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GSE12000
Mus musculus
48 Downloadable Samples
Sentrix MouseRef-8 Expression BeadChip (Target ID), Rosetta/Merck Mouse TOE 75k Array 1 microarray
Description
A major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.
Publication Title
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 16 Downloadable Samples
Sentrix MouseRef-8 Expression BeadChip (Target ID)
Description
A major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.
Publication Title
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 14 Downloadable Samples
- Sentrix MouseRef-8 Expression BeadChip (Target ID)
Description
A major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.
Publication Title
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 10 Downloadable Samples
- Sentrix MouseRef-8 Expression BeadChip (Target ID)
Description
A major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.
Publication Title
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 8 Downloadable Samples
- Sentrix MouseRef-8 Expression BeadChip (Target ID)
Description
A major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes, and identification of involved pathways and networks.
Publication Title
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 22 Downloadable Samples
Illumina HiSeq 2000
Description
In this project we analyze the transcriptome of the human multiple myeloma isogenic cell lines ARP-1 (UTX wild-type) and ARD (UTX null). The transcriptome is studied at baseline, upon restoration of UTX levels in ARD cells for 3 and 6 days, and upon treatment of the cell lines with the EZH2 inhibitor GSK343. Moreover, we analyzed the transcriptome of a ARD resistant cell line that we generated. Overall design: Examination of transcriptome of two cell lines upon restoration of UTX and treatment with EZH2 inhibitors
Publication Title
UTX/KDM6A Loss Enhances the Malignant Phenotype of Multiple Myeloma and Sensitizes Cells to EZH2 inhibition.
Sample Metadata Fields
Specimen part, Subject
View Samples- Rattus norvegicus
- 8 Downloadable Samples
- Affymetrix Rat Genome 230 2.0 Array (rat2302)
Description
Here we tested a hypothesis that epileptogenesis influences expression pattern of genes in the basolateral amygdala that are critical for fear conditioning. Whole genome molecular profiling of basolateral rat amygdala was performed to compare the transcriptome changes underlying fear learning in epileptogenic and control animals. Our analysis revealed that after acquisition of fear conditioning 26 genes were regulated differently in the basolateral amygdala of both groups. Thus, our study provides the first evidence that not only the damage to the neuronal pathways but also altered composition or activity level of molecular machinery responsible for formation of emotional memories within surviving pathways can contribute to impairment in emotional learning in epileptogenic animals. Understanding the function of those genes in emotional learning provides an attractive avenue for identification of novel drug targets for treatment of emotional disorders after epileptogenesis-inducing insult.
Publication Title
Epileptogenesis alters gene expression pattern in rats subjected to amygdala-dependent emotional learning.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 45 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Context: In many cancers, specific subpopulations of cells appear to be uniquely capable of initiating and maintaining tumors. The strongest support for this cancer stem cell model comes from transplantation assays in immune-deficient mice indicating that human acute myeloid leukemia (AML) is organized as a cellular hierarchy driven by self-renewing leukemia stem cells (LSC). This model has significant implications for the development of novel therapies, but its clinical significance remains unclear.
Publication Title
Association of a leukemic stem cell gene expression signature with clinical outcomes in acute myeloid leukemia.
Sample Metadata Fields
Disease, Disease stage, Subject
View Samples- Homo sapiens
- 98 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Acute Myeloid Leukemia AML is a cancer in which the process of normal cell hematopoietic differentiation is disrupted. Evidence exists that AML comprises a hierarchy with leukemic stem cells giving rise to more differentiated, but immature and functionally incompetent populations. The similarity of these AML subpopulations to normal stages of hematopoietic differentiation has not been dissected comprehensively at the transcriptional level. Here we introduce Normal Memory Analysis (NorMA), a data analysis method that extracts from omic data the remnants of the healthy normal-like phenotype. Applying NorMA to gene expression data from AML uncovered a wealth of information in the normal-like component of data: the normal hematopoietic memory of AML tumor cells. We found significant variation within the patient population, and we found strong association of this normal hematopoietic memory with survival. We found that undifferentiated NorMA phenotype has significantly worse survival than differentiated NorMA phenotype, showing that the NorMA classification of tumors captures a biologically meaningful stratification of patients, with highly significant survival association. Patients with NorMA phenotype in the undifferentiated Hematopoietic Stem Cell HSC stage had the worst survival, with median survival time under 6 months. We further found significant survival differences between tumor groups with differentiated NorMA phenotype, depending on their hematopoietic path: AML patients with NorMA phenotype in megakaryocyte-erythroid progenitor MEP stage had significantly better survival than those with NorMA phenotype in granulocyte-macrophage progenitor GMP stage. Thus NorMA produced a stratification of AML cohorts by differentiation stage, with significant outcome differences. It also provided clean molecular signatures for these stages. NorMA can be used in many other contexts, to explore for example the tumor cell of origin, or disease predisposition.
Publication Title
An LSC epigenetic signature is largely mutation independent and implicates the HOXA cluster in AML pathogenesis.
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 24 Downloadable Samples
- NextSeq 500
Description
Using primary cultures of normal human prostate epithelial cells, we developed a novel prostasphere-based, label-retention assay that permits identification and isolation of stem cells at a single cell level. Their bona fide stem cell nature was confirmed using in vitro and in vivo regenerative assays and documentation of symmetric/asymmetric division. Robust WNT10B and KRT13 expression without E-cadherin or KRT14 staining distinguished individual stem cells from daughter progenitors in spheroids. Following FACS to separate stem and progenitor cells, RNA-seq identified unique gene signatures for the separate populations which may serve as biomarkers. Pathways enrichment in stem cells identified ribosome biogenesis and membrane estrogen-receptor signaling with NF?B signaling enriched in progenitors and these were biologically confirmed. Further, bioassays identified heightened autophagy flux and reduced metabolism in stem cells relative to progenitors. These approaches similarly identified cancer stem-like cells from prostate cancer specimens and prostate, breast and colon cancer cell lines suggesting wide applicability. Together, the present studies isolate and identify unique characteristics of normal human prostate stem cells and uncover processes that maintain stem cell homeostasis in the prostate gland. Overall design: Comparing RNA-seq gene profiles in label-retaining prostate stem cells and non-retaining progenitor cells
Publication Title
Isolation and functional interrogation of adult human prostate epithelial stem cells at single cell resolution.
Sample Metadata Fields
Specimen part, Subject
View Samples