Promoter-interacting expression quantitative trait loci are enriched for functional genetic variants

A guide to studying 3D genome structure and dynamics in the kidney

The human genome is tightly packed into the 3D environment of the cell nucleus. Rapidly evolving and sophisticated methods of mapping 3D genome architecture have shed light on fundamental principles of genome organization and gene regulation. The genome is physically organized on different scales, from individual genes to entire chromosomes. Nuclear landmarks such as the nuclear envelope and nucleoli have important roles in compartmentalizing the genome within the nucleus. Genome activity (for example, gene transcription) is also functionally partitioned within this 3D organization. Rather than being static, the 3D organization of the genome is tightly regulated over various time scales. These dynamic changes in genome structure over time represent the fourth dimension of the genome. Innovative methods have been used to map the dynamic regulation of genome structure during important cellular processes including organism development, responses to stimuli, cell division and senescence. Furthermore, disruptions to the 4D genome have been linked to various diseases, including of the kidney. As tools and approaches to studying the 4D genome become more readily available, future studies that apply these methods to study kidney biology will provide insights into kidney function in health and disease.

A compendium of genetic variations associated with promoter usage across 49 human tissues

Promoters play a crucial role in regulating gene transcription. However, our understanding of how genetic variants influence alternative promoter selection is still incomplete. In this study, we implement a framework to identify genetic variants that affect the relative usage of alternative promoters, known as promoter usage quantitative trait loci (puQTLs). By constructing an atlas of human puQTLs across 49 different tissues from 838 individuals, we have identified approximately 76,856 independent loci associated with promoter usage, encompassing 602,009 genetic variants. Our study demonstrates that puQTLs represent a distinct type of molecular quantitative trait loci, effectively uncovering regulatory targets and patterns. Furthermore, puQTLs are regulating in a tissue-specific manner and are enriched with binding sites of epigenetic marks and transcription factors, especially those involved in chromatin architecture formation. Notably, we have also found that puQTLs colocalize with complex traits or diseases and contribute to their heritability. Collectively, our findings underscore the significant role of puQTLs in elucidating the molecular mechanisms underlying tissue development and complex diseases.

Cell-type-specific mapping of enhancers and target genes from single-cell multimodal data

Mapping enhancers and target genes in disease-related cell types has provided critical insights into the functional mechanisms of genetic variants identified by genome-wide association studies (GWAS). However, most existing analyses rely on bulk data or cultured cell lines, which may fail to identify cell-type-specific enhancers and target genes. Recently, single-cell multimodal data measuring both gene expression and chromatin accessibility within the same cells have enabled the inference of enhancer-gene pairs in a cell-type-specific and context-specific manner. However, this task is challenged by the data's high sparsity, sequencing depth variation, and the computational burden of analyzing a large number of enhancer-gene pairs. To address these challenges, we propose scMultiMap, a statistical method that infers enhancer-gene association from sparse multimodal counts using a joint latent-variable model. It adjusts for technical confounding, permits fast moment-based estimation and provides analytically derived p -values. In systematic analyses of blood and brain data, scMultiMap shows appropriate type I error control, high statistical power with greater reproducibility across independent datasets and stronger consistency with orthogonal data modalities. Meanwhile, its computational cost is less than 1% of existing methods. When applied to single-cell multimodal data from postmortem brain samples from Alzheimer's disease (AD) patients and controls, scMultiMap gave the highest heritability enrichment in microglia and revealed new insights into the regulatory mechanisms of AD GWAS variants in microglia.

Dynamic chromatin architecture identifies new autoimmune-associated enhancers for IL2 and novel genes regulating CD4+ T cell activation

Genome-wide association studies (GWAS) have identified hundreds of genetic signals associated with autoimmune disease. The majority of these signals are located in non-coding regions and likely impact cis-regulatory elements (cRE). Because cRE function is dynamic across cell types and states, profiling the epigenetic status of cRE across physiological processes is necessary to characterize the molecular mechanisms by which autoimmune variants contribute to disease risk. We localized risk variants from 15 autoimmune GWAS to cRE active during TCR-CD28 co-stimulation of naïve human CD4+ T cells. To characterize how dynamic changes in gene expression correlate with cRE activity, we measured transcript levels, chromatin accessibility, and promoter-cRE contacts across three phases of naive CD4+ T cell activation using RNA-seq, ATAC-seq, and HiC. We identified ~1200 protein-coding genes physically connected to accessible disease-associated variants at 423 GWAS signals, at least one-third of which are dynamically regulated by activation. From these maps, we functionally validated a novel stretch of evolutionarily conserved intergenic enhancers whose activity is required for activation-induced IL2 gene expression in human and mouse, and is influenced by autoimmune-associated genetic variation. The set of genes implicated by this approach are enriched for genes controlling CD4+ T cell function and genes involved in human inborn errors of immunity, and we pharmacologically validated eight implicated genes as novel regulators of T cell activation. These studies directly show how autoimmune variants and the genes they regulate influence processes involved in CD4+ T cell proliferation and activation.

Identifying genetic variants associated with chromatin looping and genome function

Here we present a comprehensive HiChIP dataset on naïve CD4 T cells (nCD4) from 30 donors and identify QTLs that associate with genotype-dependent and/or allele-specific variation of HiChIP contacts defining loops between active regulatory regions (iQTLs). We observe a substantial overlap between iQTLs and previously defined eQTLs and histone QTLs, and an enrichment for fine-mapped QTLs and GWAS variants. Furthermore, we describe a distinct subset of nCD4 iQTLs, for which the significant variation of chromatin contacts in nCD4 are translated into significant eQTL trends in CD4 T cell memory subsets. Finally, we define connectivity-QTLs as iQTLs that are significantly associated with concordant genotype-dependent changes in chromatin contacts over a broad genomic region (e.g., GWAS SNP in the RNASET2 locus). Our results demonstrate the importance of chromatin contacts as a complementary modality for QTL mapping and their power in identifying previously uncharacterized QTLs linked to cell-specific gene expression and connectivity.

Predictive Prioritization of Enhancers Associated with Pancreas Disease Risk

Genetic and epigenetic variations in regulatory enhancer elements increase susceptibility to a range of pathologies. Despite recent advances, linking enhancer elements to target genes and predicting transcriptional outcomes of enhancer dysfunction remain significant challenges. Using 3D chromatin conformation assays, we generated an extensive enhancer interaction dataset for the human pancreas, encompassing more than 20 donors and five major cell types, including both exocrine and endocrine compartments. We employed a network approach to parse chromatin interactions into enhancer-promoter tree models, facilitating a quantitative, genome-wide analysis of enhancer connectivity. With these tree models, we developed a machine learning algorithm to estimate the impact of enhancer perturbations on cell type-specific gene expression in the human pancreas. Orthogonal to our computational approach, we perturbed enhancer function in primary human pancreas cells using CRISPR interference and quantified the effects at the single-cell level through RNA FISH coupled with high-throughput imaging. Our enhancer tree models enabled the annotation of common germline risk variants associated with pancreas diseases, linking them to putative target genes in specific cell types. For pancreatic ductal adenocarcinoma, we found a stronger enrichment of disease susceptibility variants within acinar cell regulatory elements, despite ductal cells historically being assumed as the primary cell-of-origin. Our integrative approach-combining cell type-specific enhancer-promoter interaction mapping, computational models, and single-cell enhancer perturbation assays-produced a robust resource for studying the genetic basis of pancreas disorders.

Genetic regulation of microRNAs in the older adult brain and their contribution to neuropsychiatric conditions

MicroRNAs are essential post-transcriptional regulators of gene expression and involved in many biological processes; however, our understanding of their genetic regulation and role in brain illnesses is limited. Here, we mapped brain microRNA expression quantitative trait loci (miR-QTLs) using genome-wide small RNA sequencing profiles from dorsolateral prefrontal cortex (dlPFC) samples of 604 older adult donors of European ancestry. miR-QTLs were identified for 224 miRNAs (48% of 470 tested miRNAs) at false discovery rate < 1%. We found that miR-QTLs were enriched in brain promoters and enhancers, and that intragenic miRNAs often did not share QTLs with their host gene. Additionally, we integrated the brain miR-QTLs with results from 16 GWAS of psychiatric and neurodegenerative diseases using multiple independent integration approaches and identified four miRNAs that contribute to the pathogenesis of bipolar disorder, major depression, post-traumatic stress disorder, schizophrenia, and Parkinson's disease. This study provides novel insights into the contribution of miRNAs to the complex biological networks that link genetic variation to disease.

A Multilayered Post-Genome-Wide Association Study Analysis Pipeline Defines Functional Variants and Target Genes for Systemic Lupus Erythematosus

OBJECTIVE

Systemic lupus erythematosus (SLE), an autoimmune disease with incompletely understood etiology, has a strong genetic component. Although genome-wide association studies (GWASs) have revealed multiple SLE susceptibility loci and associated single-nucleotide polymorphisms (SNPs), the precise causal variants, target genes, cell types, tissues, and mechanisms of action remain largely unknown.

METHODS

Here, we report a comprehensive post-GWAS analysis using extensive bioinformatics, molecular modeling, and integrative functional genomic and epigenomic analyses to optimize fine-mapping. We compile and cross-reference immune cell-specific expression quantitative trait loci (cis- and trans-expression quantitative trait loci) with promoter capture high-throughput capture chromatin conformation (PCHi-C), allele-specific chromatin accessibility, and massively parallel reporter assay data to define predisposing variants and target genes. We experimentally validate a predicted locus using CRISPR/Cas9 genome editing, quantitative polymerase chain reaction, and Western blot.

RESULTS

Anchoring on 452 index SNPs, we selected 9,931 high linkage disequilibrium (r2 > 0.8) SNPs and defined 182 independent non-human leukocyte antigen (HLA) SLE loci. The 3,746 SNPs from 143 loci were identified as regulating 564 unique genes. Target genes are enriched in lupus-related tissues and associated with other autoimmune diseases. Of these, 329 SNPs (106 loci) showed significant allele-specific chromatin accessibility and/or enhancer activity, indicating regulatory potential. Using CRISPR/Cas9, we validated reference SNP identifier 57668933 (rs57668933) as a functional variant regulating multiple targets, including SLE-risk gene ELF1 in B cells.

CONCLUSION

We demonstrate and validate post-GWAS strategies for using multidimensional data to prioritize likely causal variants with cognate gene targets underlying SLE pathogenesis. Our results provide a catalog of significantly SLE-associated SNPs and loci, target genes, and likely biochemical mechanisms to guide experimental characterization.

Predicting gene expression state and prioritizing putative enhancers using 5hmC signal

BACKGROUND

Like its parent base 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC) is a direct epigenetic modification of cytosines in the context of CpG dinucleotides. 5hmC is the most abundant oxidized form of 5mC, generated through the action of TET dioxygenases at gene bodies of actively-transcribed genes and at active or lineage-specific enhancers. Although such enrichments are reported for 5hmC, to date, predictive models of gene expression state or putative regulatory regions for genes using 5hmC have not been developed.

RESULTS

Here, by using only 5hmC enrichment in genic regions and their vicinity, we develop neural network models that predict gene expression state across 49 cell types. We show that our deep neural network models distinguish high vs low expression state utilizing only 5hmC levels and these predictive models generalize to unseen cell types. Further, in order to leverage 5hmC signal in distal enhancers for expression prediction, we employ an Activity-by-Contact model and also develop a graph convolutional neural network model with both utilizing Hi-C data and 5hmC enrichment to prioritize enhancer-promoter links. These approaches identify known and novel putative enhancers for key genes in multiple immune cell subsets.

CONCLUSIONS

Our work highlights the importance of 5hmC in gene regulation through proximal and distal mechanisms and provides a framework to link it to genome function. With the recent advances in 6-letter DNA sequencing by short and long-read techniques, profiling of 5mC and 5hmC may be done routinely in the near future, hence, providing a broad range of applications for the methods developed here.

Effects of Akt Activator SC79 on Human M0 Macrophage Phagocytosis and Cytokine Production

Akt is an important kinase in metabolism. Akt also phosphorylates and activates endothelial and neuronal nitric oxide (NO) synthases (eNOS and nNOS, respectively) expressed in M0 (unpolarized) macrophages. We showed that e/nNOS NO production downstream of bitter taste receptors enhances macrophage phagocytosis. In airway epithelial cells, we also showed that the activation of Akt by a small molecule (SC79) enhances NO production and increases levels of nuclear Nrf2, which reduces IL-8 transcription during concomitant stimulation with Toll-like receptor (TLR) 5 agonist flagellin. We hypothesized that SC79's production of NO in macrophages might likewise enhance phagocytosis and reduce the transcription of some pro-inflammatory cytokines. Using live cell imaging of fluorescent biosensors and indicator dyes, we found that SC79 induces Akt activation, NO production, and downstream cGMP production in primary human M0 macrophages. This was accompanied by a reduction in IL-6, IL-8, and IL-12 production during concomitant stimulation with bacterial lipopolysaccharide, an agonist of pattern recognition receptors including TLR4. Pharmacological inhibitors suggested that this effect was dependent on Akt and Nrf2. Together, these data suggest that several macrophage immune pathways are regulated by SC79 via Akt. A small-molecule Akt activator may be useful in some infection settings, warranting future in vivo studies.

Lack of evidence for GWAS signals of exfoliation glaucoma working via monogenic loss-of-function mutation in the nearest gene

PURPOSE

Exfoliation syndrome (XFS) is a systemic disease of elastin-rich tissues involving a deposition of fibrillar exfoliative material (XFM) in the anterior chamber of the eye, which can promote glaucoma. The purpose of this study was to create mice with CRISPR/Cas9-induced variations in candidate genes identified from human genome-wide association studies (GWAS) and screen them for indices of XFS.

METHODS

Variants predicted to be deleterious were sought in the Agpat1, Cacna1a, Loxl1, Pomp, Rbms3, Sema6a, and Tlcd5 genes of C57BL/6J mice using CRISPR/Cas9-based gene editing. Strains were phenotyped by slit-lamp, SD-OCT imaging, and fundus exams at 1-5 mos of age. Smaller cohorts of 12-mos-old mice were also studied.

RESULTS

Deleterious variants were identified in six targets; Pomp was recalcitrant to targeting. Multiple alleles of some targets were isolated, yielding 12 strains. Across all genotypes and ages, 277 mice were assessed by 902 slit-lamp exams, 928 SD-OCT exams, and 358 fundus exams. Homozygosity for Agpat1 or Cacna1a mutations led to early lethality; homozygosity for Loxl1 mutations led to pelvic organ prolapse, preventing aging. Loxl1 homozygotes exhibited a conjunctival phenotype of potential relevance to XFS. Multiple other genotype-specific phenotypes were variously identified. XFM was not observed in any mice.

CONCLUSIONS

This study did not detect XFM in any of the strains. This may have been due to species-specific differences, background dependence, or insufficient aging. Alternatively, it is possible that the current candidates, selected based on proximity to GWAS signals, are not effectors acting via monogenic loss-of-function mechanisms.

Loop Catalog: a comprehensive HiChIP database of human and mouse samples

HiChIP enables cost-effective and high-resolution profiling of regulatory and structural loops. To leverage the increasing number of publicly available HiChIP datasets from diverse cell lines and primary cells, we developed the Loop Catalog (https://loopcatalog.lji.org), a web-based database featuring HiChIP loop calls for 1319 samples across 133 studies and 44 high-resolution Hi-C loop calls. We demonstrate its utility in interpreting fine-mapped GWAS variants (SNP-to-gene linking), in identifying enriched sequence motifs and motif pairs at loop anchors, and in network-level analysis of loops connecting regulatory elements (community detection). Our comprehensive catalog, spanning over 4M unique 5kb loops, along with the accompanying analysis modalities constitutes an important resource for studies in gene regulation and genome organization.

Omics-based construction of regulatory variants can be applied to help decipher pig liver-related traits

Genetic variants can influence complex traits by altering gene expression through changes to regulatory elements. However, the genetic variants that affect the activity of regulatory elements in pigs are largely unknown, and the extent to which these variants influence gene expression and contribute to the understanding of complex phenotypes remains unclear. Here, we annotate 90,991 high-quality regulatory elements using acetylation of histone H3 on lysine 27 (H3K27ac) ChIP-seq of 292 pig livers. Combined with genome resequencing and RNA-seq data, we identify 28,425 H3K27ac quantitative trait loci (acQTLs) and 12,250 expression quantitative trait loci (eQTLs). Through the allelic imbalance analysis, we validate two causative acQTL variants in independent datasets. We observe substantial sharing of genetic controls between gene expression and H3K27ac, particularly within promoters. We infer that 46% of H3K27ac exhibit a concomitant rather than causative relationship with gene expression. By integrating GWAS, eQTLs, acQTLs, and transcription factor binding prediction, we further demonstrate their application, through metabolites dulcitol, phosphatidylcholine (PC) (16:0/16:0) and published phenotypes, in identifying likely causal variants and genes, and discovering sub-threshold GWAS loci. We provide insight into the relationship between regulatory elements and gene expression, and the genetic foundation for dissecting the molecular mechanism of phenotypes.

Integrative high-throughput enhancer surveying and functional verification divulges a YY2-condensed regulatory axis conferring risk for osteoporosis

The precise roles of chromatin organization at osteoporosis risk loci remain largely elusive. Here, we combined chromatin interaction conformation (Hi-C) profiling and self-transcribing active regulatory region sequencing (STARR-seq) to qualify enhancer activities of prioritized osteoporosis-associated single-nucleotide polymorphisms (SNPs). We identified 319 SNPs with biased allelic enhancer activity effect (baaSNPs) that linked to hundreds of candidate target genes through chromatin interactions across 146 loci. Functional characterizations revealed active epigenetic enrichment for baaSNPs and prevailing osteoporosis-relevant regulatory roles for their chromatin interaction genes. Further motif enrichment and network mapping prioritized several putative, key transcription factors (TFs) controlling osteoporosis binding to baaSNPs. Specifically, we selected one top-ranked TF and deciphered that an intronic baaSNP (rs11202530) could allele-preferentially bind to YY2 to augment PAPSS2 expression through chromatin interactions and promote osteoblast differentiation. Our results underline the roles of TF-mediated enhancer-promoter contacts for osteoporosis, which may help to better understand the intricate molecular regulatory mechanisms underlying osteoporosis risk loci.

QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration

DNA methylation provides a crucial epigenetic mark linking genetic variations to environmental influence. We have analyzed array-based DNA methylation profiles of 160 human retinas with co-measured RNA-seq and >8 million genetic variants, uncovering sites of genetic regulation in cis (37,453 methylation quantitative trait loci and 12,505 expression quantitative trait loci) and 13,747 DNA methylation loci affecting gene expression, with over one-third specific to the retina. Methylation and expression quantitative trait loci show non-random distribution and enrichment of biological processes related to synapse, mitochondria, and catabolism. Summary data-based Mendelian randomization and colocalization analyses identify 87 target genes where methylation and gene-expression changes likely mediate the genotype effect on age-related macular degeneration. Integrated pathway analysis reveals epigenetic regulation of immune response and metabolism including the glutathione pathway and glycolysis. Our study thus defines key roles of genetic variations driving methylation changes, prioritizes epigenetic control of gene expression, and suggests frameworks for regulation of macular degeneration pathology by genotype-environment interaction in retina.

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.

Systematic identification of genotype-dependent enhancer variants in eosinophilic esophagitis

Eosinophilic esophagitis (EoE) is a rare atopic disorder associated with esophageal dysfunction, including difficulty swallowing, food impaction, and inflammation, that develops in a small subset of people with food allergies. Genome-wide association studies (GWASs) have identified 9 independent EoE risk loci reaching genome-wide significance (p < 5 × 10-8) and 27 additional loci of suggestive significance (5 × 10-8 < p < 1 × 10-5). In the current study, we perform linkage disequilibrium (LD) expansion of these loci to nominate a set of 531 variants that are potentially causal. To systematically interrogate the gene regulatory activity of these variants, we designed a massively parallel reporter assay (MPRA) containing the alleles of each variant within their genomic sequence context cloned into a GFP reporter library. Analysis of reporter gene expression in TE-7, HaCaT, and Jurkat cells revealed cell-type-specific gene regulation. We identify 32 allelic enhancer variants, representing 6 genome-wide significant EoE loci and 7 suggestive EoE loci, that regulate reporter gene expression in a genotype-dependent manner in at least one cellular context. By annotating these variants with expression quantitative trait loci (eQTL) and chromatin looping data in related tissues and cell types, we identify putative target genes affected by genetic variation in individuals with EoE. Transcription factor enrichment analyses reveal possible roles for cell-type-specific regulators, including GATA3. Our approach reduces the large set of EoE-associated variants to a set of 32 with allelic regulatory activity, providing functional insights into the effects of genetic variation in this disease.

A cis-regulatory element regulates ERAP2 expression through autoimmune disease risk SNPs

Single-nucleotide polymorphisms (SNPs) near the ERAP2 gene are associated with various autoimmune conditions, as well as protection against lethal infections. Due to high linkage disequilibrium, numerous trait-associated SNPs are correlated with ERAP2 expression; however, their functional mechanisms remain unidentified. We show by reciprocal allelic replacement that ERAP2 expression is directly controlled by the splice region variant rs2248374. However, disease-associated variants in the downstream LNPEP gene promoter are independently associated with ERAP2 expression. Allele-specific conformation capture assays revealed long-range chromatin contacts between the gene promoters of LNPEP and ERAP2 and showed that interactions were stronger in patients carrying the alleles that increase susceptibility to autoimmune diseases. Replacing the SNPs in the LNPEP promoter by reference sequences lowered ERAP2 expression. These findings show that multiple SNPs act in concert to regulate ERAP2 expression and that disease-associated variants can convert a gene promoter region into a potent enhancer of a distal gene.

Dissecting the Immune System through Gene Regulation

The immune system plays a dual role in human health, functioning both as a protector against pathogens and, at times, as a contributor to disease. This feature emphasizes the importance to uncover the underlying causes of its malfunctions, necessitating an in-depth analysis in both pathological and physiological conditions to better understand the immune system and immune disorders. Recent advances in scientific technology have enabled extensive investigations into gene regulation, a crucial mechanism governing cellular functionality. Studying gene regulatory mechanisms within the immune system is a promising avenue for enhancing our understanding of immune cells and the immune system as a whole. The gene regulatory mechanisms, revealed through various methodologies, and their implications in the field of immunology are discussed in this chapter.

Human_SNP_TATAdb: a database of SNPs that statistically significantly change the affinity of the TATA-binding protein to human gene promoters: genome-wide analysis and use cases

It was previously shown that the expression levels of human genes positively correlate with TBP affinity for the promoters of these genes. In turn, single nucleotide polymorphisms (SNPs) in human gene promoters can affect TBP affinity for DNA and, as a consequence, gene expression. The Institute of Cytology and Genetics SB RAS (ICG) has developed a method for predicting TBP affinity for gene promoters based on a three-step binding mecha- nism: (1) TBP slides along DNA, (2) TBP stops at the binding site, and (3) the TBP-promoter complex is fixed due to DNA helix bending. The method showed a high correlation of theoretical predictions with measured values during repeated experimental testing by independent groups of researchers. This model served as a base for other ICG web services, SNP_TATA_Z-tester and SNP_TATA_Comparator, which make a statistical assessment of the SNP-induced change in the affinity of TBP binding to the human gene promoter and help predict changes in expression that may be associated with a genetic predisposition to diseases or phenotypic features of the organism. In this work, we integrated into a single database information about SNPs in human gene promoters obtained by automatic extrac- tion from various heterogeneous data sources, as well as the estimates of TBP affinity for the promoter obtained using the three-step binding model and predicting their effect on gene expression for wild-type promoters and promoters with SNPs. We have shown that Human_SNP_TATAdb can be used for annotation and identification of candidate SNP markers of diseases. The results of a genome-wide data analysis are presented, including the distri- bution of genes with respect to the number of transcripts, the distribution of SNPs affecting TBP-DNA affinity with respect to positions within promoters, as well as patterns linking TBP affinity for the promoter, the specificity of the TBP binding site for the promoter and other characteristics of promoters. The results of the genome-wide analysis showed that the affinity of TBP for the promoter and the specificity of its binding site are statistically related to other characteristics of promoters important for the functional classification of promoters and the study of the features of differential gene expression.

Identifying genetic variants that influence the abundance of cell states in single-cell data

To understand genetic mechanisms driving disease, it is essential but difficult to map how risk alleles affect the composition of cells present in the body. Single-cell profiling quantifies granular information about tissues, but variant-associated cell states may reflect diverse combinations of the profiled cell features that are challenging to predefine. We introduce GeNA (Genotype-Neighborhood Associations), a statistical tool to identify cell state abundance quantitative trait loci (csaQTLs) in high-dimensional single-cell datasets. Instead of testing associations to predefined cell states, GeNA flexibly identifies the cell states whose abundance is most associated with genetic variants. In a genome-wide survey of scRNA-seq peripheral blood profiling from 969 individuals,1GeNA identifies five independent loci associated with shifts in the relative abundance of immune cell states. For example, rs3003-T (p=1.96×10-11) associates with increased abundance of NK cells expressing TNF-α response programs. This csaQTL colocalizes with increased risk for psoriasis, an autoimmune disease that responds to anti-TNF treatments. Flexibly characterizing csaQTLs for granular cell states may help illuminate how genetic background alters cellular composition to confer disease risk.

Leveraging molecular quantitative trait loci to comprehend complex diseases/traits from the omics perspective

Comprehending the molecular basis of quantitative genetic variation is a principal goal for complex diseases or traits. Molecular quantitative trait loci (molQTLs) have made it possible to investigate the effects of genetic variants hiding behind large-scale omics data. A deeper understanding of molQTL is urgently required in light of the multi-dimensionalization of omics data to more fully elucidate the pertinent biological mechanisms. Herein, we reviewed molQTLs with the corresponding resource from the omics perspective and further discussed the integrative strategy of GWAS-molQTL to infer their causal effects. Subsequently, we described the opportunities and challenges encountered by molQTL. The case studies showed that molQTL is essential for complex diseases and traits, whether single- or multi-omics QTLs. Overall, we highlighted the functional significance of genetic variants to employ the discovery of molQTL in complex diseases and traits.

Epromoters are new players in the regulatory landscape with potential pleiotropic roles

Precise spatiotemporal control of gene expression during normal development and cell differentiation is achieved by the combined action of proximal (promoters) and distal (enhancers) cis-regulatory elements. Recent studies have reported that a subset of promoters, termed Epromoters, works also as enhancers to regulate distal genes. This new paradigm opened novel questions regarding the complexity of our genome and raises the possibility that genetic variation within Epromoters has pleiotropic effects on various physiological and pathological traits by differentially impacting multiple proximal and distal genes. Here, we discuss the different observations pointing to an important role of Epromoters in the regulatory landscape and summarize the evidence supporting a pleiotropic impact of these elements in disease. We further hypothesize that Epromoter might represent a major contributor to phenotypic variation and disease.

A multilayered post-GWAS analysis pipeline defines functional variants and target genes for systemic lupus erythematosus (SLE)

Objectives

Systemic lupus erythematosus (SLE), an autoimmune disease with incompletely understood etiology, has a strong genetic component. Although genome-wide association studies (GWAS) have revealed multiple SLE susceptibility loci and associated single nucleotide polymorphisms (SNPs), the precise causal variants, target genes, cell types, tissues, and mechanisms of action remain largely unknown.

Methods

Here, we report a comprehensive post-GWAS analysis using extensive bioinformatics, molecular modeling, and integrative functional genomic and epigenomic analyses to optimize fine-mapping. We compile and cross-reference immune cell-specific expression quantitative trait loci ( cis - and trans -eQTLs) with promoter-capture Hi-C, allele-specific chromatin accessibility, and massively parallel reporter assay data to define predisposing variants and target genes. We experimentally validate a predicted locus using CRISPR/Cas9 genome editing, qPCR, and Western blot.

Results

Anchoring on 452 index SNPs, we selected 9,931 high-linkage disequilibrium (r 2 >0.8) SNPs and defined 182 independent non-HLA SLE loci. 3,746 SNPs from 143 loci were identified as regulating 564 unique genes. Target genes are enriched in lupus-related tissues and associated with other autoimmune diseases. Of these, 329 SNPs (106 loci) showed significant allele-specific chromatin accessibility and/or enhancer activity, indicating regulatory potential. Using CRISPR/Cas9, we validated rs57668933 as a functional variant regulating multiple targets, including SLE risk gene ELF1 , in B-cells.

Conclusion

We demonstrate and validate post-GWAS strategies for utilizing multi-dimensional data to prioritize likely causal variants with cognate gene targets underlying SLE pathogenesis. Our results provide a catalog of significantly SLE-associated SNPs and loci, target genes, and likely biochemical mechanisms, to guide experimental characterization.

Toward a comprehensive catalog of regulatory elements

Regulatory elements are the genomic regions that interact with transcription factors to control cell-type-specific gene expression in different cellular environments. A precise and complete catalog of functional elements encoded by the human genome is key to understanding mammalian gene regulation. Here, we review the current state of regulatory element annotation. We first provide an overview of assays for characterizing functional elements, including genome, epigenome, transcriptome, three-dimensional chromatin interaction, and functional validation assays. We then discuss computational methods for defining regulatory elements, including peak-calling and other statistical modeling methods. Finally, we introduce several high-quality lists of regulatory element annotations and suggest potential future directions.

QTL mapping of human retina DNA methylation identifies 87 gene-epigenome interactions in age-related macular degeneration

DNA methylation (DNAm) provides a crucial epigenetic mark linking genetic variations to environmental influence. We analyzed array-based DNAm profiles of 160 human retinas with co-measured RNA-seq and > 8 million genetic variants, uncovering sites of genetic regulation in cis (37,453 mQTLs and 12,505 eQTLs) and 13,747 eQTMs (DNAm loci affecting gene expression), with over one-third specific to the retina. mQTLs and eQTMs show non-random distribution and enrichment of biological processes related to synapse, mitochondria, and catabolism. Summary data-based Mendelian randomization and colocalization analyses identify 87 target genes where methylation and gene-expression changes likely mediate the genotype effect on age-related macular degeneration (AMD). Integrated pathway analysis reveals epigenetic regulation of immune response and metabolism including the glutathione pathway and glycolysis. Our study thus defines key roles of genetic variations driving methylation changes, prioritizes epigenetic control of gene expression, and suggests frameworks for regulation of AMD pathology by genotype-environment interaction in retina.

Genetic variants of the nuclear factor erythroid 2-related factor 2/antioxidant reaction element pathway on the risk of antituberculosis drug-induced liver injury: a systematic review

Aim: To evaluate the effects of genetic variants in the nuclear factor erythroid 2-related factor 2/antioxidant reaction element signaling pathway on antituberculosis drug-induced liver injury (AT-DILI) susceptibility. Methods: The PubMed, Embase, Cochrane, Web of Science, China National Knowledge Infrastructure and Wanfang databases were searched from inception to April 2022. Results: Seven case-control studies with 4676 patients were included. Six genes with 35 SNPs in the pathway have been reported. Among 17 SNPs reported in two or more studies, the meta-analysis indicated that only one SNP (rs3735656 in MAFK) was significantly associated with a decreased risk for AT-DILI under the dominant model (odds ratio: 0.636; 95% CI: 0.519-0.780; p < 0.001). Conclusion: SNP rs3735656 in the MAFK gene was significantly associated with the risk of AT-DILI.

A regulatory variant at 19p13.3 is associated with primary biliary cholangitis risk and ARID3A expression

Genome-wide association studies have identified 19p13.3 locus associated with primary biliary cholangitis (PBC). Here we aim to identify causative variant(s) and initiate efforts to define the mechanism by which the 19p13.3 locus variant(s) contributes to the pathogenesis of PBC. A genome-wide meta-analysis of 1931 PBC subjects and 7852 controls in two Han Chinese cohorts confirms the strong association between 19p13.3 locus and PBC. By integrating functional annotations, luciferase reporter assay and allele-specific chromatin immunoprecipitation, we prioritize rs2238574, an AT-Rich Interaction Domain 3A (ARID3A) intronic variant, as a potential causal variant at 19p13.3 locus. The risk allele of rs2238574 shows higher binding affinity of transcription factors, leading to an increased enhancer activity in myeloid cells. Genome-editing demonstrates the regulatory effect of rs2238574 on ARID3A expression through allele-specific enhancer activity. Furthermore, knock-down of ARID3A inhibits myeloid differentiation and activation pathway, and overexpression of the gene has the opposite effect. Finally, we find ARID3A expression and rs2238574 genotypes linked to disease severity in PBC. Our work provides several lines of evidence that a non-coding variant regulates ARID3A expression, presenting a mechanistic basis for association of 19p13.3 locus with the susceptibility to PBC.

Transcriptional analysis links B cells and TERT expression to favorable prognosis in head and neck cancer

Telomerase reverse transcriptase (TERT) is a conserved self-tumor antigen overexpressed in ∼85% of tumor cells and is immunogenic in cancer patients. The effect of TERT expression on the regulation of intratumor adaptive immunity has not yet been investigated. We used RNA sequencing data from The Cancer Genome Atlas (TCGA) in 11 solid tumor types to investigate potential interactions between TERT expression, and B and T cell infiltrate in the tumor microenvironment. We found a positive correlation between TERT expression, B and T cells in four cancer types with the strongest association in head and neck squamous cell carcinoma (HSNCC). In HNSCC a Bhigh/TERThigh signature was associated with improved progression-free survival (PFS) (P = 0.0048). This effect was independent of HPV status and not shared in comparable analysis by other conserved tumor antigens (NYESO1, MUC1, MAGE, and CEA). Bhigh/TERThigh HNSCC tumors also harbored evidence of tertiary lymphoid structure (TLS) such as signatures for germinal center (GC) and switched memory B cells, central memory CD4 and effector memory CD8 T cells. Bhigh/TERThigh HNSCC tumors also showed an up-regulation of genes and pathways related to B and T cell activation, proliferation, migration, and cytotoxicity, while factors associated with immunosuppression and cancer cell invasiveness were down-regulated. In summary, our study uncovers a new association between high TERT expression and high B cell infiltrate in HNSCC, suggesting a potential benefit from therapeutic strategies that invigorate intratumor TERT-mediated T-B cooperation.

JAML immunotherapy targets recently activated tumor-infiltrating CD8+ T cells

Junctional adhesion molecule-like protein (JAML) serves as a co-stimulatory molecule in γδ T cells. While it has recently been described as a cancer immunotherapy target in mice, its potential to cause toxicity, specific mode of action with regard to its cellular targets, and whether it can be targeted in humans remain unknown. Here, we show that JAML is induced by T cell receptor engagement, reveal that this induction is linked to cis-regulatory interactions between the CD3D and JAML gene loci. When compared with other immunotherapy targets plagued by low target specificity and end-organ toxicity, we find JAML to be mostly restricted to and highly expressed by tissue-resident memory CD8+ T cells in multiple cancer types. By delineating the key cellular targets and functional consequences of agonistic anti-JAML therapy in a murine melanoma model, we show its specific mode of action and the reason for its synergistic effects with anti-PD-1.

Multiple sclerosis risk variants influence the peripheral B-cell compartment early in life in the general population

BACKGROUND AND PURPOSE

Multiple sclerosis (MS) is associated with abnormal B-cell function, and MS genetic risk alleles affect multiple genes that are expressed in B cells. However, how these genetic variants impact the B-cell compartment in early childhood is unclear. In the current study, we aim to assess whether polygenic risk scores (PRSs) for MS are associated with changes in the blood B-cell compartment in children from the general population.

METHODS

Six-year-old children from the population-based Generation R Study were included. Genotype data were used to calculate MS-PRSs and B-cell subset-enriched MS-PRSs, established by designating risk loci based on expression and function. Analyses of variance were performed to examine the effect of MS-PRSs on total B-cell numbers (n = 1261) as well as naive and memory subsets (n = 675).

RESULTS

After correction for multiple testing, no significant associations were observed between MS-PRSs and total B-cell numbers and frequencies of subsets therein. A naive B-cell-MS-PRS (n = 26 variants) was significantly associated with lower relative, but not absolute, naive B-cell numbers (p = 1.03 × 10^-4 and p = 0.82, respectively), and higher frequencies and absolute numbers of CD27⁺ memory B cells (p = 8.83 × 10^-4 and p = 4.89 × 10^-3 , respectively). These associations remained significant after adjustment for Epstein-Barr virus seropositivity and the HLA-DRB1*15:01 genotype.

CONCLUSIONS

The composition of the blood B-cell compartment is associated with specific naive B-cell-associated MS risk variants during childhood, possibly contributing to MS pathophysiology later in life. Cell subset-specific PRSs may offer a more sensitive tool to define the impact of genetic risk on the immune system in diseases such as MS.

CRISPR/Cas9 genome editing demonstrates functionality of the autoimmunity-associated SNP rs12946510

Genome-wide association studies (GWAS) map genetic associations of complex traits with precision limited to a linkage disequilibrium group. To translate GWAS results into new understanding of disease mechanisms, individual causative polymorphisms and their target genes should be identified. CRISPR/Cas9 genome editing can be used to create isogenic cell lines bearing alternative genotypes of candidate single-nucleotide polymorphisms to test their causality and to reveal gene targets. An intergenic polymorphism rs12946510 is associated with multiple sclerosis, inflammatory bowel disease and asthma. We created sublines of the T-helper cell line bearing alternative genotypes of rs12946510 and showed that its risk ("T") allele is associated with lower expression of IKZF3 and ORMDL3 genes and reduced cell activation. Our editing procedure can become an effective tool for discovering new genes involved in pathogenesis of complex diseases.

Chromosome conformation capture approaches to investigate 3D genome architecture in Ankylosing Spondylitis

Ankylosing Spondylitis (AS) is a chronic inflammatory arthritis of the spine exhibiting a strong genetic background. The mechanistic and functional understanding of the AS-associated genomic loci, identified with Genome Wide Association Studies (GWAS), remains challenging. Chromosome conformation capture (3C) and derivatives are recent techniques which are of great help in elucidating the spatial genome organization and of enormous support in uncover a mechanistic explanation for disease-associated genetic variants. The perturbation of three-dimensional (3D) genome hierarchy may lead to a plethora of human diseases, including rheumatological disorders. Here we illustrate the latest approaches and related findings on the field of genome organization, highlighting how the instability of 3D genome conformation may be among the causes of rheumatological disease phenotypes. We suggest a new perspective on the inclusive potential of a 3C approach to inform GWAS results in rheumatic diseases. 3D genome organization may ultimately lead to a more precise and comprehensive functional interpretation of AS association, which is the starting point for emerging and more specific therapies.

Long-range chromosomal interactions increase and mark repressed gene expression during adipogenesis

Obesity perturbs central functions of human adipose tissue, centred on differentiation of preadipocytes to adipocytes, i.e., adipogenesis. The large environmental component of obesity makes it important to elucidate epigenetic regulatory factors impacting adipogenesis. Promoter Capture Hi-C (pCHi-C) has been used to identify chromosomal interactions between promoters and associated regulatory elements. However, long range interactions (LRIs) greater than 1 Mb are often filtered out of pCHi-C datasets, due to technical challenges and their low prevalence. To elucidate the unknown role of LRIs in adipogenesis, we investigated preadipocyte differentiation to adipocytes using pCHi-C and bulk and single nucleus RNA-seq data. We first show that LRIs are reproducible between biological replicates, and they increase >2-fold in frequency across adipogenesis. We further demonstrate that genomic loci containing LRIs are more epigenetically repressed than regions without LRIs, corresponding to lower gene expression in the LRI regions. Accordingly, as preadipocytes differentiate into adipocytes, LRI regions are more likely to contain repressed preadipocyte marker genes; whereas these same LRI regions are depleted of actively expressed adipocyte marker genes. Finally, we show that LRIs can be used to restrict multiple testing of the long-range cis-eQTL analysis to identify variants that regulate genes via LRIs. We exemplify this by identifying a putative long range cis regulatory mechanism at the LYPLAL1/TGFB2 obesity locus. In summary, we identify LRIs that mark repressed regions of the genome, and these interactions increase across adipogenesis, pinpointing developmental regions that need to be repressed in a cell-type specific way for adipogenesis to proceed.

High-resolution genome topology of human retina uncovers super enhancer-promoter interactions at tissue-specific and multifactorial disease loci

Chromatin organization and enhancer-promoter contacts establish unique spatiotemporal gene expression patterns in distinct cell types. Non-coding genetic variants can influence cellular phenotypes by modifying higher-order transcriptional hubs and consequently gene expression. To elucidate genomic regulation in human retina, we mapped chromatin contacts at high resolution and integrated with super-enhancers (SEs), histone marks, binding of CTCF and select transcription factors. We show that topologically associated domains (TADs) with central SEs exhibit stronger insulation and augmented contact with retinal genes relative to TADs with edge SEs. Merging genome-wide expression quantitative trait loci (eQTLs) with topology map reveals physical links between 100 eQTLs and corresponding eGenes associated with retinal neurodegeneration. Additionally, we uncover candidate genes for susceptibility variants linked to age-related macular degeneration and glaucoma. Our study of high-resolution genomic architecture of human retina provides insights into genetic control of tissue-specific functions, suggests paradigms for missing heritability, and enables the dissection of common blinding disease phenotypes.

Three-dimensional genome organization in immune cell fate and function

Immune cell development and activation demand the precise and coordinated control of transcriptional programmes. Three-dimensional (3D) organization of the genome has emerged as an important regulator of chromatin state, transcriptional activity and cell identity by facilitating or impeding long-range genomic interactions among regulatory elements and genes. Chromatin folding thus enables cell type-specific and stimulus-specific transcriptional responses to extracellular signals, which are essential for the control of immune cell fate, for inflammatory responses and for generating a diverse repertoire of antigen receptor specificities. Here, we review recent findings connecting 3D genome organization to the control of immune cell differentiation and function, and discuss how alterations in genome folding may lead to immune dysfunction and malignancy.

Tumor-infiltrated activated B cells suppress liver metastasis of colorectal cancers

More than 40% of patients with late-stage colorectal cancer (CRC) develop liver metastasis (LM). Which immune cells play important roles in CRC-LM and contribute to the difference between left-sided CRC (LCC) and right-sided CRC (RCC) remain unclear. By single-cell RNA sequencing (scRNA-seq), we not only find that activated B cells are significantly depleted in CRC with LM, but also find a subtype of B cells developed from activated B cells, namely immature plasma cell population alpha (iMPA), highly correlated with metastasis. Mechanistically, inhibition of the Wnt and transforming growth factor β (TGF-β) pathways in cancer cell promotes activated B cell migration via the SDF-1-CXCR4 axis. This study reveals that B cell subpopulations in the tumor immune microenvironment (TIME) play a key role in CRC-LM as well as in LCC and RCC. The preventive effects of modulating B cell subpopulations in CRC may provide a rationale for subsequent drug development and CRC-LM management.

Understanding the function of regulatory DNA interactions in the interpretation of non-coding GWAS variants

Genome-wide association studies (GWAS) have identified a vast number of variants associated with various complex human diseases and traits. However, most of these GWAS variants reside in non-coding regions producing no proteins, making the interpretation of these variants a daunting challenge. Prior evidence indicates that a subset of non-coding variants detected within or near cis-regulatory elements (e.g., promoters, enhancers, silencers, and insulators) might play a key role in disease etiology by regulating gene expression. Advanced sequencing- and imaging-based technologies, together with powerful computational methods, enabling comprehensive characterization of regulatory DNA interactions, have substantially improved our understanding of the three-dimensional (3D) genome architecture. Recent literature witnesses plenty of examples where using chromosome conformation capture (3C)-based technologies successfully links non-coding variants to their target genes and prioritizes relevant tissues or cell types. These examples illustrate the critical capability of 3D genome organization in annotating non-coding GWAS variants. This review discusses how 3D genome organization information contributes to elucidating the potential roles of non-coding GWAS variants in disease etiology.

Genome-wide association study identifies Sjögren's risk loci with functional implications in immune and glandular cells

Sjögren's disease is a complex autoimmune disease with twelve established susceptibility loci. This genome-wide association study (GWAS) identifies ten novel genome-wide significant (GWS) regions in Sjögren's cases of European ancestry: CD247, NAB1, PTTG1-MIR146A, PRDM1-ATG5, TNFAIP3, XKR6, MAPT-CRHR1, RPTOR-CHMP6-BAIAP6, TYK2, SYNGR1. Polygenic risk scores yield predictability (AUROC = 0.71) and relative risk of 12.08. Interrogation of bioinformatics databases refine the associations, define local regulatory networks of GWS SNPs from the 95% credible set, and expand the implicated gene list to >40. Many GWS SNPs are eQTLs for genes within topologically associated domains in immune cells and/or eQTLs in the main target tissue, salivary glands.

Rewiring of 3D Chromatin Topology Orchestrates Transcriptional Reprogramming and the Development of Human Dilated Cardiomyopathy

BACKGROUND

Transcriptional reconfiguration is central to heart failure, the most common cause of which is dilated cardiomyopathy (DCM). The effect of 3-dimensional chromatin topology on transcriptional dysregulation and pathogenesis in human DCM remains elusive.

METHODS

We generated a compendium of 3-dimensional epigenome and transcriptome maps from 101 biobanked human DCM and nonfailing heart tissues through highly integrative chromatin immunoprecipitation (H3K27ac [acetylation of lysine 27 on histone H3]), in situ high-throughput chromosome conformation capture, chromatin immunoprecipitation sequencing, assay for transposase-accessible chromatin using sequencing, and RNA sequencing. We used human induced pluripotent stem cell-derived cardiomyocytes and mouse models to interrogate the key transcription factor implicated in 3-dimensional chromatin organization and transcriptional regulation in DCM pathogenesis.

RESULTS

We discovered that the active regulatory elements (H3K27ac peaks) and their connectome (H3K27ac loops) were extensively reprogrammed in DCM hearts and contributed to transcriptional dysregulation implicated in DCM development. For example, we identified that nontranscribing NPPA-AS1 (natriuretic peptide A antisense RNA 1) promoter functions as an enhancer and physically interacts with the NPPA (natriuretic peptide A) and NPPB (natriuretic peptide B) promoters, leading to the cotranscription of NPPA and NPPB in DCM hearts. We revealed that DCM-enriched H3K27ac loops largely resided in conserved high-order chromatin architectures (compartments, topologically associating domains) and their anchors unexpectedly had equivalent chromatin accessibility. We discovered that the DCM-enriched H3K27ac loop anchors exhibited a strong enrichment for HAND1 (heart and neural crest derivatives expressed 1), a key transcription factor involved in early cardiogenesis. In line with this, its protein expression was upregulated in human DCM and mouse failing hearts. To further validate whether HAND1 is a causal driver for the reprogramming of enhancer-promoter connectome in DCM hearts, we performed comprehensive 3-dimensional epigenome mappings in human induced pluripotent stem cell-derived cardiomyocytes. We found that forced overexpression of HAND1 in human induced pluripotent stem cell-derived cardiomyocytes induced a distinct gain of enhancer-promoter connectivity and correspondingly increased the expression of their connected genes implicated in DCM pathogenesis, thus recapitulating the transcriptional signature in human DCM hearts. Electrophysiology analysis demonstrated that forced overexpression of HAND1 in human induced pluripotent stem cell-derived cardiomyocytes induced abnormal calcium handling. Furthermore, cardiomyocyte-specific overexpression of Hand1 in the mouse hearts resulted in dilated cardiac remodeling with impaired contractility/Ca2+ handling in cardiomyocytes, increased ratio of heart weight/body weight, and compromised cardiac function, which were ascribed to recapitulation of transcriptional reprogramming in DCM.

CONCLUSIONS

This study provided novel chromatin topology insights into DCM pathogenesis and illustrated a model whereby a single transcription factor (HAND1) reprograms the genome-wide enhancer-promoter connectome to drive DCM pathogenesis.

Epigenetic and transcriptional dysregulation in CD4+ T cells in patients with atopic dermatitis

Atopic dermatitis (AD) is one of the most common skin disorders among children. Disease etiology involves genetic and environmental factors, with 29 independent AD risk loci enriched for risk allele-dependent gene expression in the skin and CD4+ T cell compartments. We investigated the potential epigenetic mechanisms responsible for the genetic susceptibility of CD4+ T cells. To understand the differences in gene regulatory activity in peripheral blood T cells in AD, we measured chromatin accessibility (an assay based on transposase-accessible chromatin sequencing, ATAC-seq), nuclear factor kappa B subunit 1 (NFKB1) binding (chromatin immunoprecipitation with sequencing, ChIP-seq), and gene expression levels (RNA-seq) in stimulated CD4+ T cells from subjects with active moderate-to-severe AD, as well as in age-matched non-allergic controls. Open chromatin regions in stimulated CD4+ T cells were highly enriched for AD genetic risk variants, with almost half of the AD risk loci overlapping AD-dependent ATAC-seq peaks. AD-specific open chromatin regions were strongly enriched for NF-κB DNA-binding motifs. ChIP-seq identified hundreds of NFKB1-occupied genomic loci that were AD- or control-specific. As expected, the AD-specific ChIP-seq peaks were strongly enriched for NF-κB DNA-binding motifs. Surprisingly, control-specific NFKB1 ChIP-seq peaks were not enriched for NFKB1 motifs, but instead contained motifs for other classes of human transcription factors, suggesting a mechanism involving altered indirect NFKB1 binding. Using DNA sequencing data, we identified 63 instances of altered genotype-dependent chromatin accessibility at 36 AD risk variant loci (30% of AD risk loci) that might lead to genotype-dependent gene expression. Based on these findings, we propose that CD4+ T cells respond to stimulation in an AD-specific manner, resulting in disease- and genotype-dependent chromatin accessibility alterations involving NFKB1 binding.

Functional Characterization of Genetic Variant Effects on Expression

Thousands of common genetic variants in the human population have been associated with disease risk and phenotypic variation by genome-wide association studies (GWAS). However, the majority of GWAS variants fall into noncoding regions of the genome, complicating our understanding of their regulatory functions, and few molecular mechanisms of GWAS variant effects have been clearly elucidated. Here, we set out to review genetic variant effects, focusing on expression quantitative trait loci (eQTLs), including their utility in interpreting GWAS variant mechanisms. We discuss the interrelated challenges and opportunities for eQTL analysis, covering determining causal variants, elucidating molecular mechanisms of action, and understanding context variability. Addressing these questions can enable better functional characterization of disease-associated loci and provide insights into fundamental biological questions of the noncoding genetic regulatory code and its control of gene expression. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

CHD7 regulates bone-fat balance by suppressing PPAR-γ signaling

Chromodomain helicase DNA-binding protein 7 (CHD7), an ATP-dependent eukaryotic chromatin remodeling enzyme, is essential for the development of organs. The mutation of CHD7 is the main cause of CHARGE syndrome, but its function and mechanism in skeletal system remain unclear. Here, we show conditional knockout of Chd7 in bone marrow mesenchymal stem cells (MSCs) and preosteoblasts leads to a pathological phenotype manifested as low bone mass and severely high marrow adiposity. Mechanistically, we identify enhancement of the peroxisome proliferator-activated receptor (PPAR) signaling in Chd7-deficient MSCs. Loss of Chd7 reduces the restriction of PPAR-γ and then PPAR-γ associates with trimethylated histone H3 at lysine 4 (H3K4me3), which subsequently activates the transcription of downstream adipogenic genes and disrupts the balance between osteogenic and adipogenic differentiation. Our data illustrate the pathological manifestations of Chd7 mutation in MSCs and reveal an epigenetic mechanism in skeletal health and diseases.

CHD7 is chromatin remodeler and mutations of CHD7 are the main cause of CHARGE syndrome. Here the authors show that conditional knockout of Chd7 in bone marrow mesenchymal stem cells (MSCs) and pre-osteoblasts leads to a skeletal system development disorder in mice and upregulated PPAR signaling, disrupting the balance between osteogenic and adipogenic differentiation.

Functional annotation of breast cancer risk loci: current progress and future directions

Genome-wide association studies coupled with large-scale replication and fine-scale mapping studies have identified more than 150 genomic regions that are associated with breast cancer risk. Here, we review efforts to translate these findings into a greater understanding of disease mechanism. Our review comes in the context of a recently published fine-scale mapping analysis of these regions, which reported 352 independent signals and a total of 13,367 credible causal variants. The vast majority of credible causal variants map to noncoding DNA, implicating regulation of gene expression as the mechanism by which functional variants influence risk. Accordingly, we review methods for defining candidate-regulatory sequences, methods for identifying putative target genes and methods for linking candidate-regulatory sequences to putative target genes. We provide a summary of available data resources and identify gaps in these resources. We conclude that while much work has been done, there is still much to do. There are, however, grounds for optimism; combining statistical data from fine-scale mapping with functional data that are more representative of the normal "at risk" breast, generated using new technologies, should lead to a greater understanding of the mechanisms that influence an individual woman's risk of breast cancer.

Sincast: a computational framework to predict cell identities in single-cell transcriptomes using bulk atlases as references

Characterizing the molecular identity of a cell is an essential step in single-cell RNA sequencing (scRNA-seq) data analysis. Numerous tools exist for predicting cell identity using single-cell reference atlases. However, many challenges remain, including correcting for inherent batch effects between reference and query data andinsufficient phenotype data from the reference. One solution is to project single-cell data onto established bulk reference atlases to leverage their rich phenotype information. Sincast is a computational framework to query scRNA-seq data by projection onto bulk reference atlases. Prior to projection, single-cell data are transformed to be directly comparable to bulk data, either with pseudo-bulk aggregation or graph-based imputation to address sparse single-cell expression profiles. Sincast avoids batch effect correction, and cell identity is predicted along a continuum to highlight new cell states not found in the reference atlas. In several case study scenarios, we show that Sincast projects single cells into the correct biological niches in the expression space of the bulk reference atlas. We demonstrate the effectiveness of our imputation approach that was specifically developed for querying scRNA-seq data based on bulk reference atlases. We show that Sincast is an efficient and powerful tool for single-cell profiling that will facilitate downstream analysis of scRNA-seq data.

Single-cell eQTL analysis of activated T cell subsets reveals activation and cell type-dependent effects of disease-risk variants

The impact of genetic variants on cells challenged in biologically relevant contexts has not been fully explored. Here, we activated CD4+ T cells from 89 healthy donors and performed a single-cell RNA sequencing assay with >1 million cells to examine cell type-specific and activation-dependent effects of genetic variants. Single-cell expression quantitative trait loci (sc-eQTL) analysis of 19 distinct CD4+ T cell subsets showed that the expression of over 4000 genes is significantly associated with common genetic polymorphisms and that most of these genes show their most prominent effects in specific cell types. These genes included many that encode for molecules important for activation, differentiation, and effector functions of T cells. We also found new gene associations for disease-risk variants identified from genome-wide association studies and highlighted the cell types in which their effects are most prominent. We found that biological sex has a major influence on activation-dependent gene expression in CD4+ T cell subsets. Sex-biased transcripts were significantly enriched in several pathways that are essential for the initiation and execution of effector functions by CD4+ T cells like TCR signaling, cytokines, cytokine receptors, costimulatory, apoptosis, and cell-cell adhesion pathways. Overall, this DICE (Database of Immune Cell Expression, eQTLs, and Epigenomics) subproject highlights the power of sc-eQTL studies for simultaneously exploring the activation and cell type-dependent effects of common genetic variants on gene expression (https://dice-database.org).

Cis-regulatory sequences in plants: Their importance, discovery, and future challenges

The identification and characterization of cis-regulatory DNA sequences and how they function to coordinate responses to developmental and environmental cues is of paramount importance to plant biology. Key to these regulatory processes are cis-regulatory modules (CRMs), which include enhancers and silencers. Despite the extraordinary advances in high-quality sequence assemblies and genome annotations, the identification and understanding of CRMs, and how they regulate gene expression, lag significantly behind. This is especially true for their distinguishing characteristics and activity states. Here, we review the current knowledge on CRMs and breakthrough technologies enabling identification, characterization, and validation of CRMs; we compare the genomic distributions of CRMs with respect to their target genes between different plant species, and discuss the role of transposable elements harboring CRMs in the evolution of gene expression. This is an exciting time to study cis-regulomes in plants; however, significant existing challenges need to be overcome to fully understand and appreciate the role of CRMs in plant biology and in crop improvement.

Towards the Genetic Architecture of Complex Gene Expression Traits: Challenges and Prospects for eQTL Mapping in Humans

The discovery of expression quantitative trait loci (eQTLs) and their target genes (eGenes) has not only compensated for the limitations of genome-wide association studies for complex phenotypes but has also provided a basis for predicting gene expression. Efforts have been made to develop analytical methods in statistical genetics, a key discipline in eQTL analysis. In particular, mixed model– and deep learning–based analytical methods have been extremely beneficial in mapping eQTLs and predicting gene expression. Nevertheless, we still face many challenges associated with eQTL discovery. Here, we discuss two key aspects of these challenges: 1, the complexity of eTraits with various factors such as polygenicity and epistasis and 2, the voluminous work required for various types of eQTL profiles. The properties and prospects of statistical methods, including the mixed model method, Bayesian inference, the deep learning method, and the integration method, are presented as future directions for eQTL discovery. This review will help expedite the design and use of efficient methods for eQTL discovery and eTrait prediction.

Fine mapping with epigenetic information and 3D structure

Since 2005, thousands of genome-wide association studies (GWAS) have been published, identifying hundreds of thousands of genetic variants that increase risk of complex traits such as autoimmune diseases. This wealth of data has the potential to improve patient care, through personalized medicine and the identification of novel drug targets. However, the potential of GWAS for clinical translation has not been fully achieved yet, due to the fact that the functional interpretation of risk variants and the identification of causal variants and genes are challenging. The past decade has seen the development of great advances that are facilitating the overcoming of these limitations, by utilizing a plethora of genomics and epigenomics tools to map and characterize regulatory elements and chromatin interactions, which can be used to fine map GWAS loci, and advance our understanding of the biological mechanisms that cause disease.