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accession-icon GSE34117
Expression Data from the Riesling grape must fermentation by industrial M2 and M2 nsf1 S. cerevisiae strains for functional characterization of the NSF1 (YPL230W) gene via Correlation Clustering-based method
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 14 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

The main objectives of this study were to expand our understanding of NSF1 gene function in industrial S. cerevisiae M2 strain during fermentation by finding the largest maximal clique of co-expressed genes (i.e. Interdependent Correlation Cluster), and to establish the impact of Nsf1p on genome-wide gene expression during the fermentation process with possible implications related to wine quality and S. cerevisiae adapation to stressful fermentation conditions

Publication Title

Functional analyses of NSF1 in wine yeast using interconnected correlation clustering and molecular analyses.

Sample Metadata Fields

Time

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accession-icon GSE8536
The response of Saccharomyces cerevisiae to stress throughout a 15-day wine fermentation
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome S98 Array (ygs98)

Description

We used genome-wide expression analyses to study the response of Saccharomyces cerevisiae to stress throughout a 15-day wine fermentation. Forty percent of the yeast genome significantly changed expression levels to mediate long-term adaptation to an environment in which ethanol is both a stressor and a carbon source. Within this set, we identify a group of 223 genes, designated as the Fermentation Stress Response (FSR), that are dramatically and permanently induced; FSR genes exhibited changes ranging from four-to eighty-fold. The FSR is novel; 62% of the genes involved have not been implicated in global stress responses and 28% of the genes have no functional annotation. Genes involved in respiratory metabolism and gluconeogenesis were expressed during fermentation despite the presence of high concentrations of glucose. Ethanol, rather than nutrient depletion, was responsible for entry of yeast cells into stationary phase. Ethanol seems to regulate yeast metabolism through hitherto undiscovered regulatory networks during wine fermentation.

Publication Title

Dynamics of the yeast transcriptome during wine fermentation reveals a novel fermentation stress response.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE57140
Expression data of Col:LUC Arabidopsis treated with antimycin A (AA) in the presence or absence of a synthetic auxin analogue
  • organism-icon Arabidopsis thaliana
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Mitochondrial stress stimuli such as AA caused a transient suppression of auxin signaling and conversely, auxin treatment represses a part of the response to AA treatment.

Publication Title

A Functional Antagonistic Relationship between Auxin and Mitochondrial Retrograde Signaling Regulates Alternative Oxidase1a Expression in Arabidopsis.

Sample Metadata Fields

Treatment

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accession-icon GSE48488
Expression data of WT and Attim17-1 Arabidopsis seeds during stratification and germination
  • organism-icon Arabidopsis thaliana
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

The translocase of the inner membrane 17-1 (Tim17-1) plays a defined role in germination in Arabidopsis thaliana

Publication Title

The mitochondrial protein import component, TRANSLOCASE OF THE INNER MEMBRANE17-1, plays a role in defining the timing of germination in Arabidopsis.

Sample Metadata Fields

Specimen part, Time

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accession-icon GSE73489
Gene expression profiling from pooled samples of liver tissue of liver MyD88 WT mice and MyD88 liver specific KO mice fed either with a control diet or a high-fat diet.
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Mice wild type or knocked-out for the MyD88 gene specifically in liver, were recruited for this expression profiling experiment. Each group of mice (WT versus LKO) were fed with a control diet or a high fat diet. Then mice were sacrificed and liver samples form were processed for RNA extraction. Total liver RNA of each sample was then pooled with those of the same group and treatment for microarray hybridization.

Publication Title

Hepatocyte MyD88 affects bile acids, gut microbiota and metabolome contributing to regulate glucose and lipid metabolism.

Sample Metadata Fields

Age, Specimen part

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accession-icon GSE17375
Gene expression in colon cancer stem cells (CSC) cultures identified by Wnt signaling levels
  • organism-icon Homo sapiens
  • sample-icon 1 Downloadable Sample
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Primary colon CSC cultures were transduced with a Wnt responsive construct (TOP-GFP) and were single cell cloned. 10% highest and lowest TOP-GFP cell fractions were FACS sorted and arrayed.

Publication Title

Wnt activity defines colon cancer stem cells and is regulated by the microenvironment.

Sample Metadata Fields

Specimen part

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accession-icon GSE18497
Diagnosis-relapse in ALL
  • organism-icon Homo sapiens
  • sample-icon 81 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Almost a quarter of pediatric patients with Acute Lymphoblastic Leukemia (ALL) suffer from relapses. The biological mechanisms underlying therapy response and development of relapses have remained unclear. In an attempt to better understand this phenomenon, we have analyzed 41 matched diagnosis relapse pairs of ALL patients using genomewide expression arrays (82 arrays) on purified leukemic cells. In roughly half of the patients very few differences between diagnosis and relapse samples were found (stable group), suggesting that mostly extra-leukemic factors (e.g., drug distribution, drug metabolism, compliance) contributed to the relapse. Therefore, we focused our further analysis on 20 samples with clear differences in gene expression (skewed group), reasoning that these would allow us to better study the biological mechanisms underlying relapsed ALL. After finding the differences between diagnosis and relapse pairs in this group, we identified four major gene clusters corresponding to several pathways associated with changes in cell cycle, DNA replication, recombination and repair, as well as B cell developmental genes. We also identified cancer genes commonly associated with colon carcinomas and ubiquitination to be upregulated in relapsed ALL. Thus, about half of relapses are due to selection or emergence of a clone with deregulated expression of a genes involved in pathways that regulate B cell signaling, development, cell cycle, cellular division and replication.

Publication Title

Genome-wide expression analysis of paired diagnosis-relapse samples in ALL indicates involvement of pathways related to DNA replication, cell cycle and DNA repair, independent of immune phenotype.

Sample Metadata Fields

Sex, Specimen part, Disease

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accession-icon GSE68648
Recipient myeloid cell subsets in transplanted allografts
  • organism-icon Mus musculus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Balb/c donor hearts were transplanted into C57/BL6 recipients as previously described (Corry et al, 1973). Recipient mice were treated with 250g anti-CD40L mAb for tolerance induction on days 0, 2, and 4 as previously described (Jiang et al., 2011) or left untreated. On day 5 after transplantation graft infiltrating myeloid subsets were isolated using fluorescence activated cell sorting (FACS). Affymetrix Mouse Gene arrays were run in triplicate with the samples of interest. Raw CEL file data from Affymetrix Expression Console were background corrected, normalized, and summarized using RMA.

Publication Title

DC-SIGN(+) Macrophages Control the Induction of Transplantation Tolerance.

Sample Metadata Fields

Treatment

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accession-icon SRP170629
RNA Sequencing Analysis of Intracranial Aneurysm Walls Reveals Involvement of Lysosomes and Immunoglobulins in Rupture
  • organism-icon Homo sapiens
  • sample-icon 60 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

Background and Purpose—Analyzing genes involved in development and rupture of intracranial aneurysms can enhance knowledge about the pathogenesis of aneurysms, and identify new treatment strategies. We compared gene expression between ruptured and unruptured aneurysms and control intracranial arteries. Methods—We determined expression levels with RNA sequencing. Applying a multivariate negative binomial model, we identified genes that were differentially expressed between 44 aneurysms and 16 control arteries, and between 22 ruptured and 21 unruptured aneurysms. The differential expression of 8 relevant and highly significant genes was validated using digital polymerase chain reaction. Pathway analysis was used to identify enriched pathways. We also analyzed genes with an extreme pattern of differential expression: only expressed in 1 condition without any expression in the other. Results—We found 229 differentially expressed genes in aneurysms versus controls and 1489 in ruptured versus unruptured aneurysms. The differential expression of all 8 genes selected for digital polymerase chain reaction validation was confirmed. Extracellular matrix pathways were enriched in aneurysms versus controls, whereas pathways involved in immune response and the lysosome pathway were enriched in ruptured versus unruptured aneurysms. Immunoglobulin genes were expressed in aneurysms, but showed no expression in controls. Conclusions—For rupture of intracranial aneurysms, we identified the lysosome pathway as a new pathway and found further evidence for the role of the immune response. Our results also point toward a role for immunoglobulins in the pathogenesis of aneurysms. Immune-modifying drugs are, therefore, interesting candidate treatment strategies in the prevention of aneurysm development and rupture. Overall design: RNA sequencing of 44 intracranial aneurysm samples (including 21 unruptured, 22 ruptured and 1 undetermined) and 16 control samples of the intracranial cortical artery

Publication Title

RNA Sequencing Analysis of Intracranial Aneurysm Walls Reveals Involvement of Lysosomes and Immunoglobulins in Rupture.

Sample Metadata Fields

Sex, Age, Subject

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accession-icon GSE40672
Dietary heme alters microbiota and mucosa of mouse colon without functional changes in host-microbe cross-talk.
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.1 ST Array (mogene11st)

Description

Colon cancer is a major cause of cancer deaths in Western countries and is associated with diets high in red meat. Heme, the iron-porphyrin pigment of red meat, induces cytotoxicity of gut contents which injures surface cells leading to compensatory hyperproliferation of crypt cells. This hyperproliferation results in epithelial hyperplasia which increases the risk of colon cancer. In humans, a high red-meat diet increases Bacteroides spp in feces. Therefore, we simultaneously investigated the effects of dietary heme on colonic microbiota and on the host mucosa of mice. Whole genome microarrays showed that heme injured the colonic surface epithelium and induced hyperproliferation by changing the surface to crypt signaling. Using 16S rRNA phylogenetic microarrays, we investigated whether bacteria play a role in this changed signaling. Heme increased Bacteroidetes and decreased Firmicutes in colonic contents. This shift was most likely caused by a selective susceptibility of Gram-positive bacteria to heme cytotoxic fecal water, which is not observed for Gram-negative bacteria, allowing expansion of the Gram-negative community. The increased amount of Gram-negative bacteria most probably increased LPS exposure to colonocytes, however, there is no appreciable immune response detected in the heme-fed mice. There was no functional change in the sensing of the bacteria by the mucosa, as changes in inflammation pathways and Toll- like receptor signaling were not detected. This unaltered host-microbe cross-talk indicates that the changes in microbiota did not play a causal role in the observed hyperproliferation and hyperplasia.

Publication Title

Dietary heme alters microbiota and mucosa of mouse colon without functional changes in host-microbe cross-talk.

Sample Metadata Fields

Sex, Age, Specimen part

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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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