29 CSEs at 5 bp resolution. Estrogen-related receptor (ERR) function in cardiomyocytes was evaluated by Cre-loxP-mediated inactivation of ERRα and ERRγ in cardiomyocytes.

RESULTS

We identified 134 066 and 97 506 regions reproducibly occupied by at least 1 transcription factor or P300, in atria or ventricles, respectively. Enhancer activities of 2639 regions bound by transcription factors or P300 were tested in aCMs and vCMs by adeno-associated virus-mediated massively parallel reporter assay. This identified 1092 active enhancers in aCMs or vCMs. Several overlapped loci associated with cardiovascular disease through genome-wide association studies, and 229 exhibited chamber-selective activity in aCMs or vCMs. Many CSEs exhibited differential chromatin accessibility between aCMs and vCMs, and CSEs were enriched for aCM- or vCM-selective acetylation of histone H3 at lysine 27-anchored loops. Tiling mutagenesis of 29 CSEs identified the binding motif of ERRα/γ as important for ventricular enhancer activity. The requirement of ERRα/γ to activate ventricular CSEs and promote vCM identity was confirmed by loss of the vCM gene profile in ERRα/γ knockout vCMs.

CONCLUSIONS

We identified 229 CSEs that could be useful research tools or direct therapeutic gene expression. We showed that chamber-selective multi-transcription factor, P300 occupancy, open chromatin, and chromatin looping are predictive features of CSEs. We found that ERRα/γ are essential for maintenance of ventricular identity. Finally, our gene expression, epigenetic, 3-dimensional genome, and enhancer activity atlas provide key resources for future studies of chamber-selective gene regulation.

Functional investigation of inherited noncoding genetic variation impacting the pharmacogenomics of childhood acute lymphoblastic leukemia treatment

Although acute lymphoblastic leukemia (ALL) is the most common childhood cancer, there is limited understanding of the contribution of inherited genetic variation on inter-individual differences in chemotherapy response. Defining genetic factors impacting therapy failure can help better predict response and identify drug resistance mechanisms. We therefore mapped inherited noncoding variants associated with chemotherapeutic drug resistance and/or treatment outcome to ALL cis-regulatory elements and investigated their gene regulatory potential and genomic connectivity using massively parallel reporter assays and promoter capture Hi-C, respectively. We identified 53 variants with reproducible allele-specific effects on transcription and high-confidence gene targets. Subsequent functional interrogation of the top variant (rs1247117) determined that it disrupted a PU.1 consensus motif and PU.1 binding affinity. Importantly, deletion of the genomic interval containing rs1247117 sensitized ALL cells to vincristine. Together, these data demonstrate that noncoding regulatory variation associated with diverse pharmacological traits harbor significant effects on allele-specific transcriptional activity and impact sensitivity to chemotherapeutic agents in ALL.

Global chromatin landscapes identify candidate noncoding modifiers of cardiac rhythm

Comprehensive cis-regulatory landscapes are essential for accurate enhancer prediction and disease variant mapping. Although cis-regulatory element (CRE) resources exist for most tissues and organs, many rare - yet functionally important - cell types remain overlooked. Despite representing only a small fraction of the heart's cellular biomass, the cardiac conduction system (CCS) unfailingly coordinates every life-sustaining heartbeat. To globally profile the mouse CCS cis-regulatory landscape, we genetically tagged CCS component-specific nuclei for comprehensive assay for transposase-accessible chromatin-sequencing (ATAC-Seq) analysis. Thus, we established a global CCS-enriched CRE database, referred to as CCS-ATAC, as a key resource for studying CCS-wide and component-specific regulatory functions. Using transcription factor (TF) motifs to construct CCS component-specific gene regulatory networks (GRNs), we identified and independently confirmed several specific TF sub-networks. Highlighting the functional importance of CCS-ATAC, we also validated numerous CCS-enriched enhancer elements and suggested gene targets based on CCS single-cell RNA-Seq data. Furthermore, we leveraged CCS-ATAC to improve annotation of existing human variants related to cardiac rhythm and nominated a potential enhancer-target pair that was dysregulated by a specific SNP. Collectively, our results established a CCS-regulatory compendium, identified novel CCS enhancer elements, and illuminated potential functional associations between human genomic variants and CCS component-specific CREs.

Unwind to the beat: chromatin and cardiac conduction

How chromatin accessibility and structure endow highly specialized cells with their unique phenotypes is an area of intense investigation. In the mammalian heart, an exclusive subset of cardiac cells comprise the conduction system. Many molecular components of this system are well studied and genetic variation in some of the components induces abnormal cardiac conduction. However, genetic risk for cardiac arrhythmias in human populations also occurs in noncoding regions. A study by Bhattacharyya, Kollipara, et al. in this issue of the JCI examines how chromatin accessibility and structure may explain the mechanisms by which noncoding variants increase susceptibility to cardiac arrhythmias. We discuss the implications of these findings for cell type-specific gene regulation and highlight potential therapeutic strategies to engineer locus-specific epigenomic remodeling in vivo.

An atrial fibrillation-associated regulatory region modulates cardiac Tbx5 levels and arrhythmia susceptibility

Heart development and rhythm control are highly Tbx5 dosage-sensitive. TBX5 haploinsufficiency causes congenital conduction disorders, whereas increased expression levels of TBX5 in human heart samples has been associated with atrial fibrillation (AF). We deleted the conserved mouse orthologues of two independent AF-associated genomic regions in the Tbx5 locus, one intronic (RE(int)) and one downstream (RE(down)) of Tbx5. In both lines, we observed a modest (30%) increase of Tbx5 in the postnatal atria. To gain insight into the effects of slight dosage increase in vivo, we investigated the atrial transcriptional, epigenetic and electrophysiological properties of both lines. Increased atrial Tbx5 expression was associated with induction of genes involved in development, ion transport and conduction, with increased susceptibility to atrial arrhythmias, and increased action potential duration of atrial cardiomyocytes. We identified an AF-associated variant in the human RE(int) that increases its transcriptional activity. Expression of the AF-associated transcription factor Prrx1 was induced in Tbx5^RE(int)KO cardiomyocytes. We found that some of the transcriptional and functional changes in the atria caused by increased Tbx5 expression were normalized when reducing cardiac Prrx1 expression in Tbx5^RE(int)KO mice, indicating an interaction between these two AF genes. We conclude that modest increases in expression of dose-dependent transcription factors, caused by common regulatory variants, significantly impact on the cardiac gene regulatory network and disease susceptibility.

Multi-omic association study identifies DNA methylation-mediated genotype and smoking exposure effects on lung function in children living in urban settings

Impaired lung function in early life is associated with the subsequent development of chronic respiratory disease. Most genetic associations with lung function have been identified in adults of European descent and therefore may not represent those most relevant to pediatric populations and populations of different ancestries. In this study, we performed genome-wide association analyses of lung function in a multiethnic cohort of children (n = 1,035) living in low-income urban neighborhoods. We identified one novel locus at the TDRD9 gene in chromosome 14q32.33 associated with percent predicted forced expiratory volume in one second (FEV1) (p = 2.4x10-9; βz = -0.31, 95% CI = -0.41- -0.21). Mendelian randomization and mediation analyses revealed that this genetic effect on FEV1 was partially mediated by DNA methylation levels at this locus in airway epithelial cells, which were also associated with environmental tobacco smoke exposure (p = 0.015). Promoter-enhancer interactions in airway epithelial cells revealed chromatin interaction loops between FEV1-associated variants in TDRD9 and the promoter region of the PPP1R13B gene, a stimulator of p53-mediated apoptosis. Expression of PPP1R13B in airway epithelial cells was significantly associated the FEV1 risk alleles (p = 1.3x10-5; β = 0.12, 95% CI = 0.06-0.17). These combined results highlight a potential novel mechanism for reduced lung function in urban youth resulting from both genetics and smoking exposure.

Integrated genomic analysis identifies novel low-frequency cis-regulatory variant rs2279658 associated with VSD risk in Chinese children

VSD combined with other cardiac or extracardiac malformations (defined as "complex VSD" by us) is one of the major causes of perinatal morbidity and mortality. Functional non-coding SNPs (cis-regulatory SNPs) have not been systematically studied in CHDs, including complex VSD. Here we report an exome-wide association analysis using WES data of 60 PA/VSD cases, 20 TOF cases and 100 controls in Chinese children. We identify 93 low-frequency non-coding SNPs associated with complex VSD risk. A functional genomics pipeline integrating ATAC-seq, ChIP-seq and promoter CHi-C recognizes the rs2279658 variant as a candidate cis-regulatory SNP. Specifically, rs2279658 resides in a cardiac-specific enhancer bound by FOXH1 and PITX2, and would abrogate binding of these two transcription factors to the identified enhancer during cardiac morphogenesis. COQ2 and FAM175A are predicted to be target genes for "rs2279658-FOXH1 or PITX2" pairs in the heart. These findings highlight the importance of cis-regulatory SNPs in the pathogenesis of complex VSD and broaden our understanding of this disease.

A pleiotropic hypoxia-sensitive EPAS1 enhancer is disrupted by adaptive alleles in Tibetans

In Tibetans, noncoding alleles in EPAS1-whose protein product hypoxia-inducible factor 2α (HIF-2α) drives the response to hypoxia-carry strong signatures of positive selection; however, their functional mechanism has not been systematically examined. Here, we report that high-altitude alleles disrupt the activity of four EPAS1 enhancers in one or more cell types. We further characterize one enhancer (ENH5) whose activity is both allele specific and hypoxia dependent. Deletion of ENH5 results in down-regulation of EPAS1 and HIF-2α targets in acute hypoxia and in a blunting of the transcriptional response to sustained hypoxia. Deletion of ENH5 in mice results in dysregulation of gene expression across multiple tissues. We propose that pleiotropic adaptive effects of the Tibetan alleles in EPAS1 underlie the strong selective signal at this gene.

SNP-to-gene linking strategies reveal contributions of enhancer-related and candidate master-regulator genes to autoimmune disease

We assess contributions to autoimmune disease of genes whose regulation is driven by enhancer regions (enhancer-related) and genes that regulate other genes in trans (candidate master-regulator). We link these genes to SNPs using several SNP-to-gene (S2G) strategies and apply heritability analyses to draw three conclusions about 11 autoimmune/blood-related diseases/traits. First, several characterizations of enhancer-related genes using functional genomics data are informative for autoimmune disease heritability after conditioning on a broad set of regulatory annotations. Second, candidate master-regulator genes defined using trans-eQTL in blood are also conditionally informative for autoimmune disease heritability. Third, integrating enhancer-related and master-regulator gene sets with protein-protein interaction (PPI) network information magnified their disease signal. The resulting PPI-enhancer gene score produced >2-fold stronger heritability signal and >2-fold stronger enrichment for drug targets, compared with the recently proposed enhancer domain score. In each case, functionally informed S2G strategies produced 4.1- to 13-fold stronger disease signals than conventional window-based strategies.

Genome-wide association and multi-omics studies identify MGMT as a novel risk gene for Alzheimer's disease among women

INTRODUCTION

Variants in the tau gene (MAPT) region are associated with breast cancer in women and Alzheimer's disease (AD) among persons lacking apolipoprotein E ε4 (ε4-).

METHODS

To identify novel genes associated with tau-related pathology, we conducted two genome-wide association studies (GWAS) for AD, one among 10,340 ε4- women in the Alzheimer's Disease Genetics Consortium (ADGC) and another in 31 members (22 women) of a consanguineous Hutterite kindred.

RESULTS

We identified novel associations of AD with MGMT variants in the ADGC (rs12775171, odds ratio [OR] = 1.4, P = 4.9 × 10-8 ) and Hutterite (rs12256016 and rs2803456, OR = 2.0, P = 1.9 × 10-14 ) datasets. Multi-omics analyses showed that the most significant and largest number of associations among the single nucleotide polymorphisms (SNPs), DNA-methylated CpGs, MGMT expression, and AD-related neuropathological traits were observed among women. Furthermore, promoter capture Hi-C analyses revealed long-range interactions of the MGMT promoter with MGMT SNPs and CpG sites.

DISCUSSION

These findings suggest that epigenetically regulated MGMT expression is involved in AD pathogenesis, especially in women.

Allele-specific aberration of imprinted domain chromosome architecture associates with large offspring syndrome

Large offspring syndrome (LOS) and Beckwith-Wiedemann syndrome are similar epigenetic congenital overgrowth conditions in ruminants and humans, respectively. We have reported global loss-of-imprinting, methylome epimutations, and gene misregulation in LOS. However, less than 4% of gene misregulation can be explained with short range (<20kb) alterations in DNA methylation. Therefore, we hypothesized that methylome epimutations in LOS affect chromosome architecture which results in misregulation of genes located at distances >20kb in cis and in trans (other chromosomes). Our analyses focused on two imprinted domains that frequently reveal misregulation in these syndromes, namely KvDMR1 and IGF2R. Using bovine fetal fibroblasts, we identified CTCF binding at IGF2R imprinting control region but not KvDMR1, and allele-specific chromosome architecture of these domains in controls. In LOS, analyses identified erroneous long-range contacts and clustering tendency in the direction of expression of misregulated genes. In conclusion, altered chromosome architecture is associated with LOS.

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IGF2R imprinted domain has allele-specific chromosome architecture in bovines

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In bovines, CTCF binds at IGF2R imprinting control region but not at KvDMR1

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Bovine large offspring syndrome (LOS) shows altered chromosome architecture at IGF2R

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Misregulated genes in LOS exhibit genomic location-based clustering tendency

Genetics and sports performance: the present and future in the identification of talent for sports based on DNA testing

The impact of genetics on physiology and sports performance is one of the most debated research aspects in sports sciences. Nearly 200 genetic polymorphisms have been found to influence sports performance traits, and over 20 polymorphisms may condition the status of the elite athlete. However, with the current evidence, it is certainly too early a stage to determine how to use genotyping as a tool for predicting exercise/sports performance or improving current methods of training. Research on this topic presents methodological limitations such as the lack of measurement of valid exercise performance phenotypes that make the study results difficult to interpret. Additionally, many studies present an insufficient cohort of athletes, or their classification as elite is dubious, which may introduce expectancy effects. Finally, the assessment of a progressively higher number of polymorphisms in the studies and the introduction of new analysis tools, such as the total genotype score (TGS) and genome-wide association studies (GWAS), have produced a considerable advance in the power of the analyses and a change from the study of single variants to determine pathways and systems associated with performance. The purpose of the present study was to comprehensively review evidence on the impact of genetics on endurance- and power-based exercise performance to clearly determine the potential utility of genotyping for detecting sports talent, enhancing training, or preventing exercise-related injuries, and to present an overview of recent research that has attempted to correct the methodological issues found in previous investigations.

Incorporating regulatory interactions into gene-set analyses for GWAS data: A controlled analysis with the MAGMA tool

To date, genome-wide association studies have identified thousands of statistically-significant associations between genetic variants, and phenotypes related to a myriad of traits and diseases. A key goal for human-genetics research is to translate these associations into functional mechanisms. Popular gene-set analysis tools, like MAGMA, map variants to genes they might affect, and then integrate genome-wide association study data (that is, variant-level associations for a phenotype) to score genes for association with a phenotype. Gene scores are subsequently used in competitive gene-set analyses to identify biological processes that are enriched for phenotype association. By default, variants are mapped to genes in their proximity. However, many variants that affect phenotypes are thought to act at regulatory elements, which can be hundreds of kilobases away from their target genes. Thus, we explored the idea of augmenting a proximity-based mapping scheme with publicly-available datasets of regulatory interactions. We used MAGMA to analyze genome-wide association study data for ten different phenotypes, and evaluated the effects of augmentation by comparing numbers, and identities, of genes and gene sets detected as statistically significant between mappings. We detected several pitfalls and confounders of such “augmented analyses”, and introduced ways to control for them. Using these controls, we demonstrated that augmentation with datasets of regulatory interactions only occasionally strengthened the enrichment for phenotype association amongst (biologically-relevant) gene sets for different phenotypes. Still, in such cases, genes and regulatory elements responsible for the improvement could be pinpointed. For instance, using brain regulatory-interactions for augmentation, we were able to implicate two acetylcholine receptor subunits involved in post-synaptic chemical transmission, namely CHRNB2 and CHRNE, in schizophrenia. Collectively, our study presents a critical approach for integrating regulatory interactions into gene-set analyses for genome-wide association study data, by introducing various controls to distinguish genuine results from spurious discoveries.

Minor hypertrophic cardiomyopathy genes, major insights into the genetics of cardiomyopathies

Hypertrophic cardiomyopathy (HCM) was traditionally described as an autosomal dominant Mendelian disease but is now increasingly recognized as having a complex genetic aetiology. Although eight core genes encoding sarcomeric proteins account for >90% of the pathogenic variants in patients with HCM, variants in several additional genes (ACTN2, ALPK3, CSRP3, FHOD3, FLNC, JPH2, KLHL24, PLN and TRIM63), encoding non-sarcomeric proteins with diverse functions, have been shown to be disease-causing in a small number of patients. Genome-wide association studies (GWAS) have identified numerous loci in cardiomyopathy case-control studies and biobank investigations of left ventricular functional traits. Genes associated with Mendelian cardiomyopathy are enriched in the putative causal gene lists at these loci. Intriguingly, many loci are associated with both HCM and dilated cardiomyopathy but with opposite directions of effect on left ventricular traits, highlighting a genetic basis underlying the contrasting pathophysiological effects observed in each condition. This overlap extends to rare Mendelian variants with distinct variant classes in several genes associated with HCM and dilated cardiomyopathy. In this Review, we appraise the complex contribution of the non-sarcomeric, HCM-associated genes to cardiomyopathies across a range of variant classes (from common non-coding variants of individually low effect size to complete gene knockouts), which provides insights into the genetic basis of cardiomyopathies, causal genes at GWAS loci and the application of clinical genetic testing.

Regulatory Variant rs2535629 in ITIH3 Intron Confers Schizophrenia Risk By Regulating CTCF Binding and SFMBT1 Expression

Genome-wide association studies have identified 3p21.1 as a robust risk locus for schizophrenia. However, the underlying molecular mechanisms remain elusive. Here a functional regulatory variant (rs2535629) is identified that disrupts CTCF binding at 3p21.1. It is confirmed that rs2535629 is also significantly associated with schizophrenia in Chinese population and the regulatory effect of rs2535629 is validated. Expression quantitative trait loci analysis indicates that rs2535629 is associated with the expression of three distal genes (GLT8D1, SFMBT1, and NEK4) in the human brain, and CRISPR-Cas9-mediated genome editing confirmed the regulatory effect of rs2535629 on GLT8D1, SFMBT1, and NEK4. Interestingly, differential expression analysis of GLT8D1, SFMBT1, and NEK4 suggested that rs2535629 may confer schizophrenia risk by regulating SFMBT1 expression. It is further demonstrated that Sfmbt1 regulates neurodevelopment and dendritic spine density, two key pathological characteristics of schizophrenia. Transcriptome analysis also support the potential role of Sfmbt1 in schizophrenia pathogenesis. The study identifies rs2535629 as a plausibly causal regulatory variant at the 3p21.1 risk locus and demonstrates the regulatory mechanism and biological effect of this functional variant, indicating that this functional variant confers schizophrenia risk by altering CTCF binding and regulating expression of SFMBT1, a distal gene which plays important roles in neurodevelopment and synaptic morphogenesis.

Common Genetic Variants Contribute to Risk of Transposition of the Great Arteries

RATIONALE

Dextro-transposition of the great arteries (D-TGA) is a severe congenital heart defect which affects approximately 1 in 4,000 live births. While there are several reports of D-TGA patients with rare variants in individual genes, the majority of D-TGA cases remain genetically elusive. Familial recurrence patterns and the observation that most cases with D-TGA are sporadic suggest a polygenic inheritance for the disorder, yet this remains unexplored.

OBJECTIVE

We sought to study the role of common single nucleotide polymorphisms (SNPs) in risk for D-TGA.

METHODS AND RESULTS

We conducted a genome-wide association study in an international set of 1,237 patients with D-TGA and identified a genome-wide significant susceptibility locus on chromosome 3p14.3, which was subsequently replicated in an independent case-control set (rs56219800, meta-analysis P=8.6x10-10, OR=0.69 per C allele). SNP-based heritability analysis showed that 25% of variance in susceptibility to D-TGA may be explained by common variants. A genome-wide polygenic risk score derived from the discovery set was significantly associated to D-TGA in the replication set (P=4x10-5). The genome-wide significant locus (3p14.3) co-localizes with a putative regulatory element that interacts with the promoter of WNT5A, which encodes the Wnt Family Member 5A protein known for its role in cardiac development in mice. We show that this element drives reporter gene activity in the developing heart of mice and zebrafish and is bound by the developmental transcription factor TBX20. We further demonstrate that TBX20 attenuates Wnt5a expression levels in the developing mouse heart.

CONCLUSIONS

This work provides support for a polygenic architecture in D-TGA and identifies a susceptibility locus on chromosome 3p14.3 near WNT5A. Genomic and functional data support a causal role of WNT5A at the locus.

Tissue-specific multi-omics analysis of atrial fibrillation

Genome-wide association studies (GWAS) for atrial fibrillation (AF) have uncovered numerous disease-associated variants. Their underlying molecular mechanisms, especially consequences for mRNA and protein expression remain largely elusive. Thus, refined multi-omics approaches are needed for deciphering the underlying molecular networks. Here, we integrate genomics, transcriptomics, and proteomics of human atrial tissue in a cross-sectional study to identify widespread effects of genetic variants on both transcript (cis-eQTL) and protein (cis-pQTL) abundance. We further establish a novel targeted trans-QTL approach based on polygenic risk scores to determine candidates for AF core genes. Using this approach, we identify two trans-eQTLs and five trans-pQTLs for AF GWAS hits, and elucidate the role of the transcription factor NKX2-5 as a link between the GWAS SNP rs9481842 and AF. Altogether, we present an integrative multi-omics method to uncover trans-acting networks in small datasets and provide a rich resource of atrial tissue-specific regulatory variants for transcript and protein levels for cardiovascular disease gene prioritization.

Genomic enhancers in cardiac development and disease

The Human Genome Project marked a major milestone in the scientific community as it unravelled the ~3 billion bases that are central to crucial aspects of human life. Despite this achievement, it only scratched the surface of understanding how each nucleotide matters, both individually and as part of a larger unit. Beyond the coding genome, which comprises only ~2% of the whole genome, scientists have realized that large portions of the genome, not known to code for any protein, were crucial for regulating the coding genes. These large portions of the genome comprise the 'non-coding genome'. The history of gene regulation mediated by proteins that bind to the regulatory non-coding genome dates back many decades to the 1960s. However, the original definition of 'enhancers' was first used in the early 1980s. In this Review, we summarize benchmark studies that have mapped the role of cardiac enhancers in disease and development. We highlight instances in which enhancer-localized genetic variants explain the missing link to cardiac pathogenesis. Finally, we inspire readers to consider the next phase of exploring enhancer-based gene therapy for cardiovascular disease.

Genomic frontiers in congenital heart disease

The application of next-generation sequencing to study congenital heart disease (CHD) is increasingly providing new insights into the causes and mechanisms of this prevalent birth anomaly. Whole-exome sequencing analysis identifies damaging gene variants altering single or contiguous nucleotides that are assigned pathogenicity based on statistical analyses of families and cohorts with CHD, high expression in the developing heart and depletion of damaging protein-coding variants in the general population. Gene classes fulfilling these criteria are enriched in patients with CHD and extracardiac abnormalities, evidencing shared pathways in organogenesis. Developmental single-cell transcriptomic data demonstrate the expression of CHD-associated genes in particular cell lineages, and emerging insights indicate that genetic variants perturb multicellular interactions that are crucial for cardiogenesis. Whole-genome sequencing analyses extend these observations, identifying non-coding variants that influence the expression of genes associated with CHD and contribute to the estimated ~55% of unexplained cases of CHD. These approaches combined with the assessment of common and mosaic genetic variants have provided a more complete knowledge of the causes and mechanisms of CHD. Such advances provide knowledge to inform the clinical care of patients with CHD or other birth defects and deepen our understanding of the complexity of human development. In this Review, we highlight known and candidate CHD-associated human genes and discuss how the integration of advances in developmental biology research can provide new insights into the genetic contributions to CHD.

Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome

Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.

Integration of high-resolution promoter profiling assays reveals novel, cell type-specific transcription start sites across 115 human cell and tissue types

Accurate transcription start site (TSS) annotations are essential for understanding transcriptional regulation and its role in human disease. Gene collections such as GENCODE contain annotations for tens of thousands of TSSs, but not all of these annotations are experimentally validated nor do they contain information on cell type–specific usage. Therefore, we sought to generate a collection of experimentally validated TSSs by integrating RNA Annotation and Mapping of Promoters for the Analysis of Gene Expression (RAMPAGE) data from 115 cell and tissue types, which resulted in a collection of approximately 50 thousand representative RAMPAGE peaks. These peaks are primarily proximal to GENCODE-annotated TSSs and are concordant with other transcription assays. Because RAMPAGE uses paired-end reads, we were then able to connect peaks to transcripts by analyzing the genomic positions of the 3′ ends of read mates. Using this paired-end information, we classified the vast majority (37 thousand) of our RAMPAGE peaks as verified TSSs, updating TSS annotations for 20% of GENCODE genes. We also found that these updated TSS annotations are supported by epigenomic and other transcriptomic data sets. To show the utility of this RAMPAGE rPeak collection, we intersected it with the NHGRI/EBI genome-wide association study (GWAS) catalog and identified new candidate GWAS genes. Overall, our work shows the importance of integrating experimental data to further refine TSS annotations and provides a valuable resource for the biological community.

A missense variant in NDUFA6 confers schizophrenia risk by affecting YY1 binding and NAGA expression

Genome-wide association studies (GWASs) have revealed that genetic variants at the 22q13.2 risk locus were robustly associated with schizophrenia. However, the causal variants at this risk locus and their roles in schizophrenia remain elusive. Here we identify the risk missense variant rs1801311 (located in the 1st exon of NDUFA6 gene) as likely causal for schizophrenia at 22q13.2 by disrupting binding of YY1, TAF1, and POLR2A. We systematically elucidated the regulatory mechanisms of rs1801311 and validated the regulatory effect of this missense variant. Intriguingly, rs1801311 physically interacted with NAGA (encodes the alpha-N-acetylgalactosaminidase, which is mainly involved in regulating metabolisms of glycoproteins and glycolipids in lysosome) and showed the most significant association with NAGA expression in the human brain, with the risk allele (G) associated with higher NAGA expression. Consistent with eQTL analysis, expression analysis showed that NAGA was significantly upregulated in brains of schizophrenia cases compared with controls, further supporting that rs1801311 may confer schizophrenia risk by regulating NAGA expression. Of note, we found that NAGA regulates important neurodevelopmental processes, including proliferation and differentiation of neural stem cells. Transcriptome analysis corroborated that NAGA regulates pathways associated with neuronal differentiation. Finally, we independently confirmed the association between rs1801311 and schizophrenia in a large Chinese cohort. Our study elucidates the regulatory mechanisms of the missense schizophrenia risk variant rs1801311 and provides mechanistic links between risk variant and schizophrenia etiology. In addition, this study also revealed the novel role of coding variants in gene regulation and schizophrenia risk, i.e., genetic variant in coding region of a specific gene may confer disease risk through regulating distal genes (act as regulatory variant for distal genes).

Control of cardiomyocyte differentiation timing by intercellular signaling pathways

Congenital Heart Disease (CHD), malformations of the heart present at birth, is the most common class of life-threatening birth defect (Hoffman (1995) [1], Gelb (2004) [2], Gelb (2014) [3]). A major research challenge is to elucidate the genetic determinants of CHD and mechanistically link CHD ontogeny to a molecular understanding of heart development. Although the embryonic origins of CHD are unclear in most cases, dysregulation of cardiovascular lineage specification, patterning, proliferation, migration or differentiation have been described (Olson (2004) [4], Olson (2006) [5], Srivastava (2006) [6], Dunwoodie (2007) [7], Bruneau (2008) [8]). Cardiac differentiation is the process whereby cells become progressively more dedicated in a trajectory through the cardiac lineage towards mature cardiomyocytes. Defects in cardiac differentiation have been linked to CHD, although how the complex control of cardiac differentiation prevents CHD is just beginning to be understood. The stages of cardiac differentiation are highly stereotyped and have been well-characterized (Kattman et al. (2011) [9], Wamstad et al. (2012) [10], Luna-Zurita et al. (2016) [11], Loh et al. (2016) [12], DeLaughter et al. (2016) [13]); however, the developmental and molecular mechanisms that promote or delay the transition of a cell through these stages have not been as deeply investigated. Tight temporal control of progenitor differentiation is critically important for normal organ size, spatial organization, and cellular physiology and homeostasis of all organ systems (Raff et al. (1985) [14], Amthor et al. (1998) [15], Kopan et al. (2014) [16]). This review will focus on the action of signaling pathways in the control of cardiomyocyte differentiation timing. Numerous signaling pathways, including the Wnt, Fibroblast Growth Factor, Hedgehog, Bone Morphogenetic Protein, Insulin-like Growth Factor, Thyroid Hormone and Hippo pathways, have all been implicated in promoting or inhibiting transitions along the cardiac differentiation trajectory. Gaining a deeper understanding of the mechanisms controlling cardiac differentiation timing promises to yield insights into the etiology of CHD and to inform approaches to restore function to damaged hearts.

Transcriptional enhancers and their communication with gene promoters

Transcriptional enhancers play a key role in the initiation and maintenance of gene expression programmes, particularly in metazoa. How these elements control their target genes in the right place and time is one of the most pertinent questions in functional genomics, with wide implications for most areas of biology. Here, we synthesise classic and recent evidence on the regulatory logic of enhancers, including the principles of enhancer organisation, factors that facilitate and delimit enhancer-promoter communication, and the joint effects of multiple enhancers. We show how modern approaches building on classic insights have begun to unravel the complexity of enhancer-promoter relationships, paving the way towards a quantitative understanding of gene control.

Environmental Alterations during Embryonic Development: Studying the Impact of Stressors on Pluripotent Stem Cell-Derived Cardiomyocytes

Non-communicable diseases (NCDs) sauch as diabetes, obesity and cardiovascular diseases are rising rapidly in all countries world-wide. Environmental maternal factors (e.g., diet, oxidative stress, drugs and many others), maternal illnesses and other stressors can predispose the newborn to develop diseases during different stages of life. The connection between environmental factors and NCDs was formulated by David Barker and colleagues as the Developmental Origins of Health and Disease (DOHaD) hypothesis. In this review, we describe the DOHaD concept and the effects of several environmental stressors on the health of the progeny, providing both animal and human evidence. We focus on cardiovascular diseases which represent the leading cause of death worldwide. The purpose of this review is to discuss how in vitro studies with pluripotent stem cells (PSCs), such as embryonic and induced pluripotent stem cells (ESC, iPSC), can underpin the research on non-genetic heart conditions. The PSCs could provide a tool to recapitulate aspects of embryonic development “in a dish”, studying the effects of environmental exposure during cardiomyocyte (CM) differentiation and maturation, establishing a link to molecular mechanism and epigenetics.

Leveraging three-dimensional chromatin architecture for effective reconstruction of enhancer-target gene regulatory interactions

A growing amount of evidence in literature suggests that germline sequence variants and somatic mutations in non-coding distal regulatory elements may be crucial for defining disease risk and prognostic stratification of patients, in genetic disorders as well as in cancer. Their functional interpretation is challenging because genome-wide enhancer-target gene (ETG) pairing is an open problem in genomics. The solutions proposed so far do not account for the hierarchy of structural domains which define chromatin three-dimensional (3D) architecture. Here we introduce a change of perspective based on the definition of multi-scale structural chromatin domains, integrated in a statistical framework to define ETG pairs. In this work (i) we develop a computational and statistical framework to reconstruct a comprehensive map of ETG pairs leveraging functional genomics data; (ii) we demonstrate that the incorporation of chromatin 3D architecture information improves ETG pairing accuracy and (iii) we use multiple experimental datasets to extensively benchmark our method against previous solutions for the genome-wide reconstruction of ETG pairs. This solution will facilitate the annotation and interpretation of sequence variants in distal non-coding regulatory elements. We expect this to be especially helpful in clinically oriented applications of whole genome sequencing in cancer and undiagnosed genetic diseases research.

A new era in functional genomics screens

The past 25 years of genomics research first revealed which genes are encoded by the human genome and then a detailed catalogue of human genome variation associated with many diseases. Despite this, the function of many genes and gene regulatory elements remains poorly characterized, which limits our ability to apply these insights to human disease. The advent of new CRISPR functional genomics tools allows for scalable and multiplexable characterization of genes and gene regulatory elements encoded by the human genome. These approaches promise to reveal mechanisms of gene function and regulation, and to enable exploration of how genes work together to modulate complex phenotypes.

A functional genomics pipeline identifies pleiotropy and cross-tissue effects within obesity-associated GWAS loci

Genome-wide association studies (GWAS) have identified many disease-associated variants, yet mechanisms underlying these associations remain unclear. To understand obesity-associated variants, we generate gene regulatory annotations in adipocytes and hypothalamic neurons across cellular differentiation stages. We then test variants in 97 obesity-associated loci using a massively parallel reporter assay and identify putatively causal variants that display cell type specific or cross-tissue enhancer-modulating properties. Integrating these variants with gene regulatory information suggests genes that underlie obesity GWAS associations. We also investigate a complex genomic interval on 16p11.2 where two independent loci exhibit megabase-range, cross-locus chromatin interactions. We demonstrate that variants within these two loci regulate a shared gene set. Together, our data support a model where GWAS loci contain variants that alter enhancer activity across tissues, potentially with temporally restricted effects, to impact the expression of multiple genes. This complex model has broad implications for ongoing efforts to understand GWAS.

Detecting chromosomal interactions in Capture Hi-C data with CHiCAGO and companion tools

Capture Hi-C is widely used to obtain high-resolution profiles of chromosomal interactions involving, at least on one end, regions of interest such as gene promoters. Signal detection in Capture Hi-C data is challenging and cannot be adequately accomplished with tools developed for other chromosome conformation capture methods, including standard Hi-C. Capture Hi-C Analysis of Genomic Organization (CHiCAGO) is a computational pipeline developed specifically for Capture Hi-C analysis. It implements a statistical model accounting for biological and technical background components, as well as bespoke normalization and multiple testing procedures for this data type. Here we provide a step-by-step guide to the CHiCAGO workflow that is aimed at users with basic experience of the command line and R. We also describe more advanced strategies for tuning the key parameters for custom experiments and provide guidance on data preprocessing and downstream analysis using companion tools. In a typical experiment, CHiCAGO takes ~2-3 h to run, although pre- and postprocessing steps may take much longer.

Seeing the forest through the trees: prioritising potentially functional interactions from Hi-C

Eukaryotic genomes are highly organised within the nucleus of a cell, allowing widely dispersed regulatory elements such as enhancers to interact with gene promoters through physical contacts in three-dimensional space. Recent chromosome conformation capture methodologies such as Hi-C have enabled the analysis of interacting regions of the genome providing a valuable insight into the three-dimensional organisation of the chromatin in the nucleus, including chromosome compartmentalisation and gene expression. Complicating the analysis of Hi-C data, however, is the massive amount of identified interactions, many of which do not directly drive gene function, thus hindering the identification of potentially biologically functional 3D interactions. In this review, we collate and examine the downstream analysis of Hi-C data with particular focus on methods that prioritise potentially functional interactions. We classify three groups of approaches: structural-based discovery methods, e.g. A/B compartments and topologically associated domains, detection of statistically significant chromatin interactions, and the use of epigenomic data integration to narrow down useful interaction information. Careful use of these three approaches is crucial to successfully identifying potentially functional interactions within the genome.

INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants

Genome-wide association studies reveal many non-coding variants associated with complex traits. However, model organism studies largely remain as an untapped resource for unveiling the effector genes of non-coding variants. We develop INFIMA, Integrative Fine-Mapping, to pinpoint causal SNPs for diversity outbred (DO) mice eQTL by integrating founder mice multi-omics data including ATAC-seq, RNA-seq, footprinting, and in silico mutation analysis. We demonstrate INFIMA's superior performance compared to alternatives with human and mouse chromatin conformation capture datasets. We apply INFIMA to identify novel effector genes for GWAS variants associated with diabetes. The results of the application are available at http://www.statlab.wisc.edu/shiny/INFIMA/ .

Restriction enzyme selection dictates detection range sensitivity in chromatin conformation capture-based variant-to-gene mapping approaches

Promoter-focused chromatin conformation techniques directly detect interactions between gene promoters and distal genomic sequences, providing structural information relevant to gene regulation without the excessive non-genic architectural data generated by full-scale Hi-C. 3D promoter 'interactome' maps are crucial for understanding how epigenomic features such as histone modifications and open chromatin, or genetic variants identified in genome-wide association studies (GWAS), contribute to biological function. However, variation in sensitivity between such promoter-focused methods, principally due to restriction enzyme selection, has not been systematically assessed. Here, we performed a head-to-head comparison of promoter capture datasets using 4 cutters (DpnII or MboI) versus the 6 cutter HindIII from the same five cell types. While HindIII generally produces a higher signal-to-noise ratio for significant interactions in comparison to 4-cutters, we show that DpnII/MboI detects more proximal interactions and shows little overlap with the HindIII detection range. Promoter-interacting genomic regions mapped by 4-cutters are more enriched for regulatory features and disease-associated genetic variation than 6-cutters maps, suggesting that high-resolution maps better capture gene regulatory architectures than do lower resolution approaches.

Transcriptional and Epigenetic Landscape of Cardiac Pacemaker Cells: Insights Into Cellular Specialization in the Sinoatrial Node

Cardiac pacemaker cells differentiate and functionally specialize early in embryonic development through activation of critical gene regulatory networks. In general, cellular specification and differentiation require that combinations of cell type-specific transcriptional regulators activate expression of key effector genes by binding to DNA regulatory elements including enhancers and promoters. However, because genomic DNA is tightly packaged by histones that must be covalently modified in order to render DNA regulatory elements and promoters accessible for transcription, the process of development and differentiation is intimately connected to the epigenetic regulation of chromatin accessibility. Although the difficulty of obtaining sufficient quantities of pure populations of pacemaker cells has limited progress in this field, the advent of low-input genomic technologies has the potential to catalyze a rapid growth of knowledge in this important area. The goal of this review is to outline the key transcriptional networks that control pacemaker cell development, with particular attention to our emerging understanding of how chromatin accessibility is modified and regulated during pacemaker cell differentiation. In addition, we will discuss the relevance of these findings to adult sinus node function, sinus node diseases, and origins of genetic variation in heart rhythm. Lastly, we will outline the current challenges facing this field and promising directions for future investigation.

Extensive pleiotropism and allelic heterogeneity mediate metabolic effects of IRX3 and IRX5

Whereas coding variants often have pleiotropic effects across multiple tissues, noncoding variants are thought to mediate their phenotypic effects by specific tissue and temporal regulation of gene expression. Here, we investigated the genetic and functional architecture of a genomic region within the FTO gene that is strongly associated with obesity risk. We show that multiple variants on a common haplotype modify the regulatory properties of several enhancers targeting IRX3 and IRX5 from megabase distances. We demonstrate that these enhancers affect gene expression in multiple tissues, including adipose and brain, and impart regulatory effects during a restricted temporal window. Our data indicate that the genetic architecture of disease-associated loci may involve extensive pleiotropy, allelic heterogeneity, shared allelic effects across tissues, and temporally restricted effects.

3D promoter architecture re-organization during iPSC-derived neuronal cell differentiation implicates target genes for neurodevelopmental disorders

Neurodevelopmental disorders are thought to arise from interrupted development of the brain at an early age. Genome-wide association studies (GWAS) have identified hundreds of loci associated with susceptibility to neurodevelopmental disorders; however, which noncoding variants regulate which genes at these loci is often unclear. To implicate neuronal GWAS effector genes, we performed an integrated analysis of transcriptomics, epigenomics and chromatin conformation changes during the development from Induced pluripotent stem cell-derived neuronal progenitor cells (NPCs) into neurons using a combination of high-resolution promoter-focused Capture-C, ATAC-seq and RNA-seq. We observed that gene expression changes during the NPC-to-neuron transition were highly dependent on both promoter accessibility changes and long-range interactions which connect distal cis-regulatory elements (enhancer or silencers) to developmental-stage-specific genes. These genome-scale promoter-cis-regulatory-element atlases implicated 454 neurodevelopmental disorder-associated, putative causal variants mapping to 600 distal targets. These putative effector genes were significantly enriched for pathways involved in the regulation of neuronal development and chromatin organization, with 27 % expressed in a stage-specific manner. The intersection of open chromatin and chromatin conformation revealed development-stage-specific gene regulatory architectures during neuronal differentiation, providing a rich resource to aid characterization of the genetic and developmental basis of neurodevelopmental disorders.

Genome-wide association analysis in dilated cardiomyopathy reveals two new players in systolic heart failure on chromosomes 3p25.1 and 22q11.23

AIMS

Our objective was to better understand the genetic bases of dilated cardiomyopathy (DCM), a leading cause of systolic heart failure.

METHODS AND RESULTS

We conducted the largest genome-wide association study performed so far in DCM, with 2719 cases and 4440 controls in the discovery population. We identified and replicated two new DCM-associated loci on chromosome 3p25.1 [lead single-nucleotide polymorphism (SNP) rs62232870, P = 8.7 × 10-11 and 7.7 × 10-4 in the discovery and replication steps, respectively] and chromosome 22q11.23 (lead SNP rs7284877, P = 3.3 × 10-8 and 1.4 × 10-3 in the discovery and replication steps, respectively), while confirming two previously identified DCM loci on chromosomes 10 and 1, BAG3 and HSPB7. A genetic risk score constructed from the number of risk alleles at these four DCM loci revealed a 3-fold increased risk of DCM for individuals with 8 risk alleles compared to individuals with 5 risk alleles (median of the referral population). In silico annotation and functional 4C-sequencing analyses on iPSC-derived cardiomyocytes identify SLC6A6 as the most likely DCM gene at the 3p25.1 locus. This gene encodes a taurine transporter whose involvement in myocardial dysfunction and DCM is supported by numerous observations in humans and animals. At the 22q11.23 locus, in silico and data mining annotations, and to a lesser extent functional analysis, strongly suggest SMARCB1 as the candidate culprit gene.

CONCLUSION

This study provides a better understanding of the genetic architecture of DCM and sheds light on novel biological pathways underlying heart failure.

Functional genomics and epigenomics of atrial fibrillation

Atrial fibrillation is a progressive cardiac arrhythmia that increases the risk of hospitalization and adverse cardiovascular events. Despite years of study, we still do not have a full comprehension of the molecular mechanism responsible for the disease. The recent implementation of large-scale approaches in both patient samples, population studies and animal models has helped us to broaden our knowledge on the molecular drivers responsible for AF and on the mechanisms behind disease progression. Understanding genomic and epigenomic changes that take place during chronification of AF will prove essential to design novel treatments leading to improved patient care.

Genetic Variation in Enhancers Modifies Cardiomyopathy Gene Expression and Progression

BACKGROUND

Inherited cardiomyopathy associates with a range of phenotypes, mediated by genetic and nongenetic factors. Noninherited cardiomyopathy also displays varying progression and outcomes. Expression of cardiomyopathy genes is under the regulatory control of promoters and enhancers, and human genetic variation in promoters and enhancers may contribute to this variability.

METHODS

We superimposed epigenomic profiling from hearts and cardiomyocytes, including promoter-capture chromatin conformation information, to identify enhancers for 2 cardiomyopathy genes, MYH7 and LMNA. Enhancer function was validated in human cardiomyocytes derived from induced pluripotent stem cells. We also conducted a genome-wide search to ascertain genomic variation in enhancers positioned to alter cardiac expression and correlated one of these variants to cardiomyopathy progression using biobank data.

RESULTS

Multiple enhancers were identified and validated for LMNA and MYH7, including a key enhancer that regulates the switch from MYH6 expression to MYH7 expression. Deletion of this enhancer resulted in a dose-dependent increase in MYH6 and faster contractile rate in engineered heart tissues. We searched for genomic variation in enhancer sequences across the genome, with a focus on nucleotide changes that create or interrupt transcription factor binding sites. The sequence variant, rs875908, disrupts a T-Box Transcription Factor 5 binding motif and maps to an enhancer region 2 kilobases from the transcriptional start site of MYH7. Gene editing to remove the enhancer that harbors this variant markedly reduced MYH7 expression in human cardiomyocytes. Using biobank-derived data, rs875908 associated with longitudinal echocardiographic features of cardiomyopathy.

CONCLUSIONS

Enhancers regulate cardiomyopathy gene expression, and genomic variation within these enhancer regions associates with cardiomyopathic progression over time. This integrated approach identified noncoding modifiers of cardiomyopathy and is applicable to other cardiac genes.

Functional Interrogation of Enhancer Connectome Prioritizes Candidate Target Genes at Ovarian Cancer Susceptibility Loci

Identifying causal regulatory variants and their target genes from the majority of non-coding disease-associated genetic loci is the main challenge in post-Genome-Wide Association Studies (GWAS) functional studies. Although chromosome conformation capture (3C) and its derivative technologies have been successfully applied to nominate putative causal genes for non-coding variants, many GWAS target genes have not been identified yet. This study generated a high-resolution contact map from epithelial ovarian cancer (EOC) cells with two H3K27ac-HiChIP libraries and analyzed the underlying gene networks for 15 risk loci identified from the largest EOC GWAS. By combinatory analysis of 4,021 fine-mapped credible variants of EOC GWAS and high-resolution contact map, we obtained 162 target genes that mainly enriched in cancer related pathways. Compared with GTEx eQTL genes in ovarian tissue and annotated proximal genes, 132 HiChIP targets were first identified for EOC causal variants. More than half of the credible variants (CVs) involved interactions that were over 185 kb in distance, indicating that long-range transcriptional regulation is an important mechanism for the function of GWAS variants in EOC. We also found that many HiChIP gene targets showed significantly differential expressions between normal ovarian and EOC tumor samples. We validated one of these targets by manipulating the rs9303542 located region with CRISPR-Cas9 deletion and dCas9-VP64 activation experiments and found altered expression of HOXB7 and HOXB8 at 17q21.32. This study presents a systematic analysis to identify putative target genes for causal variants of EOC, providing an in-depth investigation of the mechanisms of non-coding regulatory variants in the etiology and pathogenesis of ovarian cancer.

Taking Data Science to Heart: Next Scale of Gene Regulation

PURPOSE OF REVIEW

Technical advances have facilitated high-throughput measurements of the genome in the context of cardiovascular biology. These techniques bring a deluge of gargantuan datasets, which in turn present two fundamentally new opportunities for innovation-data processing and knowledge integration-toward the goal of meaningful basic and translational discoveries.

RECENT FINDINGS

Big data, integrative analyses, and machine learning have brought cardiac investigations to the cutting edge of chromatin biology, not only to reveal basic principles of gene regulation in the heart, but also to aid in the design of targeted epigenetic therapies.

SUMMARY

Cardiac studies using big data are only beginning to integrate the millions of recorded data points and the tools of machine learning are aiding this process. Future experimental design should take into consideration insights from existing genomic datasets, thereby focusing on heretofore unexplored epigenomic contributions to disease pathology.