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accession-icon SRP070776
Activin A regulates human T follicular helper (Tfh) cell differentiation
  • organism-icon Homo sapiens
  • sample-icon 28 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

To determine the role of the cytokine activin A in the regulation of human T follicular helper (Tfh) cell gene program, we performed a transcriptomic analysis (RNA-seq) of human naïve CD4 T cells differentiated in vitro with activin A. The analysis of the gene expression profile driven by activin A, alone or in combination with IL-12 (a know regulator of human Tfh differentiation/function), revealed that activin A can regulate the expression of multiple molecules involved in the differentiation and/or function of human Tfh cells. Overall design: Human naïve CD4 T cells were isolated from fresh PBMCs of healthy control subjects by magnetic bead isolation. Purity was measured by FACS as percentage of CD4+CD45RA+ cells and was 95% or higher. Upon isolation, naïve CD4 T cells were stimulated with anti-CD3/CD28 coated beads in the presence of the following cytokine combinations: no exogenous cytokines (beads only), activin A, IL-12, activin A+IL-12, TGFb, TGFb +IL12. Following 5 days of in vitro culture, live CD4 T cells were FACS sorted and gene expression was analyzed by RNA-seq. Data are from independent donors.

Publication Title

Activin A programs the differentiation of human TFH cells.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE36035
Expression data from melanoma subpopulations
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We aimed at identifying lymphangiogenic subpopulations by comparative analysis of single cell clones derived from a melanoma of a single patient. Selected clones were grafted into SCID mice, where they induced lymphangiogenesis and metastasized into sentinel nodes, whereas non-lymphangiogenic clones from the same patient did not metastasize. RNA isolated from primary SCID mouse tumors were used for transcriptome analysis.

Publication Title

MET expression in melanoma correlates with a lymphangiogenic phenotype.

Sample Metadata Fields

No sample metadata fields

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accession-icon E-MTAB-125
Transcription profiling of mouse erythroleukemia cells following activation of Gata1-ER or PU.1-ER transgenes
  • organism-icon Mus musculus
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

17b-Estradiol added to MEL cells expressing Gata1-ER or PU.1-ER transgenes to stimulate either erythropoietic Gata-1 dependent or myeloid PU.1 dependent gene espression in different time points

Publication Title

PU.1 activation relieves GATA-1-mediated repression of Cebpa and Cbfb during leukemia differentiation.

Sample Metadata Fields

Disease, Disease stage

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accession-icon GSE20916
Modeling oncogenic signaling in colon tumors by multidirectional analyses of microarray data
  • organism-icon Homo sapiens
  • sample-icon 144 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Background. Most colorectal cancers (CRC) arise in a progression through adenoma to carcinoma phenotypes as a consequence of altered genetic information. Clinical progression of CRC may occur in parallel with distinctive signaling alterations. We designed multidirectional analyses integrating microarray-based data with biostatistics and bioinformatics to elucidate the signaling and metabolic alterations underlying CRC development in the adenoma-carcinoma sequence. Methodology/Principal Findings. Studies were performed on normal mucosa, adenoma, and CRC samples obtained during surgery or colonoscopy. Collections of cryostat sections prepared from the tissue samples were evaluated by a pathologist to control the relative cell type content. RNA was isolated from 105 macro- and 40 microdissected specimens. The measurements were done using Affymetrix GeneChip HG-U133plus2, and probe set data were generated using two normalization algorithms: MAS5 and GCRMA with LVS. The data were evaluated using pair-wise comparisons and data decomposition into SVD modes. The method selected for the functional analysis used the Kolmogorov-Smirnov test. Based on a consensus of the results obtained by two tissue handling procedures, two normalization algorithms, and two probe set sorting criteria, we identified six KEGG signaling and metabolic pathways (cell cycle, DNA replication, p53 signaling pathway, purine metabolism, pyrimidine metabolism, and RNA polymerase) that are significantly altered in both macro- and microdissected tumor samples compared to normal colon. On the other hand, pathways altered between benign and malignant tumors were identified only in the macrodissected tissues. Conclusion/Significance. Multidirectional analyses of microarray data allow the identification of essential signaling alterations underlying CRC development. Although the proposed strategy is computationally complex and laborintensive, it may reduce the number of false results.

Publication Title

Modeling oncogenic signaling in colon tumors by multidirectional analyses of microarray data directed for maximization of analytical reliability.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE55599
DNA methylation status is more sensitive than gene expression at detecting cancer in prostate core biopsies
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge IconIllumina HumanHT-12 V4.0 expression beadchip

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

DNA methylation status is more reliable than gene expression at detecting cancer in prostate biopsy.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE36223
Molecular defense mechanisms of Barrett's metaplasia estimated by an integrative genomics
  • organism-icon Homo sapiens
  • sample-icon 45 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Barrett's esophagus is characterized by the replacement of squamous epithelium with specialized intestinal metaplastic mucosa. The exact mechanisms of initiation and development of Barrett's metaplasia remain unknown, but a hypothesis of successful adaptation against noxious reflux components has been proposed. To search for the repertoire of adaptation mechanisms of Barrett's metaplasia, we employed high-throughput functional genomic and proteomic methods that defined the molecular background of metaplastic mucosa resistance to reflux. Transcriptional profiling was established for 23 pairs of esophageal squamous epithelium and Barrett's metaplasia tissue samples using Affymetrix U133A 2.0 GeneChips and validated by quantitative real-time polymerase chain reaction. Differences in protein composition were assessed by electrophoretic and mass-spectrometry-based methods. Among 2,822 genes differentially expressed between Barrett's metaplasia and squamous epithelium, we observed significantly overexpressed metaplastic mucosa genes that encode cytokines and growth factors, constituents of extracellular matrix, basement membrane and tight junctions, and proteins involved in prostaglandin and phosphoinositol metabolism, nitric oxide production, and bioenergetics. Their expression likely reflects defense and repair responses of metaplastic mucosa, whereas overexpression of genes encoding heat shock proteins and several protein kinases in squamous epithelium may reflect lower resistance of normal esophageal epithelium than Barrett's metaplasia to reflux components. Despite the methodological and interpretative difficulties in data analyses discussed in this paper, our studies confirm that Barrett's metaplasia may be regarded as a specific microevolution allowing for accumulation of mucosal morphological and physiological changes that better protect against reflux injury.

Publication Title

Molecular defense mechanisms of Barrett's metaplasia estimated by an integrative genomics.

Sample Metadata Fields

Sex, Age

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accession-icon GSE34215
Knockout of GPx4 gene in mouse keratinocyte
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Comparative analysis of gene expression in cultured primary keratinocytes isolated from newborn control (K14-cre; GPx4fl/+) and knockout (K14-cre; GPx4fl/fl) mice.

Publication Title

Targeted disruption of glutathione peroxidase 4 in mouse skin epithelial cells impairs postnatal hair follicle morphogenesis that is partially rescued through inhibition of COX-2.

Sample Metadata Fields

Specimen part

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accession-icon SRP198760
Systematic evaluation of RNA-Seq preparation protocol performance (RNASeq: SMARTer)
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

In this study, we present a comprehensive evaluation of four RNA-Seq library preparation methods. We used three standard input protocols, the Illumina TruSeq Stranded Total RNA and TruSeq Stranded mRNA kits, and a modified NuGEN Ovation v2 kit; and an ultra-low-input RNA protocol, the TaKaRa SMARTer Ultra Low RNA Kit v3. Our evaluation of these kits included quality control measures such as overall reproducibility, 5' and 3' end-bias, and the identification of DEGs, lncRNAs, and alternatively spliced transcripts. Overall, we found that the two Illumina kits were most similar in terms of recovering DEGs, and the Illumina, modified NuGEN, and TaKaRa kits allowed identification of a similar set of DEGs. However, we also discovered that the Illumina, NuGEN and TaKaRa kits each enriched for different sets of genes. Overall design: Two mESC cell lines (biological replicates) from Zbtb24 knockout (1lox/1lox) clones are compared with two wild-type (2lox/+) clones (biological replicates) using the TaKaRa SMARTer Ultra Low RNA protocol directly on cells with no RNA preparation step. Total RNA from 100 mESCs cells and 1000 mESCs cells or approximately 1 and 10 ng RNA were used respectively.

Publication Title

Systematic evaluation of RNA-Seq preparation protocol performance.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP198761
Systematic evaluation of RNA-Seq preparation protocol performance (RNASeq: TruSeq)
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

In this study, we present a comprehensive evaluation of four RNA-Seq library preparation methods. We used three standard input protocols, the Illumina TruSeq Stranded Total RNA and TruSeq Stranded mRNA kits, and a modified NuGEN Ovation v2 kit; and an ultra-low-input RNA protocol, the TaKaRa SMARTer Ultra Low RNA Kit v3. Our evaluation of these kits included quality control measures such as overall reproducibility, 5' and 3' end-bias, and the identification of DEGs, lncRNAs, and alternatively spliced transcripts. Overall, we found that the two Illumina kits were most similar in terms of recovering DEGs, and the Illumina, modified NuGEN, and TaKaRa kits allowed identification of a similar set of DEGs. However, we also discovered that the Illumina, NuGEN and TaKaRa kits each enriched for different sets of genes. Overall design: Three mESC cell lines (biological replicates) from Zbtb24 knockout (1lox/1lox) clones are compared with three wild-type (2lox/+) clones (biological replicates) using the TruSeq mRNA protocol.

Publication Title

Systematic evaluation of RNA-Seq preparation protocol performance.

Sample Metadata Fields

Specimen part, Cell line, Subject

View Samples
accession-icon SRP072993
Targeted deletion of an Nr4a1­ associated enhancer ablates Ly6Clow monocytes while protecting pleiotropic gene function in macrophages [RNA-seq]
  • organism-icon Mus musculus
  • sample-icon 11 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Mononuclear phagocytes are a diverse cell family that occupy all tissues and assume numerous functions to support tissue and systemic homeostasis. Our ability to investigate the roles of individual subsets is limited by an absence of approaches to ablate gene function within specific sub-populations. Using Nr4a1-dependent Ly6Clow monocytes as a representative cell type we show that enhancer deletion addresses these limitations. Combining ChIP-Seq and molecular approaches we identify a single, conserved, sub-domain within the Nr4a1 enhancer that is essential for Ly6Clow monocyte development. Mice lacking this enhancer lack Ly6Clow monocytes but retain Nr4a1 gene expression in macrophages during steady state and in response to LPS. Nr4a1 is a key negative regulator of inflammatory gene expression and decoupling these processes allows Ly6Clow monocytes to be studied without confounding influences. Enhancer targeting possesses greater specificity than cre recombinase-mediated gene deletion, providing a route to generate loss-of-function models in closely related cell types. Overall design: Paired End mRNA sequencing of FACS purified primary murine MDP, cMoP, Ly6Chi and Ly6Clow monocytes from the bone marrow and Ly6Chi and Ly6Clow monocytes from the peripheral blood

Publication Title

Deleting an Nr4a1 Super-Enhancer Subdomain Ablates Ly6C<sup>low</sup> Monocytes while Preserving Macrophage Gene Function.

Sample Metadata Fields

Specimen part, Cell line, Subject

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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