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accession-icon GSE84079
A comparison of the intestinal phenotype and transcriptome profile analysis in the oral-fed mice with substances to affect the intestinal homeostasis
  • organism-icon Mus musculus
  • sample-icon 15 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 2.0 ST Array (mogene20st)

Description

Epithelial cells in the intestinal mucosa maintain gut homeostasis by interacting with different types of microbiota. Proper appropriate immune responses in the intestinal epithelium are essential for the preservation of the intestinal homeostasis. In the present study, we aimed to identify genotypic and phenotypic changes in mice following oral feeding of various substances which has been shown to differentially affect intestinal homeostasis. We orally fed C57BL/6 mice for either one or seven days with one of the four substances: dextran sulfate sodium (DSS); Typhoid VI Polysaccharide vaccine (Vi vaccine); antibiotic cocktails (AB) of ampicillin, vancomycin, neomycin, and metronidazole; or(probiotics)consisting of Lactobacillus Rhamnosus R0011and L. Acidophilus R0052.While DSS and AB feeding resulted in severe gut pathology characterized by infiltration of inflammatory cells, epithelium shedding, and distortion of paneth cells. Vi vaccine and probiotics feeding resulted in phenotypic improvement of the gut health characterized by epithelial cell proliferation and increased formation of tight junctions between epithelial cells. Interestingly, microarray data showed significant increase in the expression levels of genes regulating cell proliferation and intestinal homeostasis in the gut epithelium of probiotics-and Vi vaccine-fed mice compared to DSS-or AB-fed mice. In addition, expression levels of genes regulating cell death and inflammation were significantly increased in the gut epithelium of DSS- and AB-fed mice. These results suggest that intestinal homeostasis play a pivotal role in maintaining gut health and, subsequently, in protecting host against enteric bacteria and external pathogens infection.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

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accession-icon GSE41159
Gene expression from the rice leaf elongation zone of 7th leaf under various soil moisture treatments
  • organism-icon Oryza sativa
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

Leaf rate elongation is extremely sensitive to soil water status.

Publication Title

Transcriptome profiling of leaf elongation zone under drought in contrasting rice cultivars.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE15071
Detection of genomic deletions in rice by genomic DNA hybridization to oligonucleotide microarrays
  • organism-icon Oryza sativa indica group
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

Rice deletion mutants have not been widely used in functional genomics, because the mutated genes are not tagged and therefore, difficult to identify

Publication Title

Detection of genomic deletions in rice using oligonucleotide microarrays.

Sample Metadata Fields

Specimen part

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accession-icon GSE38871
Expression data from IR64 rice transformed with 35S::OsPSTOL1 gene
  • organism-icon Oryza sativa
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

OsPSTOL1 confers phosphorus (P)-deficiency tolerance in rice through enhancement of early root growth. The larger root surface area at early stage provides the plants an advantage for nutrient uptake.

Publication Title

The protein kinase Pstol1 from traditional rice confers tolerance of phosphorus deficiency.

Sample Metadata Fields

Specimen part

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accession-icon GSE7793
Vancomycin nephrotoxicity assessed by DNA microarray
  • organism-icon Mus musculus
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The glycopeptide antibiotic vancomycin (VCM) represents one of the last lines of defense against methicillin-resistant Staphylococcus aureus infections. However, vancomycin is nephrotoxic, but the mechanism of toxicity is still unclear.

Publication Title

Gene expression analysis reveals new possible mechanisms of vancomycin-induced nephrotoxicity and identifies gene markers candidates.

Sample Metadata Fields

Specimen part

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accession-icon GSE40013
Whole saliva expression data from human populations stratified by psychosocial stress exposure
  • organism-icon Homo sapiens
  • sample-icon 46 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

The objective of this study was analysis of the whole saliva transcriptome to search for biomarkers of psychosocial stressor exposure and substance use in young adults drawn from a population-based longitudinal cohort, the Oregon Youth Substance Use Project. We conducted genome-wide gene expression analysis on whole saliva RNA from 48 individuals stratified by psychosocial stressor exposure using an Affymetrix Gene ST 1.0 array. We applied Weighted Gene Co-expression Network Analysis (WCGNA) to characterize the high-level structure in the data and to relate expression patterns among samples to participant clinical characteristics. This approach finds clusters of correlated genes (modules) which can reflect clinical, histological, or intracellular organization and function.

Publication Title

No associated publication

Sample Metadata Fields

Sex, Age, Specimen part, Race

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accession-icon GSE29673
Toxicogenomic Study of Pentamethylchromanol (PMCol)
  • organism-icon Rattus norvegicus
  • sample-icon 29 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

The objective of this study is to determine the molecular mechanisms of PMCol-induced hapatotoxicity using microarray

Publication Title

Toxicogenomics and metabolomics of pentamethylchromanol (PMCol)-induced hepatotoxicity.

Sample Metadata Fields

Specimen part, Treatment, Time

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accession-icon GSE51284
Expression data from monozygotic twins discordant for nicotine metabolism
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.1 ST Array (hugene11st)

Description

The Nicotine Metabolic Ratio (NMR), the ratio of two stable metabolites of nicotine, cotinine and trans-3hydroxycotinin, is a determinant of the number of cigarettes smoked per day (CPD), of smoking topography, responsiveness to treatment via transdermal nicotine for smoking cessation, and carcinogen activation and level. The predominant gene involved in nicotine metabolism is CYP2A6, a highly polymorphic locus located in a cluster of P450 cytochrome protein loci on chr19q13. A recent study comprehensively modeling CYP2A6 genetic variation at seven polymorphisms and a related Nicotine Metabolic Ratio, the cotinine: cotinine+nicotine ratio, explains 72% of NMRC/C+N variation. These results suggest that additional genes may be contributing to nicotine and cotinine metabolism directly or via interaction with CYP2A6 or other genes. To identify additional genes that may influence the NMR, we conducted a genome-wide gene expression analysis of lymphoblastoid cell line (LCL) gene expression in a sample of monozygotic twins discordant for the NMR.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part, Subject

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accession-icon GSE17951
Gene expression analysis of prostate cancer samples using Affymetrix U133Plus2 array
  • organism-icon Homo sapiens
  • sample-icon 153 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Over one million prostate biopsies are performed in the U.S. every year. However, pathology examination is not definitive in a significant percentage of cases due limited diagnostic tumor. We have observed that the microenvironment of prostate tumor cells exhibits numerous differential gene expression changes and have asked whether such information can be used to distinguish tumor from nontumor. We initially compared expression analysis data (Affymetrix U133plus2) from 18 volunteer biopsy specimens to 17 specimens containing largely tumor-adjacent stroma and identified 964 significant (p_adj < 0.01 and B > 0) expression changes. These genes were filtered to eliminate possible aging-related genes and genes expressed in tumor cells > 10% of the stroma cell expression level leading to 23 candidate genes (28 Affymetrix probe sets). A classifier based on the 28 probe sets was tested on 289 independent cases, including 195 tumor-bearing cases, 99 nontumor cases (normal biopsies, normal autopsies, remote stroma as well as pure tumor adjacent stroma) all with accuracies >85%, sensitivities >90% and specificities >85%. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for categorization as tumor and nontumor.

Publication Title

In silico estimates of tissue components in surgical samples based on expression profiling data.

Sample Metadata Fields

Subject

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accession-icon GSE8218
Gene expression data from prostate cancer samples
  • organism-icon Homo sapiens
  • sample-icon 125 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

Prostate cancer gene expression profiles were studied in this project. A total RNA from 148 prostate sample with various amount of different cell types were hybridized to Affymetrix U133A arrays. The percentage of different cell types vary considerably among samples and were determined by pathologist. Cell type specific genes can be determined by linear regression using the methods of Stuart et al, PNAS, 2004.

Publication Title

In silico estimates of tissue components in surgical samples based on expression profiling data.

Sample Metadata Fields

No sample metadata fields

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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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