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accession-icon GSE53957
Transcriptomic profiling of Arabidopsis exposed to E-2-hexenal
  • organism-icon Arabidopsis thaliana
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Plants are known to be responsive to volatiles, but knowledge about the molecular players involved in transducing their perception remain scarce.

Publication Title

WRKY40 and WRKY6 act downstream of the green leaf volatile E-2-hexenal in Arabidopsis.

Sample Metadata Fields

Treatment

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accession-icon GSE25628
Endometriosis transcription profiling
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

Endometriosis is a complex pathological condition in which multiple components are involved in the disease development and clinical outcome. Endometriosis is mainly an inflammatory codition estrogen-dependent, with unknown pathogenesis, that is characterized by dissemination of edometrium tissue in ectopic position (ovary or pelvic peritoneum). Two main theories rise the pathologic onset: the presence of retrograde menstruation and celomic metaplasia in the pelvic peritoneum, that can occur for development defects. Endometriosis is related not only to genetic or immunological changes and to environmental pollution factors, as the endocrine interferents. The disease phenotype results from multiple events (genetics and enviromental), thus it is difficult to find a single gene as causative while is more probable that a gene network/s might involved in the onset and mantainement of the disease state. The peculiarity of endometriosis rely on the tissue speificity manteinance in the ectopic position, where it responds to the hormone stimuli as the tissue in the eutopic position.

Publication Title

Transcriptional profiling of endometriosis tissues identifies genes related to organogenesis defects.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Subject

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accession-icon E-MEXP-1131
Transcription profiling of E2F4 double knockout mice and heterozygous littermates
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430A 2.0 Array (mouse430a2)

Description

We considered the possibility that removal of E2F4, as a key regulator of cellular quiescence, would cause systemic perturbations in the expression of E2F4 bound genes involved in cell cycle and proliferation. To test whether these pertubrations were reflected in the adult tissues' gene expression programs, we compared the gene expression profile of E2F4 double knockout mice to the gene expression found in identical tissues from E2F4 heterozygous littermates, that are phenotypically normal. We selected liver, testes, and kidney to profile by gene expression analysis, because two of these tissues are affected at some point during development when E2F4 is missing.

Publication Title

Cell cycle genes are the evolutionarily conserved targets of the E2F4 transcription factor.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage, Subject

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accession-icon SRP018886
Global analyses of how 3'' UTR-isoform choice influences mRNA stability and translational efficiency
  • organism-icon Mus musculus
  • sample-icon 14 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000, Illumina Genome Analyzer II

Description

We obtained global measurements of decay and translation rates for mammalian mRNAs with alternative 3'' untranslated regions (3'' UTRs). Overall design: 1 3P-Seq sample from 3T3 cells and 1 3P-Seq sample from mouse ES cells; 2 2P-Seq steady state and 4 2P-Seq with actinomycin D; 6 polysome fraction 2P-Seq

Publication Title

3' UTR-isoform choice has limited influence on the stability and translational efficiency of most mRNAs in mouse fibroblasts.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon SRP049508
Constraint and divergence of global gene expression in the mammalian embryo
  • organism-icon Mus musculus
  • sample-icon 174 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000, IlluminaGenomeAnalyzerIIx

Description

We profiled genome-wide gene expression of 170 individual mid-gestation (embryonic day 11.5) whole mouse embryos derived from a 2-generation interspecies mouse cross and asked to what extent genetic variation drives four important parameters of regulatory architecture: allele-specific expression (ASE), imprinting, trans-regulatory effects, and maternal effect. The inbred strain C57BL/6J and wild-derived inbred strain CAST/EiJ were used in reciprocal crosses to generate F1 embryos. F1 progeny were backcrossed to C57BL/6J in reciprocal crosses to generate 154 N2 embryos. We employed a backcross design, in which N2 offspring have genotypically distinct parents, to enable comparison of gene expression for offspring from each side of the reciprocal cross. Our findings demonstrate that genetic variation contributes to widespread gene expression differences during mammalian embryogenesis. Overall design: Transcriptome analysis of E11.5 mouse embryos: 16 F1 embryos from reciprocally crossed C57BL/6J and CastEi/J parents; and 154 N2 embryos from reciprocal backcross of F1s to the C57BL/6J parent.

Publication Title

Constraint and divergence of global gene expression in the mammalian embryo.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE18997
Transcriptional profiling of testicular biopsies with Sertoli-cell-only and spermatogonial presence
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The aim of the study was to identify in vivo spermatogonial gene expression within the context of their biological niche.

Publication Title

Screening for biomarkers of spermatogonia within the human testis: a whole genome approach.

Sample Metadata Fields

Specimen part

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accession-icon GSE35640
Identification of a predictive gene signature to recMAGE A3 antigen-specific cancer immunotherapy in metastatic melanoma and non-small-cell lung cancer
  • organism-icon Homo sapiens
  • sample-icon 64 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Purpose: To evaluate the presence of a gene expression signature present before treatment as predictive of response to treatment with MAGEA3

Publication Title

Predictive gene signature in MAGE-A3 antigen-specific cancer immunotherapy.

Sample Metadata Fields

Specimen part

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accession-icon SRP148892
Transcriptomic profiling of mock-infected primary CD4+ T cells and a model of HIV latency treated with suberoylanilide hydroxamic acid (SAHA) and Romidepsin (RMD)
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Purpose: The goal of this study is to identify host genes whose expression is perturbed in primary CD4+ T cells by histone deacetylase (HDAC) inhibitors (HDACi) SAHA and RMD, which have different potencies and specificities for various HDACs. The study aims to evaluate the effects of SAHA and RMD that may promote or inhibit reactivation of HIV provirus out of latency. Methods: Peripheral blood mononuclear cells were collected from 4 HIV-seronegative donors. CD4+ T cells were isolated and utilized to generate an in vitro model of latent HIV infection (model developed in the Spina laboratory and previously described in Spina et al., 2013). Mock-infected cells were cultured in parallel to evaluate effects of SAHA and RMD that may be dependent on the exposure of cells to virus. Following generation of the model, cells were treated with SAHA, RMD or their solvent dimethyl sulfoxide (DMSO) for 24 hours. Mock-infected cells were treated in parallel. The experiment had 4 biological replicates, 6 conditions for each, for a total of 24 samples. ERCC spikes (Thermo Fisher Scientific, Inc.) were added to cell lysates based on cell number in each sample (10 ul of 1:800 dilution per million cells). Mix 1 was used for DMSO- and mix 2 for SAHA- and RMD-treated cells. After all samples were collected, RNA was extracted and subjected to deep sequencing by Expression Analysis, Inc. Sequence reads that passed quality filters were mapped using Tophat (human genome) or Bowtie (ERCC spikes and HIV) and counted using HTSeq. ERCC spikes with the same concentration in mixes 1 and 2 were utilized to remove unwanted technical variation. Any human gene which did not achieve at least 1 count per million reads in at least 4 samples or any ERCC that did not achieve at least 5 reads in at least 4 samples was discarded. Differential gene expression analysis was performed using library EdgeR in Bioconductor R. National Center for Biotechnology Information (NCBI) HIV-1 Human Interaction Database was then searched for genes that have been implicated in controlling HIV latency. EdgeR output was used to extract expression information of the genes of interest from the NCBI database to identify genes implicated in HIV latency that were modulated by SAHA and RMD. The resulting lists were manually curated to verify relevance to HIV latency, using the Description column of the NCBI database, as well as available PubMed references. Results: Using a custom built data analysis pipeline, ~100 million reads per sample were mapped to the human genome (build hg38). After applying filtering criteria, 16058 human transcripts, 19 ERCC spikes transcripts, and HIV NL4-3 transcripts were identified with the Tophat/Bowtie and HTSeq workflow. Differential expression analysis was performed between SAHA or RMD-treated and DMSO-treated cells. In addition, differential modulation of gene expression by SAHA and RMD in the model of HIV latency and mock-infected cells was assessed using EdgeR. In mock-infected cells, SAHA upregulated 3,971 genes and downregulated 2,940 genes; RMD upregulated 5,068 genes and downregulated 4,050 genes. In the model of HIV latency, SAHA upregulated 3,498 genes and downregulated 2,904 genes; RMD upregulated 5,116 genes and downregulated 4,053 genes (FDR < 0.05). SAHA modulated 6, and RMD 11 genes differentially between mock-infected cells and the model of HIV latency. Following search of the NCBI HIV-1 Human Interaction Database, 27 genes upregulated and 29 downregulated in common between SAHA and RMD were found to be relevant to regulation of HIV latency; 31 were up- and 32 downregulated by RMD only; and 6 were up- and 2 were downregulated by SAHA only. Conclusions: This study demonstrates that SAHA and RMD, which have different potencies and specificities for HDACs, modulate a set of overlapping genes implicated in regulation of HIV latency. Some of these genes may be explored as additional host targets for improving the outcomes of “shock and kill” strategies. Overall design: Transcriptomic profiling of the in vitro model of HIV latency and mock-infected cells treated with SAHA, RMD or the solvent DMSO (N=4 donors) by deep sequencing at Expression Analysis, Inc.

Publication Title

Long non-coding RNAs and latent HIV - A search for novel targets for latency reversal.

Sample Metadata Fields

Specimen part, Treatment, Subject

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accession-icon GSE47621
Interferon-gamma critically determines dendritic cell function
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

A growing body of evidence suggests that inflammatory cytokines have a dualistic role in immunity. In this study, we sought to determine the direct effects IFN-gamma on the differentiation and maturation of human peripheral blood monocyte-derived dendritic cells (moDC). Here, we report that following differentiation of human peripheral-blood monocytes into moDCs with granulocyte-macrophage colony-stimulating factor (GM-CSF) and IL-4, interferon-gamma (IFN-gamma) induces moDC maturation and up-regulates the co-stimulatory markers CD80, CD86, CD95, and MHC Class I, enabling moDCs to effectively generate antigen-specific CD4+ and CD8+ T cell responses for multiple viral and tumor antigens. Interestingly, early exposure of monocytes to high concentrations of IFN-gamma promotes monocyte differentiation into macrophages, despite the presence of GM-CSF and IL-4. However, under low concentrations of IFN-gamma, monocytes continue to differentiate into dendritic cells possessing a unique gene-expression profile, resulting in impairments in subsequent maturation by IFN-gamma and an inability to generate effective antigen-specific CD4+ and CD8+ T cell responses compared to standard moDCs. Monocytes differentiated in the presence of low levels of IFN-gamma downregulate IFN-gamma receptor expression, impairing their response to an inflammatory rechallenge. These findings demonstrate the ability of IFN-gamma to impart differential programs on human moDCs which shape the antigen-specific T cell responses they induce. Timing and intensity of exposure to IFN-gamma can thus determine whether moDCs are tolerogenic or immunostimulating.

Publication Title

Timing and intensity of exposure to interferon-γ critically determines the function of monocyte-derived dendritic cells.

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE58190
Tumor-mast cell transcriptional interactions in malignant pleural effusion
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st), Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Mast cells mediate malignant pleural effusion formation.

Sample Metadata Fields

Specimen part, Cell line

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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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