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GSE4870
Mus musculus
45 Downloadable Samples
Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)
Description
Tissue-specific comparison of gene expression levels in T65H translocation mice, either with or without uniparental duplications of Chrs 7 & 11. Identification of highly differentially expressed transcripts.
Publication Title
Chromosome-wide identification of novel imprinted genes using microarrays and uniparental disomies.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 12 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
Hematopoietic differentiation is strictly regulated by complex network of transcription factors that are controlled by ligands binding to cell surface receptors. Disruptions of the intricate sequences of transcriptional activation and suppression of multiple genes cause hematological diseases, such as leukemias, myelodysplastic syndromes or myeloproliferative syndromes. From a clinical standpoint, deciphering the pattern of gene expression during hematopoiesis may help unravel disease-specific mechanisms in hematopoietic malignancies. Herein, we describe a human in vitro hematopoietic model system where lineage specific differentiation of CD34+ cells was accomplished using specific cytokines. Microarray and RNAseq based whole transcriptome and exome analysis was performed on the differentiated erythropoietic, granulopoietic and megakaryopoietic cells to delineate changes in expression of whole transcripts and exons. Analysis on the Human 1.0 ST exon arrays indicated differential expression of 172 genes (P< 0.0000001) and significant splicing of 86 genes during differentiation. Pathway analysis identified these genes to be involved in Rac/RhoA signaling, Wnt/B-catenin signaling and alanine/aspartate metabolism. Comparison of the microarray data to next generation RNAseq analysis during erythroid differentiation demonstrated a high degree of correlation in gene (R= 0.72) and exon (R=0. 62) expression. Our data provides a molecular portrait of events that regulate differentiation of hematopoietic cells. Knowledge of molecular processes by which the cells acquire their cell specific fate would be beneficial in developing cell-based therapies for human diseases.
Publication Title
Transcriptome profiling and sequencing of differentiated human hematopoietic stem cells reveal lineage-specific expression and alternative splicing of genes.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 2 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Comparison of gene expression levels between MatDp(dist2) and PatDp(dist2) mice (newborn whole head). Identification of highly differentially expressed transcripts.
Publication Title
Transcript- and tissue-specific imprinting of a tumour suppressor gene.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 10 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [probe set (exon) version (huex10st)
Description
Sickle cell transcriptome was analyzed using whole blood clinical specimens on the Affymetrix Human Exon 1.0 ST arrays and Illuminas deep sequencing technologies. Data analysis indicated a strong concordance (R=0.64) between exon array and RNA-seq in both gene level and exon level expression of transcripts. The magnitude of fold changes in the expression levels for the differentially expressed genes (p<0.05) was found to be higher in RNA-seq than microarrays. However, the arrays outperformed the sequencing technology in the detection of low abundant transcripts. In addition to examining the expression level changes of transcripts, RNA-seq technology was able to identify sequence variation in the expressed transcripts. We also demonstrate herein the ability of RNA-seq technology to discover novel expression outside of the annotated genes.
Publication Title
A systematic comparison and evaluation of high density exon arrays and RNA-seq technology used to unravel the peripheral blood transcriptome of sickle cell disease.
Sample Metadata Fields
Specimen part, Disease
View Samples- Mus musculus
- 1 Downloadable Sample
- Illumina MouseWG-6 v2.0 expression beadchip
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
S-adenosylmethionine levels regulate the schwann cell DNA methylome.
Sample Metadata Fields
Specimen part, Treatment
View Samples- Mus musculus
- 1 Downloadable Sample
- Illumina MouseWG-6 v2.0 expression beadchip
Description
DNA methylation is a key epigenetic regulator of mammalian embryogenesis and somatic cell differentiation. Using high-resolution genome-scale maps of methylation patterns, we show that the formation of myelin in the peripheral nervous system, proceeds with progressive DNA demethylation, which coincides with an upregulation of critical genes of the myelination process. More importantly, we found that, in addition to expression of DNA methyltransferases and demethylases, the levels of S-adenosylmethionine (SAMe), the principal biological methyl donor, could also play a critical role in regulating DNA methylation during myelination and in the pathogenesis of diabetic neuropathy. In summary, this study provides compelling evidence that SAMe levels need to be tightly controlled to prevent aberrant DNA methylation patterns, and together with recently published studies on the influence of SAMe on histone methylation in cancer and embryonic stem cell differentiation show that in diverse biological processes, the methylome, and consequently gene expression patterns, are critically dependent on levels of SAMe.
Publication Title
S-adenosylmethionine levels regulate the schwann cell DNA methylome.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 2886 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
Description
Consider the problem of designing a panel of complex biomarkers to predict a patient's health or disease state when one can pair his or her current test sample, called a target sample, with the patient's previously acquired healthy sample, called a reference sample. As contrasted to a population averaged reference, this reference sample is individualized. Automated predictor algorithms that compare and contrast the paired samples to each other could result in a new generation of test panels that compare to a person's healthy reference to enhance predictive accuracy. This study develops such an individualized predictor and illustrates the added value of including the healthy reference for design of predictive gene expression panels. The objective is to predict each subject's state of infection, e.g., neither exposed nor infected, exposed but not infected, pre-acute phase of infection, acute phase of infection, post-acute phase of infection. Using gene microarray data collected in a large-scale serially sampled respiratory virus challenge study, we quantify the diagnostic advantage of pairing a person's baseline reference with his or her target sample.
Publication Title
An individualized predictor of health and disease using paired reference and target samples.
Sample Metadata Fields
Specimen part, Subject, Time
View Samples- Arabidopsis thaliana
- 24 Downloadable Samples
- Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)
Description
Arabidopsis fc2-1 mutants fail to properly de-etiolate after a prolonged period in the dark. Our goal was to monitor whole genome expression during the first 2 hours of de-etiolation to determine the cuase of this growth arrest.
Publication Title
Ubiquitin facilitates a quality-control pathway that removes damaged chloroplasts.
Sample Metadata Fields
Specimen part
View Samples- Rattus norvegicus
- 4 Downloadable Samples
- Affymetrix Rat Genome 230 2.0 Array (rat2302)
Description
Abstract
Publication Title
Evidence of a functional role for mast cells in the development of type 1 diabetes mellitus in the BioBreeding rat.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 268 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
Description
The transcriptional responses of human hosts towards influenza viral pathogens are important for understanding virus-mediated immunopathology. Despite great advances gained through studies using model organisms, the complete temporal host transcriptional responses in a natural human system are poorly understood. In a human challenge study using live influenza (H3N2/Wisconsin) viruses, we conducted a clinically uninformed (unsupervised) factor analysis on gene expression profiles and established an ab initio molecular signature that strongly correlates to symptomatic clinical disease. This is followed by the identification of 42 biomarkers whose expression patterns best differentiate early from late phases of infection. In parallel, a clinically informed (supervised) analysis revealed over-stimulation of multiple viral sensing pathways in symptomatic hosts and linked their temporal trajectory with development of diverse clinical signs and symptoms. The resultant inflammatory cytokine profiles were shown to contribute to the pathogenesis because their significant increase preceded disease manifestation by 36 hours. In subclinical asymptomatic hosts, we discovered strong transcriptional regulation of genes involved in inflammasome activation, genes encoding virus interacting proteins, and evidence of active anti-oxidant and cell-mediated innate immune response. Taken together, our findings offer insights into influenza virus-induced pathogenesis and provide a valuable tool for disease monitoring and management in natural environments.
Publication Title
Temporal dynamics of host molecular responses differentiate symptomatic and asymptomatic influenza a infection.
Sample Metadata Fields
Specimen part
View Samples