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GSE53546
Homo sapiens
10 Downloadable Samples
Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)
Description
Nuclear lamin B1 constitutes one of the major structural proteins in the lamina mesh. We silenced the expression of lamin B1 by RNA interference in the colon cancer cell line DLD-1 and showed a dramatic redistribution of H3K27me3 from the periphery to a more homogeneous nuclear dispersion; in addition we observed an increased frequency of micronuclei and nuclear blebs. By 3D-FISH analyses, we demonstrate that the volume and surface of chromosome territories were significantly larger in LMNB1-depleted cells, suggesting that lamin B1 is required to maintain chromatin condensation in interphase nuclei. These changes led to a prolonged S-phase due to activation of Chk1 and telomere attrition. Finally, silencing of LMNB1 resulted in extensive changes in alternative splicing of multiple genes and in a higher number of enlarged nuclear speckles. Taken together, our results suggest a mechanistic role of the nuclear lamina in the organization of chromosome territories, maintenance of genome integrity and proper gene splicing.
Publication Title
Loss of lamin B1 results in prolongation of S phase and decondensation of chromosome territories.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 42 Downloadable Samples
Illumina HiSeq 2500
Description
Transcriptome analysis was conducted on vorinostat resistant HCT116 cells (HCT116-VR) upon knockdown of potential vorinostat resistance candidate genes in the presence and absence of vorinostat. Potential vorinostat resistance candidate genes chosen for this study were GLI1 and PSMD13, which were identified through a genome-wide synthetic lethal RNA interference screen. To understand the transcriptional events underpinning the effect of GLI1 and PSMD13 knockdown (sensitisation to vorinostat-induced apoptosis), cells were first subjected to gene knockdown, then to treatment with vorinsotat or the solvent control. Two timepoints for drug treatment were assessed: a timepoint before induction of apoptosis (4hrs for siGLI1 and 8hrs for siPSMD13) and a timepoint when apoptosis could be detected (8hrs for siGLI1 and 12hrs for siPSMD13). Overall design: There are 42 samples in total, from triplicate independent biological experiments of 14 samples each.
Publication Title
A genome scale RNAi screen identifies GLI1 as a novel gene regulating vorinostat sensitivity.
Sample Metadata Fields
No sample metadata fields
View Samples- Arabidopsis thaliana
- 12 Downloadable Samples
- Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)
Description
Expression analysis of mature Arabidopsis trichomes in Col-0 and two mutants, triptychon (try-JC) and glabra3 (gl3-3)
Publication Title
Transcriptional profiling of mature Arabidopsis trichomes reveals that NOECK encodes the MIXTA-like transcriptional regulator MYB106.
Sample Metadata Fields
Specimen part
View Samples- 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- Mus musculus
- 8 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Microarray expression profiling has become a valuable tool in the evaluation of the genetic consequences of metabolic disease. Although 3-biased gene expression microarray platforms were the first generation to have widespread availability, newer platforms are gradually emerging that have more up-to-date content and/or higher cost efficiency. Deciphering the relative strengths and weaknesses of these various platforms for metabolic pathway level analyses can be daunting. We sought to determine the practical strengths and weaknesses of four leading commercially-available expression array platforms relative to biologic investigations, as well as assess the feasibility of cross-platform data integration for purposes of biochemical pathway analyses. METHODS: Liver RNA from B6.Alb/cre,Pdss2loxP/loxP mice having primary Coenzyme Q deficiency was extracted either at baseline or following treatment with an antioxidant/antihyperlipidemic agent, probucol. Target RNA samples were prepared and hybridized to Affymetrix 430 2.0, Affymetrix Gene 1.0 ST, Affymetrix Exon 1.0 ST, and Illumina Mouse WG-6 expression arrays. Probes on all platforms were re-mapped to coding sequences in the current version of the mouse genome. Data processing and statistical analysis were performed by R/Bioconductor functions, and pathway analyses were carried out by KEGG Atlas and GSEA. RESULTS: Expression measurements were generally consistent across platforms. However, intensive probe-level comparison suggested that differences in probe locations were a major source of inter-platform variance. In addition, genes expressed at low or intermediate levels had lower inter-platform reproducibility than highly expressed genes. All platforms showed similar patterns of differential expression between sample groups, with steroid biosynthesis consistently identified as the most down-regulated metabolic pathway by probucol treatment. CONCLUSIONS: This work offers a timely guide for metabolic disease investigators to enable informed end-user decisions regarding choice of expression microarray platform best-suited to specific research project goals. Successful cross-platform integration of biochemical pathway expression data is also demonstrated, especially for well-annotated and highly-expressed genes. However, integration of gene-level expression data is limited by individual platform probe design and the expression level of target genes. Cross-platform analyses of biochemical pathway data will require additional data processing and novel computational bioinformatics tools to address unique statistical challenges.
Publication Title
Cross-platform expression microarray performance in a mouse model of mitochondrial disease therapy.
Sample Metadata Fields
Sex, Age, Specimen part, Treatment
View Samples- Mus musculus
- 16 Downloadable Samples
- Affymetrix Mouse Gene 2.0 ST Array (mogene20st)
Description
The only FDA approved therapy for Pompe is directed at correcting skeletal and cardiac muscle pathology, however, clinical and animal model data show strong histological evidence for a neurological disease component. While neuronal cell death and neuroinflammation are prominent in many lysosomal disorders, these processes have not been evaluated in Pompe disease. There is also no information available regarding the impact of Pompe disease on the fundamental pathways associated with synaptic communication.
Publication Title
Transcriptome assessment of the Pompe (Gaa-/-) mouse spinal cord indicates widespread neuropathology.
Sample Metadata Fields
Age
View Samples