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Dissecting immune circuits by linking CRISPR pooled screens with single cell RNA-seq [SET2]

ABSTRACT: In multicellular organisms, dedicated regulatory circuits control cell-type diversity and response. The crosstalk and redundancies within these circuits and substantial cellular heterogeneity pose a major research challenge. We present CRISP-seq, an integrated method for massively parallel single-cell RNA-seq and CRISPR pooled screens. We show that profiling the perturbation and transcriptome in the same cell, enables to elucidate, the function of multiple factors and their interactions. In this benchmarking study, we applied this technology to probe regulatory circuits of innate immunity. By sampling tens of thousands of perturbed cells in vitro and in mice, we identified interactions and redundancies between developmental and signaling-dependent factors controlling the commitment toward different cell lineages or the inflammatory and antiviral pathways. CRISP-seq thereby emerges as a broadly applicable, comprehensive, and unbiased approach for elucidating mammalian regulatory circuits.

ORGANISM(S): Mus musculus

PROVIDER: GSE90487 | GEO | 2016/12/16

SECONDARY ACCESSION(S): PRJNA354871

REPOSITORIES: GEO

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Dissecting immune circuits by linking CRISPR pooled screens with single cell RNA-seq [SET1]

Project description:In multicellular organisms, dedicated regulatory circuits control cell-type diversity and response. The crosstalk and redundancies within these circuits and substantial cellular heterogeneity pose a major research challenge. We present CRISP-seq, an integrated method for massively parallel single-cell RNA-seq and CRISPR pooled screens. We show that profiling the perturbation and transcriptome in the same cell, enables to elucidate, the function of multiple factors and their interactions. In this benchmarking study, we applied this technology to probe regulatory circuits of innate immunity. By sampling tens of thousands of perturbed cells in vitro and in mice, we identified interactions and redundancies between developmental and signaling-dependent factors controlling the commitment toward different cell lineages or the inflammatory and antiviral pathways. CRISP-seq thereby emerges as a broadly applicable, comprehensive, and unbiased approach for elucidating mammalian regulatory circuits.

2016-12-16 | GSE90486 | GEO

Dissecting immune circuits by linking CRISPR pooled screens with single cell RNA-seq

Project description:Dissecting immune circuits by linking CRISPR pooled screens with single cell RNA-seq

| PRJNA354864 | ENA

Cis-Regulatory Circuits Regulating NEK6 Kinase Overexpression in Transformed B Cells Are Super-Enhancer-Independent (4C-seq)

Project description:Alterations in distal regulatory elements that control gene expression underlie many diseases, including cancer. Epigenomic analyses of normal and diseased cells have produced correlative predictions for connections between dysregulated enhancers and target genes involved in pathogenesis. However, with few exceptions, these predicted cis-regulatory circuits remain untested. Here, we dissect cis-regulatory circuits that lead to overexpression of NEK6, a mitosis-associated kinase, in human B cell lymphoma. We find that only a minor subset of predicted enhancers is required for NEK6 expression. Indeed, an annotated super-enhancer is dispensable for NEK6 overexpression and for maintaining the architecture of a B cell-specific regulatory hub. A CTCF cluster serves as a chromatin and architectural boundary to block communication of the NEK6 regulatory hub with neighboring genes. Our findings emphasize that validation of predicted cis-regulatory circuits and super-enhancers is needed to prioritize transcriptional control elements as therapeutic targets.

2017-02-23 | GSE87322 | GEO

Cis-Regulatory Circuits Regulating NEK6 Kinase Overexpression in Transformed B Cells Are Super-Enhancer-Independent (RNA-seq)

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Glioblastoma remodeling of neural circuits in the human brain decreases survival

Project description:Gliomas synaptically integrate into neural circuits. Prior work has demonstrated bidirectional interactions between neurons and glioma cells, with neuronal activity driving glioma growth and gliomas increasing neuronal excitability. In this study we sought to determine how glioma-induced neuronal changes influence neural circuits underlying cognition and whether these interactions influence patient survival. Using intracranial brain recordings during lexical retrieval language tasks in awake humans together with site-specific tumor tissue biopsies and cell biology experiments, we found that gliomas remodel functional neural circuitry such that task-relevant neural responses activate tumor-infiltrated cortex well beyond the cortical regions normally recruited in the healthy brain. Site-directed biopsies from regions within the tumor that exhibit high functional connectivity between the tumor and the rest of the brain are enriched for a glioblastoma subpopulation that exhibits a distinct synaptogenic and neuronotrophic phenotype. Tumor cells from functionally connected regions secrete the synaptogenic factor thrombospondin-1, which contributes to the differential neuron-glioma interactions observed in functionally connected tumor regions compared to tumor regions with less functional connectivity. Pharmacological inhibition of thrombospondin-1 through the FDA-approved drug, gabapentin decreases glioblastoma proliferation. The degree of functional connectivity between glioblastoma and the normal brain negatively impacts both patient survival and language task performance. These data demonstrate that high-grade gliomas functionally remodel neural circuits in the human brain, which both promotes tumor progression and impairs cognition.

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Charting the impact of supraphysiologic MDM2 on gene regulatory circuits in sarcoma

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Compressed Perturb-seq: highly efficient screens for regulatory circuits using random composite perturbations

Project description:Pooled CRISPR screens with single-cell RNA-seq readout (Perturb-seq) have emerged as a key technique in functional genomics, but are limited in scale by cost and combinatorial complexity. Here, we reimagine Perturb-seq’s design through the lens of algorithms applied to random, low-dimensional observations. We present compressed Perturb-seq, in which we measure multiple perturbations per cell or multiple cells per droplet, and decompress these measurements by leveraging the sparse structure of regulatory circuits. Applying compressed Perturb-seq to 598 genes in the immune response to bacterial lipopolysaccharide, we achieve the same accuracy as conventional Perturb-seq at 4 to 20-fold reduced cost, with greater power to learn genetic interactions. We identify known and novel regulators of immune responses and uncover evolutionarily constrained genes with downstream targets enriched for immune disease heritability, including many missed by existing GWAS or trans-eQTL studies. Our framework enables new scales of interrogation for a foundational method in functional genomics.

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Mapping disease-associated regulatory circuits by cell type from single-cell multiomics data (S. aureus scATAC-seq)

Project description:Resolving chromatin remodeling-linked gene expression changes is important for understanding disease states. We describe MAGICAL (Multiome Accessible Gene Integration Calling And Looping), a hierarchical Bayesian approach that leverages paired scRNA-seq and scATAC-seq data from different conditions to map disease-associated transcription factors, regulatory sites and genes as regulatory circuits. By introducing hidden Bayesian variables to allow modeling noise and signal variation across cells and conditions in both transcriptome and chromatin data, in systemic evaluations MAGICAL achieved high accuracy on circuit prediction at cell-type resolution. We applied MAGICAL to study Staphylococcus aureus sepsis from peripheral blood mononuclear single cell data that we generated from infected subjects and healthy uninfected controls. MAGICAL identified sepsis-associated regulatory circuits predominantly in CD14 monocytes, known to be sepsis activated. We addressed the challenging problem of distinguishing methicillin-resistant- (MRSA) and methicillin-sensitive Staphylococcus aureus (MSSA) infections, where differential expression analysis failed to show predictive value. MAGICAL, however, identified epigenetic circuit biomarkers that distinguished MRSA from MSSA.

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