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SRP144382
Homo sapiens
188 Downloadable Samples
Illumina HiSeq 2500
Description
Background: The main bottleneck for genomic studies of tumors is the limited availability of fresh frozen (FF) samples collected from patients, coupled with comprehensive long-term clinical follow-up. This shortage could be alleviated by using existing large archives of routinely obtained and stored Formalin-Fixed Paraffin-Embedded (FFPE) tissues. However, since these samples are partially degraded, their RNA sequencing is technically challenging. Results: In an effort to establish a reliable and practical procedure, we compared three protocols for RNA sequencing using pairs of FF and FFPE samples, both taken from the same breast tumor. In contrast to previous studies, we compared the expression profiles obtained from the two matched sample types, using the same protocol for both. Three protocols were tested on low initial amounts of RNA, as little as 100 ng, to represent the possibly limited availability of clinical samples. For two of the three protocols tested, poly(A) selection (mRNA-seq) and ribosomal-depletion, the total gene expression profiles of matched FF and FFPE pairs were highly correlated. For both protocols, differential gene expression between two FFPE samples was in agreement with their matched FF samples. Notably, although expression levels of FFPE samples by mRNA-seq were mainly represented by the 3'-end of the transcript, they yielded very similar results to those obtained by ribosomal-depletion protocol, which produces uniform coverage across the transcript. Further, focusing on clinically relevant genes, we showed that the high correlation between expression levels persists at higher resolutions. Conclusions: Using the poly(A) protocol for FFPE exhibited, unexpectedly, similar efficiency to the ribosomal-depletion protocol, with the latter requiring much higher (2-3 fold) sequencing depth to compensate for the relative low fraction of reads mapped to the transcriptome. The results indicate that standard poly(A)-based RNA sequencing of archived FFPE samples is a reliable and cost-effective alternative for measuring mRNA-seq on FF samples. Expression profiling of FFPE samples by mRNA-seq can facilitate much needed extensive retrospective clinical genomic studies. Overall design: We perform an unbiased evaluation of RNA-seq of archived tumor tissues by comparing the same library preparation methods for both FF and FFPE matched tumor samples and for small amounts of total RNA starting material. We have 3 matched FF/FFPE tumor samples with a moderate archival time of about 4-5 years (T1=T3), and additional 3 FFPE tumor samples archived for more than 10 years (T4-T6). all samples were tested with two protocols: illumina Truseq RNA after poly(A) selection (mRNA-seq); and Truseq after ribosomal depletion (RiboZero). Several initial amounts of starting material was tested for eacg protocol.
Publication Title
mRNA-seq whole transcriptome profiling of fresh frozen versus archived fixed tissues.
Sample Metadata Fields
Specimen part, Disease, Subject
View Samples- Mus musculus
- 165 Downloadable Samples
- Illumina 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- Mus musculus
- 151 Downloadable Samples
- Illumina 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- Mus musculus
- 136 Downloadable Samples
- Illumina 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- Mus musculus
- 130 Downloadable Samples
- Illumina 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- Mus musculus
- 30 Downloadable Samples
- Illumina 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- Mus musculus
- 8 Downloadable Samples
- Illumina 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- Mus musculus
- 6 Downloadable Samples
- Illumina 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- Mus musculus
- 2 Downloadable Samples
- Illumina 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- Mus musculus
- 4 Downloadable Samples
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