Chromatin Looping Links Target Genes with Genetic Risk Loci for Dermatological Traits

Resolving 3-Dimensional Genomic Landscape of CD4+ T Cells in the Peripheral Blood of Patients with Psoriasis

A precise regulation of gene expression depends on the accuracy of the 3-dimensional (3D) structure of chromatin; however, the effects of the 3D genome on gene expression in psoriasis remain unknown. In this study, we conducted Hi-C and RNA sequencing on CD4+ T cells collected from 5 patients with psoriasis and 3 healthy controls and constructed a comprehensive 3D chromatin interaction map to delineate the genomic hierarchies, including A/B compartments, topologically associated domains, and chromatin loops. Then, the specific superenhancers related to psoriasis were identified by Hi-C and H3K27ac chromatin immunoprecipitation sequencing data. Subsequently, comprehensive analyses were carried out on the differentially expressed genes that are associated with altered topologically associated domains, loops, and superenhancers in psoriasis. Finally, we screened the candidate target genes and examined the potential functional SNP in psoriasis affected by disruptions of the spatial organization. This study provides a comprehensive reference for examining the 3D genome interactions in psoriasis and elucidating the interplay between spatial organization disruption and gene regulation. We hope that our findings can help clarify the mechanisms underlying the pathogenesis of psoriasis and shed light on the role of 3D genomic structure, therefore informing potential therapeutic approaches.

Functional Genomics in Psoriasis

Psoriasis is an autoimmune cutaneous condition that significantly impacts quality of life and represents a burden on society due to its prevalence. Genome-wide association studies (GWASs) have pinpointed several psoriasis-related risk loci, underlining the disease's complexity. Functional genomics is paramount to unveiling the role of such loci in psoriasis and disentangling its complex nature. In this review, we aim to elucidate the main findings in this field and integrate our discussion with gold-standard techniques in molecular biology-i.e., Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-and high-throughput technologies. These tools are vital to understanding how disease risk loci affect gene expression in psoriasis, which is crucial in identifying new targets for personalized treatments in advanced precision medicine.

Functional Genomics and Insights into the Pathogenesis and Treatment of Psoriasis

Psoriasis is a lifelong, systemic, immune mediated inflammatory skin condition, affecting 1-3% of the world's population, with an impact on quality of life similar to diseases like cancer or diabetes. Genetics are the single largest risk factor in psoriasis, with Genome-Wide Association (GWAS) studies showing that many psoriasis risk genes lie along the IL-23/Th17 axis. Potential psoriasis risk genes determined through GWAS can be annotated and characterised using functional genomics, allowing the identification of novel drug targets and the repurposing of existing drugs. This review is focused on the IL-23/Th17 axis, providing an insight into key cell types, cytokines, and intracellular signaling pathways involved. This includes examination of currently available biological treatments, time to relapse post drug withdrawal, and rates of primary/secondary drug failure, showing the need for greater understanding of the underlying genetic mechanisms of psoriasis and how they can impact treatment. This could allow for patient stratification towards the treatment most likely to reduce the burden of disease for the longest period possible.

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.

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.

Differentiation signals induce APOBEC3A expression via GRHL3 in squamous epithelia and squamous cell carcinoma

Two APOBEC (apolipoprotein-B mRNA editing enzyme catalytic polypeptide-like) DNA cytosine deaminase enzymes (APOBEC3A and APOBEC3B) generate somatic mutations in cancer, driving tumour development and drug resistance. Here we used single cell RNA sequencing to study APOBEC3A and APOBEC3B expression in healthy and malignant mucosal epithelia, validating key observations with immunohistochemistry, spatial transcriptomics and functional experiments. Whereas APOBEC3B is expressed in keratinocytes entering mitosis, we show that APOBEC3A expression is confined largely to terminally differentiating cells and requires Grainyhead-like transcription factor 3 (GRHL3). Thus, in normal tissue, neither deaminase appears to be expressed at high levels during DNA replication, the cell cycle stage associated with APOBEC-mediated mutagenesis. In contrast, we show that in squamous cell carcinoma tissues, there is expansion of GRHL3 expression and activity to a subset of cells undergoing DNA replication and concomitant extension of APOBEC3A expression to proliferating cells. These findings indicate a mechanism for acquisition of APOBEC3A mutagenic activity in tumours.

The role of enhancers in psoriasis and atopic dermatitis

Regulatory elements, particularly enhancers, play a crucial role in disease susceptibility and progression. Enhancers are DNA sequences that activate gene expression and can be affected by epigenetic modifications, interactions with transcription factors (TFs) or changes to the enhancer DNA sequence itself. Altered enhancer activity impacts gene expression and contributes to disease. In this review, we define enhancers and the experimental techniques used to identify and characterize them. We also discuss recent studies that examine how enhancers contribute to atopic dermatitis (AD) and psoriasis. Articles in the PubMed database were identified (from 1 January 2010 to 28 February 2023) that were relevant to enhancer variants, enhancer-associated TFs and enhancer histone modifications in psoriasis or AD. Most enhancers associated with these conditions regulate genes affecting epidermal homeostasis or immune function. These discoveries present potential therapeutic targets to complement existing treatment options for AD and psoriasis.

Disentangling the complexity of psoriasis in the post-genome-wide association era

In recent years, genome-wide association studies (GWAS) have been instrumental in unraveling the genetic architecture of complex diseases, including psoriasis. The application of large-scale GWA studies in psoriasis has illustrated several associated loci that participate in the cutaneous inflammation, however explaining a fraction of the disease heritability. With the advent of high-throughput sequencing technologies and functional genomics approaches, the post-GWAS era aims to unravel the functional mechanisms underlying the inter-individual variability in psoriasis patients. In this review, we present the key advances of psoriasis GWAS in under-represented populations, rare, non-coding and structural variants and epistatic phenomena that orchestrate the interplay between different cell types. We further review the gene-gene and gene-environment interactions contributing to the disease predisposition and development of comorbidities through Mendelian randomization studies and pleiotropic effects of psoriasis-associated loci. We finally examine the holistic approaches conducted in psoriasis through system genetics and state-of-the-art transcriptomic analyses, discussing their potential implication in the expanding field of precision medicine and characterization of comorbidities.

Identification of a novel enhancer essential for Satb1 expression in TH2 cells and activated ILC2s

The genome organizer, special AT-rich binding protein-1 (SATB1), functions to globally regulate gene networks during primary T cell development and plays a pivotal role in lineage specification in CD4+ helper-, CD8+ cytotoxic-, and FOXP3+ regulatory-T cell subsets. However, it remains unclear how Satb1 gene expression is controlled, particularly in effector T cell function. Here, by using a novel reporter mouse strain expressing SATB1-Venus and genome editing, we have identified a cis-regulatory enhancer, essential for maintaining Satb1 expression specifically in TH2 cells. This enhancer is occupied by STAT6 and interacts with Satb1 promoters through chromatin looping in TH2 cells. Reduction of Satb1 expression, by the lack of this enhancer, resulted in elevated IL-5 expression in TH2 cells. In addition, we found that Satb1 is induced in activated group 2 innate lymphoid cells (ILC2s) through this enhancer. Collectively, these results provide novel insights into how Satb1 expression is regulated in TH2 cells and ILC2s during type 2 immune responses.

3D genome organization and epigenetic regulation in autoimmune diseases

Three-dimensional (3D) genomics is an emerging field of research that investigates the relationship between gene regulatory function and the spatial structure of chromatin. Chromatin folding can be studied using chromosome conformation capture (3C) technology and 3C-based derivative sequencing technologies, including chromosome conformation capture-on-chip (4C), chromosome conformation capture carbon copy (5C), and high-throughput chromosome conformation capture (Hi-C), which allow scientists to capture 3D conformations from a single site to the entire genome. A comprehensive analysis of the relationships between various regulatory components and gene function also requires the integration of multi-omics data such as genomics, transcriptomics, and epigenomics. 3D genome folding is involved in immune cell differentiation, activation, and dysfunction and participates in a wide range of diseases, including autoimmune diseases. We describe hierarchical 3D chromatin organization in this review and conclude with characteristics of C-techniques and multi-omics applications of the 3D genome. In addition, we describe the relationship between 3D genome structure and the differentiation and maturation of immune cells and address how changes in chromosome folding contribute to autoimmune diseases.

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.

A global high-density chromatin interaction network reveals functional long-range and trans-chromosomal relationships

BACKGROUND

Chromatin contacts are essential for gene-expression regulation; however, obtaining a high-resolution genome-wide chromatin contact map is still prohibitively expensive owing to large genome sizes and the quadratic scale of pairwise data. Chromosome conformation capture (3C)-based methods such as Hi-C have been extensively used to obtain chromatin contacts. However, since the sparsity of these maps increases with an increase in genomic distance between contacts, long-range or trans-chromatin contacts are especially challenging to sample.

RESULTS

Here, we create a high-density reference genome-wide chromatin contact map using a meta-analytic approach. We integrate 3600 human, 6700 mouse, and 500 fly Hi-C experiments to create species-specific meta-Hi-C chromatin contact maps with 304 billion, 193 billion, and 19 billion contacts in respective species. We validate that meta-Hi-C contact maps are uniquely powered to capture functional chromatin contacts in both cis and trans. We find that while individual dataset Hi-C networks are largely unable to predict any long-range coexpression (median 0.54 AUC), meta-Hi-C networks perform comparably in both cis and trans (0.65 AUC vs 0.64 AUC). Similarly, for long-range expression quantitative trait loci (eQTL), meta-Hi-C contacts outperform all individual Hi-C experiments, providing an improvement over the conventionally used linear genomic distance-based association. Assessing between species, we find patterns of chromatin contact conservation in both cis and trans and strong associations with coexpression even in species for which Hi-C data is lacking.

CONCLUSIONS

We have generated an integrated chromatin interaction network which complements a large number of methodological and analytic approaches focused on improved specificity or interpretation. This high-depth "super-experiment" is surprisingly powerful in capturing long-range functional relationships of chromatin interactions, which are now able to predict coexpression, eQTLs, and cross-species relationships. The meta-Hi-C networks are available at https://labshare.cshl.edu/shares/gillislab/resource/HiC/ .

HiCuT: An efficient and low input method to identify protein-directed chromatin interactions

3D genome organization regulates gene expression, and disruption of these long-range (>20kB) DNA-protein interactions results in pathogenic phenotypes. Chromosome conformation methods in conjunction with chromatin immunoprecipitation were used to decipher protein-directed chromatin interactions. However, these methods required abundant starting material (>500,000 cells), sizable number of sequencing reads (>100 million reads), and elaborate data processing methods to reduce background noise, which limited their use in primary cells. Hi-C Coupled chromatin cleavage and Tagmentation (HiCuT) is a new transposase-assisted tagmentation method that generates high-resolution protein directed long-range chromatin interactions as efficiently as existing methods, HiChIP and ChIA-PET, despite using 100,000 cells (5-fold less) and 12 million sequencing reads (8-fold fewer). Moreover, HiCuT generates high resolution fragment libraries with low background signal that are easily interpreted with minimal computational processing. We used HiCuT in human primary skin cells to link previously identified single nucleotide polymorphisms (SNPs) in skin disease to candidate genes and to identify functionally relevant transcription factors in an unbiased manner. HiCuT broadens the capacity for genomic profiling in systems previously unmeasurable, including primary cells, human tissue samples, and rare cell populations, and may be a useful tool for all investigators studying human genetics and personalized epigenomics.

DNA is precisely packaged and organized within a nucleus to regulate gene expression. Altering this structure results in disease and developmental abnormalities. Current methods to probe 3D genome organization require a minimum of 500,000 cells, 100 million sequencing reads, and elaborate computational genomics skills. This limits general adoption and prevents use in small populations of cells, including primary tissues. We report a new method called Hi-C Coupled chromatin cleavage and Tagmentation (HiCuT). This method couples current 3D genome methods in conjunction with target specific tagmentation, an enzyme-assisted approach to cut and tag DNA. We benchmarked HiCuT against existing methods and found similar efficiency and specificity in assessing target specific 3D genome organization despite reducing assay requirements to 100,000 cells (5-fold less) and 12 million sequencing reads (8-fold fewer). Strikingly, HiCuT data exhibited reduced background noise and required minimal computational processing. Taken together, HiCuT broadens the capacity for 3D genome profiling in cell populations previously unmeasurable, including primary cells and human tissues, reduces sequencing costs, and lowers the need for computational expertise. HiCuT will benefit all investigators studying gene regulation and disease pathophysiology.

Disruption of c-MYC Binding and Chromosomal Looping Involving Genetic Variants Associated With Ankylosing Spondylitis Upstream of the RUNX3 Promoter

Background: Ankylosing Spondylitis (AS) is a common form of inflammatory spinal arthritis with a complex aetiology and high heritability, involving more than 100 genetic associations. These include several AS-associated single nucleotide polymorphisms (SNPs) upstream of RUNX3, which encodes the multifunctional RUNT-related transcription factor (TF) 3. The lead associated SNP rs6600247 (p = 2.6 × 10⁻¹⁵) lies ∼13kb upstream of the RUNX3 promoter adjacent to a c-MYC TF binding-site. The effect of rs6600247 genotype on DNA binding and chromosome looping were investigated by electrophoretic mobility gel shift assays (EMSA), Western blotting-EMSA (WEMSA) and Chromosome Conformation Capture (3C).

Results: Interrogation of ENCODE published data showed open chromatin in the region overlapping rs6600247 in primary human CD14⁺ monocytes, in contrast to the Jurkat T cell line or primary human T-cells. The rs6600247 AS-risk allele is predicted to specifically disrupt a c-MYC binding-site. Using a 50bp DNA probe spanning rs6600247 we consistently observed reduced binding to the AS-risk “C” allele of both purified c-MYC protein and nuclear extracts (NE) from monocyte-like U937 cells. WEMSA on U937 NE and purified c-MYC protein confirmed these differences (n = 3; p < 0.05). 3C experiments demonstrated negligible interaction between the region encompassing rs6600247 and the RUNX3 promoter. A stronger interaction frequency was demonstrated between the RUNX3 promoter and the previously characterised AS-associated SNP rs4648889.

Conclusion: The lead SNP rs6600247, located in an enhancer-like region upstream of the RUNX3 promoter, modulates c-MYC binding. However, the region encompassing rs6600247 has rather limited physical interaction with the promoter of RUNX3. In contrast a clear chromatin looping event between the region encompassing rs4648889 and the RUNX3 promoter was observed. These data provide further evidence for complexity in the regulatory elements upstream of the RUNX3 promoter and the involvement of RUNX3 transcriptional regulation in AS.

Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics

Multimorbidity is characterized by multidimensional complexity emerging from interactions between multiple diseases across levels of biological (including genetic) and environmental determinants and the complex array of interactions between and within cells, tissues and organ systems. Advances in spatial genomic research have led to an unprecedented expansion in our ability to link alterations in genome folding with changes that are associated with human disease. Studying disease-associated genetic variants in the context of the spatial genome has enabled the discovery of transcriptional regulatory programmes that potentially link dysregulated genes to disease development. However, the approaches that have been used have typically been applied to uncover pathological molecular mechanisms occurring in a specific disease-relevant tissue. These forms of reductionist, targeted investigations are not appropriate for the molecular dissection of multimorbidity that typically involves contributions from multiple tissues. In this perspective, we emphasize the importance of a whole-body understanding of multimorbidity and discuss how spatial genomics, when integrated with additional omic datasets, could provide novel insights into the molecular underpinnings of multimorbidity.

Advanced genomics and clinical phenotypes in psoriatic arthritis

Psoriatic Arthritis (PsA) is a complex polygenic inflammatory disease showing a variable musculoskeletal involvement in patients with skin psoriasis. PsA coexist in 25-40 % of patients with the dermatological manifestations, but PsA may also predate the appearance of psoriasis. Nonetheless, the immunopathogenesis of psoriasis and PsA manifest significant similarities, with a major role of the individual susceptibility in both cases. Genome wide association studies (GWAS) identified several genes/loci associated with the risk to develop PsA, both dependent and independent of psoriasis. The major challenge is thus represented by the need to translate the identification of functional polymorphisms and other genetics findings into biological mechanisms along with the identification of novel putative drug targets. A functional genomics approach aims to increase GWAS power and recent evidence supports the use of a multilayer process, including eQTL, methylome, chromatin conformation analysis and genome editing to discover novel genes that can be affected by disease-associated variants, such as PsA. The available data have considered PsA as a unique homogeneous clinical entity while the clinical experience supports a wide variability of skin and joint manifestations coexisting in diverse patients with different mechanisms underlying the musculoskeletal and dermatological domains. A better discrimination of the patient features is encouraged by the limited data on functional genomics. We provide herein a review of the latest findings on PsA functional genomics highlighting the exciting developments in the field and how these might lead to a better understanding of gene regulation underpinning disease mechanisms and ultimately refine clinical phenotyping.

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.

Opportunity to improve livestock traits using 3D genomics

The advent of high-throughput chromosome conformation capture and sequencing (Hi-C) has enabled researchers to probe the 3D architecture of the mammalian genome in a genome-wide manner. Simultaneously, advances in epigenomic assays, such as chromatin immunoprecipitation and sequencing (ChIP-seq) and DNase-seq, have enabled researchers to study cis-regulatory interactions and chromatin accessibility across the same genome-wide scale. The use of these data has revealed many unique insights into gene regulation and disease pathomechanisms in several model organisms. With the advent of these high-throughput sequencing technologies, there has been an ever-increasing number of datasets available for study; however, this is often limited to model organisms. Livestock species play critical roles in the economies of developing and developed nations alike. Despite this, they are greatly underrepresented in the 3D genomics space; Hi-C and related technologies have the potential to revolutionise livestock breeding by enabling a more comprehensive understanding of how production traits are controlled. The growth in human and model organism Hi-C data has seen a surge in the availability of computational tools for use in 3D genomics, with some tools using machine learning techniques to predict features and improve dataset quality. In this review, we provide an overview of the 3D genome and discuss the status of 3D genomics in livestock before delving into advancing the field by drawing inspiration from research in human and mouse. We end by offering future directions for livestock research in the field of 3D genomics.

Capturing New Disease Genes in Psoriasis and Other Skin Diseases

Regulatory regions of the genome harbor most genetic variance associated with skin diseases. Because gene-regulatory networks are cell-type and cell-state specific and are subject to variation from the genetic background, current cell models that link genetic variation to gene expression are imperfect. Emerging single-cell genomics approaches may provide a new approach to understand the genetics of common skin diseases.