Dynamic genetic regulation of gene expression during cellular differentiation
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE122380 | GEO | 2018/11/10
REPOSITORIES: GEO
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Project description:The impact of genetic regulatory elements on gene expression can vary across cell states. During dynamic processes such as cellular differentiation, cells transition through multiple cell states, and may differentiate toward multiple terminal cell types. We collected time-series single-cell RNA-sequencing data from 19 human cell lines, capturing 7 time points along a 16-day differentiation from induced pluripotent stem cells to cardiomyocytes. We used unsupervised clustering, marker gene expression patterns, and pseudotime inference methods to map individual cells to a position along one of two bifurcating differentiation trajectories that were inferred from the data. We then identified genetic effects on gene regulation with varying effects across these trajectories. We identified hundreds of dynamic eQTLs that change significantly across pseudotime, including many variants whose effects are specific to one of the two lineages. We then re-analyzed previously collected bulk data, and used cell state information to infer cell type interaction eQTLs in bulk, assigning previously identified dynamic eQTLs to one of the newly characterized cellular trajectories.
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Project description:The predominant outcome of cardiovascular disease (CVD) is myocardial infarction (MI), where cardiomyocytes are deprived of oxygen. To study inter-individual differences in cardiomyocytes’ response to hypoxia, we established an in vitro model of induced pluripotent stem cell-derived cardiomyocytes from 15 individuals. We characterized gene expression levels, chromatin accessibility, and methylation profiles in these cardiomyocytes in four culturing conditions that correspond to normoxia (10% O2), hypoxia (1% O2) and short or long-term re-oxygenation (back to 10% O2). In our population sample, 2,113 genes change their expression following hypoxia and short- or long-term re-oxygenation. Using available genotypes from all individuals, we identified 1,573 genes with a cis eQTL in at least one of the four culturing conditions. Taking into account the incomplete power to identify eQTLs in any given condition, we also identified 367 dynamic eQTLs, which are classified as eQTLs in at least one, but not in all conditions. A subset of dynamic eQTLs, which are detected only following hypoxia, have not been previously annotated as eQTLs even in much larger collections of heart tissues. We did not detect differences in DNA methylation, or chromatin accessibility as the cells transitioned between normoxia and hypoxia, but we observed a change in chromatin accessibility in 831 genomic regions upon re-oxygenation. Differentially accessible regions are enriched for features of active regulatory regions, SINE elements, and E2F4 transcription factor binding sites . Finally, we found that genes associated with dynamic eQTLs are also associated with complex traits and disease. Our data thus demonstrate how unique genetic effects on gene expression, which are likely relevant for disease, can be uncovered under conditions of stress.
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Project description:The predominant outcome of cardiovascular disease (CVD) is myocardial infarction (MI), where cardiomyocytes are deprived of oxygen. To study inter-individual differences in cardiomyocytes’ response to hypoxia, we established an in vitro model of induced pluripotent stem cell-derived cardiomyocytes from 15 individuals. We characterized gene expression levels, chromatin accessibility, and methylation profiles in these cardiomyocytes in four culturing conditions that correspond to normoxia (10% O2), hypoxia (1% O2) and short or long-term re-oxygenation (back to 10% O2). In our population sample, 2,113 genes change their expression following hypoxia and short- or long-term re-oxygenation. Using available genotypes from all individuals, we identified 1,573 genes with a cis eQTL in at least one of the four culturing conditions. Taking into account the incomplete power to identify eQTLs in any given condition, we also identified 367 dynamic eQTLs, which are classified as eQTLs in at least one, but not in all conditions. A subset of dynamic eQTLs, which are detected only following hypoxia, have not been previously annotated as eQTLs even in much larger collections of heart tissues. We did not detect differences in DNA methylation, or chromatin accessibility as the cells transitioned between normoxia and hypoxia, but we observed a change in chromatin accessibility in 831 genomic regions upon re-oxygenation. Differentially accessible regions are enriched for features of active regulatory regions, SINE elements, and E2F4 transcription factor binding sites . Finally, we found that genes associated with dynamic eQTLs are also associated with complex traits and disease. Our data thus demonstrate how unique genetic effects on gene expression, which are likely relevant for disease, can be uncovered under conditions of stress.
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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.
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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.
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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:Studies correlating genetic variation to gene expression facilitate the interpretation of common human phenotypes and disease. As functional variants may be operating in a tissue-dependent manner, we performed gene expression profiling and association with genetic variants (SNPs) on three cell types of 85 individuals. After excluding 10 outlier individuals detected through principal component analysis, we detected cell type-specific genetic effects, with 69 - 80% of regulatory variants operating in a cell type-specific manner and identified multiple eQTLs per gene, unique or shared among cell types and positively correlated with the number of transcripts per gene. Cell type specific eQTLs were found at larger distances from genes and lower effect size similar to known enhancers. These data suggest that the complete regulatory variant repertoire can only be uncovered in the context of cell type specificity.
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