Genetic perturbation of PU.1 binding and chromatin looping at neutrophil enhancers associates with autoimmune disease

The Predictive Value of Neutrophil Extracellular Trap-Related Risk Score in Prognosis and Immune Microenvironment of Colorectal Cancer Patients

Colorectal cancer (CRC) has brought great healthy burden for patients. Neutrophil extracellular traps (NETs) have been explored in several tumors, while it remains largely unclear in CRC. CRC-related data were downloaded from Cancer Genome Atlas and Gene Expression Omnibus databases. Then, a NET risk score was built after univariate Cox and LASSO Cox regression analysis. Prognostic value was evaluated via survival analysis, stratification analysis, and ROC analysis. The functional enrichment analysis was conducted basing on bulk and scRNA-seq data. The immune landscape difference was analyzed using CIBERSORT, XCell, and MCPcounter portals. NET risk score was built for CRC patients, basing on G0S2, HIST1H2BC, CRISPLD2, and IL17A. In TCGA-CRC and validation datasets, regardless of age or gender, high-risk CRC patients had significantly worse prognosis, besides higher NET risk score was mainly found in samples with MSI-H and advanced T, N, and M stages. Employing multiple databases, we noticed that M0 and M2 Macrophages infiltrated the most in high-risk CRC patients, besides M2 Macrophages and neutrophils showed positive correlation with NET risk score. A novel reliable prognostic NET risk score was developed for CRC patients, and high-risk patients had unfavorable prognosis with advanced disease status.

Chromatin changes associated with neutrophil extracellular trap formation in whole blood reflect complex immune signaling

Background

Neutrophils are key players in innate immunity, forming neutrophil extracellular traps (NETs) to defend against infections. However, excess NET formation is implicated in inflammatory conditions such as sepsis and immunothrombosis. Studying NET formation in isolated neutrophils provides important mechanistic insights but does not reflect the complexity of immune interactions in whole blood, limiting our understanding of neutrophil responses.

Methods

This study investigates chromatin accessibility changes using Assay for Transposase-Accessible Chromatin with sequencing (ATAC-Seq) during phorbol 12-myristate 13-acetate (PMA) induced NET formation in whole blood. We compared chromatin accessibility patterns in neutrophils following PMA treatment in isolation and whole blood to assess the impact of other immune cells and signaling environment.

Results

Whole blood PMA stimulation elicited consistent chromatin accessibility changes across donors, demonstrating organized chromatin decondensation during NET formation. The chromatin response was characterized by increased accessibility in genomic regions enriched for immune-specific pathways, highlighting the role of immune cell interactions in NET formation. Differentially accessible regions (DARs) present following PMA induction in whole blood and isolated neutrophils showed greater association with NET-related and inflammatory transcription factors, while DARs specific to isolated neutrophils showed fewer relevant motifs. Pathway analysis indicated that whole blood responses involved more robust activation of immune-specific pathways, such as interleukin and cytokine signaling, compared to isolated neutrophils.

Conclusions

Our findings underscore the importance of studying NET formation within a whole blood environment to capture the complexity of neutrophil responses and immune cell interactions. This understanding is crucial for identifying effective therapeutic targets in NET-associated inflammatory diseases.

Investigating the shared genetic structure between rheumatoid arthritis and stroke

BACKGROUND

Rheumatoid arthritis (RA) increases the risk of stroke. However, the relationship between RA and stroke remains unclear. This study aimed to explore the shared genetics architecture (i.e., common genetic basis between different traits, diseases, or phenotypes) of RA and stroke, aiming to improve the intervention and management of patients with RA and stroke.

METHODS

Pooled statistics from publicly available genome-wide association studies for RA (8,255 cases and 409,001 controls) and stroke (43,132 cases and 43,132 controls) were used. A genome-wide positive association was conducted to (examine the comprehensive effects of genetic variants on a particular trait, disease, or phenotype at the genome-wide scale). Local genetic correlation studies used linkage disequilibrium score regression and super genetic covariance analyzer. Single nucleotide polymorphisms (SNPs) at risk were identified using genome-wide association study multiple trait analysis and PLINK software (Psnp <5e-08), followed by functional localization and annotation using Functional Mapping and Annotation of Genome-Wide Association Studies to identify specific genes and genetic variants that may contribute to the disease. Finally, a transcriptome-wide association study explored the relationship between genes and their association with RA risk.

RESULTS

A genome-wide significant positive correlation was evident between RA and stroke (genetic correlation = 0.3756). Among the localized genomic regions, the correlation between RA and stroke in the region of chr2:201572564-202,829,668 was the most significant (p = 0.0015). We identified 179 significant SNPs and five common risk genes for RA and stroke (IRF5, RNASET2, ZNF438, UBE2LS, and SYNGR1). These genes are involved in the immune-inflammatory pathway.

CONCLUSIONS

The findings suggest a shared genetic structure between RA and stroke. These findings may provide new insights into RA and stroke pathogenesis, and contribute to the development of new diagnostic markers and therapeutic targeted drugs to improve the clinical outcomes of patients with RA and stroke.

The GATA-3-dependent transcriptome and tumor microenvironment are regulated by eIF4E and XPO1 in T-cell lymphomas

ABSTRACT

The transcription factor GATA-binding protein 3 (GATA-3) and the transcriptional program it regulates have emerged as oncogenic drivers across diverse T-cell lymphomas (TCLs), many of which are resistant to conventional chemotherapeutic agents and characterized by recurrent losses of key tumor suppressor genes, including TP53 and PTEN, both of which are clients of the nuclear export protein XPO1. Here, we demonstrated that XPO1 is highly expressed by malignant T cells expressing GATA-3 and by lymphoma-associated macrophages (LAMs) within their tumor microenvironment (TME). Using complementary genetically engineered mouse models, we demonstrated that TP53- and/or phosphate and tensin homolog (PTEN)-deficient TCLs, and LAMs within their TME, are sensitive to the selective exportin-1 (XPO1) antagonist selinexor. In an effort to identify TP53- and PTEN-independent mechanisms, we used complementary and orthogonal approaches to investigate the role of eIF4E and XPO1-dependent messenger RNA nuclear export in these TCLs. We identified a novel role for eIF4E/XPO1 in exporting GATA-3 and GATA-3-dependent transcripts from the nucleus in TCLs, and in the export of therapeutically relevant transcripts, including colony-stimulating factor-1 receptor, from LAMs. Therefore, XPO1 antagonism, by impairing oncogenic transcriptional programs in TCLs and depleting LAMs from their TME, is a novel approach to target 2 independent dependencies in a group of therapeutically challenging TCLs.

Genetic coupling of enhancer activity and connectivity in gene expression control

Gene enhancers often form long-range contacts with promoters, but it remains unclear if the activity of enhancers and their chromosomal contacts are mediated by the same DNA sequences and recruited factors. Here, we study the effects of expression quantitative trait loci (eQTLs) on enhancer activity and promoter contacts in primary monocytes isolated from 34 male individuals. Using eQTL-Capture Hi-C and a Bayesian approach considering both intra- and inter-individual variation, we initially detect 19 eQTLs associated with enhancer-eGene promoter contacts, most of which also associate with enhancer accessibility and activity. Capitalising on these shared effects, we devise a multi-modality Bayesian strategy, identifying 629 "trimodal QTLs" jointly associated with enhancer accessibility, eGene promoter contact, and gene expression. Causal mediation analysis and CRISPR interference reveal causal relationships between these three modalities. Many detected QTLs overlap disease susceptibility loci and influence the predicted binding of myeloid transcription factors, including SPI1, GABPB and STAT3. Additionally, a variant associated with PCK2 promoter contact directly disrupts a CTCF binding motif and impacts promoter insulation from downstream enhancers. Jointly, our findings suggest an inherent genetic coupling of enhancer activity and connectivity in gene expression control relevant to human disease and highlight the regulatory role of genetically determined chromatin boundaries.

Redistribution of PU.1 partner transcription factor RUNX1 binding secures cell survival during leukemogenesis

Transcription factors (TFs) orchestrating lineage-development often control genes required for cellular survival. However, it is not well understood how cells survive when such TFs are lost, for example in cancer. PU.1 is an essential TF for myeloid fate, and mice with downregulated PU.1 levels develop acute myeloid leukemia (AML). Combining a multi-omics approach with a functional genetic screen, we reveal that PU.1-downregulated cells fundamentally change their survival control from cytokine-driven pathways to overexpression of an autophagy-predominated stem cell gene program, for which we also find evidence in human AML. Control of this program involves redirected chromatin occupancy of the PU.1 partner TF Runx1 to a lineage-inappropriate binding site repertoire. Hence, genomic reallocation of TF binding upon loss of a partner TF can act as a pro-oncogenic failsafe mechanism by sustaining cell survival during leukemogenesis.

Robust estimation of cancer and immune cell-type proportions from bulk tumor ATAC-Seq data

Assay for Transposase-Accessible Chromatin sequencing (ATAC-Seq) is a widely used technique to explore gene regulatory mechanisms. For most ATAC-Seq data from healthy and diseased tissues such as tumors, chromatin accessibility measurement represents a mixed signal from multiple cell types. In this work, we derive reliable chromatin accessibility marker peaks and reference profiles for most non-malignant cell types frequently observed in the microenvironment of human tumors. We then integrate these data into the EPIC deconvolution framework (Racle et al., 2017) to quantify cell-type heterogeneity in bulk ATAC-Seq data. Our EPIC-ATAC tool accurately predicts non-malignant and malignant cell fractions in tumor samples. When applied to a human breast cancer cohort, EPIC-ATAC accurately infers the immune contexture of the main breast cancer subtypes.

Translation of genome-wide association study: from genomic signals to biological insights

Since the turn of the 21st century, genome-wide association study (GWAS) have successfully identified genetic signals associated with a myriad of common complex traits and diseases. As we transition from establishing robust genetic associations with diverse phenotypes, the central challenge is now focused on characterizing the underlying functional mechanisms driving these signals. Previous GWAS efforts have revealed multiple variants, each conferring relatively subtle susceptibility, collectively contributing to the pathogenesis of various common diseases. Such variants can further exhibit associations with multiple other traits and differ across ancestries, plus disentangling causal variants from non-causal due to linkage disequilibrium complexities can lead to challenges in drawing direct biological conclusions. Combined with cellular context considerations, such challenges can reduce the capacity to definitively elucidate the biological significance of GWAS signals, limiting the potential to define mechanistic insights. This review will detail current and anticipated approaches for functional interpretation of GWAS signals, both in terms of characterizing the underlying causal variants and the corresponding effector genes.

Identifying genetic variants associated with chromatin looping and genome function

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

Non-coding variants impact cis-regulatory coordination in a cell type-specific manner

BACKGROUND

Interactions among cis-regulatory elements (CREs) play a crucial role in gene regulation. Various approaches have been developed to map these interactions genome-wide, including those relying on interindividual epigenomic variation to identify groups of covariable regulatory elements, referred to as chromatin modules (CMs). While CM mapping allows to investigate the relationship between chromatin modularity and gene expression, the computational principles used for CM identification vary in their application and outcomes.

RESULTS

We comprehensively evaluate and streamline existing CM mapping tools and present guidelines for optimal utilization of epigenome data from a diverse population of individuals to assess regulatory coordination across the human genome. We showcase the effectiveness of our recommended practices by analyzing distinct cell types and demonstrate cell type specificity of CRE interactions in CMs and their relevance for gene expression. Integration of genotype information revealed that many non-coding disease-associated variants affect the activity of CMs in a cell type-specific manner by affecting the binding of cell type-specific transcription factors. We provide example cases that illustrate in detail how CMs can be used to deconstruct GWAS loci, assess variable expression of cell surface receptors in immune cells, and reveal how genetic variation can impact the expression of prognostic markers in chronic lymphocytic leukemia.

CONCLUSIONS

Our study presents an optimal strategy for CM mapping and reveals how CMs capture the coordination of CREs and its impact on gene expression. Non-coding genetic variants can disrupt this coordination, and we highlight how this may lead to disease predisposition in a cell type-specific manner.

Reprogramming of 3D genome structure underlying HSPC development in zebrafish

BACKGROUND

Development of hematopoietic stem and progenitor cells (HSPC) is a multi-staged complex process that conserved between zebrafish and mammals. Understanding the mechanism underlying HSPC development is a holy grail of hematopoietic biology, which is helpful for HSPC clinical application. Chromatin conformation plays important roles in transcriptional regulation and cell fate decision; however, its dynamic and role in HSPC development is poorly investigated.

METHODS

We performed chromatin structure and multi-omics dissection across different stages of HSPC developmental trajectory in zebrafish for the first time, including Hi-C, RNA-seq, ATAC-seq, H3K4me3 and H3K27ac ChIP-seq.

RESULTS

The chromatin organization of zebrafish HSPC resemble mammalian cells with similar hierarchical structure. We revealed the multi-scale reorganization of chromatin structure and its influence on transcriptional regulation and transition of cell fate during HSPC development. Nascent HSPC is featured by loose conformation with obscure structure at all layers. Notably, PU.1 was identified as a potential factor mediating formation of promoter-involved loops and regulating gene expression of HSPC.

CONCLUSIONS

Our results provided a global view of chromatin structure dynamics associated with development of zebrafish HSPC and discovered key transcription factors involved in HSPC chromatin interactions, which will provide new insights into the epigenetic regulatory mechanisms underlying vertebrate HSPC fate decision.

Hi-C, a chromatin 3D structure technique advancing the functional genomics of immune cells

The functional performance of immune cells relies on a complex transcriptional regulatory network. The three-dimensional structure of chromatin can affect chromatin status and gene expression patterns, and plays an important regulatory role in gene transcription. Currently available techniques for studying chromatin spatial structure include chromatin conformation capture techniques and their derivatives, chromatin accessibility sequencing techniques, and others. Additionally, the recently emerged deep learning technology can be utilized as a tool to enhance the analysis of data. In this review, we elucidate the definition and significance of the three-dimensional chromatin structure, summarize the technologies available for studying it, and describe the research progress on the chromatin spatial structure of dendritic cells, macrophages, T cells, B cells, and neutrophils.

Evolutionary dynamics of tipifarnib in HRAS mutated head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a highly prevalent malignancy worldwide, with a significant proportion of patients developing recurrent and/or metastatic (R/M) disease. Despite recent advances in therapy, the prognosis for patients with advanced HNSCC remains poor. Here, we present the case of a patient with recurrent metastatic HNSCC harboring an HRAS G12S mutation who achieved a durable response to treatment with tipifarnib, a selective inhibitor of farnesyltransferase. The patient was a 48-year-old woman who had previously received multiple lines of therapy with no significant clinical response. However, treatment with tipifarnib resulted in a durable partial response that lasted 8 months. Serial genomic and transcriptomic analyses demonstrated upregulation of YAP1 and AXL in metastatic lesions compared with the primary tumor, the evolution of the tumor microenvironment from an immune-enriched to a fibrotic subtype with increased angiogenesis, and activation of the PI3K/AKT/mTOR pathway in tipifarnib treatment. Lastly, in HRAS-mutated PDXs and in the syngeneic HRAS model, we demonstrated that tipifarnib efficacy is limited by activation of the AKT pathway, and dual treatment with tipifarnib and the PI3K inhibitor, BYL719, resulted in enhanced anti-tumor efficacy. Our case study highlights the potential of targeting HRAS mutations with tipifarnib in R/M HNSCC and identifies potential mechanisms of acquired resistance to tipifarnib, along with immuno-, chemo-, and radiation therapy. Preclinical results provide a firm foundation for further investigation of drug combinations of HRAS-and PI3K -targeting therapeutics in R/M HRAS-driven HNSCC.

Transcription factor-binding k-mer analysis clarifies the cell type dependency of binding specificities and cis-regulatory SNPs in humans

BACKGROUND

Transcription factors (TFs) exhibit heterogeneous DNA-binding specificities in individual cells and whole organisms under natural conditions, and de novo motif discovery usually provides multiple motifs, even from a single chromatin immunoprecipitation-sequencing (ChIP-seq) sample. Despite the accumulation of ChIP-seq data and ChIP-seq-derived motifs, the diversity of DNA-binding specificities across different TFs and cell types remains largely unexplored.

RESULTS

Here, we applied MOCCS2, our k-mer-based motif discovery method, to a collection of human TF ChIP-seq samples across diverse TFs and cell types, and systematically computed profiles of TF-binding specificity scores for all k-mers. After quality control, we compiled a set of TF-binding specificity score profiles for 2,976 high-quality ChIP-seq samples, comprising 473 TFs and 398 cell types. Using these high-quality samples, we confirmed that the k-mer-based TF-binding specificity profiles reflected TF- or TF-family dependent DNA-binding specificities. We then compared the binding specificity scores of ChIP-seq samples with the same TFs but with different cell type classes and found that half of the analyzed TFs exhibited differences in DNA-binding specificities across cell type classes. Additionally, we devised a method to detect differentially bound k-mers between two ChIP-seq samples and detected k-mers exhibiting statistically significant differences in binding specificity scores. Moreover, we demonstrated that differences in the binding specificity scores between k-mers on the reference and alternative alleles could be used to predict the effect of variants on TF binding, as validated by in vitro and in vivo assay datasets. Finally, we demonstrated that binding specificity score differences can be used to interpret disease-associated non-coding single-nucleotide polymorphisms (SNPs) as TF-affecting SNPs and provide candidates responsible for TFs and cell types.

CONCLUSIONS

Our study provides a basis for investigating the regulation of gene expression in a TF-, TF family-, or cell-type-dependent manner. Furthermore, our differential analysis of binding-specificity scores highlights noncoding disease-associated variants in humans.

Blood cell traits' GWAS loci colocalization with variation in PU.1 genomic occupancy prioritizes causal noncoding regulatory variants

Genome-wide association studies (GWASs) have uncovered numerous trait-associated loci across the human genome, most of which are located in noncoding regions, making interpretation difficult. Moreover, causal variants are hard to statistically fine-map at many loci because of widespread linkage disequilibrium. To address this challenge, we present a strategy utilizing transcription factor (TF) binding quantitative trait loci (bQTLs) for colocalization analysis to identify trait associations likely mediated by TF occupancy variation and to pinpoint likely causal variants using motif scores. We applied this approach to PU.1 bQTLs in lymphoblastoid cell lines and blood cell trait GWAS data. Colocalization analysis revealed 69 blood cell trait GWAS loci putatively driven by PU.1 occupancy variation. We nominate PU.1 motif-altering variants as the likely shared causal variants at 51 loci. Such integration of TF bQTL data with other GWAS data may reveal transcriptional regulatory mechanisms and causal noncoding variants underlying additional complex traits.

Understanding the evolution of immune genes in jawed vertebrates

Driven by co-evolution with pathogens, host immunity continuously adapts to optimize defence against pathogens within a given environment. Recent advances in genetics, genomics and transcriptomics have enabled a more detailed investigation into how immunogenetic variation shapes the diversity of immune responses seen across domestic and wild animal species. However, a deeper understanding of the diverse molecular mechanisms that shape immunity within and among species is still needed to gain insight into-and generate evolutionary hypotheses on-the ultimate drivers of immunological differences. Here, we discuss current advances in our understanding of molecular evolution underpinning jawed vertebrate immunity. First, we introduce the immunome concept, a framework for characterizing genes involved in immune defence from a comparative perspective, then we outline how immune genes of interest can be identified. Second, we focus on how different selection modes are observed acting across groups of immune genes and propose hypotheses to explain these differences. We then provide an overview of the approaches used so far to study the evolutionary heterogeneity of immune genes on macro and microevolutionary scales. Finally, we discuss some of the current evidence as to how specific pathogens affect the evolution of different groups of immune genes. This review results from the collective discussion on the current key challenges in evolutionary immunology conducted at the ESEB 2021 Online Satellite Symposium: Molecular evolution of the vertebrate immune system, from the lab to natural populations.

Identification of potential biomarkers for ankylosing spondylitis based on bioinformatics analysis

OBJECTIVE

The aim of this study was to search for key genes in ankylosing spondylitis (AS) through comprehensive bioinformatics analysis, thus providing some theoretical support for future diagnosis and treatment of AS and further research.

METHODS

Gene expression profiles were collected from Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/ ) by searching for the term "ankylosing spondylitis". Ultimately, two microarray datasets (GSE73754 and GSE11886) were downloaded from the GEO database. A bioinformatic approach was used to screen differentially expressed genes and perform functional enrichment analysis to obtain biological functions and signalling pathways associated with the disease. Weighted correlation network analysis (WGCNA) was used to further obtain key genes. Immune infiltration analysis was performed using the CIBERSORT algorithm to conduct a correlation analysis of key genes with immune cells. The GWAS data of AS were analysed to identify the pathogenic regions of key genes in AS. Finally, potential therapeutic agents for AS were predicted using these key genes.

RESULTS

A total of 7 potential biomarkers were identified: DYSF, BASP1, PYGL, SPI1, C5AR1, ANPEP and SORL1. ROC curves showed good prediction for each gene. T cell, CD4 naïve cell, and neutrophil levels were significantly higher in the disease group than in the paired normal group, and key gene expression was strongly correlated with immune cells. CMap results showed that the expression profiles of ibuprofen, forskolin, bongkrek-acid, and cimaterol showed the most significant negative correlation with the expression profiles of disease perturbations, suggesting that these drugs may play a role in AS treatment.

CONCLUSION

The potential biomarkers of AS screened in this study are closely related to the level of immune cell infiltration and play an important role in the immune microenvironment. This may provide help in the clinical diagnosis and treatment of AS and provide new ideas for further research.

Colocalization of blood cell traits GWAS associations and variation in PU.1 genomic occupancy prioritizes causal noncoding regulatory variants

Genome-wide association studies (GWAS) have uncovered numerous trait-associated loci across the human genome, most of which are located in noncoding regions, making interpretations difficult. Moreover, causal variants are hard to statistically fine-map at many loci because of widespread linkage disequilibrium. To address this challenge, we present a strategy utilizing transcription factor (TF) binding quantitative trait loci (bQTLs) for colocalization analysis to identify trait associations likely mediated by TF occupancy variation and to pinpoint likely causal variants using motif scores. We applied this approach to PU.1 bQTLs in lymphoblastoid cell lines and blood cell traits GWAS data. Colocalization analysis revealed 69 blood cell trait GWAS loci putatively driven by PU.1 occupancy variation. We nominate PU.1 motif-altering variants as the likely shared causal variants at 51 loci. Such integration of TF bQTL data with other GWAS data may reveal transcriptional regulatory mechanisms and causal noncoding variants underlying additional complex traits.

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.

3D genome alterations in T cells associated with disease activity of systemic lupus erythematosus

OBJECTIVES

Three-dimensional (3D) genome alterations can dysregulate gene expression by rewiring physical interactions within chromosomes in a tissue-specific or cell-specific manner and lead to diseases. We aimed to elucidate the 3D genome structure and its role in gene expression networks dysregulated in systemic lupus erythematosus (SLE).

METHODS

We performed Hi-C experiments using CD4+ T cells from 7 patients with SLE and 5 age-matched and sex-matched healthy controls (HCs) combined with RNA sequencing analysis. Further integrative analyses, including transcription factor motif enrichment, SPI1 knockdown and histone modifications (H3K27ac, H3K4me1, H3K4me3), were performed for altered loop-associated gene loci in SLE.

RESULTS

We deciphered the 3D chromosome organisation in T cells of patients with SLE and found it was clearly distinct from that of HCs and closely associated with the disease activity of SLE. Importantly, we identified loops within chromosomes associated with the disease activity of SLE and differentially expressed genes and found some key histone modifications close to these loops. Moreover, we demonstrated the contribution of the transcription factor SPI1, whose motif is located in the altered loop in SLE, to the overexpression of interferon pathway gene. In addition, we identified the potential influences of genetic variations in 3D genome alterations in SLE.

CONCLUSIONS

Our results highlight the 3D genome structure alterations associated with SLE development and provide a foundation for future interrogation of the relationships between chromosome structure and gene expression control in SLE.

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

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

Diagnostic and therapeutic potential of RNASET2 in Crohn's disease: Disease-risk polymorphism modulates allelic-imbalance in expression and circulating protein levels and recombinant-RNASET2 attenuates pro-inflammatory cytokine secretion

Ribonuclease T2 gene (RNASET2) variants are associated in genome wide association studies (GWAS) with risk for several autoimmune diseases, including Crohn's disease (CD). In T cells, a functional and biological relationship exists between TNFSF15-mediated enhancement of IFN-γ production, mucosal inflammation and RNASET2. Disease risk variants are associated with decreased mRNA expression and clinical characteristics of severe CD; however, functional classifications of variants and underlying molecular mechanisms contributing to pathogenesis remain largely unknown. In this study we demonstrate that allelic imbalance of RNASET2 disease risk variant rs2149092 is associated with transcriptional and post-transcriptional mechanisms regulating transcription factor binding, promoter-transactivation and allele-specific expression. RNASET2 mRNA expression decreases in response to multiple modes of T cell activation and recovers following elimination of activator. In CD patients with severe disease necessitating surgical intervention, preoperative circulating RNASET2 protein levels were decreased compared to non-IBD subjects and rebounded post-operatively following removal of the inflamed region, with levels associated with allelic carriage. Furthermore, overexpression or treatment with recombinant RNASET2 significantly reduced IFN-γ secretion. These findings reveal that RNASET2 cis- and trans-acting variation contributed regulatory complexity and determined expression and provide a basis for linking genetic variation with CD pathobiology. These data may ultimately identify RNASET2 as an effective therapeutic target in a subset of CD patients with severe disease.

The role of a key transcription factor PU.1 in autoimmune diseases

PU.1, a transcription factor member of the E26 transformation-specific family, affects the function of a variety of immune cells in several physiological and pathological conditions. Previous studies studying the role of PU.1 in pathological conditions have mainly focused on immune system-related cancers, and a series of articles have confirmed that PU.1 mutation can induce a variety of immune cell-related malignancies. The underlying mechanism has also been extensively validated. However, the role of PU.1 in other major immune system-related diseases, namely, systemic autoimmune diseases, is still unclear. It was only in recent years that researchers began to gradually realize that PU.1 also played an important role in a variety of autoimmune diseases, such as rheumatoid arthritis (RA), experimental autoimmune encephalomyelitis (EAE) and systemic lupus erythematosus (SLE). This review article summarizes the findings of recent studies that investigated the role of PU.1 in various autoimmune diseases and the related underlying mechanisms. Furthermore, it presents new ideas and provides insight into the role of PU.1 as a potential treatment target for autoimmune diseases and highlights existing research problems and future research directions in related fields.

A novel neutrophil extracellular trap signature to predict prognosis and immunotherapy response in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignant cancers, and patients with HNSCC possess early metastases and poor prognosis. Systematic therapies (including chemotherapy, targeted therapy, and immunotherapy) are generally applied in the advanced/late stages of HNSCC, but primary and acquired resistance eventually occurs. At present, reliable biomarkers to predict the prognosis of HNSCC have not been completely identified. Recent studies have shown that neutrophil extracellular traps (NETs) are implicated in cancer progression, metastasis and cancer immune response, and NET-related gene signatures are associated with the prognosis of patients with several human cancers. To explore whether NET-related genes play crucial roles in HNSCC, we have performed systematic analysis and reported several findings in the current study. Firstly, we identified seven novel NET-related genes and developed a NET-score signature, which was highly associated with the clinicopathological and immune traits of the HNSCC patients. Then, we, for the first time, found that NIFK was significantly upregulated in HNSCC patient samples, and its levels were significantly linked to tumor malignancy and immune status. Moreover, functional experiments confirmed that NIFK was required for HNSCC cell proliferation and metastasis. Altogether, this study has identified a novel NET-score signature based on seven novel NET-related genes to predict the prognosis of HNSCC and NIFK has also explored a new method for personalized chemo-/immuno-therapy of HNSCC.

Evolutionary gain and loss of a pathological immune response to parasitism

Parasites impose fitness costs on their hosts. Biologists often assume that natural selection favors infection-resistant hosts. Yet, when the immune response itself is costly, theory suggests that selection may sometimes favor loss of resistance, which may result in alternative stable states where some populations are resistant and others are tolerant. Intraspecific variation in immune costs is rarely surveyed in a manner that tests evolutionary patterns, and there are few examples of adaptive loss of resistance. Here, we show that when marine threespine stickleback colonized freshwater lakes, they gained resistance to the freshwater-associated cestode Schistocephalus solidus. Extensive peritoneal fibrosis and inflammation are a commonly observed phenotype that contributes to suppression of cestode growth and viability but also imposes a substantial cost on fecundity. Combining genetic mapping and population genomics, we find that opposing selection generates immune system differences between tolerant and resistant populations, consistent with divergent optimization.

Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebase

Investigator-generated transcriptomic datasets interrogating circulating immune cell (CIC) gene expression in clinical type 1 diabetes (T1D) have underappreciated re-use value. Here, we repurposed these datasets to create an open science environment for the generation of hypotheses around CIC signaling pathways whose gain or loss of function contributes to T1D pathogenesis. We firstly computed sets of genes that were preferentially induced or repressed in T1D CICs and validated these against community benchmarks. We then inferred and validated signaling node networks regulating expression of these gene sets, as well as differentially expressed genes in the original underlying T1D case:control datasets. In a set of three use cases, we demonstrated how informed integration of these networks with complementary digital resources supports substantive, actionable hypotheses around signaling pathway dysfunction in T1D CICs. Finally, we developed a federated, cloud-based web resource that exposes the entire data matrix for unrestricted access and re-use by the research community.

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Re-use of transcriptomic type 1 diabetes (T1D) circulating immune cells (CICs) datasets

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We generated transcriptional regulatory networks for T1D CICs

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Use cases generate substantive hypotheses around signaling pathway dysfunction in T1D CICs

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Networks are freely accessible on the web for re-use by the research community

Genetic associations at regulatory phenotypes improve fine-mapping of causal variants for 12 immune-mediated diseases

The resolution of causal genetic variants informs understanding of disease biology. We used regulatory quantitative trait loci (QTLs) from the BLUEPRINT, GTEx and eQTLGen projects to fine-map putative causal variants for 12 immune-mediated diseases. We identify 340 unique loci that colocalize with high posterior probability (≥98%) with regulatory QTLs and apply Bayesian frameworks to fine-map associations at each locus. We show that fine-mapping credible sets derived from regulatory QTLs are smaller compared to disease summary statistics. Further, they are enriched for more functionally interpretable candidate causal variants and for putatively causal insertion/deletion (INDEL) polymorphisms. Finally, we use massively parallel reporter assays to evaluate candidate causal variants at the ITGA4 locus associated with inflammatory bowel disease. Overall, our findings suggest that fine-mapping applied to disease-colocalizing regulatory QTLs can enhance the discovery of putative causal disease variants and enhance insights into the underlying causal genes and molecular mechanisms.

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.

Current Understanding of the Neutrophil Transcriptome in Health and Disease

Neutrophils are key cells of the innate immune system. It is now understood that this leukocyte population is diverse in both the basal composition and functional plasticity. Underlying this plasticity is a post-translational framework for rapidly achieving early activation states, but also a transcriptional capacity that is becoming increasingly recognized by immunologists. Growing interest in the contribution of neutrophils to health and disease has resulted in more efforts to describe their transcriptional activity. Whilst initial efforts focused predominantly on understanding the existing biology, investigations with advanced methods such as single cell RNA sequencing to understand interactions of the entire immune system are revealing higher flexibility in neutrophil transcription than previously thought possible and multiple transition states. It is now apparent that neutrophils utilise many forms of RNA in the regulation of their function. This review collates current knowledge on the nuclei structure and gene expression activity of human neutrophils across homeostasis and disease, before highlighting knowledge gaps that are research priority areas.