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Mus musculus
113 Downloadable Samples
Affymetrix Mouse Gene 1.1 ST Array (mogene11st)
Description
Homeodomain interacting protein kinase 2 (Hipk2) has previously been implicated in control of several transcription factors involved in embryonic development, apoptosis, cell proliferation and tumour development13. Analysis of gene expression in tissues from genetically heterogeneous mouse or human populations can reveal motifs associated with the structural or functional components of the tissue, and may predict roles for genes of unknown function4,5. Here we have applied this network strategy to uncover a novel role for the Hipk2 gene in the transcriptional system controlling adipogenesis. Both in vitro and in vivo models were used to show that knockdown or loss of Hipk2 specifically inhibits white adipose cell differentiation and tissue development. In addition, loss of Hipk2 leads to induction of pockets of multilocular brown fat-like cells in remaining white adipose depots. These cells express markers of brown and beige fat such as uncoupling protein 1 (Ucp1) and transmembrane protein 26 (Tmem26), and thermogenic genes including PPAR- coactivator 1a (Ppargc1a), and cell death-inducing DFFA-like effector a (Cidea). These changes are accompanied by increased insulin sensitivity in Hipk2 knock-out mice and reduced high fat diet-induced weight gain, highlighting a potential role for this kinase in diseases such as diabetes and obesity. Our study underscores the versatility and power of a readily available tissue, such as skin, for network modelling of systemic transcriptional programs involved in multiple pathways, including lipid metabolism and adipogenesis.
Publication Title
Identification of Hipk2 as an essential regulator of white fat development.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Homo sapiens
- 6 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The hematopoietic microenvironment consists of non-hematopoietic derived stromal elements and hematopoietic derived monocytes and macrophages which interact and function together to control the proliferation and differentiation of early blood-forming cells. Two human stromal cell lines (HS-5 and HS-27a) representing distinct functional components of this microenvironment have been extensively characterized and shown to influence monocyte gene expression. This series of gene expression profiles is intended to extend the previous studies and identify which gene expression changes may require cell-cell contact or occur in the stromal cells as a result of monocyte influence;or in the monocytes as a result of stormal influences.
Publication Title
Functionally and phenotypically distinct subpopulations of marrow stromal cells are fibroblast in origin and induce different fates in peripheral blood monocytes.
Sample Metadata Fields
Sex
View Samples- Homo sapiens
- 6 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
The bone marrow microenvironment is a complex mixture of cells that function in concert to regulate hematopoiesis. Cellular components include fixed nonhematopoietic stromal elements as well as monocytes and resident macrophages, which are derived from the hematopoietic stem cells. Although these monocyte-lineage cells are reported to modify stromal cell function, the reverse also occurs. Given the secretory capability of the monocyte/macrophage and their various potential functions, it is not surprising that stromal cells contained within a particular niche can modify monocyte gene expression and functional maturation.
Publication Title
Functionally and phenotypically distinct subpopulations of marrow stromal cells are fibroblast in origin and induce different fates in peripheral blood monocytes.
Sample Metadata Fields
Sex
View Samples- Homo sapiens
- 22 Downloadable Samples
- Illumina HumanHT-12 V4.0 expression beadchip
Description
Short sleep duration is associated with adverse metabolic, cardiovascular, and inflammatory effects. Co-twin study methodologies account for familial (e.g., genetics and shared environmental) confounding, allowing assessment of subtle environmental effects, such as the effect of short habitual sleep duration on gene expression. Therefore, we sought to investigate gene expression in monozygotic twins discordant for actigraphically phenotyped habitual sleep duration. Eleven healthy monozygotic twin pairs (82% female; mean age 42.7 years; SD=18.1), selected based on subjective sleep duration discordance, were objectively phenotyped for habitual sleep duration with two-weeks of wrist actigraphy. Peripheral blood leukocyte (PBL) RNA from fasting blood samples was obtained on the final day of actigraphic measurement and hybridized to Illumina humanHT-12 microarrays. Differential gene expression was determined between paired samples and mapped to functional categories using Gene Ontology. Next, a more comprehensive gene set enrichment analysis was performed based on the entire PBL transcriptome. The mean 24 hour sleep duration of the total sample was 439.2 minutes (SD=46.8 minutes; range 325.4 to 521.6 minutes). Mean within-pair sleep duration difference per 24 hours was 64.4 minutes (SD=21.2; range 45.9 to 114.6 minutes). The twin cohort displayed distinctive pathway enrichment based on sleep duration differences. Short sleep was associated with up-regulation of genes involved in transcription, ribosome, translation and oxidative phosphorylation. Unexpectedly, genes down-regulated in short sleep twins were highly enriched in immuno-inflammatory pathways such interleukin signaling and leukocyte activation, as well as developmental programs, coagulation cascade, and cell adhesion. Objectively assessed habitual sleep duration in monozygotic twin pairs appears to be associated with distinct patterns of differential gene expression and pathway enrichment. By accounting for familial confounding and measuring real life sleep duration, our study shows the transcriptomic effects of short sleep on dysregulated immune response and provides a potential link between sleep deprivation and adverse metabolic, cardiovascular and inflammatory outcomes.
Publication Title
Transcriptional Signatures of Sleep Duration Discordance in Monozygotic Twins.
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 109 Downloadable Samples
- Affymetrix Mouse Gene 1.1 ST Array (mogene11st)
Description
Human tumours show a high level of clonal heterogeneity that contributes to malignant progression and metastasis, but the processes that influence the timing of metastatic dissemination of subclones are unknown. Here, we have used whole exome sequencing of 98 matched benign, malignant, and metastatic skin tumours from genetically heterogeneous mice to demonstrate that most metastases disseminate synchronously from the primary tumour, but then evolve separately, acquiring an additional set of mutations during growth at distant sites. Shared mutations between primary carcinomas and their matched metastases have the distinct A>T signature of the initiating carcinogen Dimethylbanzanthracene (DMBA), but non-shared mutations are primarily G>T or C>T substitutions, associated with oxidative stress. We found recurrent point mutations in several hundred genes, including several in the Ras (Hras, Kras, and Pik3ca) pathway. We propose that carcinogen-driven mouse tumour models can aid our understanding of the forces that shape clonal and genetic evolution of human cancers.
Publication Title
Evolution of metastasis revealed by mutational landscapes of chemically induced skin cancers.
Sample Metadata Fields
Sex
View Samples- Mus musculus
- 307 Downloadable Samples
- Affymetrix Mouse Gene 1.1 ST Array (mogene11st)
Description
Gene expression levels in normal tissues can differ substantially between individuals, due to inherited polymorphisms acting in cis or trans. Analysis of this variation across a population of genetically distinct individuals allows us to visualize a network of co-expressed genes under normal homeostatic conditions, and the consequences of perturbation by tissue damage or disease development. Here, we explore gene expression networks in normal adult skin from 470 genetically unique mice, and demonstrate the dependence of the architecture of signaling pathways on skin tissue location (dorsal or tail skin) and perturbation by induction of inflammation or tumorigenesis. Gene networks related to specific cell types, as well as signaling pathways including Sonic Hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is extensively rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for eQTL network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules.
Publication Title
Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer.
Sample Metadata Fields
Sex, Age, Specimen part, Treatment
View Samples
GSE52524- Mus musculus
- 195 Downloadable Samples
- Affymetrix Mouse Gene 1.1 ST Array (mogene11st)
Description
Gene expression levels in normal tissues can differ substantially between individuals, due to inherited polymorphisms acting in cis or trans. Analysis of this variation across a population of genetically distinct individuals allows us to visualize a network of co-expressed genes under normal homeostatic conditions, and the consequences of perturbation by tissue damage or disease development. Here, we explore gene expression networks in normal adult skin from 470 genetically unique mice, and demonstrate the dependence of the architecture of signaling pathways on skin tissue location (dorsal or tail skin) and perturbation by induction of inflammation or tumorigenesis. Gene networks related to specific cell types, as well as signaling pathways including Sonic Hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is extensively rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for eQTL network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules.
Publication Title
Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer.
Sample Metadata Fields
Sex, Specimen part
View Samples GSE52639- Mus musculus
- 153 Downloadable Samples
- Affymetrix Mouse Gene 1.1 ST Array (mogene11st)
Description
Gene expression levels in normal tissues can differ substantially between individuals, due to inherited polymorphisms acting in cis or trans. Analysis of this variation across a population of genetically distinct individuals allows us to visualize a network of co-expressed genes under normal homeostatic conditions, and the consequences of perturbation by tissue damage or disease development. Here, we explore gene expression networks in normal adult skin from 470 genetically unique mice, and demonstrate the dependence of the architecture of signaling pathways on skin tissue location (dorsal or tail skin) and perturbation by induction of inflammation or tumorigenesis. Gene networks related to specific cell types, as well as signaling pathways including Sonic Hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is extensively rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for eQTL network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules.
Publication Title
Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer.
Sample Metadata Fields
Sex
View Samples- Mus musculus
- 130 Downloadable Samples
- Affymetrix Mouse Gene 1.1 ST Array (mogene11st)
Description
Hair follicles are self-renewing organs within the skin which cycle through periods of growth and destruction, with an intervening period of outward quiescence. The hair follicle cycle is driven by Hedgehog and Wnt signaling and affects epithelial thickness, melanin production, immune function, and tumor susceptibility. We have previously shown that somatic alterations to the genome affect the genetic architecture of the skin. This study examines how the hair follicle cycle affects gene the genetic architecture in vivo by genomic and genetic analysis of 343 genetically heterogeneous mice during the hair follicle growth phase (anagen) and quiescent phase (telogen). We use eQTL analysis and differential correlation to identify changes in metabolic and stem cell activity not detected by differential expression. Germline influence in gene expression is profoundly higher during anagen, but this increase is not a simple factor of higher levels of gene expression. The most strongly induced eQTLs were involved in cellular energy metabolism and melanogenesis rather than hair follicle growth or hedgehog signaling. We demonstrate that hair follicle and circadian rhythm pathways are sexually dimorphic, but do not find evidence for an effect of sex on eQTL networks. We also use eQTL gene network analysis to identify candidate causal relationships between expression of genes in the hair follicle and melanin pathways, identifying Mcoln3 as a candidate for the familial melanoma locus on 1p22. To lower the bioinformatic barriers to eQTL network analysis we produced CARMEN, a free open-source stand-alone software package. This study demonstrates how to perform a systems genetic analysis of a heterogeneous tissue studied in vivo under physiologically relevant growth signals.
Publication Title
Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Mus musculus
- 68 Downloadable Samples
- Affymetrix Mouse Gene 1.1 ST Array (mogene11st)
Description
Gene expression levels in normal tissues can differ substantially between individuals, due to inherited polymorphisms acting in cis or trans. Analysis of this variation across a population of genetically distinct individuals allows us to visualize a network of co-expressed genes under normal homeostatic conditions, and the consequences of perturbation by tissue damage or disease development. Here, we explore gene expression networks in normal adult skin from 470 genetically unique mice, and demonstrate the dependence of the architecture of signaling pathways on skin tissue location (dorsal or tail skin) and perturbation by induction of inflammation or tumorigenesis. Gene networks related to specific cell types, as well as signaling pathways including Sonic Hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is extensively rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for eQTL network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules.
Publication Title
Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer.
Sample Metadata Fields
Specimen part, Treatment
View Samples