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accession-icon SRP066314
Single-cell transcriptional profiling of Th17 cells, harvested at peak of disease in EAE from CNS [EAE-CNS-IL-17A/GFP+]
  • organism-icon Mus musculus
  • sample-icon 165 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

Extensive cellular heterogeneity exists within specific immune-cell subtypes classified as a single lineage, but its molecular underpinnings are rarely characterized at a genomic scale. Here, we use single-cell RNA-seq to investigate the molecular mechanisms governing heterogeneity and pathogenicity of Th17 cells isolated from the central nervous system (CNS) and lymph nodes (LN) at the peak of autoimmune encephalomyelitis (EAE) or polarized in vitro under either pathogenic or non-pathogenic differentiation conditions. Computational analysis reveals a spectrum of cellular states in vivo, including a self-renewal state, Th1-like effector/memory states and a dysfunctional/senescent state. Relating these states to in vitro differentiated Th17 cells, unveils genes governing pathogenicity and disease susceptibility. Using knockout mice, we validate four novel genes: Gpr65, Plzp, Toso and Cd5l (in a companion paper). Cellular heterogeneity thus informs Th17 function in autoimmunity, and can identify targets for selective suppression of pathogenic Th17 cells while sparing non-pathogenic tissue-protective ones. Overall design: Single-cell transcriptional profiling of Th17 cells, harvested at peak of disease in EAE from CNS

Publication Title

Simulating multiple faceted variability in single cell RNA sequencing.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP066322
Single-cell transcriptional profiling of Th17 cells, differentiated in vitro for 48h [TGFB1_IL6-48h-IL-17A/GFP+]
  • organism-icon Mus musculus
  • sample-icon 151 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

Extensive cellular heterogeneity exists within specific immune-cell subtypes classified as a single lineage, but its molecular underpinnings are rarely characterized at a genomic scale. Here, we use single-cell RNA-seq to investigate the molecular mechanisms governing heterogeneity and pathogenicity of Th17 cells isolated from the central nervous system (CNS) and lymph nodes (LN) at the peak of autoimmune encephalomyelitis (EAE) or polarized in vitro under either pathogenic or non-pathogenic differentiation conditions. Computational analysis reveals a spectrum of cellular states in vivo, including a self-renewal state, Th1-like effector/memory states and a dysfunctional/senescent state. Relating these states to in vitro differentiated Th17 cells, unveils genes governing pathogenicity and disease susceptibility. Using knockout mice, we validate four novel genes: Gpr65, Plzp, Toso and Cd5l (in a companion paper). Cellular heterogeneity thus informs Th17 function in autoimmunity, and can identify targets for selective suppression of pathogenic Th17 cells while sparing non-pathogenic tissue-protective ones. Overall design: Single-cell transcriptional profiling of Th17 cells, differentiated in vitro for 48h

Publication Title

Simulating multiple faceted variability in single cell RNA sequencing.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP066317
Single-cell transcriptional profiling of Th17 cells, harvested at peak of disease in EAE from LN [EAE-LN-IL-17A/GFP+]
  • organism-icon Mus musculus
  • sample-icon 136 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

Extensive cellular heterogeneity exists within specific immune-cell subtypes classified as a single lineage, but its molecular underpinnings are rarely characterized at a genomic scale. Here, we use single-cell RNA-seq to investigate the molecular mechanisms governing heterogeneity and pathogenicity of Th17 cells isolated from the central nervous system (CNS) and lymph nodes (LN) at the peak of autoimmune encephalomyelitis (EAE) or polarized in vitro under either pathogenic or non-pathogenic differentiation conditions. Computational analysis reveals a spectrum of cellular states in vivo, including a self-renewal state, Th1-like effector/memory states and a dysfunctional/senescent state. Relating these states to in vitro differentiated Th17 cells, unveils genes governing pathogenicity and disease susceptibility. Using knockout mice, we validate four novel genes: Gpr65, Plzp, Toso and Cd5l (in a companion paper). Cellular heterogeneity thus informs Th17 function in autoimmunity, and can identify targets for selective suppression of pathogenic Th17 cells while sparing non-pathogenic tissue-protective ones. Overall design: Single-cell transcriptional profiling of Th17 cells, harvested at peak of disease in EAE from LN

Publication Title

Simulating multiple faceted variability in single cell RNA sequencing.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP066321
Single-cell transcriptional profiling of Th17 cells, differentiated in vitro for 48h [TGFB1_IL6-48h]
  • organism-icon Mus musculus
  • sample-icon 130 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

Extensive cellular heterogeneity exists within specific immune-cell subtypes classified as a single lineage, but its molecular underpinnings are rarely characterized at a genomic scale. Here, we use single-cell RNA-seq to investigate the molecular mechanisms governing heterogeneity and pathogenicity of Th17 cells isolated from the central nervous system (CNS) and lymph nodes (LN) at the peak of autoimmune encephalomyelitis (EAE) or polarized in vitro under either pathogenic or non-pathogenic differentiation conditions. Computational analysis reveals a spectrum of cellular states in vivo, including a self-renewal state, Th1-like effector/memory states and a dysfunctional/senescent state. Relating these states to in vitro differentiated Th17 cells, unveils genes governing pathogenicity and disease susceptibility. Using knockout mice, we validate four novel genes: Gpr65, Plzp, Toso and Cd5l (in a companion paper). Cellular heterogeneity thus informs Th17 function in autoimmunity, and can identify targets for selective suppression of pathogenic Th17 cells while sparing non-pathogenic tissue-protective ones. Overall design: Single-cell transcriptional profiling of Th17 cells, differentiated in vitro for 48h

Publication Title

Simulating multiple faceted variability in single cell RNA sequencing.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP066313
Population transcriptional profiling of KO or WT cells,, differentiated in vitro for 48-96h towards Th17 cells
  • organism-icon Mus musculus
  • sample-icon 30 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

Extensive cellular heterogeneity exists within specific immune-cell subtypes classified as a single lineage, but its molecular underpinnings are rarely characterized at a genomic scale. Here, we use single-cell RNA-seq to investigate the molecular mechanisms governing heterogeneity and pathogenicity of Th17 cells isolated from the central nervous system (CNS) and lymph nodes (LN) at the peak of autoimmune encephalomyelitis (EAE) or polarized in vitro under either pathogenic or non-pathogenic differentiation conditions. Computational analysis reveals a spectrum of cellular states in vivo, including a self-renewal state, Th1-like effector/memory states and a dysfunctional/senescent state. Relating these states to in vitro differentiated Th17 cells, unveils genes governing pathogenicity and disease susceptibility. Using knockout mice, we validate four novel genes: Gpr65, Plzp, Toso and Cd5l (in a companion paper). Cellular heterogeneity thus informs Th17 function in autoimmunity, and can identify targets for selective suppression of pathogenic Th17 cells while sparing non-pathogenic tissue-protective ones. Overall design: Population transcriptional profiling of KO or WT cells,, differentiated in vitro for 48-96h towards Th17 cells

Publication Title

Simulating multiple faceted variability in single cell RNA sequencing.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP066311
Population transcriptional profiling of in vitro polarized Th17 cells, either sorted for IL17A/GFP+ or unsorted
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

Extensive cellular heterogeneity exists within specific immune-cell subtypes classified as a single lineage, but its molecular underpinnings are rarely characterized at a genomic scale. Here, we use single-cell RNA-seq to investigate the molecular mechanisms governing heterogeneity and pathogenicity of Th17 cells isolated from the central nervous system (CNS) and lymph nodes (LN) at the peak of autoimmune encephalomyelitis (EAE) or polarized in vitro under either pathogenic or non-pathogenic differentiation conditions. Computational analysis reveals a spectrum of cellular states in vivo, including a self-renewal state, Th1-like effector/memory states and a dysfunctional/senescent state. Relating these states to in vitro differentiated Th17 cells, unveils genes governing pathogenicity and disease susceptibility. Using knockout mice, we validate four novel genes: Gpr65, Plzp, Toso and Cd5l (in a companion paper). Cellular heterogeneity thus informs Th17 function in autoimmunity, and can identify targets for selective suppression of pathogenic Th17 cells while sparing non-pathogenic tissue-protective ones. Overall design: Population transcriptional profiling of in vitro polarized Th17 cells, either sorted for IL17A/GFP+ or unsorted.

Publication Title

Simulating multiple faceted variability in single cell RNA sequencing.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP066312
Population transcriptional profiling of Th17 cells, isolated from CNS or LN at peak of disease in EAE
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

Extensive cellular heterogeneity exists within specific immune-cell subtypes classified as a single lineage, but its molecular underpinnings are rarely characterized at a genomic scale. Here, we use single-cell RNA-seq to investigate the molecular mechanisms governing heterogeneity and pathogenicity of Th17 cells isolated from the central nervous system (CNS) and lymph nodes (LN) at the peak of autoimmune encephalomyelitis (EAE) or polarized in vitro under either pathogenic or non-pathogenic differentiation conditions. Computational analysis reveals a spectrum of cellular states in vivo, including a self-renewal state, Th1-like effector/memory states and a dysfunctional/senescent state. Relating these states to in vitro differentiated Th17 cells, unveils genes governing pathogenicity and disease susceptibility. Using knockout mice, we validate four novel genes: Gpr65, Plzp, Toso and Cd5l (in a companion paper). Cellular heterogeneity thus informs Th17 function in autoimmunity, and can identify targets for selective suppression of pathogenic Th17 cells while sparing non-pathogenic tissue-protective ones. Overall design: Population transcriptional profiling of Th17 cells, isolated from CNS or LN at peak of disease in EAE

Publication Title

Simulating multiple faceted variability in single cell RNA sequencing.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP066315
Population transcriptional profiling of Th17 cells, isolated from the lamina propria of the large intestine from 3-6 month old IL-17GFP KI mice
  • organism-icon Mus musculus
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer II

Description

Extensive cellular heterogeneity exists within specific immune-cell subtypes classified as a single lineage, but its molecular underpinnings are rarely characterized at a genomic scale. Here, we use single-cell RNA-seq to investigate the molecular mechanisms governing heterogeneity and pathogenicity of Th17 cells isolated from the central nervous system (CNS) and lymph nodes (LN) at the peak of autoimmune encephalomyelitis (EAE) or polarized in vitro under either pathogenic or non-pathogenic differentiation conditions. Computational analysis reveals a spectrum of cellular states in vivo, including a self-renewal state, Th1-like effector/memory states and a dysfunctional/senescent state. Relating these states to in vitro differentiated Th17 cells, unveils genes governing pathogenicity and disease susceptibility. Using knockout mice, we validate four novel genes: Gpr65, Plzp, Toso and Cd5l (in a companion paper). Cellular heterogeneity thus informs Th17 function in autoimmunity, and can identify targets for selective suppression of pathogenic Th17 cells while sparing non-pathogenic tissue-protective ones. Overall design: Population transcriptional profiling of Th17 cells, isolated from the lamina propria of the large intestine from 3-6 month old IL-17GFP KI mice

Publication Title

Simulating multiple faceted variability in single cell RNA sequencing.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon GSE43956
Induction of pathogenic Th17 cells by salt inducible kinase SGK-1 (SGK-1 KO)
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Th17 cells are highly proinflammatory cells that are critical for clearing extracellular pathogens like fungal infections and for induction of multiple autoimmune diseases1. IL-23 plays a critical role in stabilizing and endowing Th17 cells with pathogenic effector functions2. Previous studies have shown that IL-23 signaling reinforces the Th17 phenotype by increasing expression of IL-23 receptor (IL-23R)3. However, the precise molecular mechanism by which IL-23 sustains the Th17 response and induces pathogenic effector functions has not been elucidated. Here, we used unbiased transcriptional profiling of developing Th17 cells to construct a model of their signaling network and identify major nodes that regulate Th17 development. We identified serum glucocorticoid kinase-1 (SGK1), as an essential node downstream of IL-23 signaling, critical for regulating IL-23R expression and for stabilizing the Th17 cell phenotype by deactivation of Foxo1, a direct repressor of IL-23R expression. A serine-threonine kinase homologous to AKT4, SGK1 has been associated with cell cycle and apoptosis, and has been shown to govern Na+ transport and homeostasis5, 6 7, 8. We here show that a modest increase in salt (NaCl) concentration induces SGK1 expression, promotes IL-23R expression and enhances Th17 cell differentiation in vitro and in vivo, ultimately accelerating the development of autoimmunity. The loss of SGK1 resulted in abrogation of Na+-mediated Th17 differentiation in an IL-23-dependent manner. These data indicate that SGK1 is a critical regulator for the induction of pathogenic Th17 cells and provides a molecular insight by which an environmental factor such as a high salt diet could trigger Th17 development and promote tissue inflammation.

Publication Title

Induction of pathogenic TH17 cells by inducible salt-sensing kinase SGK1.

Sample Metadata Fields

Specimen part

View Samples
accession-icon GSE43957
Induction of pathogenic Th17 cells by salt inducible kinase SGK-1 (NaCl)
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Th17 cells are highly proinflammatory cells that are critical for clearing extracellular pathogens like fungal infections and for induction of multiple autoimmune diseases1. IL-23 plays a critical role in stabilizing and endowing Th17 cells with pathogenic effector functions2. Previous studies have shown that IL-23 signaling reinforces the Th17 phenotype by increasing expression of IL-23 receptor (IL-23R)3. However, the precise molecular mechanism by which IL-23 sustains the Th17 response and induces pathogenic effector functions has not been elucidated. Here, we used unbiased transcriptional profiling of developing Th17 cells to construct a model of their signaling network and identify major nodes that regulate Th17 development. We identified serum glucocorticoid kinase-1 (SGK1), as an essential node downstream of IL-23 signaling, critical for regulating IL-23R expression and for stabilizing the Th17 cell phenotype by deactivation of Foxo1, a direct repressor of IL-23R expression. A serine-threonine kinase homologous to AKT4, SGK1 has been associated with cell cycle and apoptosis, and has been shown to govern Na+ transport and homeostasis5, 6 7, 8. We here show that a modest increase in salt (NaCl) concentration induces SGK1 expression, promotes IL-23R expression and enhances Th17 cell differentiation in vitro and in vivo, ultimately accelerating the development of autoimmunity. The loss of SGK1 resulted in abrogation of Na+-mediated Th17 differentiation in an IL-23-dependent manner. These data indicate that SGK1 is a critical regulator for the induction of pathogenic Th17 cells and provides a molecular insight by which an environmental factor such as a high salt diet could trigger Th17 development and promote tissue inflammation.

Publication Title

Induction of pathogenic TH17 cells by inducible salt-sensing kinase SGK1.

Sample Metadata Fields

Specimen part, Treatment

View Samples
...

refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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