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accession-icon GSE56421
Corneal Gene Expression Analysis
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Transplantation of amniotic membrane-expanded limbal epithelium (AMLE) in place of donor tissue grafts results in significantly improved outcomes for patients suffering from severe limbal stem cell deficiency; however the reasons for such superior results are unclear. The purpose of this study was to identify transcriptional gene profiles specific to AMLE and donor central corneal epithelium (CE), which may contribute to the divergent clinical outcomes observed following transplant. Limbal fibroblasts which underlie the epithelium and secrete extracellular matrix proteins following injury/surgery were also profiled. Using cell culture, immunofluorescence, microarray gene expression profiling and qRT-PCR validation; this study aims to identify enriched biological processes and pathways which characterise AMLE and CE tissues. We hope the study outcomes will shed light onto the factors which contribute to provide the improved clinical outcomes associated with AMLE transplantation.

Publication Title

Comparative transcriptomic analysis of cultivated limbal epithelium and donor corneal tissue reveals altered wound healing gene expression.

Sample Metadata Fields

Specimen part

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accession-icon GSE46909
Expression data from human Jurkat T cells exposed to 31 compounds
  • organism-icon Homo sapiens
  • sample-icon 127 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Compounds with direct immunotoxic properties, including metals, mycotoxins, agricultural pesticides and industrial chemicals, form potential human health risks due to exposure through food, drinking water, and the environment. Insights into the mechanisms of action are currently lacking for the majority of these direct immunotoxicants. Therefore, the present work aimed to gain insights into the molecular mechanisms underlying direct immunotoxicity. To this end, we assessed in vitro the effects of 31 test compounds on the transcriptome of the human Jurkat T cell line. These compounds included direct immunotoxicants, immunosuppressive drugs with different mode of actions, and non-immunotoxic control chemicals. Pathway analysis of the microarray data allowed us to identify canonical pathways and Gene Ontology processes that were transcriptionally regulated in common by immunotoxicants (i) with structural similarities, such as the tributyltins TBTC and TBTO that activated the retinoic acid / X receptor (RAR / RXR) signaling pathway, and (ii) without structural similarities, such as As2O3, DBTC, diazinon, MeHg, ochratoxin A, S9 treated ochratoxin A, S9 treated cyclophosphamide, and S9 treated benzo[a]pyrene, that activated unfolded protein response, and FTY720, lindane, and propanil, that activated the cholesterol biosynthesis pathway. In addition, processes uniquely affected by individual immunotoxicants were identified, such as the induction of Notch receptor signaling and the down regulation of acute phase response genes by ochratoxin A. These findings were validated by quantitative Real-Time PCR (Q-RT-PCR) analysis of genes involved in these processes. Our study indicated that diverse modes of action are involved in direct immunotoxicity and that a set of pathways or genes, rather than one single gene can be used to screen compounds for direct immunotoxicity.

Publication Title

Toxicogenomics-based identification of mechanisms for direct immunotoxicity.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon SRP073495
RNA-sequencing of mouse knockout models for Cnp, Plp1, and Ugt8 in the frontal cortex and cerebellum
  • organism-icon Mus musculus
  • sample-icon 174 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Oligodendrocytes (OLs) and myelin are critical for normal brain function and they have been implicated in neurodegeneration. Human neuroimaging studies have demonstrated that alterations in axons and myelin occur early in Alzheimer's Disease (AD) course. However, the molecular mechanism underlying the role of OLs in AD remains largely unknown. In this study, we systematically interrogated OL-enriched gene networks constructed from large-scale genomic, transcriptomic, and proteomic data in human AD postmortem brain samples. These robust OL networks were highly enriched for genes associated with AD risk variants, including BIN1. We corroborated the structure of the AD OL coexpression and gene-gene interaction networks through ablation of genes identified as key drivers of the networks, including UGT8, CNP, MYRF, PLP1, NPC1, and NDGR1. Perturbations of these key drivers not only caused dysregulation in their associated network neighborhoods, but also mimicked pathways of gene expression dysregulation seen in human AD postmortem brain samples. In particular, the OL subnetwork controlled by the AD risk gene PSEN1 was strongly dysregulated in AD, suggesting a potential role of PSEN1 in disrupting the myelination pathway towards the onset of AD. In summary, this study built and systematically validated the first comprehensive molecular blueprint of OL dysregulation in AD, and identified key OL- and myelination-related genes and networks as potential candidate targets for the future development of AD therapies. Overall design: The mouse knockout models have been previously described for each of Ugt8 (Coetzee et al., 1996), Cnp (Lappe-Siefke et al., 2003), and Plp1 (Klugmann et al., 1997). For each of the two conditions studied (control and homozygous knockout mice), five mice of either sex were sacrificed at postnatal day 20 and brains were flashed-frozen until analysis. The frontal cortex (FC) and cerebellum (CBM) were dissected out and individually processed. RNA was isolated using Trizol reagent and processed using Ribo-Zero rRNA removal. RNA-sequencing was performed using the Illumina HiSeq2000 with 100 nucleotide paired-end reads. RNA-sequencing reads were mapped to the mouse genome (mm10, UCSC assembly) using Bowtie (version 2.2.3.0), TopHat (version 2.0.11), and SamTools (version 0.1.19.0) using a read length of 100. Reads were converted to counts at the gene level using HTSeq on the BAM files from TopHat2 using the UCSC known genes data set.

Publication Title

Multiscale network modeling of oligodendrocytes reveals molecular components of myelin dysregulation in Alzheimer's disease.

Sample Metadata Fields

Specimen part, Subject

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accession-icon E-MEXP-2401
Transcription profiling of Oryza sativa subtypes Cultivar Nagina-22 (N22) and IR64 subtypes under normal and drougth conditions
  • organism-icon Oryza sativa indica group
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Rice Genome Array (rice)

Description

High quality RNA was extracted from the whole seedlings (Combined root and leaf samples) using TRI Reagent (Ambion, Inc. USA) and pooled from 12 independent stressed and non-stressed plant samples separately, and treated with DNase-I (QIAGEN GmbH, Germany). Subsequently, RNA cleanup was carried out using RNeasy Plant Mini Kit (QIAGEN GmbH, Germany) and 5 ug of total RNA from each sample in triplicates were reverse-transcribed to double stranded cDNA using the GeneChipᆴ One-Cycle cDNA Synthesis Kit. The biotin-labelled cRNA was made using the GeneChipᆴ IVT Labelling Kit (Affymetrix, CA, USA). Twenty microgram of cRNA samples was fragmented and out of which which 7.5 ug cRNA were hybridized for 16 hours at 45C to the Affymetrix GeneChipᆴ Rice Genome Array (Santa Clara, CA, USA). After washing and staining with R-phycoerythrin streptavidin in a Fluidics Station, using the Genechipᆴ Fluidics Station 450, the arrays were scanned by the Genechipᆴ 3000 Scanner. The chip images were scanned and extracted using default settings and the CEL files were produced with the Affymetrix GeneChip Operating Software (GCOS 1.2). The resulting .CEL files were imported into the GeneSpring GX 10 (Agilent Technologies Inc, Santa Clara CA) and normalized with the PLIER16 algorithm. The resulting expression values were log2-transformed. Average log signal intensity values of three technical replicates for each sample were used for advance analysis.

Publication Title

Comparative analysis of drought-responsive transcriptome in Indica rice genotypes with contrasting drought tolerance.

Sample Metadata Fields

Specimen part

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accession-icon GSE93923
MLL is essential for NUP98-HOXA9-induced leukemia
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Rearrangements involving the NUP98 gene resulting in fusions to several partner genes occur in acute myeloid leukemia and myelodysplastic syndromes. This study demonstrates that the second FG repeat domain of the NUP98 moiety of the NUP98-HOXA9 fusion protein is important for its cell immortalization and leukemogenesis activities. We demonstrate that NUP98-HOXA9 interacts with MLL via this FG repeat domain and that, in the absence of MLL, NUP98-HOXA9-induced cell immortalization and leukemogenesis are severely inhibited. Molecular analyses indicate that MLL is important for the recruitment of NUP98-HOXA9 to the HOXA locus and for NUP98-HOXA9-induced HOXA gene expression. Our data indicate that MLL is crucial for NUP98-HOXA9 leukemia initiation.

Publication Title

MLL is essential for NUP98-HOXA9-induced leukemia.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE54868
JAK/STAT coordinates cell proliferation during disc regeneration with Dilp8-mediated developmental delay in Drosophila melanogaster
  • organism-icon Drosophila melanogaster
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Drosophila Genome 2.0 Array (drosophila2)

Description

Regeneration of fragmented Drosophila imaginal discs occurs in an epimorphic manner, involving local cell proliferation at the wound site. Following disc fragmentation, cells at the wound site activate a restoration program through wound healing, regenerative cell proliferation and repatterning of the tissue. However, the interplay of signaling cascades, driving these early reprogramming steps, is not well understood. Here we profiled the transcriptome of regenerating cells in the early phase within twenty-four hours after wounding. We found that JAK/STAT signaling becomes activated at the wound site and promotes regenerative cell proliferation in cooperation with Wingless (Wg) signaling. In addition, we demonstrated that the expression of Drosophila insulin-like peptide 8 (dilp8), which encodes a paracrine peptide to delay the onset of pupariation, is controlled by JAK/STAT signaling in early regenerating discs. Our findings suggest that JAK/STAT signaling plays a pivotal role in coordinating regenerative disc growth with organismal developmental timing.

Publication Title

During Drosophila disc regeneration, JAK/STAT coordinates cell proliferation with Dilp8-mediated developmental delay.

Sample Metadata Fields

Sex, Specimen part, Treatment

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accession-icon SRP055424
High-throughput RNA-sequencing analysis in human glioma stem cell
  • organism-icon Homo sapiens
  • sample-icon 2 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerIIx

Description

Glioblastomas show heterogeneous histological features. These distinct phenotypic states are thought to be associated with the presence of glioma stem cells (GSCs), which are highly tumorigenic and self-renewing sub-population of tumor cells that have different functional characteristics. To investigate gene expression including lncRNA (long non-coding RNA) in GSC, we have performed high-throughput RNA-sequencing (RNA-seq) experiment using Illumina GAIIx. Overall design: Profiles of gene expression including lncRNA in GSC were generated by RNA-seq using Illumina GAIIx.

Publication Title

Targeting the Notch-regulated non-coding RNA TUG1 for glioma treatment.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE42349
Integrative genomics of gene regulation by estrogen receptors and and coregulators
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Integrative genomics of gene and metabolic regulation by estrogen receptors α and β, and their coregulators.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE42347
Integrative genomics of gene and metabolic regulation by estrogen receptors and and coregulators [expression]
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A 2.0 Array (hgu133a2)

Description

The closely related transcription factors (TFs), estrogen receptors ER and ER, regulate divergent gene expression programs and proliferative outcomes in breast cancer. Utilizing MCF-7 breast cancer cells with ER, ER, or both receptors as a model system to define the basis of differing response specification by related TFs, we show that these TFs and their key coregulators, SRC3 and RIP140, generate overlapping as well as unique chromatin-binding and transcription-regulating modules.

Publication Title

Integrative genomics of gene and metabolic regulation by estrogen receptors α and β, and their coregulators.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE9936
Expression data from human breast cancer cells (MCF-7) coexpressing ERalpha and Erbeta, treated with phytoestrogens
  • organism-icon Homo sapiens
  • sample-icon 104 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133A Array (hgu133a)

Description

We used microarrays to detail the global transcriptional response mediated by ERalpha or ERbeta to the phytoestrogen genistein in the MCF-7 human breast cancer cell model.

Publication Title

Estrogen Receptors alpha and beta as determinants of gene expression: influence of ligand, dose, and chromatin binding.

Sample Metadata Fields

No sample metadata fields

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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