Abstract Background/Aims We recently performed the largest juvenile idiopathic arthritis (JIA) genome-wide association study (GWAS) to date. Disease-associated loci contain multiple single nucleotide polymorphism (SNPs), and the majority map to non-coding enhancers, making it challenging to define causal variants and genes. Functional genomics datasets in disease-relevant tissues have been shown to be essential for the functional interpretation of GWAS loci. In particular, capture Hi-C (CHi-C) has been successful in detecting chromosomal interactions linking GWAS loci to their target genes. However, such datasets are lacking in JIA. The aim of this study is to bridge this gap and advance the knowledge of the biological mechanisms that underpin susceptibility to JIA, by integrating GWAS with public epigenomics datasets and in-house generated CHi-C from JIA patients. We focus on CD4+ T-cells, which have been shown to be one of the most relevant cell types in JIA. In addition, we use CRISPR-Cas9 to validate the regulatory effect of prioritised variants on their predicted target genes. Methods Credible SNP sets for the top JIA risk loci (P < 5x10-6) were annotated using EpiMap data. Low input whole genome promoter CHi-C (PCHi-C) was performed on CD4+ T-cells isolated from blood from 3 JIA oligoarthritis patients, and data was analysed using CHiCAGO. We employed CRISPR activation (CRISPRa) and CRISPR interference (CRISPRi) in Jurkats to assess whether prioritized JIA variants are capable of regulating the expression of the interacting genes. Results 614 SNPs (out of 735) were found to overlap active enhancers in CD4+ T-cells, and were prioritized for further analysis. We identified numerous significant chromatin interactions in 19 out of 44 non-MHC JIA associated loci, linking JIA SNPs mapping to T-cell enhancers to a total of 61 target genes and revealing potential novel disease pathways. A JIA-associated locus on chromosome 3 contains 39 SNPs. It maps to an intergenic region and the causal gene/s are unclear. Our PCHi-C data revealed that this JIA locus presents chromatin interactions with the promoters of several genes, such as CCRL2, CCR2, CCR3 and CCR5. Two variants were selected for further analysis: rs79815064, which had the highest posterior probability, and rs8005404, the only variant within a CD4+ T-cell enhancer linked to surrounding gene activity. When both SNPs were targeted with CRISPRa and CRISPRi, we observed an increased and decreased expression, respectively, of CCRL2, CCR2, CCR3 and CCR5, confirming their role in disease. These genes belong to the chemokine receptor family and are important regulators of the inflammatory response. Conclusion Our work shows how functional genomics can help identify biological mechanisms by which GWAS variants increase risk of JIA, which in turn will benefit patients through personalised medicine and the identification of therapeutic targets. Disclosure A. Frantzeskos: None. V. Malysheva: None. C. Shi: None. J. Ding: None. J. Bowes: None. W. Thomson: None. S. Eyre: None. M. Spivakov: Shareholder/stock ownership; M.S. is co-founder and shareholder of Enhanc3D Genomics Ltd. G. Orozco: None.
MYC target genes as determined by the analysis of publically available ChIP-seq profiles and defined by the association of the MACS peaks (p value threshold = −30) with the TSS of genes using a 10-kb distance as an association criterion. (XLS 199 kb)
SUMMARY The ongoing pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is currently affecting millions of lives worldwide. Large retrospective studies indicate that an elevated level of inflammatory cytokines and pro-inflammatory factors are associated with both increased disease severity and mortality. Here, using multidimensional epigenetic, transcriptional, in vitro and in vivo analyses, we report that Topoisomerase 1 (Top1) inhibition suppresses lethal inflammation induced by SARS-CoV-2. Therapeutic treatment with two doses of Topotecan (TPT), a FDA-approved Top1 inhibitor, suppresses infection-induced inflammation in hamsters. TPT treatment as late as four days post-infection reduces morbidity and rescues mortality in a transgenic mouse model. These results support the potential of Top1 inhibition as an effective host-directed therapy against severe SARS-CoV-2 infection. TPT and its derivatives are inexpensive clinical-grade inhibitors available in most countries. Clinical trials are needed to evaluate the efficacy of repurposing Top1 inhibitors for COVID-19 in humans.
Abstract Gene enhancers often form long-range contacts with promoters, but it remains unclear if enhancer activity and their chromosomal contacts are mediated by the same DNA sequences and recruited factors. We studied the effects of expression quantitative trait loci (eQTLs) on enhancer activity and promoter contacts in primary monocytes isolated from 34 individuals. Using eQTL-Capture Hi-C and a Bayesian approach considering both intra- and inter-individual variation, we initially detected 19 eQTLs associated with enhancer-eGene promoter contacts, most of which also associated with enhancer accessibility and activity. Capitalising on these shared effects, we devised a multi-modality Bayesian strategy, which identified 629 “trimodal QTLs” jointly associated with enhancer accessibility, eGene promoter contact, and gene expression. Causal mediation analysis and CRISPR interference revealed causal relationships between these three modalities. Many detected QTLs overlapped disease susceptibility loci and influenced the predicted binding of myeloid transcription factors, including SPI1, GABPB and STAT3. Additionally, a variant associated with PCK2 promoter contact directly disrupted a CTCF binding motif and impacted promoter insulation from downstream enhancers. Jointly, our findings suggest an inherent genetic link between the activity and connectivity of enhancers with relevance for human disease, and highlight the role of genetically-determined chromatin boundaries in gene control.
Abstract Innate lymphoid cells (ILCs) are rare tissue-resident “helper” lymphocytes that do not express diversified antigen receptors. Type 3 ILCs (ILC3s) are an important class of these cells enriched in the respiratory and intestinal mucosa, where they regulate inflammation and mucosal homeostasis. To gain insight into the cis-regulatory circuitries underlying ILC3 function, we used high-resolution Capture Hi-C to profile promoter-anchored chromosomal contacts in human primary ILC3s. Combining significant interaction detection with the Activity-By-Contact approach adapted to Capture Hi-C, we reveal a multitude of contacts between promoters and distal regulatory elements and obtain evidence for distinct regulatory wiring of alternative promoters. We find that promoter-interacting regions in ILC3s are enriched for genetic variants associated with multiple immune diseases. Focusing on Crohn’s disease (CD), in which ILC3s are established mediators, we devised a Bayesian approach that incorporates multivariate fine-mapping to link CD-associated genetic variants with putative target genes. We identify known and previously unimplicated genes in conferring genetic risk of CD through activity in ILC3s. This includes the C LN3 gene that is mutated in most cases of the neurodegenerative disorder Batten disease. Using Cln3 mutant mice, we show that CLN3 is a putative negative regulator of IL-17 production in an inflammatory subset of ILC3s. This finding suggests a functional role for CLN3 in ILC3 biology, with mechanistic implications for Crohn’s and Batten diseases.
Proximity ligation-mediated methods are essential to study the impact of three-dimensional chromatin organization on gene programming. Albeit significant progress has been made in the development of computational tools that assess long-range chromatin interactions, next to nothing is known about the quality of the generated datasets. We have developed LOGIQA ( www.ngs-qc.org/logiqa ), a database hosting quality scores for long-range genome interaction assays, accessible through a user-friendly web-based environment. Currently, LOGIQA harbors QC scores for >900 datasets, which provides a global view of their relative quality and reveals the impact of genome size, coverage and other technical aspects. LOGIQA provides a user-friendly dataset query panel and a genome viewer to assess local genome-interaction maps at different resolution and quality-assessment conditions. LOGIQA is the first database hosting quality scores dedicated to long-range chromatin interaction assays, which in addition provides a platform for visualizing genome interactions made available by the scientific community.
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