Similar Datasets
Project description:The human immune system displays remarkable variation between individuals, leading to differences in susceptibility to autoimmune disease. We present single cell RNA sequence data from 1,267,768 peripheral blood mononuclear cells from 982 healthy human subjects. For 14 cell types, we identified 26,597 independent cis-expression quantitative trait loci (eQTLs) and 990 trans-eQTL, with the majority showing cell type specific effects on gene expression. We subsequently show how eQTLs have dynamic allelic effects in B cells transitioning from naïve to memory states and demonstrate how commonly segregating alleles lead to inter-individual variation in immune function. Finally, utilizing a Mendelian randomization approach, we identify the causal route by which 305 risk loci contribute to autoimmune disease at the cellular level. This work brings together genetic epidemiology with scRNA-seq to uncover drivers of inter-individual variation in the immune system.
2022-04-08 | GSE196829 | GEO
Project description:The human immune system displays remarkable variation between individuals, leading to differences in susceptibility to autoimmune disease. We present single cell RNA sequence data from 1,267,768 peripheral blood mononuclear cells from 982 healthy human subjects. For 14 cell types, we identified 26,597 independent cis-expression quantitative trait loci (eQTLs) and 990 trans-eQTL, with the majority showing cell type specific effects on gene expression. We subsequently show how eQTLs have dynamic allelic effects in B cells transitioning from naïve to memory states and demonstrate how commonly segregating alleles lead to inter-individual variation in immune function. Finally, utilizing a Mendelian randomization approach, we identify the causal route by which 305 risk loci contribute to autoimmune disease at the cellular level. This work brings together genetic epidemiology with scRNA-seq to uncover drivers of inter-individual variation in the immune system.
2022-04-08 | GSE196735 | GEO
Project description:Single-cell eQTL mapping identifies cell type specific genetic control of autoimmune disease
| PRJNA807386 | ENA
Project description:Single-cell eQTL mapping identifies cell type specific genetic control of autoimmune disease [scRNAseq_data]
| PRJNA807049 | ENA
Project description:Single-cell eQTL mapping identifies cell type specific genetic control of autoimmune disease [Genotype_data]
| PRJNA807390 | ENA
Project description:BackgroundThe discovery that somatic cells can be reprogrammed to induced pluripotent stem cells (iPSCs) has provided a foundation for in vitro human disease modelling, drug development and population genetics studies. Gene expression plays a critical role in complex disease risk and therapeutic response. However, while the genetic background of reprogrammed cell lines has been shown to strongly influence gene expression, the effect has not been evaluated at the level of individual cells which would provide significant resolution. By integrating single cell RNA-sequencing (scRNA-seq) and population genetics, we apply a framework in which to evaluate cell type-specific effects of genetic variation on gene expression.ResultsHere, we perform scRNA-seq on 64,018 fibroblasts from 79 donors and map expression quantitative trait loci (eQTLs) at the level of individual cell types. We demonstrate that the majority of eQTLs detected in fibroblasts are specific to an individual cell subtype. To address if the allelic effects on gene expression are maintained following cell reprogramming, we generate scRNA-seq data in 19,967 iPSCs from 31 reprogramed donor lines. We again identify highly cell type-specific eQTLs in iPSCs and show that the eQTLs in fibroblasts almost entirely disappear during reprogramming.ConclusionsThis work provides an atlas of how genetic variation influences gene expression across cell subtypes and provides evidence for patterns of genetic architecture that lead to cell type-specific eQTL effects.
| S-EPMC7934233 | biostudies-literature
Project description:Genome-wide gene expression quantitative trait loci (eQTL) mapping have been focused on single-nucleotide polymorphisms and have helped interpret findings from diseases mapping studies. The functional effect of structure variants, especially short insertions and deletions (indel) has not been well investigated. Here we impute 1,380,133 indels based on the latest 1,000 Genomes Project panel into three eQTL data sets from multiple tissues. Imputation of indels increased 9.9% power and identifies indel-specific eQTLs for 325 genes. We find introns and vicinities of UTRs are more enriched of indel eQTLs and 3.6 (single-tissue)-9.2%(multi-tissue) of previous identified eSNPs were taggers of eindels. Functional analyses identifies epigenetics marks, gene ontology categories and disease GWAS loci affected by SNPs and indels eQTLs showing tissue-consistent or tissue-specific effects. This study provides new insights into the underlying genetic architecture of gene expression across tissues and new resource to interpret function of diseases and traits associated structure variants.
| S-EPMC4929061 | biostudies-literature
Project description:Understanding how the genetic control of gene expression varies between cell types and contexts is key for our understanding of complex traits including disease. To this end, we leveraged single cell RNA sequencing (scRNA-seq) to characterize the genetic architecture of gene regulation in an organ with one of the most cellularly diverse organs, the human lung. We profile these effects across two conditions, tissue samples from healthy controls and patients with pulmonary fibrosis (PF), a chronic, progressive condition characterized by the scarring of lung tissue. In total, we have generated expression profiles of 475,047 cells from primary human lung tissue from 116 individuals, including 67 with PF and 49 unaffected donors. Employing a pseudo-bulk approach, we have mapped expression quantitative trait loci (eQTL) across 38 cell types, identifying shared and cell type-specific effects. Further, we identify disease-interaction eQTL demonstrating this class of associations are more likely to be cell-type specific and linked to key drivers of dysregulation in PF. Finally, we connect PF risk variants implicated by genome-wide association studies to their regulatory targets in disease-relevant cell types. This study represents the first use of scRNA-seq to identify cell type level eQTL in the human lung, and one of only a small number of studies to carry out these characterizations in solid tissues. These results provide valuable insights into lung biology and disease risk.
2023-03-20 | GSE227136 | GEO
Project description:Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated these predictions with transcription and cis-regulatory element annotations, derived by mapping RNA and chromatin in primary immune cells, including resting and stimulated CD4(+) T-cell subsets, regulatory T cells, CD8(+) T cells, B cells, and monocytes. We find that ∼90% of causal variants are non-coding, with ∼60% mapping to immune-cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune stimulation. Causal variants tend to occur near binding sites for master regulators of immune differentiation and stimulus-dependent gene activation, but only 10-20% directly alter recognizable transcription factor binding motifs. Rather, most non-coding risk variants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models.
| S-EPMC4336207 | biostudies-literature
Project description:Autoimmune polyglandular disease type I (APECED) is an autosomal recessive autoimmune disease (MIM 240300) characterized by hypoparathyroidism, primary adrenocortical failure, and chronic mucocutaneous candidiasis. The disease is highly prevalent in two isolated populations, the Finnish population and the Iranian Jewish one. Sporadic cases have been identified in many other countries, including almost all European countries. The APECED locus has previously been assigned to chromosome 21q22.3 by linkage analyses in 14 Finnish families. Locus heterogeneity is a highly relevant question in this disease affecting multiple tissues and with great phenotypic diversity. To solve this matter, we performed linkage and haplotype analyses on APECED families rising from different populations. Six microsatellite markers on the critical chromosomal region of 2.6 cM on 21q22.3 were analyzed. Pairwise linkage analyses revealed significant LOD scores for all these markers, maximum LOD score being 10.23. The obtained haplotype data and the geographic distribution of the great-grandparents of the Finnish APECED patients suggest the presence of one major, relatively old mutation responsible for approximately 90% of the Finnish cases. Similar evidence for one founder mutation was also found in analyses of Iranian Jewish APECED haplotypes. These haplotypes, however, differed totally from the Finnish ones. The linkage analyses in 21 non-Finnish APECED families originating from several European countries provided independent evidence for linkage to the same chromosomal region on 21q22.3 and revealed no evidence for locus heterogeneity. The haplotype analyses of APECED chromosomes suggest that in different populations APECED is due to a spectrum of mutations in a still unknown gene on chromosome 21.
| S-EPMC1914815 | biostudies-literature