Multi-omics gene regulatory network analysis of resting and stimulated PBMCs [stimulation scRNA-seq]
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ABSTRACT:
PROVIDER: PRJNA738946 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14856600_1.fastq.gz | Fastqsanger.gz | |||
| SRR14856600_2.fastq.gz | Fastqsanger.gz | |||
| SRR14856700_1.fastq.gz | Fastqsanger.gz | |||
| SRR14856700_2.fastq.gz | Fastqsanger.gz | |||
| SRR14856800_1.fastq.gz | Fastqsanger.gz |
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Project description:Multi-omics gene regulatory network analysis of resting and stimulated PBMCs
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Project description:Cells require coordinated control over gene expression changes when responding to environmental stimuli. Recent advancements in single-cell technologies have enabled studies of regulatory dynamics associated with cellular perturbation response in immune cells. However, associating these changes to underlying differences in epigenetic regulation through integration of multi-omic data has not been achieved at single-cell resolution. Here, we apply single-cell ATAC-seq (scATAC-seq) and scRNA-seq to assay chromatin accessibility and gene expression in resting and stimulated human blood cells. Collectively, we generate ~91,000 high-coverage single-cell profiles, allowing us to probe the cis-regulatory landscape of immunological response across cell types, stimuli and time. Advancing tools to integrate multiomic data, we connect distal cis-regulatory elements to genes, identifying key regulatory hubs associated with immune signaling and stress response. Subsequently, we design FigR - a method to infer gene regulatory networks (GRNs) to identify candidate TF regulators across single cells. Importantly, construction of a GRN using stimulus response data identifies TF regulatory activity associated with genetic variants in inflammatory diseases. Lastly, we assess the time-dependent regulatory dynamics of immune stimulation, where we find that cells alter chromatin accessibility prior to productive gene expression, a process occurring at time scales of minutes. Extending this concept of chromatin-mediated priming, and incorporating regulatory relationships defined by FigR, we detect a rare subpopulation of monocytes marked by a primed chromatin state predictive of enhanced immunological response. Overall, we build upon computational tools for GRN construction and demonstrate the utility of GRNs for analysis of multi-omic single cell data.
2022-06-20 | GSE178429 | GEO
Project description:Cells require coordinated control over gene expression changes when responding to environmental stimuli. Recent advancements in single-cell technologies have enabled studies of regulatory dynamics associated with cellular perturbation response in immune cells. However, associating these changes to underlying differences in epigenetic regulation through integration of multi-omic data has not been achieved at single-cell resolution. Here, we apply single-cell ATAC-seq (scATAC-seq) and scRNA-seq to assay chromatin accessibility and gene expression in resting and stimulated human blood cells. Collectively, we generate ~91,000 high-coverage single-cell profiles, allowing us to probe the cis-regulatory landscape of immunological response across cell types, stimuli and time. Advancing tools to integrate multiomic data, we connect distal cis-regulatory elements to genes, identifying key regulatory hubs associated with immune signaling and stress response. Subsequently, we design FigR - a method to infer gene regulatory networks (GRNs) to identify candidate TF regulators across single cells. Importantly, construction of a GRN using stimulus response data identifies TF regulatory activity associated with genetic variants in inflammatory diseases. Lastly, we assess the time-dependent regulatory dynamics of immune stimulation, where we find that cells alter chromatin accessibility prior to productive gene expression, a process occurring at time scales of minutes. Extending this concept of chromatin-mediated priming, and incorporating regulatory relationships defined by FigR, we detect a rare subpopulation of monocytes marked by a primed chromatin state predictive of enhanced immunological response. Overall, we build upon computational tools for GRN construction and demonstrate the utility of GRNs for analysis of multi-omic single cell data.
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Project description:Cells require coordinated control over gene expression changes when responding to environmental stimuli. Recent advancements in single-cell technologies have enabled studies of regulatory dynamics associated with cellular perturbation response in immune cells. However, associating these changes to underlying differences in epigenetic regulation through integration of multi-omic data has not been achieved at single-cell resolution. Here, we apply single-cell ATAC-seq (scATAC-seq) and scRNA-seq to assay chromatin accessibility and gene expression in resting and stimulated human blood cells. Collectively, we generate ~91,000 high-coverage single-cell profiles, allowing us to probe the cis-regulatory landscape of immunological response across cell types, stimuli and time. Advancing tools to integrate multiomic data, we connect distal cis-regulatory elements to genes, identifying key regulatory hubs associated with immune signaling and stress response. Subsequently, we design FigR - a method to infer gene regulatory networks (GRNs) to identify candidate TF regulators across single cells. Importantly, construction of a GRN using stimulus response data identifies TF regulatory activity associated with genetic variants in inflammatory diseases. Lastly, we assess the time-dependent regulatory dynamics of immune stimulation, where we find that cells alter chromatin accessibility prior to productive gene expression, a process occurring at time scales of minutes. Extending this concept of chromatin-mediated priming, and incorporating regulatory relationships defined by FigR, we detect a rare subpopulation of monocytes marked by a primed chromatin state predictive of enhanced immunological response. Overall, we build upon computational tools for GRN construction and demonstrate the utility of GRNs for analysis of multi-omic single cell data.
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Project description:Memory T cells respond to stimulation with more rapid expression of effector cell functions than their naM-CM-/ve counterparts, yet the gene expression signature underlying this enhanced recall response is not known. Therefore, we performed comprehensive, whole-genome expression profiling of murine memory CD8 T cells before and shortly after ex vivo stimulation. We compared this differential expression profile to its counterpart from stimulated naive cells. Given that memory cells arise from naive cells, the quiescent state of both cell populations prior to stimulation, and the early time point analyzed (four hours post-stimulation), it was possible that the stimulation-induced changes in gene expression were identical between the two populations. While there was a high degree of overlap, we found that the majority of up-regulated genes were more highly induced following stimulation of memory cells. This more robust increase in transcript levels was observed for a functionally diverse set of genes, including cytokines, chemokines, amino acid metabolic enzymes and transporters, transcription factors and regulators of RNA processing. We also identified the unique, stimulation-induced signatures of naive and memory CD8 T cells and found that the former was enriched for factors involved in regulating chromatin modifications. Specifically, we found that Hdac 5,7 and 8 transcript levels were rapidly down-regulated following stimulation of naive cells, which correlated with an increase in their total level of acetylated histone H3 (AcH3). This was in contrast to stimulated memory cells, which had higher levels of total AcH3 ex vivo that did not change following short-term stimulation. Furthermore, the unique stimulation-induced expression profile of memory cells was enriched for factors involved in regulating transport of molecules between the nucleus and cytoplasm, including multiple members of the nuclear pore complex. Together, these results support a model whereby the chromatin modifications that occur during the differentiation of naM-CM-/ve cells into memory cells are preserved in resting memory populations, facilitating their more robust re-activation of a functionally diverse set of genes that contribute to rapid recall of effector functions. NaM-CM-/ve (CD44lo) and memory phenotype (CD44hi) CD8 T cells from 7-wk old female B6 mice were FACS-purified and cultured in vitro for four hours in the presence or absence of PMA and ionomycin. Total RNA was purified from un-stimulated (resting) naM-CM-/ve, resting memory, stimulated naive, and stimulated memory cells and hybridized to individual single-color arrays. This purification and stimulation protocol was performed four independent times.
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Project description:This experiment aims to identify the biological pathways and diseases associated with the cytokine Interleukin 13 (IL-13) using gene expression measured in peripheral blood mononuclear cells (PBMCs). The experiment comprised of samples obtained from 3 healthy donors. The expression profiles of in vitro IL-13 stimulation were generated using RNA-seq technology for 3 PBMC samples at 24 hours. The transcriptional profiles of PBMCs without IL-13 stimulation were also generated to be used as controls. An IL-13R-alpha antagonist (Redpath et al. Biochemical Journal, 2013) was introduced into IL-13 stimulated PBMCs and the gene expression levels after 24h were profiled to examine the neutralization of IL-13 signaling by the antagonist.
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