TCF1-LEF1 co-expression identifies a multipotent progenitor cell (TH2-MPP) across human allergic diseases.

Repetitive exposure to antigen in chronic infection and cancer drives T cell exhaustion, limiting adaptive immunity. In contrast, aberrant, sustained T cell responses can persist over decades in human allergic disease. To understand these divergent outcomes, we employed bioinformatic, immunophenotyping and functional approaches with human diseased tissues, identifying an abundant population of type 2 helper T (TH2) cells with co-expression of TCF7 and LEF1, and features of chronic activation. These cells, which we termed TH2-multipotent progenitors (TH2-MPP) could self-renew and differentiate into cytokine-producing effector cells, regulatory T (Treg) cells and follicular helper T (TFH) cells. Single-cell T-cell-receptor lineage tracing confirmed lineage relationships between TH2-MPP, TH2 effectors, Treg cells and TFH cells. TH2-MPP persisted despite in vivo IL-4 receptor blockade, while thymic stromal lymphopoietin (TSLP) drove selective expansion of progenitor cells and rendered them insensitive to glucocorticoid-induced apoptosis in vitro. Together, our data identify TH2-MPP as an aberrant T cell population with the potential to sustain type 2 inflammation and support the paradigm that chronic T cell responses can be coordinated over time by progenitor cells.

Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes.

Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction1. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity1,2. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments.

History of tuberculosis disease is associated with genetic regulatory variation in Peruvians.

A quarter of humanity is estimated to have been exposed to Mycobacterium tuberculosis (Mtb) with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to Mtb infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs). We recruited former household contacts of TB patients who previously progressed to TB (cases, n = 63) or did not progress to TB (controls, n = 63). Transcriptomic profiling of monocyte-derived DCs and macrophages measured the impact of genetic variants on gene expression by identifying expression quantitative trait loci (eQTL). We identified 330 and 257 eQTL genes in DCs and macrophages (False Discovery Rate (FDR) < 0.05), respectively. Four genes in DCs showed interaction between eQTL variants and TB progression status. The top eQTL interaction for a protein-coding gene was with FAH, the gene encoding fumarylacetoacetate hydrolase, which mediates the last step in mammalian tyrosine catabolism. FAH expression was associated with genetic regulatory variation in cases but not controls. Using public transcriptomic and epigenomic data of Mtb-infected monocyte-derived dendritic cells, we found that Mtb infection results in FAH downregulation and DNA methylation changes in the locus. Overall, this study demonstrates effects of genetic variation on gene expression levels that are dependent on history of infectious disease and highlights a candidate pathogenic mechanism through pathogen-response genes. Furthermore, our results point to tyrosine metabolism and related candidate TB progression pathways for further investigation.

Poly(ADP-ribose) polymerase 1 participates in the phase entrainment of circadian clocks to feeding.

Circadian clocks in peripheral organs are tightly coupled to cellular metabolism and are readily entrained by feeding-fasting cycles. However, the molecular mechanisms involved are largely unknown. Here we show that in liver the activity of PARP-1, an NAD(+)-dependent ADP-ribosyltransferase, oscillates in a daily manner and is regulated by feeding. We provide biochemical evidence that PARP-1 binds and poly(ADP-ribosyl)ates CLOCK at the beginning of the light phase. The loss of PARP-1 enhances the binding of CLOCK-BMAL1 to DNA and leads to a phase-shift of the interaction of CLOCK-BMAL1 with PER and CRY repressor proteins. As a consequence, CLOCK-BMAL1-dependent gene expression is altered in PARP-1-deficient mice, in particular in response to changes in feeding times. Our results show that Parp-1 knockout mice exhibit impaired food entrainment of peripheral circadian clocks and support a role for PARP-1 in connecting feeding with the mammalian timing system.

Understanding Spondyloarthritis Pathogenesis: The Promise of Single-Cell Profiling.

PURPOSE OF REVIEW: Single-cell profiling, either in suspension or within the tissue context, is a rapidly evolving field. The purpose of this review is to outline recent advancements and emerging trends with a specific focus on studies in spondyloarthritis. RECENT FINDINGS: The introduction of sequencing-based approaches for the quantification of RNA, protein, or epigenetic modifications at single-cell resolution has provided a major boost to discovery-driven research. Fluorescent flow cytometry, mass cytometry, and image-based cytometry continue to evolve. Spatial transcriptomics and imaging mass cytometry have extended high-dimensional analysis to cells in tissues. Applications in spondyloarthritis include the indexing and functional characterization of cells, discovery of disease-associated cell states, and identification of signatures associated with therapeutic responses. Single-cell TCR-seq has provided evidence for clonal expansion of CD8+ T cells in spondyloarthritis. The use of single-cell profiling approaches in spondyloarthritis research is still in its early stages. Challenges include high cost and limited availability of diseased tissue samples. To harness the full potential of the rapidly expanding technical capabilities, large-scale collaborative efforts are imperative.

Type 2 inflammation drives an airway basal stem cell program through insulin receptor substrate signaling.

BACKGROUND: Chronic rhinosinusitis with nasal polyposis (CRSwNP) is a type 2 (T2) inflammatory disease associated with an increased number of airway basal cells (BCs). Recent studies have identified transcriptionally distinct BCs, but the molecular pathways that support or inhibit human BC proliferation and differentiation are largely unknown. OBJECTIVE: We sought to determine the role of T2 cytokines in regulating airway BCs. METHODS: Single-cell and bulk RNA sequencing of sinus and lung airway epithelial cells was analyzed. Human sinus BCs were stimulated with IL-4 and IL-13 in the presence and absence of inhibitors of IL-4R signaling. Confocal analysis of human sinus tissue and murine airway was performed. Murine BC subsets were sorted for RNA sequencing and functional assays. Fate labeling was performed in a murine model of tracheal injury and regeneration. RESULTS: Two subsets of BCs were found in human and murine respiratory mucosa distinguished by the expression of basal cell adhesion molecule (BCAM). BCAM expression identifies airway stem cells among P63+KRT5+NGFR+ BCs. In the sinonasal mucosa, BCAMhi BCs expressing TSLP, IL33, CCL26, and the canonical BC transcription factor TP63 are increased in patients with CRSwNP. In cultured BCs, IL-4/IL-13 increases the expression of BCAM and TP63 through an insulin receptor substrate-dependent signaling pathway that is increased in CRSwNP. CONCLUSIONS: These findings establish BCAM as a marker of airway stem cells among the BC pool and demonstrate that airway epithelial remodeling in T2 inflammation extends beyond goblet cell metaplasia to the support of a BC stem state poised to perpetuate inflammation.

Comparison between qPCR and RNA-seq reveals challenges of quantifying HLA expression.

Human leukocyte antigen (HLA) class I and II loci are essential elements of innate and acquired immunity. Their functions include antigen presentation to T cells leading to cellular and humoral immune responses, and modulation of NK cells. Their exceptional influence on disease outcome has now been made clear by genome-wide association studies. The exons encoding the peptide-binding groove have been the main focus for determining HLA effects on disease susceptibility/pathogenesis. However, HLA expression levels have also been implicated in disease outcome, adding another dimension to the extreme diversity of HLA that impacts variability in immune responses across individuals. To estimate HLA expression, immunogenetic studies traditionally rely on quantitative PCR (qPCR). Adoption of alternative high-throughput technologies such as RNA-seq has been hampered by technical issues due to the extreme polymorphism at HLA genes. Recently, however, multiple bioinformatic methods have been developed to accurately estimate HLA expression from RNA-seq data. This opens an exciting opportunity to quantify HLA expression in large datasets but also brings questions on whether RNA-seq results are comparable to those by qPCR. In this study, we analyze three classes of expression data for HLA class I genes for a matched set of individuals: (a) RNA-seq, (b) qPCR, and (c) cell surface HLA-C expression. We observed a moderate correlation between expression estimates from qPCR and RNA-seq for HLA-A, -B, and -C (0.2 ≤ rho ≤ 0.53). We discuss technical and biological factors which need to be accounted for when comparing quantifications for different molecular phenotypes or using different techniques.

SARS-CoV-2-specific T cell responses in patients with multisystem inflammatory syndrome in children.

Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of SARS-CoV-2 infections that occurs in the pediatric population. We sought to characterize T cell responses in MIS-C compared to COVID-19 and pediatric hyperinflammatory syndromes. MIS-C was distinct from COVID-19 and hyperinflammatory syndromes due to an expansion of T cells expressing TRBV11-2 that was not associated with HLA genotype. Children diagnosed with MIS-C, but who were negative for SARS-CoV-2 by PCR and serology, did not display Vß skewing. There was no difference in the proportion of T cells that became activated after stimulation with SARS-CoV-2 peptides in children with MIS-C compared to convalescent COVID-19. The frequency of SARS-CoV-2-specific TCRs and the antigens recognized by these TCRs were comparable in MIS-C and COVID-19. Expansion of Vß11-2+ T cells was a specific biomarker of MIS-C patients with laboratory confirmed SARS-CoV-2 infections. Children with MIS-C had robust antigen-specific T cell responses to SARS-CoV-2.

Autoimmune diseases - connecting risk alleles with molecular traits of the immune system.

Genome-wide strategies have driven the discovery of more than 300 susceptibility loci for autoimmune diseases. However, for almost all loci, understanding of the mechanisms leading to autoimmunity remains limited, and most variants that are likely to be causal are in non-coding regions of the genome. A critical next step will be to identify the in vivo and ex vivo immunophenotypes that are affected by risk variants. To do this, key cell types and cell states that are implicated in autoimmune diseases will need to be defined. Functional genomic annotations from these cell types and states can then be used to resolve candidate genes and causal variants. Together with longitudinal studies, this approach may yield pivotal insights into how autoimmunity is triggered.

The landscape of genomic imprinting across diverse adult human tissues.

Genomic imprinting is an important regulatory mechanism that silences one of the parental copies of a gene. To systematically characterize this phenomenon, we analyze tissue specificity of imprinting from allelic expression data in 1582 primary tissue samples from 178 individuals from the Genotype-Tissue Expression (GTEx) project. We characterize imprinting in 42 genes, including both novel and previously identified genes. Tissue specificity of imprinting is widespread, and gender-specific effects are revealed in a small number of genes in muscle with stronger imprinting in males. IGF2 shows maternal expression in the brain instead of the canonical paternal expression elsewhere. Imprinting appears to have only a subtle impact on tissue-specific expression levels, with genes lacking a systematic expression difference between tissues with imprinted and biallelic expression. In summary, our systematic characterization of imprinting in adult tissues highlights variation in imprinting between genes, individuals, and tissues.

Tissue-specific effects of genetic and epigenetic variation on gene regulation and splicing.

Understanding how genetic variation affects distinct cellular phenotypes, such as gene expression levels, alternative splicing and DNA methylation levels, is essential for better understanding of complex diseases and traits. Furthermore, how inter-individual variation of DNA methylation is associated to gene expression is just starting to be studied. In this study, we use the GenCord cohort of 204 newborn Europeans' lymphoblastoid cell lines, T-cells and fibroblasts derived from umbilical cords. The samples were previously genotyped for 2.5 million SNPs, mRNA-sequenced, and assayed for methylation levels in 482,421 CpG sites. We observe that methylation sites associated to expression levels are enriched in enhancers, gene bodies and CpG island shores. We show that while the correlation between DNA methylation and gene expression can be positive or negative, it is very consistent across cell-types. However, this epigenetic association to gene expression appears more tissue-specific than the genetic effects on gene expression or DNA methylation (observed in both sharing estimations based on P-values and effect size correlations between cell-types). This predominance of genetic effects can also be reflected by the observation that allele specific expression differences between individuals dominate over tissue-specific effects. Additionally, we discover genetic effects on alternative splicing and interestingly, a large amount of DNA methylation correlating to alternative splicing, both in a tissue-specific manner. The locations of the SNPs and methylation sites involved in these associations highlight the participation of promoter proximal and distant regulatory regions on alternative splicing. Overall, our results provide high-resolution analyses showing how genome sequence variation has a broad effect on cellular phenotypes across cell-types, whereas epigenetic factors provide a secondary layer of variation that is more tissue-specific. Furthermore, the details of how this tissue-specificity may vary across inter-relations of molecular traits, and where these are occurring, can yield further insights into gene regulation and cellular biology as a whole.

Gene age predicts the strength of purifying selection acting on gene expression variation in humans.

Gene expression levels can be subject to selection. We hypothesized that the age of gene origin is associated with expression constraints, given that it affects the level of gene integration into the functional cellular environment. By studying the genetic variation affecting gene expression levels (cis expression quantitative trait loci [cis-eQTLs]) and protein levels (cis protein QTLs [cis-pQTLs]), we determined that young, primate-specific genes are enriched in cis-eQTLs and cis-pQTLs. Compared to cis-eQTLs of old genes originating before the zebrafish divergence, cis-eQTLs of young genes have a higher effect size, are located closer to the transcription start site, are more significant, and tend to influence genes in multiple tissues and populations. These results suggest that the expression constraint of each gene increases throughout its lifespan. We also detected a positive correlation between expression constraints (approximated by cis-eQTL properties) and coding constraints (approximated by Ka/Ks) and observed that this correlation might be driven by gene age. To uncover factors associated with the increase in gene-age-related expression constraints, we demonstrated that gene connectivity, gene involvement in complex regulatory networks, gene haploinsufficiency, and the strength of posttranscriptional regulation increase with gene age. We also observed an increase in heritability of gene expression levels with age, implying a reduction of the environmental component. In summary, we show that gene age shapes key gene properties during evolution and is therefore an important component of genome function.

Genetic and epigenetic regulation of human lincRNA gene expression.

Large intergenic noncoding RNAs (lincRNAs) are still poorly functionally characterized. We analyzed the genetic and epigenetic regulation of human lincRNA expression in the GenCord collection by using three cell types from 195 unrelated European individuals. We detected a considerable number of cis expression quantitative trait loci (cis-eQTLs) and demonstrated that the genetic regulation of lincRNA expression is independent of the regulation of neighboring protein-coding genes. lincRNAs have relatively more cis-eQTLs than do equally expressed protein-coding genes with the same exon number. lincRNA cis-eQTLs are located closer to transcription start sites (TSSs) and their effect sizes are higher than cis-eQTLs found for protein-coding genes, suggesting that lincRNA expression levels are less constrained than that of protein-coding genes. Additionally, lincRNA cis-eQTLs can influence the expression level of nearby protein-coding genes and thus could be considered as QTLs for enhancer activity. Enrichment of expressed lincRNA promoters in enhancer marks provides an additional argument for the involvement of lincRNAs in the regulation of transcription in cis. By investigating the epigenetic regulation of lincRNAs, we observed both positive and negative correlations between DNA methylation and gene expression (expression quantitative trait methylation [eQTMs]), as expected, and found that the landscapes of passive and active roles of DNA methylation in gene regulation are similar to protein-coding genes. However, lincRNA eQTMs are located closer to TSSs than are protein-coding gene eQTMs. These similarities and differences in genetic and epigenetic regulation between lincRNAs and protein-coding genes contribute to the elucidation of potential functions of lincRNAs.

Transcriptome genetics using second generation sequencing in a Caucasian population.

Gene expression is an important phenotype that informs about genetic and environmental effects on cellular state. Many studies have previously identified genetic variants for gene expression phenotypes using custom and commercially available microarrays. Second generation sequencing technologies are now providing unprecedented access to the fine structure of the transcriptome. We have sequenced the mRNA fraction of the transcriptome in 60 extended HapMap individuals of European descent and have combined these data with genetic variants from the HapMap3 project. We have quantified exon abundance based on read depth and have also developed methods to quantify whole transcript abundance. We have found that approximately 10 million reads of sequencing can provide access to the same dynamic range as arrays with better quantification of alternative and highly abundant transcripts. Correlation with SNPs (small nucleotide polymorphisms) leads to a larger discovery of eQTLs (expression quantitative trait loci) than with arrays. We also detect a substantial number of variants that influence the structure of mature transcripts indicating variants responsible for alternative splicing. Finally, measures of allele-specific expression allowed the identification of rare eQTLs and allelic differences in transcript structure. This analysis shows that high throughput sequencing technologies reveal new properties of genetic effects on the transcriptome and allow the exploration of genetic effects in cellular processes.

Sex-biased genetic effects on gene regulation in humans.

Human regulatory variation, reported as expression quantitative trait loci (eQTLs), contributes to differences between populations and tissues. The contribution of eQTLs to differences between sexes, however, has not been investigated to date. Here we explore regulatory variation in females and males and demonstrate that 12%-15% of autosomal eQTLs function in a sex-biased manner. We show that genes possessing sex-biased eQTLs are expressed at similar levels across the sexes and highlight cases of genes controlling sexually dimorphic and shared traits that are under the control of distinct regulatory elements in females and males. This study illustrates that sex provides important context that can modify the effects of functional genetic variants.

Patterns of cis regulatory variation in diverse human populations.

The genetic basis of gene expression variation has long been studied with the aim to understand the landscape of regulatory variants, but also more recently to assist in the interpretation and elucidation of disease signals. To date, many studies have looked in specific tissues and population-based samples, but there has been limited assessment of the degree of inter-population variability in regulatory variation. We analyzed genome-wide gene expression in lymphoblastoid cell lines from a total of 726 individuals from 8 global populations from the HapMap3 project and correlated gene expression levels with HapMap3 SNPs located in cis to the genes. We describe the influence of ancestry on gene expression levels within and between these diverse human populations and uncover a non-negligible impact on global patterns of gene expression. We further dissect the specific functional pathways differentiated between populations. We also identify 5,691 expression quantitative trait loci (eQTLs) after controlling for both non-genetic factors and population admixture and observe that half of the cis-eQTLs are replicated in one or more of the populations. We highlight patterns of eQTL-sharing between populations, which are partially determined by population genetic relatedness, and discover significant sharing of eQTL effects between Asians, European-admixed, and African subpopulations. Specifically, we observe that both the effect size and the direction of effect for eQTLs are highly conserved across populations. We observe an increasing proximity of eQTLs toward the transcription start site as sharing of eQTLs among populations increases, highlighting that variants close to TSS have stronger effects and therefore are more likely to be detected across a wider panel of populations. Together these results offer a unique picture and resource of the degree of differentiation among human populations in functional regulatory variation and provide an estimate for the transferability of complex trait variants across populations.

Rare and common regulatory variation in population-scale sequenced human genomes.

Population-scale genome sequencing allows the characterization of functional effects of a broad spectrum of genetic variants underlying human phenotypic variation. Here, we investigate the influence of rare and common genetic variants on gene expression patterns, using variants identified from sequencing data from the 1000 genomes project in an African and European population sample and gene expression data from lymphoblastoid cell lines. We detect comparable numbers of expression quantitative trait loci (eQTLs) when compared to genotypes obtained from HapMap 3, but as many as 80% of the top expression quantitative trait variants (eQTVs) discovered from 1000 genomes data are novel. The properties of the newly discovered variants suggest that mapping common causal regulatory variants is challenging even with full resequencing data; however, we observe significant enrichment of regulatory effects in splice-site and nonsense variants. Using RNA sequencing data, we show that 46.2% of nonsynonymous variants are differentially expressed in at least one individual in our sample, creating widespread potential for interactions between functional protein-coding and regulatory variants. We also use allele-specific expression to identify putative rare causal regulatory variants. Furthermore, we demonstrate that outlier expression values can be due to rare variant effects, and we approximate the number of such effects harboured in an individual by effect size. Our results demonstrate that integration of genomic and RNA sequencing analyses allows for the joint assessment of genome sequence and genome function.

Increased glycolysis and cellular crosstalk in eosinophilic chronic rhinosinusitis with nasal polyps.

Introduction: Chronic rhinosinusitis (CRS) is a chronic inflammatory disease of the sinonasal mucosa with distinct endotypes including type 2 (T2) high eosinophilic CRS with nasal polyps (eCRSwNP), T2 low non-eosinophilic CRS with nasal polyps (neCRSwNP), and CRS without nasal polyps (CRSsNP). Methods: Given the heterogeneity of disease, we hypothesized that assessment of single cell RNA sequencing (scRNA-seq) across this spectrum of disease would reveal connections between infiltrating and activated immune cells and the epithelial and stromal populations that reside in sinonasal tissue. Results: Here we find increased expression of genes encoding glycolytic enzymes in epithelial cells (EpCs), stromal cells, and memory T-cell subsets from patients with eCRSwNP, as compared to healthy controls. In basal EpCs, this is associated with a program of cell motility and Rho GTPase effector expression. Across both stromal and immune subsets, glycolytic programming was associated with extracellular matrix interactions, proteoglycan generation, and collagen formation. Furthermore, we report increased cell-cell interactions between EpCs and stromal/immune cells in eCRSwNP compared to healthy control tissue, and we nominate candidate receptor-ligand pairs that may drive tissue remodeling. Discussion: These findings support a role for glycolytic reprograming in T2-elicited tissue remodeling and implicate increased cellular crosstalk in eCRSwNP.

High-throughput identification of functional regulatory SNPs in systemic lupus erythematosus.

Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift and luciferase reporter assays. To validate the approach, we studied rs2297550 in detail, finding that the risk allele enhanced binding to the transcription factor Ikaros (IKZF1), thereby modulating expression of IKBKE. Correspondingly, primary cells from genotyped healthy donors bearing the risk allele expressed higher levels of the interferon / NF-κB regulator IKKϵ. Together, these findings define a set of likely functional non-coding lupus risk variants and identify a new regulatory pathway involving rs2297550, Ikaros, and IKKϵ implicated by human genetics in risk for SLE.

FORGEdb: a tool for identifying candidate functional variants and uncovering target genes and mechanisms for complex diseases.

The majority of disease-associated variants identified through genome-wide association studies are located outside of protein-coding regions. Prioritizing candidate regulatory variants and gene targets to identify potential biological mechanisms for further functional experiments can be challenging. To address this challenge, we developed FORGEdb ( https://forgedb.cancer.gov/ ; https://forge2.altiusinstitute.org/files/forgedb.html ; and https://doi.org/10.5281/zenodo.10067458 ), a standalone and web-based tool that integrates multiple datasets, delivering information on associated regulatory elements, transcription factor binding sites, and target genes for over 37 million variants. FORGEdb scores provide researchers with a quantitative assessment of the relative importance of each variant for targeted functional experiments.