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Comparative analysis of cis-regulation following stroke and seizures in subspaces of conserved eigensystems.

Dabrowski M, Dojer N, Zawadzka M, Mieczkowski J, Kaminska B - BMC Syst Biol (2010)

Bottom Line: It is often desirable to separate effects of different regulators on gene expression, or to identify effects of the same regulator across several systems.We identified a novel antagonistic effect of the motif recognized by the nuclear matrix attachment region-binding protein Satb1 on AP1-driven transcriptional activation, suggesting a link between chromatin loop structure and gene activation by AP1.The effects of motifs binding Satb1 and Creb on gene expression in brain conform to the assumption of the linear response model of gene regulation.

View Article: PubMed Central - HTML - PubMed

Affiliation: Laboratory of Transcription Regulation, Department of Cell Biology, Nencki Institute, Pasteura 3, 02-093 Warsaw, Poland. m.dabrowski@nencki.gov.pl

ABSTRACT

Background: It is often desirable to separate effects of different regulators on gene expression, or to identify effects of the same regulator across several systems. Here, we focus on the rat brain following stroke or seizures, and demonstrate how the two tasks can be approached simultaneously.

Results: We applied SVD to time-series gene expression datasets from the rat experimental models of stroke and seizures. We demonstrate conservation of two eigensystems, reflecting inflammation and/or apoptosis (eigensystem 2) and neuronal synaptic activity (eigensystem 3), between the stroke and seizures. We analyzed cis-regulation of gene expression in the subspaces of the conserved eigensystems. Bayesian networks analysis was performed separately for either experimental model, with cross-system validation of the highest-ranking features. In this way, we correctly re-discovered the role of AP1 in the regulation of apoptosis, and the involvement of Creb and Egr in the regulation of synaptic activity-related genes. We identified a novel antagonistic effect of the motif recognized by the nuclear matrix attachment region-binding protein Satb1 on AP1-driven transcriptional activation, suggesting a link between chromatin loop structure and gene activation by AP1. The effects of motifs binding Satb1 and Creb on gene expression in brain conform to the assumption of the linear response model of gene regulation. Our data also suggest that numerous enhancers of neuronal-specific genes are important for their responsiveness to the synaptic activity.

Conclusion: Eigensystems conserved between stroke and seizures separate effects of inflammation/apoptosis and neuronal synaptic activity, exerted by different transcription factors, on gene expression in rat brain.

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Design of the study (A) The datasets from gene profiling of rat brain following stroke in the MCAO model and kainate-induced seizures were each separately transformed by SVD. (B) The eigenarrays resulting from the SVD of either dataset were compared by correlation analysis performed for the genes common between the two datasets. (C) For the emerging conserved eigensystems 2 and 3, separately for all the genes in either dataset, we studied their functional Gene Ontology (GO) associations and employed Bayesian Networks (BN) to study their cis-regulation. The results obtained on one dataset were then compared (GO) or statistically tested (BN) on the other.
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Figure 1: Design of the study (A) The datasets from gene profiling of rat brain following stroke in the MCAO model and kainate-induced seizures were each separately transformed by SVD. (B) The eigenarrays resulting from the SVD of either dataset were compared by correlation analysis performed for the genes common between the two datasets. (C) For the emerging conserved eigensystems 2 and 3, separately for all the genes in either dataset, we studied their functional Gene Ontology (GO) associations and employed Bayesian Networks (BN) to study their cis-regulation. The results obtained on one dataset were then compared (GO) or statistically tested (BN) on the other.

Mentions: The overall design of our study is illustrated in Figure 1. We transform each dataset (MCAO, kainate) separately by SVD (Figure 1A) and identify eigenarrays conserved between the two systems (Figure 1B). This is followed by analysis of biological function using Gene Ontology (GO), and gene cis-regulation using Bayesian networks (BN) and our TRAM database of putative regulatory regions and motifs. These analyses are performed separately for either dataset and then the results for the corresponding eigensystems are compared (GO terms) or statistically cross-validated (BN results) on the other dataset. The cross-validation between the stroke and seizures data is not contradictory with the goal of gaining information by comparison of the two, because the two experimental models can be assumed - on biological grounds - to share some, but not all, regulatory mechanisms. Note that features specific for one model can be identified, as for each model we separately account for the multiplicity of testing.


Comparative analysis of cis-regulation following stroke and seizures in subspaces of conserved eigensystems.

Dabrowski M, Dojer N, Zawadzka M, Mieczkowski J, Kaminska B - BMC Syst Biol (2010)

Design of the study (A) The datasets from gene profiling of rat brain following stroke in the MCAO model and kainate-induced seizures were each separately transformed by SVD. (B) The eigenarrays resulting from the SVD of either dataset were compared by correlation analysis performed for the genes common between the two datasets. (C) For the emerging conserved eigensystems 2 and 3, separately for all the genes in either dataset, we studied their functional Gene Ontology (GO) associations and employed Bayesian Networks (BN) to study their cis-regulation. The results obtained on one dataset were then compared (GO) or statistically tested (BN) on the other.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2902439&req=5

Figure 1: Design of the study (A) The datasets from gene profiling of rat brain following stroke in the MCAO model and kainate-induced seizures were each separately transformed by SVD. (B) The eigenarrays resulting from the SVD of either dataset were compared by correlation analysis performed for the genes common between the two datasets. (C) For the emerging conserved eigensystems 2 and 3, separately for all the genes in either dataset, we studied their functional Gene Ontology (GO) associations and employed Bayesian Networks (BN) to study their cis-regulation. The results obtained on one dataset were then compared (GO) or statistically tested (BN) on the other.
Mentions: The overall design of our study is illustrated in Figure 1. We transform each dataset (MCAO, kainate) separately by SVD (Figure 1A) and identify eigenarrays conserved between the two systems (Figure 1B). This is followed by analysis of biological function using Gene Ontology (GO), and gene cis-regulation using Bayesian networks (BN) and our TRAM database of putative regulatory regions and motifs. These analyses are performed separately for either dataset and then the results for the corresponding eigensystems are compared (GO terms) or statistically cross-validated (BN results) on the other dataset. The cross-validation between the stroke and seizures data is not contradictory with the goal of gaining information by comparison of the two, because the two experimental models can be assumed - on biological grounds - to share some, but not all, regulatory mechanisms. Note that features specific for one model can be identified, as for each model we separately account for the multiplicity of testing.

Bottom Line: It is often desirable to separate effects of different regulators on gene expression, or to identify effects of the same regulator across several systems.We identified a novel antagonistic effect of the motif recognized by the nuclear matrix attachment region-binding protein Satb1 on AP1-driven transcriptional activation, suggesting a link between chromatin loop structure and gene activation by AP1.The effects of motifs binding Satb1 and Creb on gene expression in brain conform to the assumption of the linear response model of gene regulation.

View Article: PubMed Central - HTML - PubMed

Affiliation: Laboratory of Transcription Regulation, Department of Cell Biology, Nencki Institute, Pasteura 3, 02-093 Warsaw, Poland. m.dabrowski@nencki.gov.pl

ABSTRACT

Background: It is often desirable to separate effects of different regulators on gene expression, or to identify effects of the same regulator across several systems. Here, we focus on the rat brain following stroke or seizures, and demonstrate how the two tasks can be approached simultaneously.

Results: We applied SVD to time-series gene expression datasets from the rat experimental models of stroke and seizures. We demonstrate conservation of two eigensystems, reflecting inflammation and/or apoptosis (eigensystem 2) and neuronal synaptic activity (eigensystem 3), between the stroke and seizures. We analyzed cis-regulation of gene expression in the subspaces of the conserved eigensystems. Bayesian networks analysis was performed separately for either experimental model, with cross-system validation of the highest-ranking features. In this way, we correctly re-discovered the role of AP1 in the regulation of apoptosis, and the involvement of Creb and Egr in the regulation of synaptic activity-related genes. We identified a novel antagonistic effect of the motif recognized by the nuclear matrix attachment region-binding protein Satb1 on AP1-driven transcriptional activation, suggesting a link between chromatin loop structure and gene activation by AP1. The effects of motifs binding Satb1 and Creb on gene expression in brain conform to the assumption of the linear response model of gene regulation. Our data also suggest that numerous enhancers of neuronal-specific genes are important for their responsiveness to the synaptic activity.

Conclusion: Eigensystems conserved between stroke and seizures separate effects of inflammation/apoptosis and neuronal synaptic activity, exerted by different transcription factors, on gene expression in rat brain.

Show MeSH
Related in: MedlinePlus