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Homo sapiens
8 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The recruitment of mesenchymal stem cells in order to reconstruct damaged cartilage of osteoarthritis joints is a challenging tissue engineering task. Vision towards this goal is blurred by a lack of knowledge about the underlying differences between chondrocytes and MSC during the chondrogenic cultivation process. The aim of this study was to shed light on the differences between chondrocytes and MSC occurring during chondral differentiation through tissue engineering.
Publication Title
Expression pattern differences between osteoarthritic chondrocytes and mesenchymal stem cells during chondrogenic differentiation.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 32 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Discrimination of rheumatoid arthritis (RA) patients from patients with other inflammatory/degenerative joint diseases or healthy individuals purely on the basis of genes differentially expressed in high-throughput data has proven very difficult. Thus, the present study sought to achieve such discrimination by employing a novel unbiased approach using rule-based classifiers. Three multi-center genome-wide transcriptomic data sets (Affymetrix HG- U133 A/B) from a total of 79 individuals, including 20 healthy controls (control group - CG), as well as 26 osteoarthritis (OA) and 33 RA patients, were used to infer rule- based classifiers to discriminate the disease groups. The rules were ranked with respect to Kiendls statistical relevance index, and the resulting rule set was optimized by pruning. The rule sets were inferred separately from data of one of three centers and applied to the two remaining centers for validation. All rules from the optimized rule sets of all centers were used to analyze their biological relevance applying the software Pathway Studio.
Publication Title
Identification of rheumatoid arthritis and osteoarthritis patients by transcriptome-based rule set generation.
Sample Metadata Fields
Sex, Age
View Samples- Homo sapiens
- 29 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Discrimination of rheumatoid arthritis (RA) patients from patients with other inflammatory/degenerative joint diseases or healthy individuals purely on the basis of genes differentially expressed in high-throughput data has proven very difficult. Thus, the present study sought to achieve such discrimination by employing a novel unbiased approach using rule-based classifiers. Three multi-center genome-wide transcriptomic data sets (Affymetrix HG- U133 A/B) from a total of 79 individuals, including 20 healthy controls (control group - CG), as well as 26 osteoarthritis (OA) and 33 RA patients, were used to infer rule- based classifiers to discriminate the disease groups. The rules were ranked with respect to Kiendls statistical relevance index, and the resulting rule set was optimized by pruning. The rule sets were inferred separately from data of one of three centers and applied to the two remaining centers for validation. All rules from the optimized rule sets of all centers were used to analyze their biological relevance applying the software Pathway Studio.
Publication Title
Identification of rheumatoid arthritis and osteoarthritis patients by transcriptome-based rule set generation.
Sample Metadata Fields
Specimen part, Disease, Disease stage
View Samples- Homo sapiens
- 18 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Expression data from microdissected glomeruli to examine the role of hypoxia in glomerulosclerosis of human Nephrosclerosis (NSC).
Publication Title
Human nephrosclerosis triggers a hypoxia-related glomerulopathy.
Sample Metadata Fields
Specimen part, Disease, Disease stage
View Samples- Homo sapiens
- 15 Downloadable Samples
- Affymetrix Human Genome U133A Array (hgu133a)
Description
Discrimination of rheumatoid arthritis (RA) patients from patients with other inflammatory/degenerative joint diseases or healthy individuals purely on the basis of genes differentially expressed in high-throughput data has proven very difficult. Thus, the present study sought to achieve such discrimination by employing a novel unbiased approach using rule-based classifiers. Three multi-center genome-wide transcriptomic data sets (Affymetrix HG- U133 A/B) from a total of 79 individuals, including 20 healthy controls (control group - CG), as well as 26 osteoarthritis (OA) and 33 RA patients, were used to infer rule- based classifiers to discriminate the disease groups. The rules were ranked with respect to Kiendls statistical relevance index, and the resulting rule set was optimized by pruning. The rule sets were inferred separately from data of one of three centers and applied to the two remaining centers for validation. All rules from the optimized rule sets of all centers were used to analyze their biological relevance applying the software Pathway Studio. The optimized rule sets for the three centers contained a total of 29, 20, and 8 rules (including 10, 8, and 4 rules for RA), respectively. The mean sensitivity for the prediction of RA based on six center-to-center tests was 96% (range 90% to 100%), that for OA 86% (range 40% to 100%). The mean specificity for RA prediction was 94% (range 80% to 100%), that for OA 96% (range 83.3% to 100%). The average overall accuracy of the three different rule-based classifiers was 91% (range 80% to 100%). Unbiased analyses by Pathway Studio of the gene sets obtained by discrimination of RA from OA and CG with rule-based classifiers resulted in the identification of the pathogenetically and/or therapeutically relevant interferon-gamma and GM-CSF pathways. First-time application of rule-based classifiers for the discrimination of RA resulted in high performance, with means for all assessment parameters close to or higher than 90%. In addition, this unbiased, new approach resulted in the identification not only of pathways known to be critical to RA, but also of novel molecules such as serine/threonine kinase 10.
Publication Title
Identification of rheumatoid arthritis and osteoarthritis patients by transcriptome-based rule set generation.
Sample Metadata Fields
Sex, Age
View Samples- Arabidopsis thaliana
- 6 Downloadable Samples
Illumina HiSeq 2500
Description
Plant meristems carry pools of continuously active stem cells, whose activity is controlled by developmental and environmental signals. After stem cell division, daughter cells that exit the stem cell domain acquire transit amplifying cell identity before they are incorporated into organs and differentiate. In this study, we used an integrated approach to elucidate the role of HECATE (HEC) genes in regulating developmental trajectories of shoot stem cells in Arabidopsis thaliana. Our work reveals that HEC function stabilizes cell fate in distinct zones of the shoot meristem thereby controlling the spatio-temporal dynamics of stem cell differentiation. Importantly, this activity is concomitant with the local modulation of cellular responses to cytokinin and auxin, two key phytohormones regulating cell behaviour. Mechanistically, we show that HEC factors directly modulate auxin signal transduction by physical interaction with MONOPTEROS (MP), a key regulator of auxin signalling, and thus interfere with the autocatalytic stabilization of auxin signalling. Overall design: p16:HEC1-linker-GR;inflorescence meristems; 14hours; mock1,mock2,mock3,dex1,dex2,dex3
Publication Title
Control of plant cell fate transitions by transcriptional and hormonal signals.
Sample Metadata Fields
Age, Specimen part, Subject
View Samples- Mus musculus
- 474 Downloadable Samples
- Illumina HiSeq 2000, Illumina HiSeq 3000
Description
Single cell RNA-seq of neural stem cell and astrocytes from old mice Overall design: Single cell RNA-seq of neural stem cell and astrocytes from old mice
Publication Title
Quiescence Modulates Stem Cell Maintenance and Regenerative Capacity in the Aging Brain.
Sample Metadata Fields
Sex, Age, Specimen part, Cell line, Subject
View Samples
GSE83136- Arabidopsis thaliana
- 18 Downloadable Samples
- Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)
Description
Abiotic stress is a major factor for crop productivity, a problem likely to be exacerbated by climate change. Improving the tolerance to environmental stress is one of the most important goals of crop breeding programmes. While the early responses to abiotic stress in plants are well studied, plant adaptation to enduring or recurring stress conditions has received little attention. This project investigates the molecular mechanism of the maintenance of acquired thermotolerance as a model case of stress memory in Arabidopsis. Arabidopsis seedlings acquire thermotolerance through a heat treatment at sublethal temperatures. To investigate the underlying mechanisms, we are investigating changes in the transcriptome at two timepoints after a heat acclimation treatment using Arabidopsis thaliana seedlings.
Publication Title
Arabidopsis miR156 Regulates Tolerance to Recurring Environmental Stress through SPL Transcription Factors.
Sample Metadata Fields
Treatment
View Samples- Mus musculus
- 12 Downloadable Samples
- Affymetrix Mouse Gene 2.0 ST Array (mogene20st)
Description
The histone acetyltransferase (HAT) Mof is essential for mouse embryonic stem cells (mESC) pluripotency and early development. Mof is the enzymatic subunit of two different HAT complexes, MSL (Male-Specific Lethal) and NSL (Non-specific lethal). The individual contribution of MSL and NSL complexes to transcription regulation in mESCs is not well understood. Our genome-wide analysis of MSL and NSL localization show that i) MSL and NSL bind to specific and common sets of expressed genes, ii) NSL binds at promoters, iii) while MSL binds in gene bodies. Knockdown of Msl1 leads to a global loss of histone H4K16ac indicating that MSL is the main HAT acetylating H4K16 in mESCs. MSL was enriched at many mESC-specific genes, but also at bivalent domains. Thus, NSL and MSL HAT complexes differentially regulate specific sets of expressed genes in mESCs. Furthermore, MSL is essential for the regulation of key mESC-specific and bivalent developmental genes.
Publication Title
Mof-associated complexes have overlapping and unique roles in regulating pluripotency in embryonic stem cells and during differentiation.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 8 Downloadable Samples
- Affymetrix Mouse Gene 1.1 ST Array (mogene11st)
Description
Recent studies have identified intracellular metabolism as a fundamental determinant of macrophage function. In obesity, proinflammatory macrophages accumulate in adipose tissue and trigger chronic low-grade inflammation, that promotes the development of systemic insulin resistance, yet changes in their intracellular energy metabolism are currently unknown. We therefore set out to study metabolic signatures of adipose tissue macrophages (ATMs) in lean and obese conditions. F4/80-positive ATMs were isolated from obese vs lean mice. High-fat feeding of wild-type mice and myeloid-specific Hif1-/- mice was used to examine the role of hypoxia-inducible factor-1 (HIF-1) in ATMs part of obese adipose tissue. In vitro, bone marrow-derived macrophages were co-cultured with adipose tissue explants to examine adipose tissue-induced changes in macrophage phenotypes. Transcriptome analysis, real-time flux measurements, ELISA and several other approaches were used to determine the metabolic signatures and inflammatory status of macrophages. In addition, various metabolic routes were inhibited to determine their relevance for cytokine production. Transcriptome analysis and extracellular flux measurements of mouse ATMs revealed unique metabolic rewiring in obesity characterised by both increased glycolysis and oxidative phosphorylation. Similar metabolic activation of CD14+ cells in obese individuals was associated with diabetes outcome. These changes were not observed in peritoneal macrophages from obese vs lean mice and did not resemble metabolic rewiring in M1-primed macrophages. Instead, metabolic activation of macrophages was dose-dependently induced by a set of adipose tissue-derived factors that could not be reduced to leptin or lactate. Using metabolic inhibitors, we identified various metabolic routes, including fatty acid oxidation, glycolysis and glutaminolysis, that contributed to cytokine release by ATMs in lean adipose tissue. Glycolysis appeared to be the main contributor to the proinflammatory trait of macrophages in obese adipose tissue. HIF-1, a key regulator of glycolysis, nonetheless appeared to play no critical role in proinflammatory activation of ATMs during early stages of obesity. Our results reveal unique metabolic activation of ATMs in obesity that promotes inflammatory cytokine release. Further understanding of metabolic programming in ATMs will most likely lead to novel therapeutic targets to curtail inflammatory responses in obesity.
Publication Title
Unique metabolic activation of adipose tissue macrophages in obesity promotes inflammatory responses.
Sample Metadata Fields
Sex, Specimen part
View Samples