Capture Hi-C identifies a novel causal gene, IL20RA, in the pan-autoimmune genetic susceptibility region 6q23

Cross-Species Prediction of Transcription Factor Binding by Adversarial Training of a Novel Nucleotide-Level Deep Neural Network

Cross-species prediction of TF binding remains a major challenge due to the rapid evolutionary turnover of individual TF binding sites, resulting in cross-species predictive performance being consistently worse than within-species performance. In this study, a novel Nucleotide-Level Deep Neural Network (NLDNN) is first proposed to predict TF binding within or across species. NLDNN regards the task of TF binding prediction as a nucleotide-level regression task, which takes DNA sequences as input and directly predicts experimental coverage values. Beyond predictive performance, it also assesses model performance by locating potential TF binding regions, discriminating TF-specific single-nucleotide polymorphisms (SNPs), and identifying causal disease-associated SNPs. The experimental results show that NLDNN outperforms the competing methods in these tasks. Then, a dual-path framework is designed for adversarial training of NLDNN to further improve the cross-species prediction performance by pulling the domain space of human and mouse species closer. Through comparison and analysis, it finds that adversarial training not only can improve the cross-species prediction performance between humans and mice but also enhance the ability to locate TF binding regions and discriminate TF-specific SNPs. By visualizing the predictions, it is figured out that the framework corrects some mispredictions by amplifying the coverage values of incorrectly predicted peaks.

Genetics of rheumatoid arthritis

In the past four decades, a plethora of genetic association studies have been carried out in cohorts of patients with rheumatoid arthritis. These studies have highlighted key aspects of disease pathogenesis and suggested causal mechanisms. In this review, we discuss major advances in our understanding of the genetic architecture of rheumatoid arthritis susceptibility, severity and treatment response and explain how genetics supports current models of disease pathogenesis and outcome. We outline future research directions, like Mendelian randomisation, and present a number of potential avenues for clinical translation, including risk and outcome prediction, patient stratification into treatment response groups and pharmacological applications.

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.

Identification of an novel genetic variant associated with osteoporosis: insights from the Taiwan Biobank Study

Purpose

The purpose of this study was to identify new independent significant SNPs associated with osteoporosis using data from the Taiwan Biobank (TWBB).

Material and Methods

The dataset was divided into discovery (60%) and replication (40%) subsets. Following data quality control, genome-wide association study (GWAS) analysis was performed, adjusting for sex, age, and the top 5 principal components, employing the Scalable and Accurate Implementation of the Generalized mixed model approach. This was followed by a meta-analysis of TWBB1 and TWBB2. The Functional Mapping and Annotation (FUMA) platform was used to identify osteoporosis-associated loci. Manhattan and quantile-quantile plots were generated using the FUMA platform to visualize the results. Independent significant SNPs were selected based on genome-wide significance (P < 5 × 10-8) and independence from each other (r2 < 0.6) within a 1 Mb window. Positional, eQTL(expression quantitative trait locus), and Chromatin interaction mapping were used to map SNPs to genes.

Results

A total of 29 084 individuals (3154 osteoporosis cases and 25 930 controls) were used for GWAS analysis (TWBB1 data), and 18 918 individuals (1917 cases and 17 001 controls) were utilized for replication studies (TWBB2 data). We identified a new independent significant SNP for osteoporosis in TWBB1, with the lead SNP rs76140829 (minor allele frequency = 0.055, P-value = 1.15 × 10-08). Replication of the association was performed in TWBB2, yielding a P-value of 6.56 × 10-3. The meta-analysis of TWBB1 and TWBB2 data demonstrated a highly significant association for SNP rs76140829 (P-value = 7.52 × 10-10). In the positional mapping of rs76140829, 6 genes (HABP2, RP11-481H12.1, RNU7-165P, RP11-139 K1.2, RP11-57H14.3, and RP11-214 N15.5) were identified through chromatin interaction mapping in mesenchymal stem cells.

Conclusions

Our GWAS analysis using the Taiwan Biobank dataset unveils rs76140829 in the VTI1A gene as a key risk variant associated with osteoporosis. This finding expands our understanding of the genetic basis of osteoporosis and highlights the potential regulatory role of this SNP in mesenchymal stem cells.

Exploring noncoding variants in genetic diseases: from detection to functional insights

Previous studies on genetic diseases predominantly focused on protein-coding variations, overlooking the vast noncoding regions in the human genome. The development of high-throughput sequencing technologies and functional genomics tools has enabled the systematic identification of functional noncoding variants. These variants can impact gene expression, regulation, and chromatin conformation, thereby contributing to disease pathogenesis. Understanding the mechanisms that underlie the impact of noncoding variants on genetic diseases is indispensable for the development of precisely targeted therapies and the implementation of personalized medicine strategies. The intricacies of noncoding regions introduce a multitude of challenges and research opportunities. In this review, we introduce a spectrum of noncoding variants involved in genetic diseases, along with research strategies and advanced technologies for their precise identification and in-depth understanding of the complexity of the noncoding genome. We will delve into the research challenges and propose potential solutions for unraveling the genetic basis of rare and complex diseases.

Genomic associations with antibody response to an oral cholera vaccine

Oral cholera vaccine is one of the key interventions used in our fight to end the longest pandemic of our time, cholera. The immune response conferred by the currently available cholera vaccines, as measured by serum antibody levels, is variable amongst its recipients. We undertook a genome wide association study (GWAS) on antibody response to the cholera vaccine; globally, the first GWAS on cholera vaccine response. We identified three clusters of bi-allelic SNPs, in high within-cluster linkage disequilibrium that were moderately (p < 5 × 10-6) associated with antibody response to the cholera vaccine and mapped to chromosomal regions 4p14, 4p16.1 and 6q23.3. Intronic SNPs of TBC1D1 comprised the cluster on 4p14, intronic SNPs of TBC1D14 comprised that on 4p16.1 and SNPs upstream of TNFAIP3 formed the cluster on 6q23.3. SNPs within and around these clusters have been implicated in immune cell function and immunological aspects of autoimmune or infectious diseases (e.g., diseases caused by Helicobacter pylori and malarial parasite). 6q23.3 is a prominent region harbouring many loci associated with immune related diseases, including multiple sclerosis, rheumatoid arthritis and systemic lupus erythematosus, as well as IL2 and INFα response to a smallpox vaccine. The gene clusters identified in this study play roles in vesicle-mediated pathway, autophagy and NF-κB signaling. No significant effect of O blood group on antibody response to the cholera vaccine was observed in this study.

Cerium oxide nanoparticles-carrying human umbilical cord mesenchymal stem cells counteract oxidative damage and facilitate tendon regeneration

BACKGROUND

Tendon injuries have a high incidence and limited treatment options. Stem cell transplantation is essential for several medical conditions like tendon injuries. However, high local concentrations of reactive oxygen species (ROS) inhibit the activity of transplanted stem cells and hinder tendon repair. Cerium oxide nanoparticles (CeONPs) have emerged as antioxidant agents with reproducible reducibility.

RESULTS

In this study, we synthesized polyethylene glycol-packed CeONPs (PEG-CeONPs), which were loaded into the human umbilical cord mesenchymal stem cells (hUCMSCs) to counteract oxidative damage. H2O2 treatment was performed to evaluate the ROS scavenging ability of PEG-CeONPs in hUCMSCs. A rat model of patellar tendon defect was established to assess the effect of PEG-CeONPs-carrying hUCMSCs in vivo. The results showed that PEG-CeONPs exhibited excellent antioxidant activity both inside and outside the hUCMSCs. PEG-CeONPs protect hUCMSCs from senescence and apoptosis under excessive oxidative stress. Transplantation of hUCMSCs loaded with PEG-CeONPs reduced ROS levels in the tendon injury area and facilitated tendon healing. Mechanistically, NFκB activator tumor necrosis factor α and MAPK activator dehydrocrenatine, reversed the therapeutic effect of PEG-CeONPs in hUCMSCs, indicating that PEG-CeONPs act by inhibiting the NFκB and MAPK signaling pathways.

CONCLUSIONS

The carriage of the metal antioxidant oxidase PEG-CeONPs maintained the ability of hUCMSCs in the injured area, reduced the ROS levels in the microenvironment, and facilitated tendon regeneration. The data presented herein provide a novel therapeutic strategy for tendon healing and new insights into the use of stem cells for disease treatment.

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.

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.

Decoding the genetic and epigenetic basis of asthma

Asthma is a complex and heterogeneous chronic inflammatory disease of the airways. Alongside environmental factors, asthma susceptibility is strongly influenced by genetics. Given its high prevalence and our incomplete understanding of the mechanisms underlying disease susceptibility, asthma is frequently studied in genome-wide association studies (GWAS), which have identified thousands of genetic variants associated with asthma development. Virtually all these genetic variants reside in non-coding genomic regions, which has obscured the functional impact of asthma-associated variants and their translation into disease-relevant mechanisms. Recent advances in genomics technology and epigenetics now offer methods to link genetic variants to gene regulatory elements embedded within non-coding regions, which have started to unravel the molecular mechanisms underlying the complex (epi)genetics of asthma. Here, we provide an integrated overview of (epi)genetic variants associated with asthma, focusing on efforts to link these disease associations to biological insight into asthma pathophysiology using state-of-the-art genomics methodology. Finally, we provide a perspective as to how decoding the genetic and epigenetic basis of asthma has the potential to transform clinical management of asthma and to predict the risk of asthma development.

Human Macrophage Long Intergenic Noncoding RNA, SIMALR, Suppresses Inflammatory Macrophage Apoptosis via NTN1 (Netrin-1)

BACKGROUND

Long noncoding RNAs (lncRNAs) have emerged as novel regulators of macrophage biology and inflammatory cardiovascular diseases. However, studies focused on lncRNAs in human macrophage subtypes, particularly human lncRNAs that are not conserved in rodents, are limited.

METHODS

Through RNA-sequencing of human monocyte-derived macrophages, we identified suppressor of inflammatory macrophage apoptosis lncRNA (SIMALR). Lipopolysaccharide/IFNγ (interferon γ) stimulated human macrophages were treated with SIMALR antisense oligonucleotides and subjected to RNA-sequencing to investigate the function of SIMALR. Western blots, luciferase assay, and RNA immunoprecipitation were performed to validate function and potential mechanism of SIMALR. RNAscope was performed to identify SIMALR expression in human carotid atherosclerotic plaques.

RESULTS

RNA-sequencing of human monocyte-derived macrophages identified SIMALR, a human macrophage-specific long intergenic noncoding RNA that is highly induced in lipopolysaccharide/IFNγ-stimulated macrophages. SIMALR knockdown in lipopolysaccharide/IFNγ stimulated THP1 human macrophages induced apoptosis of inflammatory macrophages, as shown by increased protein expression of cleaved PARP (poly[ADP-ribose] polymerase), caspase 9, caspase 3, and Annexin V+. RNA-sequencing of control versus SIMALR knockdown in lipopolysaccharide/IFNγ-stimulated macrophages showed Netrin-1 (NTN1) to be significantly decreased upon SIMALR knockdown. We confirmed that NTN1 knockdown in lipopolysaccharide/IFNγ-stimulated macrophages induced apoptosis. The SIMALR knockdown-induced apoptotic phenotype was rescued by adding recombinant NTN1. NTN1 promoter-luciferase reporter activity was increased in HEK293T (human embryonic kidney 293) cells treated with lentiviral overexpression of SIMALR. NTN1 promoter activity is known to require HIF1α (hypoxia-inducible factor 1 subunit alpha), and our studies suggest that SIMALR may interact with HIF1α to regulate NTN1 transcription, thereby regulating macrophages apoptosis. SIMALR was found to be expressed in macrophages in human carotid atherosclerotic plaques of symptomatic patients.

CONCLUSIONS

SIMALR is a nonconserved, human macrophage lncRNA expressed in atherosclerosis that suppresses macrophage apoptosis. SIMALR partners with HIF1α (hypoxia-inducible factor 1 subunit alpha) to regulate NTN1, which is a known macrophage survival factor. This work illustrates the importance of interrogating the functions of human lncRNAs and exploring their translational and therapeutic potential in human atherosclerosis.

Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution

Long-range interactions between regulatory elements and promoters are key in gene transcriptional control; however, their study requires large amounts of starting material, which is not compatible with clinical scenarios nor the study of rare cell populations. Here we introduce low input capture Hi-C (liCHi-C) as a cost-effective, flexible method to map and robustly compare promoter interactomes at high resolution. As proof of its broad applicability, we implement liCHi-C to study normal and malignant human hematopoietic hierarchy in clinical samples. We demonstrate that the dynamic promoter architecture identifies developmental trajectories and orchestrates transcriptional transitions during cell-state commitment. Moreover, liCHi-C enables the identification of disease-relevant cell types, genes and pathways potentially deregulated by non-coding alterations at distal regulatory elements. Finally, we show that liCHi-C can be harnessed to uncover genome-wide structural variants, resolve their breakpoints and infer their pathogenic effects. Collectively, our optimized liCHi-C method expands the study of 3D chromatin organization to unique, low-abundance cell populations, and offers an opportunity to uncover factors and regulatory networks involved in disease pathogenesis.

Integration of 3D genome topology and local chromatin features uncovers enhancers underlying craniofacial-specific cartilage defects

Aberrations in tissue-specific enhancers underlie many developmental defects. Disrupting a noncoding region distal from the human SOX9 gene causes the Pierre Robin sequence (PRS) characterized by the undersized lower jaw. Such a craniofacial-specific defect has been previously linked to enhancers transiently active in cranial neural crest cells (CNCCs). We demonstrate that the PRS region also strongly regulates Sox9 in CNCC-derived Meckel's cartilage (MC), but not in limb cartilages, even after decommissioning of CNCC enhancers. Such an MC-specific regulatory effect correlates with the MC-specific chromatin contacts between the PRS region and Sox9, highlighting the importance of lineage-dependent chromatin topology in instructing enhancer usage. By integrating the enhancer signatures and chromatin topology, we uncovered >10,000 enhancers that function differentially between MC and limb cartilages and demonstrated their association with human diseases. Our findings provide critical insights for understanding the choreography of gene regulation during development and interpreting the genetic basis of craniofacial pathologies.

Systemic lupus erythematosus variants modulate the function of an enhancer upstream of TNFAIP3

TNFAIP3/A20 is a prominent autoimmune disease risk locus that is correlated with hypomorphic TNFAIP3 expression and exhibits complex chromatin architecture with over 30 predicted enhancers. This study aimed to functionally characterize an enhancer ∼55 kb upstream of the TNFAIP3 promoter marked by the systemic lupus erythematosus (SLE) risk haplotype index SNP, rs10499197. Allele effects of rs10499197, rs58905141, and rs9494868 were tested by EMSA and/or luciferase reporter assays in immune cell types. Co-immunoprecipitation, ChIP-qPCR, and 3C-qPCR were performed on patient-derived EBV B cells homozygous for the non-risk or SLE risk TNFAIP3 haplotype to assess haplotype-specific effects on transcription factor binding and chromatin regulation at the TNFAIP3 locus. This study found that the TNFAIP3 locus has a complex chromatin regulatory network that spans ∼1M bp from the promoter region of IL20RA to the 3' untranslated region of TNFAIP3. Functional dissection of the enhancer demonstrated co-dependency of the RelA/p65 and CEBPB binding motifs that, together, increase IL20RA and IFNGR1 expression and decreased TNFAIP3 expression in the context of the TNFAIP3 SLE risk haplotype through dynamic long-range interactions up- and downstream. Examination of SNPs in linkage disequilibrium (D' = 1.0) with rs10499197 identified rs9494868 as a functional SNP with risk allele-specific increase in nuclear factor binding and enhancer activation in vitro. In summary, this study demonstrates that SNPs carried on the ∼109 kb SLE risk haplotype facilitate hypermorphic IL20RA and IFNGR1 expression, while suppressing TNFAIP3 expression, adding to the mechanistic potency of this critically important locus in autoimmune disease pathology.

The landscape of GWAS validation; systematic review identifying 309 validated non-coding variants across 130 human diseases

Background

The remarkable growth of genome-wide association studies (GWAS) has created a critical need to experimentally validate the disease-associated variants, 90% of which involve non-coding variants.

Methods

To determine how the field is addressing this urgent need, we performed a comprehensive literature review identifying 36,676 articles. These were reduced to 1454 articles through a set of filters using natural language processing and ontology-based text-mining. This was followed by manual curation and cross-referencing against the GWAS catalog, yielding a final set of 286 articles.

Results

We identified 309 experimentally validated non-coding GWAS variants, regulating 252 genes across 130 human disease traits. These variants covered a variety of regulatory mechanisms. Interestingly, 70% (215/309) acted through cis-regulatory elements, with the remaining through promoters (22%, 70/309) or non-coding RNAs (8%, 24/309). Several validation approaches were utilized in these studies, including gene expression (n = 272), transcription factor binding (n = 175), reporter assays (n = 171), in vivo models (n = 104), genome editing (n = 96) and chromatin interaction (n = 33).

Conclusions

This review of the literature is the first to systematically evaluate the status and the landscape of experimentation being used to validate non-coding GWAS-identified variants. Our results clearly underscore the multifaceted approach needed for experimental validation, have practical implications on variant prioritization and considerations of target gene nomination. While the field has a long way to go to validate the thousands of GWAS associations, we show that progress is being made and provide exemplars of validation studies covering a wide variety of mechanisms, target genes, and disease areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01216-w.

Reorganization of 3D genome architecture across wild boar and Bama pig adipose tissues

BACKGROUND

A growing body of evidence has revealed that the mammalian genome is organized into hierarchical layers that are closely correlated with and may even be causally linked with variations in gene expression. Recent studies have characterized chromatin organization in various porcine tissues and cell types and compared them among species and during the early development of pigs. However, how chromatin organization differs among pig breeds is poorly understood.

RESULTS

In this study, we investigated the 3D genome organization and performed transcriptome characterization of two adipose depots (upper layer of backfat [ULB] and greater omentum [GOM]) in wild boars and Bama pigs; the latter is a typical indigenous pig in China. We found that over 95% of the A/B compartments and topologically associating domains (TADs) are stable between wild boars and Bama pigs. In contrast, more than 70% of promoter-enhancer interactions (PEIs) are dynamic and widespread, involving over a thousand genes. Alterations in chromatin structure are associated with changes in the expression of genes that are involved in widespread biological functions such as basic cellular functions, endocrine function, energy metabolism and the immune response. Approximately 95% and 97% of the genes associated with reorganized A/B compartments and PEIs in the two pig breeds differed between GOM and ULB, respectively.

CONCLUSIONS

We reported 3D genome organization in adipose depots from different pig breeds. In a comparison of Bama pigs and wild boar, large-scale compartments and TADs were mostly conserved, while fine-scale PEIs were extensively reorganized. The chromatin architecture in these two pig breeds was reorganized in an adipose depot-specific manner. These results contribute to determining the regulatory mechanism of phenotypic differences between Bama pigs and wild boar.

Capturing 3D Chromatin Maps of Human Primary Monocytes: Insights From High-Resolution Hi-C

Although the variation in chromatin architecture during adaptive immune responses has been thoroughly investigated, the 3D landscape of innate immunity is still unknown. Herein, chromatin regulation and heterogeneity among human primary monocytes were investigated. Peripheral blood was collected from two healthy persons and two patients with systemic lupus erythematosus (SLE), and CD14+ monocytes were selected to perform Hi-C, RNA-seq, ATAC-seq and ChIP-seq analyses. Raw data from the THP1 cell line Hi-C library were used for comparison. For each sample, we constructed three Hi-C libraries and obtained approximately 3 billion paired-end reads in total. Resolution analysis showed that more than 80% of bins presented depths greater than 1000 at a 5 kb resolution. The constructed high-resolution chromatin interaction maps presented similar landscapes in the four individuals, which showed significant divergence from the THP1 cell line chromatin structure. The variability in chromatin interactions around HLA-D genes in the HLA complex region was notable within individuals. We further found that the CD16-encoding gene (FCGR3A) is located at a variable topologically associating domain (TAD) boundary and that chromatin loop dynamics might modulate CD16 expression. Our results indicate both the stability and variability of high-resolution chromatin interaction maps among human primary monocytes. This work sheds light on the potential mechanisms by which the complex interplay of epigenetics and spatial 3D architecture regulates chromatin in innate immunity.

Shared Genetic Architecture Between Rheumatoid Arthritis and Varying Osteoporotic Phenotypes

Rheumatoid arthritis (RA) and low bone mineral density (BMD), an indicator of osteoporosis (OP), appear epidemiologically associated. Shared genetic factors may explain this association. This study aimed to investigate the presence of pleiotropy to clarify the potential genetic association between RA and OP. We examined BMDs at varying skeletal sites reported in UK Biobank as well as OP fracture acquired from the Genetic Factors for Osteoporosis (GEFOS) Consortium and the TwinsUK study. PRSice-2 was used to assess the potential shared genetic overlap between RA and OP. The presence of pleiotropy was examined using colocalization analysis. PRSice-2 revealed that RA was significantly associated with OP fracture (β = 351.6 ± 83.9, p value = 2.76E-05), total BMD (β = -1763.5 ± 612.8, p = 4.00E-03), spine BMD (β = -919.8 ± 264.6, p value = 5.09E-04), and forearm BMD (β = -66.09 ± 31.40, p value = 3.53E-02). Through colocalization analysis, the same causal genetic variants, associated with both RA and OP, were apparent in 12 genes: PLCL1, BOLL, AC011997.1, TNFAIP3, RP11-158I9.1, CDK6, CHCHD4P2, RP11-505C13.1, PHF19, TRAF1, C5, and C11orf49 with moderate posterior probabilities (>50%). Pleiotropy is involved in the association between RA and OP phenotypes. These findings contribute to the understanding of disease mechanisms and provide insight into possible therapeutic advancements and enhanced screening measures. © 2021 American Society for Bone and Mineral Research (ASBMR).

Base-resolution prediction of transcription factor binding signals by a deep learning framework

Transcription factors (TFs) play an important role in regulating gene expression, thus the identification of the sites bound by them has become a fundamental step for molecular and cellular biology. In this paper, we developed a deep learning framework leveraging existing fully convolutional neural networks (FCN) to predict TF-DNA binding signals at the base-resolution level (named as FCNsignal). The proposed FCNsignal can simultaneously achieve the following tasks: (i) modeling the base-resolution signals of binding regions; (ii) discriminating binding or non-binding regions; (iii) locating TF-DNA binding regions; (iv) predicting binding motifs. Besides, FCNsignal can also be used to predict opening regions across the whole genome. The experimental results on 53 TF ChIP-seq datasets and 6 chromatin accessibility ATAC-seq datasets show that our proposed framework outperforms some existing state-of-the-art methods. In addition, we explored to use the trained FCNsignal to locate all potential TF-DNA binding regions on a whole chromosome and predict DNA sequences of arbitrary length, and the results show that our framework can find most of the known binding regions and accept sequences of arbitrary length. Furthermore, we demonstrated the potential ability of our framework in discovering causal disease-associated single-nucleotide polymorphisms (SNPs) through a series of experiments.

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.

Predict long-range enhancer regulation based on protein-protein interactions between transcription factors

Long-range regulation by distal enhancers plays critical roles in cell-type specific transcriptional programs. Computational predictions of genome-wide enhancer-promoter interactions are still challenging due to limited accuracy and the lack of knowledge on the molecular mechanisms. Based on recent biological investigations, the protein-protein interactions (PPIs) between transcription factors (TFs) have been found to participate in the regulation of chromatin loops. Therefore, we developed a novel predictive model for cell-type specific enhancer-promoter interactions by leveraging the information of TF PPI signatures. Evaluated by a series of rigorous performance comparisons, the new model achieves superior performance over other methods. The model also identifies specific TF PPIs that may mediate long-range regulatory interactions, revealing new mechanistic understandings of enhancer regulation. The prioritized TF PPIs are associated with genes in distinct biological pathways, and the predicted enhancer-promoter interactions are strongly enriched with cis-eQTLs. Most interestingly, the model discovers enhancer-mediated trans-regulatory links between TFs and genes, which are significantly enriched with trans-eQTLs. The new predictive model, along with the genome-wide analyses, provides a platform to systematically delineate the complex interplay among TFs, enhancers and genes in long-range regulation. The novel predictions also lead to mechanistic interpretations of eQTLs to decode the genetic associations with gene expression.

Unraveling the complexities of psoriatic arthritis by the use of -Omics and their relevance for clinical care

-Omic technologies represent a novel approach to unravel ill-defined aspects of psoriatic arthritis (PsA). Large-scale information can be acquired from analysis of affected tissues in PsA via high-throughput studies in the domains of genomics, transcriptomics, epigenetics, proteomics and metabolomics. This is a critical overview of the current knowledge of -omics in PsA, with emphasis on the pathophysiological insights of diagnostic and therapeutic relevance, the advent of novel biomarkers and their potential use for precision medicine in PsA.

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.

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

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

Functional genomics atlas of synovial fibroblasts defining rheumatoid arthritis heritability

BACKGROUND

Genome-wide association studies have reported more than 100 risk loci for rheumatoid arthritis (RA). These loci are shown to be enriched in immune cell-specific enhancers, but the analysis so far has excluded stromal cells, such as synovial fibroblasts (FLS), despite their crucial involvement in the pathogenesis of RA. Here we integrate DNA architecture, 3D chromatin interactions, DNA accessibility, and gene expression in FLS, B cells, and T cells with genetic fine mapping of RA loci.

RESULTS

We identify putative causal variants, enhancers, genes, and cell types for 30-60% of RA loci and demonstrate that FLS account for up to 24% of RA heritability. TNF stimulation of FLS alters the organization of topologically associating domains, chromatin state, and the expression of putative causal genes such as TNFAIP3 and IFNAR1. Several putative causal genes constitute RA-relevant functional networks in FLS with roles in cellular proliferation and activation. Finally, we demonstrate that risk variants can have joint-specific effects on target gene expression in RA FLS, which may contribute to the development of the characteristic pattern of joint involvement in RA.

CONCLUSION

Overall, our research provides the first direct evidence for a causal role of FLS in the genetic susceptibility for RA accounting for up to a quarter of RA heritability.

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

Chromatin looping between regulatory elements and gene promoters presents a potential mechanism whereby disease risk variants affect their target genes. In this study, we use H3K27ac HiChIP, a method for assaying the active chromatin interactome in two cell lines: keratinocytes and skin lymphoma-derived CD8+ T cells. We integrate public datasets for a lymphoblastoid cell line and primary CD4+ T cells and identify gene targets at risk loci for skin-related disorders. Interacting genes enrich for pathways of known importance in each trait, such as cytokine response (psoriatic arthritis and psoriasis) and replicative senescence (melanoma). We show examples of how our analysis can inform changes in the current understanding of multiple psoriasis-associated risk loci. For example, the variant rs10794648, which is generally assigned to IFNLR1, was linked to GRHL3, a gene essential in skin repair and development, in our dataset. Our findings, therefore, indicate a renewed importance of skin-related factors in the risk of disease.

Three-Dimensional Genome Interactions Identify Potential Adipocyte Metabolism-Associated Gene STON1 and Immune-Correlated Gene FSHR at the rs13405728 Locus in Polycystic Ovary Syndrome

Background

rs13405728 was identified as one of the most prevalent susceptibility loci for polycystic ovary syndrome (PCOS) in Han Chinese and Caucasian women. However, the target genes and potential mechanisms of the rs13405728 locus remain to be determined.

Methods

Three-dimensional (3D) genome interactions from the ovary tissue were characterized via high-through chromosome conformation capture (Hi-C) and Capture Hi-C technologies to identify putative targets at the rs13405728 locus. Combined analyses of eQTL, RNA-Seq, DNase-Seq, ChIP-Seq, and sing-cell sequencing were performed to explore the molecular roles of these target genes in PCOS. PCOS-like mice were applied to verify the expression patterns.

Results

Generally, STON1 and FSHR were identified as potential targets of the rs13405728 locus in 3D genomic interactions with epigenomic regulatory peaks, with STON1 (P=0.0423) and FSHR (P=0.0013) being highly expressed in PCOS patients. STON1 co-expressed genes were associated with metabolic processes (P=0.0008) in adipocytes (P=0.0001), which was validated in the fat tissue (P<0.0001) and ovary (P=0.0035) from fat-diet mice. The immune system process (GO:0002376) was enriched in FSHR co-expressed genes (P=0.0002) and PCOS patients (P=0.0002), with CD4 high expression in PCOS patients (P=0.0316) and PCOS-like models (P=0.0079). Meanwhile, FSHR expression was positively correlated with CD4 expression in PCOS patients (P=0.0252) and PCOS-like models (P=0.0178). Furthermore, androgen receptor (AR) was identified as the common transcription factor for STON1 and FSHR and positively correlated with the expression of STON1 (P=0.039) and FSHR (P=4e-06) in ovary tissues and PCOS-like mice.

Conclusion

Overall, we identified STON1 and FSHR as potential targets for the rs13405728 locus and their roles in the processes of adipocyte metabolism and CD4 immune expression in PCOS, which provides 3D genomic insight into the pathogenesis of PCOS.

Islet Epigenetic Impacts on β-Cell Identity and Function

The development and maintenance of differentiation is vital to the function of mature cells. Terminal differentiation is achieved by locking in the expression of genes essential for the function of those cells. Gene expression and its memory through generations of cell division is controlled by transcription factors and a host of epigenetic marks. In type 2 diabetes, β cells have altered gene expression compared to controls, accompanied by altered chromatin marks. Mutations, diet, and environment can all disrupt the implementation and preservation of the distinctive β-cell transcriptional signature. Understanding of the full complement of genomic control in β cells is still nascent. This article describes the known effects of histone marks and variants, DNA methylation, how they are regulated in the β cell, and how they affect cell-fate specification, maintenance, and lineage propagation. © 2021 American Physiological Society. Compr Physiol 11:1-18, 2021.

Immune Regulation in Time and Space: The Role of Local- and Long-Range Genomic Interactions in Regulating Immune Responses

Mammals face and overcome an onslaught of endogenous and exogenous challenges in order to survive. Typical immune cells and barrier cells, such as epithelia, must respond rapidly and effectively to encountered pathogens and aberrant cells to prevent invasion and eliminate pathogenic species before they become overgrown and cause harm. On the other hand, inappropriate initiation and failed termination of immune cell effector function in the absence of pathogens or aberrant tissue gives rise to a number of chronic, auto-immune, and neoplastic diseases. Therefore, the fine control of immune effector functions to provide for a rapid, robust response to challenge is essential. Importantly, immune cells are heterogeneous due to various factors relating to cytokine exposure and cell-cell interaction. For instance, tissue-resident macrophages and T cells are phenotypically, transcriptionally, and functionally distinct from their circulating counterparts. Indeed, even the same cell types in the same environment show distinct transcription patterns at the single cell level due to cellular noise, despite being robust in concert. Additionally, immune cells must remain quiescent in a naive state to avoid autoimmunity or chronic inflammatory states but must respond robustly upon activation regardless of their microenvironment or cellular noise. In recent years, accruing evidence from next-generation sequencing, chromatin capture techniques, and high-resolution imaging has shown that local- and long-range genome architecture plays an important role in coordinating rapid and robust transcriptional responses. Here, we discuss the local- and long-range genome architecture of immune cells and the resultant changes upon pathogen or antigen exposure. Furthermore, we argue that genome structures contribute functionally to rapid and robust responses under noisy and distinct cellular environments and propose a model to explain this phenomenon.

A catalog of GWAS fine-mapping efforts in autoimmune disease

Genome-wide association studies (GWASs) have enabled unbiased identification of genetic loci contributing to common complex diseases. Because GWAS loci often harbor many variants and genes, it remains a major challenge to move from GWASs’ statistical associations to the identification of causal variants and genes that underlie these association signals. Researchers have applied many statistical and functional fine-mapping strategies to prioritize genetic variants and genes as potential candidates. There is no gold standard in fine-mapping approaches, but consistent results across different approaches can improve confidence in the fine-mapping findings. Here, we combined text mining with a systematic review and formed a catalog of 85 studies with evidence of fine mapping for at least one autoimmune GWAS locus. Across all fine-mapping studies, we compiled 230 GWAS loci with allelic heterogeneity estimates and predictions of causal variants and trait-relevant genes. These 230 loci included 455 combinations of locus-by-disease association signals with 15 autoimmune diseases. Using these estimates, we assessed the probability of mediating disease risk associations across genes in GWAS loci and identified robust signals of causal disease biology. We predict that this comprehensive catalog of GWAS fine-mapping efforts in autoimmune disease will greatly help distill the plethora of information in the field and inform therapeutic strategies.

Using functional genomics to advance the understanding of psoriatic arthritis

Psoriatic arthritis (PsA) is a complex disease where susceptibility is determined by genetic and environmental risk factors. Clinically, PsA involves inflammation of the joints and the skin, and, if left untreated, results in irreversible joint damage. There is currently no cure and the few treatments available to alleviate symptoms do not work in all patients. Over the past decade, genome-wide association studies (GWAS) have uncovered a large number of disease-associated loci but translating these findings into functional mechanisms and novel targets for therapeutic use is not straightforward. Most variants have been predicted to affect primarily long-range regulatory regions such as enhancers. There is now compelling evidence to support the use of chromatin conformation analysis methods to discover novel genes that can be affected by disease-associated variants. Here, we will review the studies published in the field that have given us a novel understanding of gene regulation in the context of functional genomics and how this relates to the study of PsA and its underlying disease mechanism.

Approaching Shared Pathophysiology in Immune-Mediated Diseases through Functional Genomics

Immune-mediated diseases (IMDs) are complex pathologies that are strongly influenced by environmental and genetic factors. Associations between genetic loci and susceptibility to these diseases have been widely studied, and hundreds of risk variants have emerged during the last two decades, with researchers observing a shared genetic pattern among them. Nevertheless, the pathological mechanism behind these associations remains a challenge that has just started to be understood thanks to functional genomic approaches. Transcriptomics, regulatory elements, chromatin interactome, as well as the experimental characterization of genomic findings, constitute key elements in the emerging understandings of how genetics affects the etiopathogenesis of IMDs. In this review, we will focus on the latest advances in the field of functional genomics, centering our attention on systemic rheumatic IMDs.

Functional genomics in autoimmune diseases

Associations between genetic loci and increased susceptibility to autoimmune disease have been well characterized, however, translating this knowledge into mechanistic insight and patient benefit remains a challenge. While improvements in the precision, completeness and accuracy of our genetic understanding of autoimmune diseases will undoubtedly be helpful, meeting this challenge will require two interlinked problems to be addressed: first which of the highly correlated variants at an individual locus is responsible for increased disease risk, and second what are the downstream effects of this variant. Given that the majority of loci are thought to affect non-coding regulatory elements, the second question is often reframed as what are the target gene(s) and pathways affected by causal variants. Currently, these questions are being addressed using a wide variety of novel techniques and datasets. In many cases, these approaches are complementary and it is likely that the most accurate picture will be generated by consolidating information relating to transcription, regulatory activity, chromatin accessibility, chromatin conformation and readouts from functional experiments, such as genome editing and reporter assays. It is clear that it will be necessary to gather this information from disease relevant cell types and conditions and that by doing so our understanding of disease etiology will be improved. This review is focused on the field of autoimmune disease functional genomics with a particular focus on the most exciting and significant research to be published within the last couple of years.

Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis

Genome-wide association studies have identified genetic variation contributing to complex disease risk. However, assigning causal genes and mechanisms has been more challenging because disease-associated variants are often found in distal regulatory regions with cell-type specific behaviours. Here, we collect ATAC-seq, Hi-C, Capture Hi-C and nuclear RNA-seq data in stimulated CD4+ T cells over 24 h, to identify functional enhancers regulating gene expression. We characterise changes in DNA interaction and activity dynamics that correlate with changes in gene expression, and find that the strongest correlations are observed within 200 kb of promoters. Using rheumatoid arthritis as an example of T cell mediated disease, we demonstrate interactions of expression quantitative trait loci with target genes, and confirm assigned genes or show complex interactions for 20% of disease associated loci, including FOXO1, which we confirm using CRISPR/Cas9.

The Role of Noncoding Variants in Heritable Disease

The genetic basis of disease has largely focused on coding regions. However, it has become clear that a large proportion of the noncoding genome is functional and harbors genetic variants that contribute to disease etiology. Here, we review recent examples of inherited noncoding alterations that are responsible for Mendelian disorders or act to influence complex traits. We explore both rare and common genetic variants and discuss the wide range of mechanisms by which they affect gene regulation to promote disease. We also debate the challenges and progress associated with identifying and interpreting the functional and clinical significance of genetic variation in the context of the noncoding regulatory landscape.

Resolving mechanisms of immune-mediated disease in primary CD4 T cells

Deriving mechanisms of immune-mediated disease from GWAS data remains a formidable challenge, with attempts to identify causal variants being frequently hampered by strong linkage disequilibrium. To determine whether causal variants could be identified from their functional effects, we adapted a massively parallel reporter assay for use in primary CD4 T cells, the cell type whose regulatory DNA is most enriched for immune-mediated disease SNPs. This enabled the effects of candidate SNPs to be examined in a relevant cellular context and generated testable hypotheses into disease mechanisms. To illustrate the power of this approach, we investigated a locus that has been linked to six immune-mediated diseases but cannot be fine-mapped. By studying the lead expression-modulating SNP, we uncovered an NF-κB-driven regulatory circuit which constrains T-cell activation through the dynamic formation of a super-enhancer that upregulates TNFAIP3 (A20), a key NF-κB inhibitor. In activated T cells, this feedback circuit is disrupted-and super-enhancer formation prevented-by the risk variant at the lead SNP, leading to unrestrained T-cell activation via a molecular mechanism that appears to broadly predispose to human autoimmunity.

Mapping DNA interaction landscapes in psoriasis susceptibility loci highlights KLF4 as a target gene in 9q31

BACKGROUND

Genome-wide association studies (GWAS) have uncovered many genetic risk loci for psoriasis, yet many remain uncharacterised in terms of the causal gene and their biological mechanism in disease. This is largely a result of the findings that over 90% of GWAS variants map outside of protein-coding DNA and instead are enriched in cell type- and stimulation-specific gene regulatory regions.

RESULTS

Here, we use a disease-focused Capture Hi-C (CHi-C) experiment to link psoriasis-associated variants with their target genes in psoriasis-relevant cell lines (HaCaT keratinocytes and My-La CD8+ T cells). We confirm previously assigned genes, suggest novel candidates and provide evidence for complexity at psoriasis GWAS loci. For one locus, uniquely, we combine further epigenomic evidence to demonstrate how a psoriasis-associated region forms a functional interaction with the distant (> 500 kb) KLF4 gene. This interaction occurs between the gene and active enhancers in HaCaT cells, but not in My-La cells. We go on to investigate this long-distance interaction further with Cas9 fusion protein-mediated chromatin modification (CRISPR activation) coupled with RNA-seq, demonstrating how activation of the psoriasis-associated enhancer upregulates KLF4 and its downstream targets, relevant to skin cells and apoptosis.

CONCLUSIONS

This approach utilises multiple functional genomic techniques to follow up GWAS-associated variants implicating relevant cell types and causal genes in each locus; these are vital next steps for the translation of genetic findings into clinical benefit.

Functional effects of variation in transcription factor binding highlight long-range gene regulation by epromoters

Identifying DNA cis-regulatory modules (CRMs) that control the expression of specific genes is crucial for deciphering the logic of transcriptional control. Natural genetic variation can point to the possible gene regulatory function of specific sequences through their allelic associations with gene expression. However, comprehensive identification of causal regulatory sequences in brute-force association testing without incorporating prior knowledge is challenging due to limited statistical power and effects of linkage disequilibrium. Sequence variants affecting transcription factor (TF) binding at CRMs have a strong potential to influence gene regulatory function, which provides a motivation for prioritizing such variants in association testing. Here, we generate an atlas of CRMs showing predicted allelic variation in TF binding affinity in human lymphoblastoid cell lines and test their association with the expression of their putative target genes inferred from Promoter Capture Hi-C and immediate linear proximity. We reveal >1300 CRM TF-binding variants associated with target gene expression, the majority of them undetected with standard association testing. A large proportion of CRMs showing associations with the expression of genes they contact in 3D localize to the promoter regions of other genes, supporting the notion of 'epromoters': dual-action CRMs with promoter and distal enhancer activity.

Prioritizing disease and trait causal variants at the TNFAIP3 locus using functional and genomic features

Genome-wide association studies have associated thousands of genetic variants with complex traits and diseases, but pinpointing the causal variant(s) among those in tight linkage disequilibrium with each associated variant remains a major challenge. Here, we use seven experimental assays to characterize all common variants at the multiple disease-associated TNFAIP3 locus in five disease-relevant immune cell lines, based on a set of features related to regulatory potential. Trait/disease-associated variants are enriched among SNPs prioritized based on either: (1) residing within CRISPRi-sensitive regulatory regions, or (2) localizing in a chromatin accessible region while displaying allele-specific reporter activity. Of the 15 trait/disease-associated haplotypes at TNFAIP3, 9 have at least one variant meeting one or both of these criteria, 5 of which are further supported by genetic fine-mapping. Our work provides a comprehensive strategy to characterize genetic variation at important disease-associated loci, and aids in the effort to identify trait causal genetic variants.

Quantifying functional impact of non-coding variants with multi-task Bayesian neural network

MOTIVATION

Advances in high-throughput genotyping and sequencing technologies during recent years have revealed essential roles of non-coding regions in gene regulation. Genome-wide association studies (GWAS) suggested that a large proportion of risk variants are located in non-coding regions and remain unexplained by current expression quantitative trait loci catalogs. Interpreting the causal effects of these genetic modifications is crucial but difficult owing to our limited knowledge of how regulatory elements function. Although several computational methods have been designed to prioritize regulatory variants that substantially impact human phenotypes, few of them achieve consistently high performance even when large-scale multi-omic data are integrated.

RESULTS

We propose a novel multi-task framework based on Bayesian deep neural networks, MtBNN, to quantify the deleterious impact of single nucleotide polymorphisms in non-coding genomic regions. With the high-efficiency provided by the multi-task Bayesian framework to integrate information from different sources, MtBNN is capable of extracting features from genomic sequences of large-scale chromatin-profiling data, such as chromatin accessibility and transcript factor binding affinities, and calculating the distribution of the probability that a non-coding variant disrupts regulatory activities. A series of comprehensive experiments show that MtBNN quantifies the functional impact of cis-regulatory variations with high accuracy, including expression quantitative trait locus, DNase I sensitivity quantitative trait locus and functional genetic variants located within ATAC-peaks that affect the accessibility of the corresponding peak and achieves significantly better performance than the existing methods. Moreover, MtBNN has applications in the discovery of potentially causal disease-associated single-nucleotide polymorphisms (SNPs), thus helping fine-map the GWAS SNPs.

AVAILABILITY AND IMPLEMENTATION

Code can be downloaded from https://github.com/Zoesgithub/MtBNN.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Chromatin interactome mapping at 139 independent breast cancer risk signals

BACKGROUND

Genome-wide association studies have identified 196 high confidence independent signals associated with breast cancer susceptibility. Variants within these signals frequently fall in distal regulatory DNA elements that control gene expression.

RESULTS

We designed a Capture Hi-C array to enrich for chromatin interactions between the credible causal variants and target genes in six human mammary epithelial and breast cancer cell lines. We show that interacting regions are enriched for open chromatin, histone marks for active enhancers, and transcription factors relevant to breast biology. We exploit this comprehensive resource to identify candidate target genes at 139 independent breast cancer risk signals and explore the functional mechanism underlying altered risk at the 12q24 risk region.

CONCLUSIONS

Our results demonstrate the power of combining genetics, computational genomics, and molecular studies to rationalize the identification of key variants and candidate target genes at breast cancer GWAS signals.

Towards a Better Classification and Novel Therapies Based on the Genetics of Systemic Sclerosis

PURPOSE OF THE REVIEW

Nowadays, important advances have occurred in our understanding of the pathogenesis of systemic sclerosis (SSc), which is a rare immune-mediated inflammatory disease (IMID) characterized by vascular damage, immune imbalance, and fibrosis. Its etiology remains unknown; nevertheless, both environmental and genetic factors play a major role in the disease. This review will focus on the main advances made in the field of genetics of SSc.

RECENT FINDINGS

The assessment of how interindividual genetic variability affects disease onset and progression has enhanced our knowledge of disease biology, and this will eventually translate in the development of new diagnostic and therapeutic tools, which is the final goal of personalized medicine. We will provide an overview of the most relevant achievements in the genetics of SSc, its shared genetics among IMIDs with special attention on drug repurposing, current challenges for the functional characterization of risk variants, and future directions.

Chromatin interactions reveal novel gene targets for drug repositioning in rheumatic diseases

Objectives

There is a need to identify effective treatments for rheumatic diseases, and while genetic studies have been successful it is unclear which genes contribute to the disease. Using our existing Capture Hi-C data on three rheumatic diseases, we can identify potential causal genes which are targets for existing drugs and could be repositioned for use in rheumatic diseases.

Methods

High confidence candidate causal genes were identified using Capture Hi-C data from B cells and T cells. These genes were used to interrogate drug target information from DrugBank to identify existing treatments, which could be repositioned to treat these diseases. The approach was refined using Ingenuity Pathway Analysis to identify enriched pathways and therefore further treatments relevant to the disease.

Results

Overall, 454 high confidence genes were identified. Of these, 48 were drug targets (108 drugs) and 11 were existing therapies used in the treatment of rheumatic diseases. After pathway analysis refinement, 50 genes remained, 13 of which were drug targets (33 drugs). However considering targets across all enriched pathways, a further 367 drugs were identified for potential repositioning.

Conclusion

Capture Hi-C has the potential to identify therapies which could be repositioned to treat rheumatic diseases. This was particularly successful for rheumatoid arthritis, where six effective, biologic treatments were identified. This approach may therefore yield new ways to treat patients, enhancing their quality of life and reducing the economic impact on healthcare providers. As additional cell types and other epigenomic data sets are generated, this prospect will improve further.

Identification of rheumatoid arthritis causal genes using functional genomics

Over the past decade, genome-wide association studies have contributed a wealth of knowledge to our understanding of polygenic disorders such as rheumatoid arthritis. As the size of sample cohorts has improved so too have the computational and experimental methods used to robustly define variants associated with disease susceptibility. The challenge now remains to translate these findings into improved understanding of disease aetiology and patient care. Whilst much of the focus of translating the findings of genome-wide association studies has been on global analysis of all variants identified, careful functional study of individual disease susceptibility loci will be required in order to refine our understanding of how individual variants contribute to disease risk. Here, we present the argument behind such an approach and describe some of the novel tools being used to investigate risk loci. This includes the use of chromosomal conformation capture techniques and modifications of the CRISPR-Cas9 system, with several examples of their implementation being described.

CRISPR/cas9 mediated knockout of an intergenic variant rs6927172 identified IL-20RA as a new risk gene for multiple autoimmune diseases

Genetic variants near the tumor necrosis factor-α-induced protein 3 gene (TNFAIP3) at the chromosomal region 6q23 demonstrated significant associations with multiple autoimmune diseases. The signals of associations have been explained to the TNFAIP3 gene, the most likely causal gene. In this study, we employed CRISPR/cas9 genome-editing tool to generate cell lines with deletions including a candidate causal variant, rs6927172, at 140 kb upstream of the TNFAIP3 gene. Interestingly, we observed alterations of multiple genes including IL-20RA encoding a subunit of the receptor for interleukin 20. Using Electrophoretic mobility shift assay (EMSA), Western blotting, and chromatin conformation capture we characterized the molecular mechanism that the DNA element carrying the variant rs6927172 influences expression of IL-20RA and TNFAIP3 genes. Additionally, we developed a new use of the transcription activator-like effector (TALE) to study the role of the variant in regulating expressions of its target genes. In summary, we generated deletion knockouts that included the candidate causal variant rs6927172 in HEK293T cells provided new evidence and mechanism for IL-20RA gene as a risk factor for multiple autoimmune diseases.

What are the dominant cytokines in early rheumatoid arthritis?

Purpose of review

Rheumatoid arthritis is a systemic disease of evolving immune dysregulation that culminates in joint destruction and disability. The principle by which pro-inflammatory cytokines may be therapeutically targeted to abrogate disease is well established, but has yet to translate into reliable cures for patients. Emerging insights into cytokine-mediated pathobiology during rheumatoid arthritis development are reviewed, and their implications for future treatment strategies considered.

Recent findings

Accumulating data highlight cytokine perturbations before the clinical onset of rheumatoid arthritis. Some of these have now been linked to the arthritogenic activation of autoantibodies and associated pain and bone destruction in affected joints. These observations suggest cytokines may trigger the transition from systemic immunity to arthritis. Cytokine exposure could furthermore ‘prime’ synovial stromal cells to perpetuate a dominant pro-inflammatory environment. By facilitating cross-talk between infiltrating immune cells and even sustaining ectopic lymphoid structure development in some cases, cytokine interplay ultimately underpins the failure of arthritis to resolve.

Summary

Successful therapeutic stratification will depend upon an increasingly sophisticated appreciation of how dominant players amongst cytokine networks vary across time and anatomical space during incipient rheumatoid arthritis. The prize of sustained remission for all patients justifies the considerable effort required to achieve this understanding.

GOPHER: Generator Of Probes for capture Hi-C Experiments at high Resolution

BACKGROUND

Target enrichment combined with chromosome conformation capturing methodologies such as capture Hi-C (CHC) can be used to investigate spatial layouts of genomic regions with high resolution and at scalable costs. A common application of CHC is the investigation of regulatory elements that are in contact with promoters, but CHC can be used for a range of other applications. Therefore, probe design for CHC needs to be adapted to experimental needs, but no flexible tool is currently available for this purpose.

RESULTS

We present a Java desktop application called GOPHER (Generator Of Probes for capture Hi-C Experiments at high Resolution) that implements three strategies for CHC probe design. GOPHER's simple approach is similar to the probe design of previous approaches that employ CHC to investigate all promoters, with one probe being placed at each margin of a single digest that overlaps the transcription start site (TSS) of each promoter. GOPHER's simple-patched approach extends this methodology with a heuristic that improves coverage of viewpoints in which the TSS is located near to one of the boundaries of the digest. GOPHER's extended approach is intended mainly for focused investigations of smaller gene sets. GOPHER can also be used to design probes for regions other than TSS such as GWAS hits or large blocks of genomic sequence. GOPHER additionally provides a number of features that allow users to visualize and edit viewpoints, and outputs a range of files useful for documentation, ordering probes, and downstream analysis.

CONCLUSION

GOPHER is an easy-to-use and robust desktop application for CHC probe design. Source code and a precompiled executable can be downloaded from the GOPHER GitHub page at https://github.com/TheJacksonLaboratory/Gopher .