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Single-cell eQTL mapping identifies cell type specific genetic control of autoimmune disease [Genotype_data]

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE196829 | GEO | 2022/04/08

REPOSITORIES: GEO

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Single-cell eQTL mapping identifies cell type specific genetic control of autoimmune disease [scRNAseq_data]

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 na√Øve 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.

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Gene expression variability in human and chimpanzee populations share common determinants

Project description:Inter-individual variation in gene regulation has been shown to be heritable and it is quite often associated with differences in disease susceptibility between individuals. While many human studies focused on mapping associations between genetic and gene regulatory variation, much less attention has been paid to the evolutionary processes that shape the observed differences in gene regulation between individuals in humans or any other primate. To begin addressing this gap, we performed a comparative expression quantitative trait loci (eQTL) mapping study in humans and chimpanzees, using gene expression data from primary heart samples. While expression variability in both species is strongly determined by non-genetic sources, such as cell type heterogeneity, we found evidence that the degree of inter-individual variation in gene regulation is generally conserved in humans and chimpanzees. In particular, we found a significant overlap of genes associated with eQTLs in the two species. We conclude that humans and chimpanzees share sources common determinants of gene expression variability, including genetically regulated constraints from stabilizing and diversifying selection pressures.

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Project description:Genetic variants that impact gene regulation are important contributors to human phenotypic variation. For this reason, considerable efforts have been made to identify genetic associations with differences in mRNA levels of nearby genes, namely, cis expression quantitative trait loci (eQTLs). The phenotypic consequences of eQTLs are presumably due, in most cases, to their ultimate effects on protein expression levels. Yet, only few studies have quantified the impact of genetic variation on proteins levels directly. It remains unclear how faithfully eQTLs are reflected at the protein level, and whether there is a significant layer of cis regulatory variation acting primarily on translation or steady state protein levels. To address these questions, we measured ribosome occupancy by high-throughput sequencing, and relative protein levels by high-resolution quantitative mass spectrometry, in a panel of lymphoblastoid cell lines (LCLs) in which we had previously measured transcript expression using RNA sequencing. We then mapped genetic variants that are associated with changes in transcript expression (eQTLs), ribosome occupancy (rQTLs), or protein abundance (pQTLs). Most of the QTLs we detected are associated with transcript expression levels, with consequent effects on ribosome and protein levels. However, we found that eQTLs tend to have significantly reduced effect sizes on protein levels, suggesting that their potential impact on downstream phenotypes is often attenuated or buffered. Additionally, we confirmed the presence of a class of cis QTLs that specifically affect protein abundance with little or no effect on mRNA levels; most of these QTLs have little effect on ribosome occupancy, and hence may arise from differences in post-translational regulation.

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Project description:The innate immune system provides the first response to pathogen infection and orchestrates the activation of the adaptive immune system. Though a large component of the innate immune response is common to all infections, pathogen-specific innate immune responses have been documented as well. The innate immune response is thought to be especially critical for fighting infection with Mycobacterium tuberculosis (MTB), the causative agent of tuberculosis (TB). While TB can be a deadly disease, only 5-10% of individuals infected with MTB develop active disease, and this inter-individual variation is, at least partly, heritable. Studies of inter-individual variation in the innate immune response to MTB infection may therefore shed light on the genetic basis for variation in susceptibility to TB. Yet, to date, we still do not know which properties of the innate immune response are specific to MTB infection and which represent a general response to pathogen infection. To begin addressing this gap, we infected macrophages with eight different bacterial pathogens, including different MTB strains and related mycobacteria, and studied the transcriptional response to infection. We found that although the gene expression changes were largely consistent across the bacterial infection treatments, we were able to identify a novel subset of genes whose regulation was affected specifically by infection with mycobacteria. Genetic variants that are associated with regulatory differences in these genes should be considered candidate loci for explaining inter-individual susceptibility TB.

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