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Mus musculus
110 Downloadable Samples
Sentrix MouseRef-8 Expression BeadChip
Description
Linkage analysis of complex traits in mice is a powerful tool to find loci affecting the phenotype but it has a poor resolution making it difficult to identify the underlying genes. We show here, using whole genome association analysis of gene expression traits in an outbred mouse population, the MF1 stock, that mapping resolution is greatly increased as compared to linkage. The fact that eQTLs discovered in other crosses were replicated and successfully mapped with high resolution in this population provides a strong proof of concept. In addition, we show that this population is a useful resource to resolve the eQTL hotspots detected in other studies. Finally, we highlight the importance of correcting for population structure in whole genome association studies in the outbred stock.
Publication Title
High-resolution mapping of gene expression using association in an outbred mouse stock.
Sample Metadata Fields
No sample metadata fields
View Samples
GSE38705- Mus musculus
- 510 Downloadable Samples
- Affymetrix HT Mouse Genome 430A Array (htmg430a)
Description
Identify genes involved in regulation of inflammatory responses and gene-environemnt interactions, in macrophages from a set of mouse inbred strains termed the HMDP. The HMDP is a genetically diverse mapping panel comprised of classical inbred and recombinant inbred wild type mice. The RMA values of genes were used for genome wide association as described in Bennett et al Genome Research 2010.
Publication Title
Unraveling inflammatory responses using systems genetics and gene-environment interactions in macrophages.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Mus musculus
- 288 Downloadable Samples
- Affymetrix HT Mouse Genome 430A Array (htmg430a)
Description
Novel, systems-based approach to mouse genetics.
Publication Title
A high-resolution association mapping panel for the dissection of complex traits in mice.
Sample Metadata Fields
Specimen part
View Samples- Saccharomyces cerevisiae
- 8 Downloadable Samples
- Affymetrix Yeast Genome S98 Array (ygs98)
Description
In Saccharomyces cerevisiae, the maturation of both pre-rRNA and pre-small nucleolar RNAs (pre-snoRNAs) involves common factors, thereby providing a potential mechanism for the coregulation of snoRNA and rRNA synthesis. In this study, we examined the global impact of the double-stranded-RNA-specific RNase Rnt1p, which is required for pre-rRNA processing, on the maturation of all known snoRNAs. In silico searches for Rnt1p cleavage signals, and genome-wide analysis of the Rnt1p-dependent expression profile, identified seven new Rnt1p substrates. Interestingly, two of the newly identified Rnt1p-dependent snoRNAs, snR39 and snR59, are located in the introns of the ribosomal protein genes RPL7A and RPL7B. In vitro and in vivo experiments indicated that snR39 is normally processed from the lariat of RPL7A, suggesting that the expressions of RPL7A and snR39 are linked. In contrast, snR59 is produced by a direct cleavage of the RPL7B pre-mRNA, indicating that a single pre-mRNA transcript cannot be spliced to produce a mature RPL7B mRNA and processed by Rnt1p to produce a mature snR59 simultaneously. The results presented here reveal a new role of yeast RNase III in the processing of intron-encoded snoRNAs that permits independent regulation of the host mRNA and its associated snoRNA.
Publication Title
Genome-wide prediction and analysis of yeast RNase III-dependent snoRNA processing signals.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 12 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Three different recombinant forms of CyaA were used to investigate transcriptional responses of murine bone marrow-derived macrophages (BMDMs) using Affymetrix Mouse Genome Genechips. These forms were enzymically active, invasive CyaA, nonenzymically active, invasive CyaA (CyaA*) and non-enzymically active, non-invasive CyaA (proCyaA*). BMMs, treated with 20 ng/ml of CyaA for 24 h, showed over 1000 significant changes in gene transcription compared with control cells. CyaA caused an increase in transcription of many inflammatory genes and genes associated with various signalling cascades such as those involved in cyclic AMP-dependent protein kinase A signalling. Most strikingly, CyaA caused down-regulation of numerous genes involved in cell proliferation. CyaA* at 20 ng/ml significantly up-regulated the transcription of only twelve genes after 24 h whereas proCyaA* at this concentration significantly increased the transcription of only two genes.
Publication Title
Transcriptional responses of murine macrophages to the adenylate cyclase toxin of Bordetella pertussis.
Sample Metadata Fields
Sex, Age, Specimen part, Treatment
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