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accession-icon SRP063837
Genome-wide analysis of 6 month old hippocampal gene expression in Ogg1- and/or Mutyh-deficent mice
  • organism-icon Mus musculus
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Oxidative DNA damage has been associated with cognitive decline. The Ogg1 and Mutyh DNA glycosylases cooperate to prevent mutations caused by 8-oxoG, a major premutagenic oxidative DNA base lesion. Here, we have examined behavior and cognitive function in mice deficient of these glycosylases. We found that Ogg1-/-Mutyh-/- mice were more active and less anxious and that their learning ability was impaired. In contrast, Mutyh-/- mice showed moderately improved memory compared to WT. There was no change in genomic 8-oxoG levels, suggesting that Ogg1 and Mutyh play minor roles in global repair in adult brain. Notably, transcriptome analysis of hippocampus revealed that differentially expressed genes in the mutant mice belong to pathways known to be involved in anxiety and cognitive function. Thus, beyond their involvement in DNA repair, Ogg1 and Mutyh modulate cognitive function and behavior, and related hippocampal gene expression, suggesting a novel role for 8-oxoG in regulating adaptive behavior. Overall design: The mRNA profiles from hippocampus of WT, Ogg1-/-, Mutyh-/- and Ogg1-/- Mutyh-/- C57BL/6 mice at 6month of age were generated by RNA sequencing using Illumina Hiseq 2000

Publication Title

Synergistic Actions of Ogg1 and Mutyh DNA Glycosylases Modulate Anxiety-like Behavior in Mice.

Sample Metadata Fields

Age, Specimen part, Cell line, Subject

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accession-icon GSE145460
Expression data from INS1E cells stimulated with vitamin D metabolites and glucose
  • organism-icon Rattus norvegicus
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Gene 1.0 ST Array (ragene10st)

Description

Studies have shown that vitamin D can enhance glucose-stimulated insulin secretion (GSIS) and change the expression of genes in pancreatic β-cells. Still the mechanisms linking vitamin D and GSIS are unknown.

Publication Title

Vitamin D metabolites influence expression of genes concerning cellular viability and function in insulin producing β-cells (INS1E).

Sample Metadata Fields

Specimen part, Cell line, Treatment

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accession-icon GSE2430
Azithromycin-treated PAO1 vs untreated PAO1
  • organism-icon Pseudomonas aeruginosa
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

Experimental Design

Publication Title

Quorum-sensing antagonistic activities of azithromycin in Pseudomonas aeruginosa PAO1: a global approach.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE72088
Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity
  • organism-icon Mus musculus
  • sample-icon 177 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302), miRCURY LNA microRNA Array, 5th and 7th generation combined - hsa, mmu & rno (miRBase 19.0)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity.

Sample Metadata Fields

Specimen part, Compound

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accession-icon GSE72081
Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity (mRNA)
  • organism-icon Mus musculus
  • sample-icon 177 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The well-defined battery of in vitro systems applied within chemical cancer risk assessment is often characterised by a high false-positive rate, thus repeatedly failing to correctly predict the in vivo genotoxic and carcinogenic properties of test compounds. Toxicogenomics, i.e. mRNA-profiling, has been proven successful in improving the prediction of genotoxicity in vivo and the understanding of underlying mechanisms. Recently, microRNAs have been discovered as post-transcriptional regulators of mRNAs. It is thus hypothesised that using microRNA response-patterns may further improve current prediction methods. This study aimed at predicting genotoxicity and non-genotoxic carcinogenicity in vivo, by comparing microRNA- and mRNA-based profiles, using a frequently applied in vitro liver model and exposing this to a range of well-chosen prototypical carcinogens. Primary mouse hepatocytes (PMH) were treated for 24 and 48h with 21 chemical compounds [genotoxins (GTX) vs. non-genotoxins (NGTX) and non-genotoxic carcinogens (NGTX-C) versus non-carcinogens (NC)]. MicroRNA and mRNA expression changes were analysed by means of Exiqon and Affymetrix microarray-platforms, respectively. Classification was performed by using Prediction Analysis for Microarrays (PAM). Compounds were randomly assigned to training and validation sets (repeated 10 times). Before prediction analysis, pre-selection of microRNAs and mRNAs was performed by using a leave-one-out t-test. No microRNAs could be identified that accurately predicted genotoxicity or non-genotoxic carcinogenicity in vivo. However, mRNAs could be detected which appeared reliable in predicting genotoxicity in vivo after 24h (7 genes) and 48h (2 genes) of exposure (accuracy: 90% and 93%, sensitivity: 65% and 75%, specificity: 100% and 100%). Tributylinoxide and para-Cresidine were misclassified. Also, mRNAs were identified capable of classifying NGTX-C after 24h (5 genes) as well as after 48h (3 genes) of treatment (accuracy: 78% and 88%, sensitivity: 83% and 83%, specificity: 75% and 93%). Wy-14,643, phenobarbital and ampicillin trihydrate were misclassified. We conclude that genotoxicity and non-genotoxic carcinogenicity probably cannot be accurately predicted based on microRNA profiles. Overall, transcript-based prediction analyses appeared to clearly outperform microRNA-based analyses.

Publication Title

Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity.

Sample Metadata Fields

Specimen part, Compound

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accession-icon GSE57132
Evaluating mRNA and microRNA profiles reveals discriminative and compound-specific responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes
  • organism-icon Mus musculus
  • sample-icon 56 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302), miRCURY LNA microRNA Array, 5th and 7th generation combined - hsa, mmu & rno (miRBase 19.0)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Evaluating microRNA profiles reveals discriminative responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes.

Sample Metadata Fields

Specimen part, Compound

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accession-icon GSE57129
Evaluating microRNA profiles reveals discriminative responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes [Affymetrix]
  • organism-icon Mus musculus
  • sample-icon 56 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The study investigated differential gene expression in primary mouse hepatocyte mRNA following 24 and 48 hours of exposure to aflatoxin B1, cisplatin, benzo(a)pyrene, 2,3,7,8-tetrachloordibenzo-p-dioxine, cyclosporin A or Wy-14,643 or their responsive solvent. Three (four for Wy-14,643) biological replicates per compound/solvent.

Publication Title

Evaluating microRNA profiles reveals discriminative responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes.

Sample Metadata Fields

Specimen part, Compound

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accession-icon GSE7764
mRNA expression profiles of resting and IL-15 activated murine NK cells
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Murine NK cells were compared at rest and following 24 hours of IL-15 stimulation for their mRNA expression profiles on the Affymetrix MOE430_2 microarray platform. Additional comparators included resting bulk splenocytes.

Publication Title

Acquisition of murine NK cell cytotoxicity requires the translation of a pre-existing pool of granzyme B and perforin mRNAs.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE16924
Determining direct targets of the bHLH MIST1
  • organism-icon Homo sapiens
  • sample-icon 5 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The transcription factor MIST1 is required for final maturation of secretory cells of diverse tissues, including gastric digestive-enzyme secreting zymogenic (chief) cells (ZCs). Here, we show that MIST1 directly activates RAB26, RAB3D and several other genes.

Publication Title

RAB26 and RAB3D are direct transcriptional targets of MIST1 that regulate exocrine granule maturation.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon SRP106454
Parental exposure to gamma radiation causes progressively altered transcriptomes that are linked to adverse effects in zebrafish offspring
  • organism-icon Danio rerio
  • sample-icon 14 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq4000

Description

In zebrafish, parental exposure to ionizing radiation has been associated with effects in offspring, such as increased DNA damage and reactive oxygen species. Here, we assessed short (one month) and long term effects (one year) on gene expression in embryonic offspring (5.5 hours post fertilization) from zebrafish exposed during gametogenesis to gamma radiation (8.7 or 53 mGy/h for 27 days, total dose 5.2 or 31 Gy). One month after exposure, a global change in gene expression was observed in offspring from the 53 mGy/h group, followed by embryonic death at late gastrula, whereas offspring from the 8.7 mGy/h group was unaffected. One year after exposure, embryos from the 8.7 mGy/h group exhibited 2455(61.8% downregulated) differentially expressed genes. Overlaps in differentially expressed genes and enriched biological pathways were evident between the 53 mGy/h group one month and 8.7 mGy/h one year after exposure, which could be linked to effects in adults and offspring, such as DNA damage and lipid peroxidation. Interestingly, pathways between the two groups were oppositely regulated. Our results indicate latent effects following ionizing radiation exposure in parents that can be transmitted to offspring and warrants monitoring effects over subsequent generations. Overall design: One month after exposure, mRNA from F1 5.5 hpf embryos from parents exposed to 8.7 and 53 mGy/h gamma radiation during gametogenesis was sequenced on the Illumina 4000 platform with three replicas per treatment. One year after exposure, mRNA from F1 embryos from the same parents exposed to 8.7 mGy/h was sequenced with three biological replicates. In both cases, F1 embryos from non-exposed parents were used as control and mRNA sequenced in triplicates, taken at the same time points as the exposed samples.

Publication Title

Parental exposure to gamma radiation causes progressively altered transcriptomes linked to adverse effects in zebrafish offspring.

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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