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Genome-wide analysis of the mouse lung transcriptome reveals novel molecular gene interaction networks and cell-specific expression signatures.

Alberts R, Lu L, Williams RW, Schughart K - Respir. Res. (2011)

Bottom Line: Our goal is to provide a key community resource on the genetics of the normative lung transcriptome that can serve as a foundation for experimental analysis and allow predicting genetic predisposition and response to pathogens, allergens, and xenobiotics.This interval contains the transcription factor Ahr that has a critical mis-sense allele in the DBA/2J haplotype and evidently modulates transcriptional activation by AhR.Large-scale gene expression analyses in genetic reference populations revealed lung-specific and immune-cell gene expression profiles and suggested specific gene regulatory interactions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Infection Genetics, University of Veterinary Medicine Hannover, Inhoffenstr, Braunschweig, Germany.

ABSTRACT

Background: The lung is critical in surveillance and initial defense against pathogens. In humans, as in mice, individual genetic differences strongly modulate pulmonary responses to infectious agents, severity of lung disease, and potential allergic reactions. In a first step towards understanding genetic predisposition and pulmonary molecular networks that underlie individual differences in disease vulnerability, we performed a global analysis of normative lung gene expression levels in inbred mouse strains and a large family of BXD strains that are widely used for systems genetics. Our goal is to provide a key community resource on the genetics of the normative lung transcriptome that can serve as a foundation for experimental analysis and allow predicting genetic predisposition and response to pathogens, allergens, and xenobiotics.

Methods: Steady-state polyA+ mRNA levels were assayed across a diverse and fully genotyped panel of 57 isogenic strains using the Affymetrix M430 2.0 array. Correlations of expression levels between genes were determined. Global expression QTL (eQTL) analysis and network covariance analysis was performed using tools and resources in GeneNetwork http://www.genenetwork.org.

Results: Expression values were highly variable across strains and in many cases exhibited a high heritability factor. Several genes which showed a restricted expression to lung tissue were identified. Using correlations between gene expression values across all strains, we defined and extended memberships of several important molecular networks in the lung. Furthermore, we were able to extract signatures of immune cell subpopulations and characterize co-variation and shared genetic modulation. Known QTL regions for respiratory infection susceptibility were investigated and several cis-eQTL genes were identified. Numerous cis- and trans-regulated transcripts and chromosomal intervals with strong regulatory activity were mapped. The Cyp1a1 P450 transcript had a strong trans-acting eQTL (LOD 11.8) on Chr 12 at 36 ± 1 Mb. This interval contains the transcription factor Ahr that has a critical mis-sense allele in the DBA/2J haplotype and evidently modulates transcriptional activation by AhR.

Conclusions: Large-scale gene expression analyses in genetic reference populations revealed lung-specific and immune-cell gene expression profiles and suggested specific gene regulatory interactions.

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The cytokeratin network. Pearson correlations (listed below the diagonal) showed very high correlations between all pairs of the 20 selected genes. Spearman Rank correlations are shown above the diagonal.
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Figure 3: The cytokeratin network. Pearson correlations (listed below the diagonal) showed very high correlations between all pairs of the 20 selected genes. Spearman Rank correlations are shown above the diagonal.

Mentions: In a similar way, we identified another gene network of 20 genes that exhibited very high correlations of their expression levels across all mouse strains. All possible pairs of genes in this network showed a correlation above 0.95 (Figure 3). The network contained two keratin genes, Krt4 (keratin 4) and Krt13 (keratin 13) and genes involved in cytoskeleton functions, again pointing to a possible interaction of these genes in the same pathway or biological process. Further gene networks found by correlation studies were related to B and T cells (see below).


Genome-wide analysis of the mouse lung transcriptome reveals novel molecular gene interaction networks and cell-specific expression signatures.

Alberts R, Lu L, Williams RW, Schughart K - Respir. Res. (2011)

The cytokeratin network. Pearson correlations (listed below the diagonal) showed very high correlations between all pairs of the 20 selected genes. Spearman Rank correlations are shown above the diagonal.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3105947&req=5

Figure 3: The cytokeratin network. Pearson correlations (listed below the diagonal) showed very high correlations between all pairs of the 20 selected genes. Spearman Rank correlations are shown above the diagonal.
Mentions: In a similar way, we identified another gene network of 20 genes that exhibited very high correlations of their expression levels across all mouse strains. All possible pairs of genes in this network showed a correlation above 0.95 (Figure 3). The network contained two keratin genes, Krt4 (keratin 4) and Krt13 (keratin 13) and genes involved in cytoskeleton functions, again pointing to a possible interaction of these genes in the same pathway or biological process. Further gene networks found by correlation studies were related to B and T cells (see below).

Bottom Line: Our goal is to provide a key community resource on the genetics of the normative lung transcriptome that can serve as a foundation for experimental analysis and allow predicting genetic predisposition and response to pathogens, allergens, and xenobiotics.This interval contains the transcription factor Ahr that has a critical mis-sense allele in the DBA/2J haplotype and evidently modulates transcriptional activation by AhR.Large-scale gene expression analyses in genetic reference populations revealed lung-specific and immune-cell gene expression profiles and suggested specific gene regulatory interactions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Infection Genetics, University of Veterinary Medicine Hannover, Inhoffenstr, Braunschweig, Germany.

ABSTRACT

Background: The lung is critical in surveillance and initial defense against pathogens. In humans, as in mice, individual genetic differences strongly modulate pulmonary responses to infectious agents, severity of lung disease, and potential allergic reactions. In a first step towards understanding genetic predisposition and pulmonary molecular networks that underlie individual differences in disease vulnerability, we performed a global analysis of normative lung gene expression levels in inbred mouse strains and a large family of BXD strains that are widely used for systems genetics. Our goal is to provide a key community resource on the genetics of the normative lung transcriptome that can serve as a foundation for experimental analysis and allow predicting genetic predisposition and response to pathogens, allergens, and xenobiotics.

Methods: Steady-state polyA+ mRNA levels were assayed across a diverse and fully genotyped panel of 57 isogenic strains using the Affymetrix M430 2.0 array. Correlations of expression levels between genes were determined. Global expression QTL (eQTL) analysis and network covariance analysis was performed using tools and resources in GeneNetwork http://www.genenetwork.org.

Results: Expression values were highly variable across strains and in many cases exhibited a high heritability factor. Several genes which showed a restricted expression to lung tissue were identified. Using correlations between gene expression values across all strains, we defined and extended memberships of several important molecular networks in the lung. Furthermore, we were able to extract signatures of immune cell subpopulations and characterize co-variation and shared genetic modulation. Known QTL regions for respiratory infection susceptibility were investigated and several cis-eQTL genes were identified. Numerous cis- and trans-regulated transcripts and chromosomal intervals with strong regulatory activity were mapped. The Cyp1a1 P450 transcript had a strong trans-acting eQTL (LOD 11.8) on Chr 12 at 36 ± 1 Mb. This interval contains the transcription factor Ahr that has a critical mis-sense allele in the DBA/2J haplotype and evidently modulates transcriptional activation by AhR.

Conclusions: Large-scale gene expression analyses in genetic reference populations revealed lung-specific and immune-cell gene expression profiles and suggested specific gene regulatory interactions.

Show MeSH
Related in: MedlinePlus