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Response to Influenza infection in the pre-CC

ABSTRACT: 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.

ORGANISM(S): Mus musculus

PROVIDER: GSE30506 | GEO | 2011/12/13

SECONDARY ACCESSION(S): PRJNA143321

REPOSITORIES: GEO

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Response to Influenza infection in the pre-CC

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)

2011-12-13 | E-GEOD-30506 | biostudies-arrayexpress

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