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GSE25322
Mus musculus
299 Downloadable Samples
Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
A QTL analysis between inbred mouse strains MRL/MpJ and SM/J was performed to identify genetic loci influencing high-density lipoprotein (HDL) cholesterol and triglycerides (TG) at eight weeks of age in F2 mice fed a chow diet. In order to narrow down lists of candidate genes, expression levels from liver tissue were used to test for differential expression among parental and F1 strains and to scan for eQTL in F2 animals. We provide evidence for Mppe1 (Chr 18) as an HDL QTL candidate gene and Cyp2d26 (Chr 15) as a TG QTL candidate gene.
Publication Title
Integration of QTL and bioinformatic tools to identify candidate genes for triglycerides in mice.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Mus musculus
- 214 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
To better understand the temporal dynamics of gene expression during normal murine lung development we characterized global gene expression at 26 time points in three common inbred strains of mice (A/J, C57BL/6J, and C3H/HeJ). The data set provides a unique resource for identifying patterns of gene expression changes during normal lung development and for investigating the developmental origins of respiratory disease.
Publication Title
Temporal dynamics of the developing lung transcriptome in three common inbred strains of laboratory mice reveals multiple stages of postnatal alveolar development.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 207 Downloadable Samples
- Illumina MouseWG-6 v2.0 expression beadchip
Description
The data was used for eQTL analysis of cecum gene expression in the Collaborative Cross Breeding Population.
Publication Title
No associated publication
Sample Metadata Fields
Sex
View Samples- Mus musculus
- 173 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
Identifying the genes underlying quantitative trait loci (QTL) for disease has proven difficult, mainly due to the low resolution of the approach and the complex genetics involved. However, recent advances in bioinformatics and the availability of genetic resources now make it possible to narrow the genetic intervals and test candidate genes. In addition to identifying the causative genes, defining the pathways that are affected by these QTL is of major importance as it can give us insight into the disease process and provide evidence to support candidate genes. In this study we mapped three significant and one suggestive QTL on Chromosomes (Chrs) 1, 4, 15, and 17, respectively, for increased albumin excretion (measured as albumin-to-creatinine ratio) in a cross between the MRL/MpJ and SM/J mouse inbred strains. By combining data from several sources and by utilizing gene expression data, we identified Tlr12 as a likely candidate for the Chr 4 QTL. Through the mapping of 33,881 transcripts measured by microarray on kidney RNA from each of the 173 male F2 animals, we identified several downstream pathways associated with these QTL. Among these were the glycan degradation, leukocyte migration, and antigen presenting pathways. We demonstrate that by combining data from multiple sources, we can identify not only genes that are likely to be causal candidates for QTL, but also the pathways through which these genes act to alter phenotypes. This combined approach provides valuable insights into the causes and consequences of renal disease.
Publication Title
Uncovering genes and regulatory pathways related to urinary albumin excretion.
Sample Metadata Fields
Sex, Age
View Samples- Mus musculus
- 157 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
The Collaborative Cross (CC) recombinant inbred panel was conceived as an ideal resource for mammalian system genetics. The pre-CC is a proof-of-concept experiment involving CC lines that have undergone at least five generations of inbreeding. Siblings from these lines were each involved in one of four distinct phenotyping arms, then genotyped on a high-density Affymetrix platform. The genetic profile of these emerging lines reveals high diversity, balanced allele frequencies, and well-distributed recombination all ideal qualities for a mapping panel. We have mapped white spot, a discrete trait; body weight, a highly polygenic complex trait; and more than 11,000 liver gene expression traits. These analyses provide a glimpse of the potential mapping power and resolution of the CC.
Publication Title
Genetic analysis of complex traits in the emerging Collaborative Cross.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 144 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
High-fat diets are associated with increased obesity and metabolic disease in mice and humans. Here we used analysis of variance (ANOVA) to scrutinize a microarray data set consisting of 10 inbred strains of mice from both sexes fed atherogenic high-fat and control chow diets. An overall F-test was applied to the 40 unique groups of strain-diet-sex to identify 15,288 genes with altered transcription. Bootstrapping k-means clustering separated these changes into four strain-dependent expression patterns, including two sex-related profiles and two diet-related profiles. Sex-induced effects correspond to secretion (males) or fat and energy metabolism (females), whereas diet-induced changes relate to neurological processes (chow) or immune response (high-fat). The full set of pairwise contrasts for differences between strains within sex (90 different statistical tests) uncovered 32,379 total changes. These differences were unevenly distributed across strains and between sexes, indicating that strain-specific responses to high-fat diet differ between sexes. Correlations between expression levels and 8 obesity-related traits identified 5,274 associations between transcript abundance and measured phenotypic endpoints. From this number, 2,678 genes are positively correlated with total cholesterol levels and associate with immune-related categories while 2,596 genes are negatively correlated with cholesterol and connect to cholesterol synthesis.
Publication Title
Practical applications of the bioinformatics toolbox for narrowing quantitative trait loci.
Sample Metadata Fields
Sex
View Samples- Mus musculus
- 24 Downloadable Samples
- Affymetrix Mouse Gene 1.0 ST Array (mogene10st)
Description
BACKGROUND: The transcript levels of many genes exhibit significant variation in tissue samples from inbred laboratory mice. A microarray experiment was designed to separate transcript abundance variation across samples from adipose, heart, kidney, and liver tissues of C57BL/6J mice into within-mouse and between-mouse components. Within-mouse variance captures variation due to heterogeneity of gene expression within tissues, RNA-extraction, and array processing. Between-mouse variance reflects differences in transcript levels between these genetically identical mice. Many biological sources can contribute to heterogeneous transcript levels within a tissue sample including inherent stochasticity of biochemical processes such as intrinsic and extrinsic noise within cells and differences in cell-type composition which can result from heterogeneity of stem and progenitor cell populations. Differences in global signaling patterns between individuals and micro-environmental influences such as interactions with pathogens and cage mates can also contribute to variation, but are likely to contribute more to the between-mouse variance component.
Publication Title
Stochastic variation of transcript abundance in C57BL/6J mice.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Mus musculus
- 108 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
In this study that was specifically designed to identify early stages of glaucoma in DBA/2J mice, we used genome-wide expression profiling and a series of computational methods. Our methods successfully subdivided eyes with no detectable glaucoma by conventional assays into molecularly defined stages of disease. These stages represent a temporally ordered sequence of glaucoma states. Using an array of tools, we then determined networks and biological processes that are altered at these early stages. Our strategy proved very sensitive, suggesting that similar approaches will be valuable for uncovering early processes in other complex, later-onset diseases. Early changes included upregulation of both the complement cascade and endothelin system, and so we tested the therapeutic value of separately inhibiting them. Mice with a mutation in the complement component 1a gene (C1qa) were robustly protected from glaucoma with the protection being among the greatest reported. Similarly, inhibition of the endothelin system was strongly protective. Since EDN2 is potently vasoconstrictive and was produced by microglial/macrophages, our data provide a novel link between these cell types and vascular dysfunction in glaucoma. Targeting early events such as the upregulation of the complement and endothelin pathways may provide effective new treatments for human glaucoma.
Publication Title
Molecular clustering identifies complement and endothelin induction as early events in a mouse model of glaucoma.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Mus musculus
- 96 Downloadable Samples
- Illumina mouse-6 v1.1 expression beadchip
Description
Analysis of tissues of DBA/2 mice fed a standard breeding diet (SBD) and high fat diet (HFD) revealed tissue specific roles in inflammation and disease, and altered communication between tissues. The tissues surveyed incuded adipose tissues (brown, inguinal, mesenteric, retro-peritoneal, subcutaneious and gonadal), muscle and liver.
Publication Title
High-fat diet leads to tissue-specific changes reflecting risk factors for diseases in DBA/2J mice.
Sample Metadata Fields
Specimen part, Treatment
View Samples- Saccharomyces cerevisiae
- 70 Downloadable Samples
- Affymetrix Yeast Genome S98 Array (ygs98)
Description
We construced combinations of genetic deletions to infer genetic interactions in genomic expression data.
Publication Title
Prediction of phenotype and gene expression for combinations of mutations.
Sample Metadata Fields
No sample metadata fields
View Samples