RNAseq analysis of CC F2 female mice after infection with Ebola virus
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE165142 | GEO | 2022/08/31
REPOSITORIES: GEO
Similar Datasets
Project description:F2 female mice were generated from a cross of two collaborative cross (CC) strains, CC011 x CC074. These mice were infected with Ebola virus and liver samples were prepared at day three after infection. RNA from the livers were prepared and subjected to RNAseq analysis. This data set can be combined with data from GSE165142, in which female mice from the same cross were infected with Ebola virus, and liver samples were prepared at day six after infection. Results: Variations in gene expression levels that may be perdictive for severity
2022-08-31 | GSE173914 | GEO
Project description:RNAseq analysis of CC F2 female mice after infection with Ebola virus
| PRJNA693338 | ENA
Project description:RNAseq analysis of CC F2 female mice at day3 after infection with Ebola virus
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Project description:Gene expression changes in the lung was studied by RNAseq in different CC mouse strains infected with influenza A virus. Results: Strong differences between the genetically CC mouse strains can be observed in the activation of host defense genes. These differences can be related to genetic variants in the genome of the CC strains. Furthermore, different strains exhibit variant susceptibility to infections (body weight loss and survival). These differences can be correlated to differences in gene expression profiles.
2020-07-08 | GSE136748 | GEO
Project description:Obesity is associated with an increased risk of colon cancer. Our current study examines whether weight loss and/or treatment with the non-steroidal anti-inflammatory drug (NSAID) sulindac suppresses the protumor effects of obesity in a mouse model of colon cancer. Azoxymethane-treated male FVB/N mice were fed a low-fat diet (LFD) or high-fat diet (HFD) for 15 weeks, then HFD mice were randomized to remain on HFD (obese) or switch to LFD (formerly obese (FOb-LFD)). Within the control (LFD), obese, and FOb-LFD groups, half the mice were also randomized to start sulindac treatment (140 ppm in the diet). All mice were euthanized seven weeks later. FOb-LFD mice had intermediate levels of body weight, lower than obese but higher than control mice (P<0.05). Sulindac did not affect body weight. Obese mice had greater tumor multiplicity and burden than all other groups (P<0.05). Transcriptomic profiling indicated that both weight loss and sulindac modulate the expression of tumor genes related to invasion and may promote a more anti-tumor immune landscape. Furthermore, the fecal microbes Prevotella and Akkermansia muciniphila, both known to be elevated in colorectal cancer patients, were positively correlated with tumor multiplicity and reduced by sulindac in obese mice. In sum, either moderate weight loss or sulindac treatment completely reversed the effects of chronic obesity on colon tumorigenesis. Our findings suggest that an investigation regarding the effects of NSAID treatment on colon cancer risk and/or progression in obese individuals is warranted, particularly for those unable to achieve moderate weight loss.
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Project description:Using the distribution of Influenza-infected phenotypes (immunohistochemical (IHC) staining for viral protein and weight loss at 4 days post infection) in 99 Influenza-infected pre-Collaborative Cross (CC) lines, we have categorized the extreme phenotypes with regard to host response: severe (“high”) response to infection (N=26, IHC score: 4 or 5, % Weight loss > 15%) and mild (“low”) response to infection (N=18, IHC score: 0 or 1, % Weight loss < 5%). Global transcriptome profiling identified 2,671 transcripts that were significantly differentially expressed (DE; q-value < .05 and > 1.5 fold change either direction) due to differences in the host response phenotype. Using these DE transcripts, e-QTL mapping was performed to identify putative regulatory regions potentially controlling the expression of the transcripts. 21 significant e-QTLs (based on Bonferroni adjustment) were identified allowing direct examination of genes associated with regulation of host response. This is the first systems genetics study of influenza in a complex mouse model (where the level of genetic diversity approximates that seen in human populations), providing a framework for identification of causal variants and elucidation of the underlying biological sub-networks involved in response to infectious disease. 44 samples each derived from a different CC line with expression measured from lung tissue at day 4 post infection. Infection was with the mouse adapted influenza A strain A/PR/8/34 (H1N1)
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Project description:The purpose of this study was to conduct a randomized-controlled trial to evaluate the effect of a high-protein (HP) diet weight loss (WL) on changes in body composition, insulin sensitivity and skeletal muscle gene expression profile in postmenopausal women who were obese and randomized to one of three dietary intervention groups: 1) a weight maitenance group, 2) a weight loss group (normal protein intake, 0.8 g protein/kg body weight per day) and 3) a weight loss group (high protein intake, 1.2 g protein/kg body weight per day) and studies before and after they lost 10% of their body weight (WL groups) or a time-matched weight maintenacne period.
2016-12-01 | GSE73525 | GEO
Project description:Using the distribution of Influenza-infected phenotypes (immunohistochemical (IHC) staining for viral protein and weight loss at 4 days post infection) in 99 Influenza-infected pre-Collaborative Cross (CC) lines, we have categorized the extreme phenotypes with regard to host response: severe (“high”) response to infection (N=26, IHC score: 4 or 5, % Weight loss > 15%) and mild (“low”) response to infection (N=18, IHC score: 0 or 1, % Weight loss < 5%). Global transcriptome profiling identified 2,671 transcripts that were significantly differentially expressed (DE; q-value < .05 and > 1.5 fold change either direction) due to differences in the host response phenotype. Using these DE transcripts, e-QTL mapping was performed to identify putative regulatory regions potentially controlling the expression of the transcripts. 21 significant e-QTLs (based on Bonferroni adjustment) were identified allowing direct examination of genes associated with regulation of host response. This is the first systems genetics study of influenza in a complex mouse model (where the level of genetic diversity approximates that seen in human populations), providing a framework for identification of causal variants and elucidation of the underlying biological sub-networks involved in response to infectious disease.
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