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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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Gene signatures for B-cells. List of the strongest correlates for Cd19 (probe set 1450570_at), all correlated at p < 10-12.
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Figure 5: Gene signatures for B-cells. List of the strongest correlates for Cd19 (probe set 1450570_at), all correlated at p < 10-12.

Mentions: The hemoglobin genes Hba-a1 (hemoglobin alpha, adult chain 1) and Hbb-b2 (hemoglobin beta, adult minor chain) were among the top 10 genes with highest expression values in our lung data set. The high levels of hemoglobin transcripts suggested that circulating blood cells, including immune cells, may also be analyzed in our data set. Therefore, we investigated the gene expression networks of known immune cell markers, e.g. Cd3 genes as specific markers for T cells. We calculated the correlations of Cd3d (Cd3 antigen, delta polypeptide) expression levels over all BXD lines with all other genes. This analysis revealed 20 genes with a very highly correlated expression value (p-value below 10-14, Figure 4). Most of these genes were known T cell markers or involved in T cell regulation. Eight out of the 12 genes with the strongest correlations were also exclusively expressed in T cells according to the BioGPS database (Wu et al., 2009): Cd3d, Itk, Tcrb-13V Cd3e, Cd3g, Scap1, Cd6 and Cd5 (see Figure 4 for full gene names). Similarly, we searched for B cell-specific signatures starting with the B cell marker gene Cd19 (CD19 antigen). The probe set "1450570_a_at" detected Cd19 mRNA levels and showed a mean expression level of 9.3. We found 14 probe sets with a correlation above 0.80 (p-value < 10-14, Figure 5). A comparison with the BioGPS database revealed that eight of them, Cd19, Cd79b, Faim3, Cd79a, Blk, B3gnt5, Cd22 and Blr1 (see Figure 5 for full gene names) were also exclusively expressed in B cells. Therefore, these genes can be considered as T and B cell signature genes which may be used to follow the presence and infiltration of T and B cells in the lung under normal and pathological conditions.


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)

Gene signatures for B-cells. List of the strongest correlates for Cd19 (probe set 1450570_at), all correlated at p < 10-12.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 5: Gene signatures for B-cells. List of the strongest correlates for Cd19 (probe set 1450570_at), all correlated at p < 10-12.
Mentions: The hemoglobin genes Hba-a1 (hemoglobin alpha, adult chain 1) and Hbb-b2 (hemoglobin beta, adult minor chain) were among the top 10 genes with highest expression values in our lung data set. The high levels of hemoglobin transcripts suggested that circulating blood cells, including immune cells, may also be analyzed in our data set. Therefore, we investigated the gene expression networks of known immune cell markers, e.g. Cd3 genes as specific markers for T cells. We calculated the correlations of Cd3d (Cd3 antigen, delta polypeptide) expression levels over all BXD lines with all other genes. This analysis revealed 20 genes with a very highly correlated expression value (p-value below 10-14, Figure 4). Most of these genes were known T cell markers or involved in T cell regulation. Eight out of the 12 genes with the strongest correlations were also exclusively expressed in T cells according to the BioGPS database (Wu et al., 2009): Cd3d, Itk, Tcrb-13V Cd3e, Cd3g, Scap1, Cd6 and Cd5 (see Figure 4 for full gene names). Similarly, we searched for B cell-specific signatures starting with the B cell marker gene Cd19 (CD19 antigen). The probe set "1450570_a_at" detected Cd19 mRNA levels and showed a mean expression level of 9.3. We found 14 probe sets with a correlation above 0.80 (p-value < 10-14, Figure 5). A comparison with the BioGPS database revealed that eight of them, Cd19, Cd79b, Faim3, Cd79a, Blk, B3gnt5, Cd22 and Blr1 (see Figure 5 for full gene names) were also exclusively expressed in B cells. Therefore, these genes can be considered as T and B cell signature genes which may be used to follow the presence and infiltration of T and B cells in the lung under normal and pathological conditions.

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