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accession-icon SRP155373
Transcriptome analysis of murine B cell and CLL samples
  • organism-icon Mus musculus
  • sample-icon 14 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Transcriptional profiling revealed that murine VH11 and non-VH11 CLL differed in the upregulation of specific pathways implicated in cell signaling and metabolism. We identified a gene expression signature (including Ccdc88a, Clip3, Zcchc18, Chd3 and Itm2a) that was significantly upregulated in T cell-dependent non-VH11 CLL compared with T cell-independent VH11/Vk14 or mutated IgH.TEµ CLL. Overall design: biological replicate (n=3-4) RNA-Seq experiments Please note that the ''countTable_exons_def_norm_rpkm_all.txt'' contains the ''FPKM'' column headers (as a default output setting for the HOMER software package). However, the .txt file contains RPKM value as described in the sample data processing field.

Publication Title

Identification of Distinct Unmutated Chronic Lymphocytic Leukemia Subsets in Mice Based on Their T Cell Dependency.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon GSE98640
Expression data from human CD8+ T cell subsets, defined using CD27 and CD45RA
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

CD27 and CD45RA can be used to split T cells into 4 subsets, nave cells, CD27+CD45RA+, central memory cells CD27+CD45RA-, effector memory cells CD27-CD45RA-, effector memory CD45RA re-expressing cell, CD27-CD45RA+. It is with in this final EMRA subset that it is belived the senenscent T cells reside. Cellular senescence is accompanied by a senescence-associated secretory phenotype (SASP), to date a SASP has not been demonstrated in T cells.

Publication Title

Human CD8<sup>+</sup> EMRA T cells display a senescence-associated secretory phenotype regulated by p38 MAPK.

Sample Metadata Fields

Sex

View Samples
accession-icon GSE156249
Comparative transcriptome analysis of human skeletal muscle in response to cold acclimation and exercise training in human volunteers.
  • organism-icon Homo sapiens
  • sample-icon 50 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Comparative transcriptome analysis of human skeletal muscle in response to cold acclimation and exercise training in human volunteers.

Sample Metadata Fields

Sex, Disease, Subject, Time

View Samples
accession-icon GSE156247
Comparative transcriptome analysis of human skeletal muscle in response to cold acclimation and exercise training in human volunteers. [A294]
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

Background: Cold acclimation and exercise training were previously shown to increase peripheral insulin sensitivity in human volunteers with type 2 diabetes. Although cold is a potent activator of brown adipose tissue, the increase in peripheral insulin sensitivity by cold is largely mediated by events occurring in skeletal muscle and at least partly involves GLUT4 translocation, as is also observed for exercise training. Results: To investigate if cold acclimation and exercise training overlap in the molecular adaptive response in skeletal muscle, we performed transcriptomics analysis on vastus lateralis muscle collected from human subjects before and after 10 days of cold acclimation, as well as before and after a 12-week exercise training intervention. Methods: Cold acclimation altered the expression of 756 genes (422 up, 334 down, P<0.01), while exercise training altered the expression of 665 genes (444 up, 221 down, P<0.01). Principal Component Analysis, Venn diagram, similarity analysis and Rank–rank Hypergeometric Overlap all indicated significant overlap between cold acclimation and exercise training in upregulated genes, but not in downregulated genes. Overlapping gene regulation was especially evident for genes and pathways associated with extracellular matrix remodeling. Interestingly, the genes most highly induced by cold acclimation were involved in contraction and in signal transduction between nerve and muscle cells, while no significant changes were observed in genes and pathways related to insulin signaling or glucose metabolism. Conclusions: Overall, our results indicate that cold acclimation and exercise training have overlapping effects on gene expression in human skeletal muscle, but strikingly these overlapping genes are designated to pathways related to cell remodeling rather than metabolic pathways.

Publication Title

Comparative transcriptome analysis of human skeletal muscle in response to cold acclimation and exercise training in human volunteers.

Sample Metadata Fields

Sex, Disease, Subject, Time

View Samples
accession-icon GSE156248
Comparative transcriptome analysis of human skeletal muscle in response to cold acclimation and exercise training in human volunteers. [A391]
  • organism-icon Homo sapiens
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

Background: Cold acclimation and exercise training were previously shown to increase peripheral insulin sensitivity in human volunteers with type 2 diabetes. Although cold is a potent activator of brown adipose tissue, the increase in peripheral insulin sensitivity by cold is largely mediated by events occurring in skeletal muscle and at least partly involves GLUT4 translocation, as is also observed for exercise training. Results: To investigate if cold acclimation and exercise training overlap in the molecular adaptive response in skeletal muscle, we performed transcriptomics analysis on vastus lateralis muscle collected from human subjects before and after 10 days of cold acclimation, as well as before and after a 12-week exercise training intervention. Methods: Cold acclimation altered the expression of 756 genes (422 up, 334 down, P<0.01), while exercise training altered the expression of 665 genes (444 up, 221 down, P<0.01). Principal Component Analysis, Venn diagram, similarity analysis and Rank–rank Hypergeometric Overlap all indicated significant overlap between cold acclimation and exercise training in upregulated genes, but not in downregulated genes. Overlapping gene regulation was especially evident for genes and pathways associated with extracellular matrix remodeling. Interestingly, the genes most highly induced by cold acclimation were involved in contraction and in signal transduction between nerve and muscle cells, while no significant changes were observed in genes and pathways related to insulin signaling or glucose metabolism. Conclusions: Overall, our results indicate that cold acclimation and exercise training have overlapping effects on gene expression in human skeletal muscle, but strikingly these overlapping genes are designated to pathways related to cell remodeling rather than metabolic pathways.

Publication Title

Comparative transcriptome analysis of human skeletal muscle in response to cold acclimation and exercise training in human volunteers.

Sample Metadata Fields

Sex, Disease, Subject, Time

View Samples
accession-icon GSE85695
Identification of Super-enhancer-associated Cancer Genes Provides Novel Therapeutic Targets in Adult T-cell Leukemia/Lymphoma
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Enhancer profiling identifies critical cancer genes and characterizes cell identity in adult T-cell leukemia.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE85694
Microarray gene expression analysis after THZ1 treatment in TL-Om1 cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Microarray gene expression profiling was performed in an adult T-cell leukemia/lymphoma cell line (TL-Om1) to analyze genes regulated by the THZ1 CDK7 inhibitor.

Publication Title

Enhancer profiling identifies critical cancer genes and characterizes cell identity in adult T-cell leukemia.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE54219
Molecular genomic and transcriptomic profiling of familial breast cancer.
  • organism-icon Homo sapiens
  • sample-icon 155 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Genomic profiling of CHEK2*1100delC-mutated breast carcinomas.

Sample Metadata Fields

Specimen part

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accession-icon SRP042975
Phagocytosis of mycobacteria by zebrafish macrophages is dependent on the scavenger receptor Marco, a key control factor of pro-inflammatory signalling
  • organism-icon Danio rerio
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Scavenger receptors on the cell surface of macrophages play an important role in host defence through their ability to bind microbial ligands and induce phagocytosis. Concurrently, signal transduction pathways are initiated that aid in defence mechanisms against the invading microbe. Here we report on the function of scavenger receptor Marco (macrophage receptor with collagenous structure) during infection of zebrafish embryos with Mycobacterium marinum, a close relative of Mycobacterium tuberculosis. Morpholino knockdown demonstrates that Marco is required for the rapid phagocytosis of M. marinum following intravenous infection. Furthermore, gene expression analysis shows that Marco controls the initial transient pro-inflammatory response to M. marinum and remains a determining factor for the immune response signature at later stages of infection. Increased bacterial burden following marco knockdown indicates that this scavenger receptor is important for control of M. marinum growth, likely due to delayed phagocytosis and reduced pro-inflammatory signalling observed under conditions of Marco deficiency Overall design: Embryos were injected at the one cell stage with a morpholino targeting marco, or with the standard control morpholino from GeneTools for comparison. Subsequently, at 24 hours post fertilization (hpf) the morphants and their controls were manually dechorionated at 24 hpf and at 28 hpf they were infected by injecting 200 colony forming units of M. marinum Mma20 into the caudal vein, or mock-injected with PBS/2%PVP. After injections embryos were transferred into fresh egg water containing 0.003% 1-phenyl-2-thiourea (Sigma-Aldrich) to prevent melanization and incubated for 4 days at 28°C. After the incubation period, infected and uninfected morphants, mutants and their controls were imaged and groups of 30 embryos were snap-frozen in liquid nitrogen and RNA was isolated for Illumina RNAseq analysis.

Publication Title

Phagocytosis of mycobacteria by zebrafish macrophages is dependent on the scavenger receptor Marco, a key control factor of pro-inflammatory signalling.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP068026
Transcriptomic approaches in the zebrafish model for tuberculosis – insights into host- and pathogen-specific determinants of the innate immune response
  • organism-icon Danio rerio
  • sample-icon 72 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

Both embryonic and adult zebrafish Mycobacterium marinum infection studies have contributed to our knowledge of the development and function of tuberculous granulomas, which are typical for mycobacterial pathogenesis. In this review we discuss how transcriptome profiling studies have helped to characterize this infection process and we include new RNA sequencing (RNA-Seq) data that reveals three main phases in the host response to M. marinum during the early stages of granuloma development in zebrafish embryos and larvae. The late-phase response shares common components with the strong and acute host transcriptome response that has previously been reported for S. typhimurium infection in zebrafish embryos. In contrast, the early/mid-phase response to M. marinum infection, characterized by suppressed pro-inflammatory signaling, is strikingly different from the acute response to S. typhimurium infection. Furthermore, M. marinum infection shows a collective and strongly fluctuating regulation of lipoproteins, while S. typhimurium infection has pronounced effects on amino acid metabolism and glycolysis. Overall design: Embryos were infected at 28 hpf by injecting 250 colony forming units of M. marinum Mma20 in 2%PVP into the caudal vein, or mock-injected with PBS/2%PVP. After injections, embryos were transferred into fresh egg water containing 0.003% 1-phenyl-2-thiourea (Sigma-Aldrich) to prevent melanization and incubated at 28°C. After the incubation period, infected and uninfected groups of 30 embryos were snap-frozen in liquid nitrogen and RNA was isolated for Illumina RNAseq analysis. Samples were taken at the following timepoints: 2, 4, 6, 8 hpi and 1, 2, 3, 4, 5 dpi.

Publication Title

Transcriptomic Approaches in the Zebrafish Model for Tuberculosis-Insights Into Host- and Pathogen-specific Determinants of the Innate Immune Response.

Sample Metadata Fields

No sample metadata fields

View Samples
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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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