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RNAseq analysis of heart tissue from mice treated with atenolol and isoproterenol reveals a reciprocal transcriptional response

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ABSTRACT

Background: The transcriptional response to many widely used drugs and its modulation by genetic variability is poorly understood. Here we present an analysis of RNAseq profiles from heart tissue of 18 inbred mouse strains treated with the β-blocker atenolol (ATE) and the β-agonist isoproterenol (ISO).

Results: Differential expression analyses revealed a large set of genes responding to ISO (n = 1770 at FDR = 0.0001) and a comparatively small one responding to ATE (n = 23 at FDR = 0.0001). At a less stringent definition of differential expression, the transcriptional responses to these two antagonistic drugs are reciprocal for many genes, with an overall anti-correlation of r = −0.3. This trend is also observed at the level of most individual strains even though the power to detect differential expression is significantly reduced. The inversely expressed gene sets are enriched with genes annotated for heart-related functions. Modular analysis revealed gene sets that exhibit coherent transcription profiles across some strains and/or treatments. Correlations between these modules and a broad spectrum of cardiovascular traits are stronger than expected by chance. This provides evidence for the overall importance of transcriptional regulation for these organismal responses and explicits links between co-expressed genes and the traits they are associated with. Gene set enrichment analysis of differentially expressed groups of genes pointed to pathways related to heart development and functionality.

Conclusions: Our study provides new insights into the transcriptional response of the heart to perturbations of the β-adrenergic system, implicating several new genes that had not been associated to this system previously.

Electronic supplementary material: The online version of this article (doi:10.1186/s12864-016-3059-6) contains supplementary material, which is available to authorized users.

No MeSH data available.


Module-trait correlations are larger than those of randomized controls. a Bi-clustered module-phenotype correlation matrix for the real data and (b) reshuffled data. The color code and distributions for these correlations are shown in (c). The two distributions are significantly different from each other (F ≈ 0.52, p ≈ 3.3 × 10−51) with heavier tails for the real data (Additional file 1: Figure S26). The phenotypes are described in Additional file 2: Table S4 [17]
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Fig4: Module-trait correlations are larger than those of randomized controls. a Bi-clustered module-phenotype correlation matrix for the real data and (b) reshuffled data. The color code and distributions for these correlations are shown in (c). The two distributions are significantly different from each other (F ≈ 0.52, p ≈ 3.3 × 10−51) with heavier tails for the real data (Additional file 1: Figure S26). The phenotypes are described in Additional file 2: Table S4 [17]

Mentions: We next asked whether module gene expression (i.e. the average expression of all genes associated with a module) is correlated with any of the organismal traits that had previously been measured in these mice [17] (Additional file 2: Table S4). Figure 4 shows that indeed on average module-trait correlations tend to be significantly larger than those of randomized controls (Additional file 1: Figure S26 and Methods). Importantly, different modules correlate with different traits, indicating that there might be specific aspects of the transcriptional program that mediate the different organismal responses (Additional file 2: Tables S5-S8).Fig. 4


RNAseq analysis of heart tissue from mice treated with atenolol and isoproterenol reveals a reciprocal transcriptional response
Module-trait correlations are larger than those of randomized controls. a Bi-clustered module-phenotype correlation matrix for the real data and (b) reshuffled data. The color code and distributions for these correlations are shown in (c). The two distributions are significantly different from each other (F ≈ 0.52, p ≈ 3.3 × 10−51) with heavier tails for the real data (Additional file 1: Figure S26). The phenotypes are described in Additional file 2: Table S4 [17]
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5015234&req=5

Fig4: Module-trait correlations are larger than those of randomized controls. a Bi-clustered module-phenotype correlation matrix for the real data and (b) reshuffled data. The color code and distributions for these correlations are shown in (c). The two distributions are significantly different from each other (F ≈ 0.52, p ≈ 3.3 × 10−51) with heavier tails for the real data (Additional file 1: Figure S26). The phenotypes are described in Additional file 2: Table S4 [17]
Mentions: We next asked whether module gene expression (i.e. the average expression of all genes associated with a module) is correlated with any of the organismal traits that had previously been measured in these mice [17] (Additional file 2: Table S4). Figure 4 shows that indeed on average module-trait correlations tend to be significantly larger than those of randomized controls (Additional file 1: Figure S26 and Methods). Importantly, different modules correlate with different traits, indicating that there might be specific aspects of the transcriptional program that mediate the different organismal responses (Additional file 2: Tables S5-S8).Fig. 4

View Article: PubMed Central - PubMed

ABSTRACT

Background: The transcriptional response to many widely used drugs and its modulation by genetic variability is poorly understood. Here we present an analysis of RNAseq profiles from heart tissue of 18 inbred mouse strains treated with the β-blocker atenolol (ATE) and the β-agonist isoproterenol (ISO).

Results: Differential expression analyses revealed a large set of genes responding to ISO (n = 1770 at FDR = 0.0001) and a comparatively small one responding to ATE (n = 23 at FDR = 0.0001). At a less stringent definition of differential expression, the transcriptional responses to these two antagonistic drugs are reciprocal for many genes, with an overall anti-correlation of r = −0.3. This trend is also observed at the level of most individual strains even though the power to detect differential expression is significantly reduced. The inversely expressed gene sets are enriched with genes annotated for heart-related functions. Modular analysis revealed gene sets that exhibit coherent transcription profiles across some strains and/or treatments. Correlations between these modules and a broad spectrum of cardiovascular traits are stronger than expected by chance. This provides evidence for the overall importance of transcriptional regulation for these organismal responses and explicits links between co-expressed genes and the traits they are associated with. Gene set enrichment analysis of differentially expressed groups of genes pointed to pathways related to heart development and functionality.

Conclusions: Our study provides new insights into the transcriptional response of the heart to perturbations of the β-adrenergic system, implicating several new genes that had not been associated to this system previously.

Electronic supplementary material: The online version of this article (doi:10.1186/s12864-016-3059-6) contains supplementary material, which is available to authorized users.

No MeSH data available.