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GSE23617
Arabidopsis thaliana
17 Downloadable Samples
Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)
Description
BRCA2A: We used microarrays to identify differentially expressed genes. We focused on those genes that were dramatically salicylic acid-induced (>2-fold) and BRCA2A-dependent in npr1 sni1 double mutants
Publication Title
Arabidopsis BRCA2 and RAD51 proteins are specifically involved in defense gene transcription during plant immune responses.
Sample Metadata Fields
Specimen part, Treatment, Time
View Samples- Homo sapiens
- 33 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Longitudinal study of recurrent metastatic melanoma cell lines underscores the individuality of cancer biology.
Sample Metadata Fields
Specimen part, Disease, Subject
View Samples- Mus musculus
- 14 Downloadable Samples
Illumina HiSeq 2000, Illumina Genome Analyzer II
Description
We obtained global measurements of decay and translation rates for mammalian mRNAs with alternative 3'' untranslated regions (3'' UTRs). Overall design: 1 3P-Seq sample from 3T3 cells and 1 3P-Seq sample from mouse ES cells; 2 2P-Seq steady state and 4 2P-Seq with actinomycin D; 6 polysome fraction 2P-Seq
Publication Title
3' UTR-isoform choice has limited influence on the stability and translational efficiency of most mRNAs in mouse fibroblasts.
Sample Metadata Fields
Specimen part, Treatment, Subject
View Samples- Homo sapiens
- 65 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Dysfunction in type I interferon (IFN) signaling occurs in patients with stage II or more advanced cancer. After screening the effects of a panel of 12 melanoma cell lines on PBMCs of healthy volunteers of IFNalpha signal pathway, two groups of melanoma cell lines could be identified one with stronger suppression (low pSTAT-1 group) than the other (high pSTAT-1 group). Comparative global gene expression between two groups identified 6771 differential expression genes. This gene list indicated down regulation of IFNalpha signal in immune suppressive melanoma cells. To evaluate this gene list for predictive power on IFNalpha signal modulatory function, we analyzed gene expression 41 independent melanoma cell lines and heat map clusters these cell lines into two groups, one with strong immune suppressive function and other with less effect.
Publication Title
Melanoma NOS1 expression promotes dysfunctional IFN signaling.
Sample Metadata Fields
Disease, Disease stage, Cell line
View Samples- Mus musculus
- 174 Downloadable Samples
- IlluminaHiSeq2000, IlluminaGenomeAnalyzerIIx
Description
We profiled genome-wide gene expression of 170 individual mid-gestation (embryonic day 11.5) whole mouse embryos derived from a 2-generation interspecies mouse cross and asked to what extent genetic variation drives four important parameters of regulatory architecture: allele-specific expression (ASE), imprinting, trans-regulatory effects, and maternal effect. The inbred strain C57BL/6J and wild-derived inbred strain CAST/EiJ were used in reciprocal crosses to generate F1 embryos. F1 progeny were backcrossed to C57BL/6J in reciprocal crosses to generate 154 N2 embryos. We employed a backcross design, in which N2 offspring have genotypically distinct parents, to enable comparison of gene expression for offspring from each side of the reciprocal cross. Our findings demonstrate that genetic variation contributes to widespread gene expression differences during mammalian embryogenesis. Overall design: Transcriptome analysis of E11.5 mouse embryos: 16 F1 embryos from reciprocally crossed C57BL/6J and CastEi/J parents; and 154 N2 embryos from reciprocal backcross of F1s to the C57BL/6J parent.
Publication Title
Constraint and divergence of global gene expression in the mammalian embryo.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 27 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
To define the molecular abnormalities at the stem cell level in polycythemia vera (PV), we examined global gene expression in circulating CD34+ cells from 19 JAK2 V617F-positive PV patients and 6 normal individuals using Affymetrix oligonucleotide microarray technology. We observed that CD34+ cell gene expression not only differed between the PV patients and the normal controls but also between men and women PV patients. Based on these gender-specific differences in gene expression, we were able to identify 102 genes differentially regulated concordantly by both men and women, which likely represent a core set of genes whose dysregulation is involved in the pathogenesis of PV. Gene expression was verified by Q-PCR of patient CD34+ cell RNA. Using the 102 gene set and unsupervised hierarchical clustering, the 19 PV patients could be separated in two groups that differed significantly with respect to hemoglobin level, thrombosis frequency, splenomegaly, splenectomy or chemotherapy exposure, leukemic transformation and overall survival. These results were confirmed using top scoring pairs, which identified a different set of 29 genes that independently segregated the 19 patients into the same two clinical groups: those with an aggressive form of the disease (7 patients), and those with an indolent form (12 patients).
Publication Title
Two clinical phenotypes in polycythemia vera.
Sample Metadata Fields
Sex, Disease
View Samples- Homo sapiens
- 8 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The aim of the study was to identify in vivo spermatogonial gene expression within the context of their biological niche.
Publication Title
Screening for biomarkers of spermatogonia within the human testis: a whole genome approach.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 324 Downloadable Samples
- Illumina MiSeq, Illumina HiSeq 2500, Illumina HiSeq 4000
Description
Vascular smooth muscle cells (VSMCs) show pronounced heterogeneity across and within vascular beds, with direct implications for their function in injury response and atherosclerosis. Here we combine single-cell transcriptomics with lineage tracing to examine VSMC heterogeneity in healthy mouse vessels. The transcriptional profiles of single VSMCs consistently reflect their region-specific developmental history and show heterogeneous expression of vascular disease-associated genes involved in inflammation, adhesion and migration. We detect a rare population of VSMC-lineage cells that express the multipotent progenitor marker Sca1, progressively downregulate contractile VSMC genes and upregulate genes associated with VSMC response to inflammation and growth factors. We find that Sca1 upregulation is a hallmark of VSMCs undergoing phenotypic switching in vitro and in vivo, and reveal an equivalent population of Sca1-positive VSMC-lineage cells in atherosclerotic plaques. Together, our analyses identify disease-relevant transcriptional signatures in VSMC-lineage cells in healthy blood vessels, with implications for disease susceptibility, diagnosis and prevention. Overall design: This entry contains data from the following analyses: (1) Bulk RNA-seq of mouse VSMCs isolated from aortic arch (AA) and descending thoracic aorta (DT) regions in triplicates. (2) Pooled RNA-seq of mouse Sca1- VSMCs and Sca1- or Sca1+ adventitial cells in triplicates. (3) Single-cell RNA-seq of VSMCs from the AA and DT regions (143 cells). (4) VSMC lineage label positive and negative cells isolated from the medial layer of mouse aorta, which expressed or did not express the Sca1 protein (155 cells). (5) 10X single-cell RNA-seq analysis of: lineage positive plaque cells isolated from mice following 14 or 18 weeks of high fat diet feeding, cells isolated from the whole aorta and lineage positive VSMCs from the medial layer.
Publication Title
Disease-relevant transcriptional signatures identified in individual smooth muscle cells from healthy mouse vessels.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 131 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Lung cancers are a heterogeneous group of diseases with respect to biology and clinical behavior. Currently, diagnosis and classification are based on histological morphology and immunohistological methods for discrimination between two main histologic groups: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) which account for 20% and 80% of lung carcinomas, respectively. NSCLCs, which are divided into the three major subtypes adenocarcinoma, squamous cell carcinoma and dedifferentiated large cell carcinoma, show different characteristics such as the expression of certain keratins or production of mucin and lack of neuroedocrine differentiation. The molecular pathogenesis of lung cancer involves the accumulation of genetic und epigenetic alterations including the activation of proto-oncogenes and inactivation of tumor suppressor genes which are different for lung cancer subgroups. The development of microarray technologies opened up the possibility to quantify the expression of a large number of genes simultaneously in a given sample. There are several recent reports on expression profiling on lung cancers but the analysis interpretation of the results might be difficult because of the heterogeneity of cellular components. The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost.
Publication Title
Lung cancer transcriptomes refined with laser capture microdissection.
Sample Metadata Fields
Specimen part, Disease, Disease stage
View Samples- Homo sapiens
- 64 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Purpose: To evaluate the presence of a gene expression signature present before treatment as predictive of response to treatment with MAGEA3
Publication Title
Predictive gene signature in MAGE-A3 antigen-specific cancer immunotherapy.
Sample Metadata Fields
Specimen part
View Samples