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accession-icon DRP001187
Simultaneous RNA-seq of bone marrow derived dendritic cells from Mus Musculus strain C57BL6/J activated with lipopolysaccharide over a period of 24 hours.
  • organism-icon Mus musculus
  • sample-icon 29 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

The innate immune response is primarily mediated by the Toll-like receptors functioning through the Myd88-dependent and TRIF-dependent pathways. Despite being widely studied, it is not yet completely understood and systems-level analyses have been lacking. In this study, we identified a high-probability network of genes activated during the innate immune response using a novel approach to analyze time course gene expression profiles of activated immune cells in combination with a large gene regulatory and protein-protein interaction network. We classified the immune response into three consecutive time-dependent stages and identified the most probable paths between genes showing a significant change in expression at each stage. The resultant network contained several novel and known regulators of the innate immune response, many of which did not show any observable change in expression at the sampled time points. The response network shows the dominance of genes from specific functional classes during different stages of the immune response. It also suggests a role for the protein phosphatase 2a catalytic subunit a in the regulation of the immunoproteasome during the late phase of the response. In order to clarify the differences between the Myd88-dependent and TRIF-dependent pathways in the innate immune response, time course gene expression profiles from Myd88-knockout and TRIF-knockout dendritic cells were analyzed. Their response networks suggest the dominance of the MyD88 dependent pathway in the innate immune response, and an association of the circadian regulators and immunoproteasomal degradation with the TRIF-dependent pathway. The response network presented here provides the most probable associations between genes expressed in the early and the late phases of the immune response, while taking into account the intermediate regulators. We propose that the method described here can also be used in the identification of time-dependent gene subnetworks in other biological systems.

Publication Title

Discovery of Intermediary Genes between Pathways Using Sparse Regression.

Sample Metadata Fields

No sample metadata fields

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accession-icon DRP003223
transcriptome analysis of Y14-kockdown HeLa cells
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

To investigate whether the EJC regulates pre-mRNA splicing, we performed a transcriptome analysis of Y14-kockdown HeLa cells using next generation RNA-sequencing.

Publication Title

No associated publication

Sample Metadata Fields

Cell line

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accession-icon SRP013931
Initial analysis of transcript levels in zebrafish with advancing age
  • organism-icon Danio rerio
  • sample-icon 20 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

This project aims at an initial characterization of changes in gene expression in zebrafish with advancing age. Transcript levels are determined in several tissues of zebrafish with differing ages using RNA-seq. Differentially expressed genes are determined to pinpoint genes that are differently regulated in young and old zebrafish. Results will be compared with other species to identify common pathways of ageing.

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP039085
Homo sapiens strain:HL-60 Transcriptome or Gene expression
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

Transcriptome of human HL-60 and HEK-293 cells depending on culture cell density

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE61864
Expression data from prostate tumors of TRAMPxPWK/PhJ F2 cross
  • organism-icon Mus musculus
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

We hypothesize that germline variation influences susceptibility to aggressive prostate tumor

Publication Title

GNL3 and SKA3 are novel prostate cancer metastasis susceptibility genes.

Sample Metadata Fields

Specimen part

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accession-icon GSE53979
Expression data from MDA-MB-231 cells over-expressing RRP1B and MDA-MB-231 control cells with endogenous RRP1B levels
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

RRP1B is a breast cancer metastasis suppressor that interacts with various regulators of gene transcription

Publication Title

Metastasis-associated protein ribosomal RNA processing 1 homolog B (RRP1B) modulates metastasis through regulation of histone methylation.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE65824
Expression data from Mvt-1 clonal isolates over-expressing Ndn 50T or Ndn 50C
  • organism-icon Mus musculus
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Ndn is a candidate metastasis suppressor gene that has been reported to regulate transcription.

Publication Title

Necdin is a breast cancer metastasis suppressor that regulates the transcription of c-Myc.

Sample Metadata Fields

Cell line

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accession-icon GSE44029
Expression data from SW480 cells with Gankyrin knockdown
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

we performed genome-wide screening using SW480 cells with Gankyrin knockdown on an Affymetrix gene expression array to identify the transcriptional targets of Gankyrin

Publication Title

Gankyrin activates IL-8 to promote hepatic metastasis of colorectal cancer.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE35665
Genome-wide expression analysis in Down syndrome: insight into immunodeficiency
  • organism-icon Homo sapiens
  • sample-icon 37 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Down syndrome (DS) is caused by triplication of Human chromosome 21 (Hsa21) and associated with an array of deleterious phenotypes, including mental retardation, heart defects and immunodeficiency. Genome-wide expression patterns of uncultured peripheral blood cells are useful to understanding of DS-associated immune dysfunction. We used a Human Exon microarray to characterize gene expression in uncultured peripheral blood cells derived from DS individuals and age-matched controls from two age groups: neonate (N) and child (C). A total of 174 transcript clusters (gene-level) with eight located on Hsa21 in N group and 383 transcript clusters including 56 on Hsa21 in C group were significantly dysregulated in DS individuals. Microarray data were validated by quantitative polymerase chain reaction. Functional analysis revealed that the dysregulated genes in DS were significantly enriched in two and six KEGG pathways in N and C group, respectively. These pathways included leukocyte trans-endothelial migration, B cell receptor signaling pathway and primary immunodeficiency, etc., which causally implicated dysfunctional immunity in DS. Our results provided a comprehensive picture of gene expression patterns in DS at the two developmental stages and pointed towards candidate genes and molecular pathways potentially associated with the immune dysfunction in DS.

Publication Title

Genome-wide expression analysis in Down syndrome: insight into immunodeficiency.

Sample Metadata Fields

Sex, Age, Specimen part, Disease

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accession-icon E-MEXP-1006
Transcription profiling time series of finite life span and immortal non-malignant human mammary epithelial cell lines
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

We analyzed gene expression in 184 (finite life span) and HMT3522 S1 (immortal non-malignant) HMECs on successive days (3, 5, and 7) post-seeding in a laminin-rich extracellular matrix assay. Both HMECs underwent growth arrest in G0/G1 and differentiated into polarized acini between days 5 and 7.

Publication Title

Gene expression signature in organized and growth-arrested mammary acini predicts good outcome in breast cancer.

Sample Metadata Fields

Sex, Specimen part, Cell line, Time

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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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Developed by the Childhood Cancer Data Lab

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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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