Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single-cell resolution

Abstract

Synthetic glucocorticoids, such as dexamethasone, have been used as a treatment for many immune conditions, such as asthma and, more recently, severe COVID-19. Single-cell data can capture more fine-grained details on transcriptional variability and dynamics to gain a better understanding of the molecular underpinnings of inter-individual variation in drug response. Here, we used single-cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated peripheral blood mononuclear cells from 96 African American children. We used novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we showed that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and showed widespread genetic regulation of the transcriptional dynamics of the gene expression response.

Genetic variants associated with cell-type-specific intra-individual gene expression variability reveal new mechanisms of genome regulation

“…In total, we identified 34 dGenes accounting for the mean-variance dependency and they were enriched in the biological pathways relevant to interferon response, interspecies interaction, allograft rejection and viral gene expression. These results suggest that the transcriptional variability at the single-cell level could arise due to immune and/or external stimulus 50 and that variability is under genetic control. Although we only identified 55 deQTL-dGene pairs in the current study, given a larger sample size and number of cells per individual, we would expect to discover thousands of genetic variants that affect the dispersion level of intra-individual gene expression.…”

Functional characterization of eQTLs and asthma risk loci with scATAC-seq across immune cell types and contexts

“…In the integrated scATAC-seq and scRNA-seq dataset, we identified four major cell types (B cells, Monocytes, Natural Killer (NK) cells and T cells) and also one minor cell type, Dendritic cells (DCs) (Figure 1B). In this integrated dataset, NK cells can be more clearly distinguished from T cells compared to scRNA-seq data alone (Resztak et al (2023)). As expected, T cells formed the largest cluster with 70,824 cells (about 71%), followed by Monocytes (10,287 cells, about 10%), B cells (8,586 cells, about 8.7%), NK cells (8,037 cells, about 8.1%) and Dendritic cells (DC, 1,084 cells, 1%).…”

“…Glucocor-ticoids main mechanism of action is through binding and activation of the glucocorticoid receptor (GR) which then translocates to the nucleus and activates the anti-inflammatory response through two main mechanisms: 1) the activated receptor binds glucocorticoid response elements (GREs) thus activating the expression of anti-inflammatory genes; 2) the activated receptor inhibits pro-inflammatory transcription factors (TFs), e.g NFKB and AP-1, from binding their target genes thus repressing the expression of inflammatory genes (Silverman et al (2005)). We previously performed scRNA-seq in peripheral blood mononuclear cells (PBMCs) of children with asthma to systematically decipher transcriptome dynamic changes in response to glucocorticoids in a cell type spe-cific way (Resztak et al (2023)). However, the effect of glucocorticoids on the chromatin conformation landscape in different immune cell types has not been characterized yet, and we don’t have a full understanding of which TFs are involved in modulating the immune response in combination with glucocorticoids.…”

“…However only few studies have investigated context-dependent eQTLs across different cell types (e.g. Resztak et al (2023); Randolph et al (2021); Oelen et al (2022); Aquino et al (2023)), and their role in immune-mediated diseases.…”

“…We per-formed scATAC-seq to study the chromatin accessibility changes and relevant transcription factor binding motifs across cell types and treatment conditions. We integrated the scATAC-seq data with previously collected scRNA-seq data from 96 ALOFT participants (Resztak et al (2023)) to study the regulatory mechanisms underlying gene expression changes in mean and variability. Finally, we derived a regulatory annotation and used it to compu-tationally fine-map eQTLs, which allowed us to further characterize asthma associated loci using colocalization and TWAS.…”