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Linking gene expression and functional network data in human heart failure.

Camargo A, Azuaje F - PLoS ONE (2007)

Bottom Line: Highly-connected proteins are not necessarily encoded by genes significantly differentially expressed.Furthermore, genes that were not defined as significantly differentially expressed may encode proteins with many interacting partners.We also found that hubs and superhubs display a significant diversity of co-expression patterns in comparison to peripheral nodes.

View Article: PubMed Central - PubMed

Affiliation: School of Computing and Mathematics, University of Ulster at Jordanstown, Newtownabbey, Northern Ireland, United Kingdom.

ABSTRACT

Background: Gene expression profiling and the analysis of protein-protein interaction (PPI) networks may support the identification of disease bio-markers and potential drug targets. Thus, a step forward in the development of systems approaches to medicine is the integrative analysis of these data sources in specific pathological conditions. We report such an integrative bioinformatics analysis in human heart failure (HF). A global PPI network in HF was assembled, which by itself represents a useful compendium of the current status of human HF-relevant interactions. This provided the basis for the analysis of interaction connectivity patterns in relation to a HF gene expression data set.

Results: Relationships between the significance of the differentiation of gene expression and connectivity degrees in the PPI network were established. In addition, relationships between gene co-expression and PPI network connectivity were analysed. Highly-connected proteins are not necessarily encoded by genes significantly differentially expressed. Genes that are not significantly differentially expressed may encode proteins that exhibit diverse network connectivity patterns. Furthermore, genes that were not defined as significantly differentially expressed may encode proteins with many interacting partners. Genes encoding network hubs may exhibit weak co-expression with the genes encoding their interacting protein partners. We also found that hubs and superhubs display a significant diversity of co-expression patterns in comparison to peripheral nodes. Gene Ontology (GO) analysis established that highly-connected proteins are likely to be engaged in higher level GO biological process terms, while low-connectivity proteins tend to be engaged in more specific disease-related processes.

Conclusion: This investigation supports the hypothesis that the integrative analysis of differential gene expression and PPI network analysis may facilitate a better understanding of functional roles and the identification of potential drug targets in human heart failure.

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Related in: MedlinePlus

PPIs networks. PPIs networks corresponding to (A) global human HF network, (B) BCAR1's PPI network, (C) AKT1's PPI network. All PPIs were retrieved from the HPRD. Up-regulated genes are represented by red nodes. Down-regulated genes are represented by green nodes. Known HF genes (KHFG) are represented by nodes in yellow. Other genes encoding interacting partner proteins are represented by nodes in purple, if they have a corresponding transcript, or in grey if they have no corresponding transcripts in the gene expression data set.
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pone-0001347-g001: PPIs networks. PPIs networks corresponding to (A) global human HF network, (B) BCAR1's PPI network, (C) AKT1's PPI network. All PPIs were retrieved from the HPRD. Up-regulated genes are represented by red nodes. Down-regulated genes are represented by green nodes. Known HF genes (KHFG) are represented by nodes in yellow. Other genes encoding interacting partner proteins are represented by nodes in purple, if they have a corresponding transcript, or in grey if they have no corresponding transcripts in the gene expression data set.

Mentions: The PPI network (Figure 1A) consisted of nodes representing proteins and their interaction partners. Some of the nodes represented proteins encoded by significantly differentially-expressed genes obtained from expression pattern analysis. Initially, 1161 genes were identified (974 up-regulated in DCM and 187 down-regulated in DCM). However, only 506 (457 up-regulated and 49 down-regulated genes) were represented in the network because their encoded proteins were reported to have at least one interacting protein partner. The network also contained 71 nodes representing proteins encoded by KHFGs only. The network contained 2835 nodes representing proteins encoded by not significantly differentially-expressed genes (Table 1).


Linking gene expression and functional network data in human heart failure.

Camargo A, Azuaje F - PLoS ONE (2007)

PPIs networks. PPIs networks corresponding to (A) global human HF network, (B) BCAR1's PPI network, (C) AKT1's PPI network. All PPIs were retrieved from the HPRD. Up-regulated genes are represented by red nodes. Down-regulated genes are represented by green nodes. Known HF genes (KHFG) are represented by nodes in yellow. Other genes encoding interacting partner proteins are represented by nodes in purple, if they have a corresponding transcript, or in grey if they have no corresponding transcripts in the gene expression data set.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2147076&req=5

pone-0001347-g001: PPIs networks. PPIs networks corresponding to (A) global human HF network, (B) BCAR1's PPI network, (C) AKT1's PPI network. All PPIs were retrieved from the HPRD. Up-regulated genes are represented by red nodes. Down-regulated genes are represented by green nodes. Known HF genes (KHFG) are represented by nodes in yellow. Other genes encoding interacting partner proteins are represented by nodes in purple, if they have a corresponding transcript, or in grey if they have no corresponding transcripts in the gene expression data set.
Mentions: The PPI network (Figure 1A) consisted of nodes representing proteins and their interaction partners. Some of the nodes represented proteins encoded by significantly differentially-expressed genes obtained from expression pattern analysis. Initially, 1161 genes were identified (974 up-regulated in DCM and 187 down-regulated in DCM). However, only 506 (457 up-regulated and 49 down-regulated genes) were represented in the network because their encoded proteins were reported to have at least one interacting protein partner. The network also contained 71 nodes representing proteins encoded by KHFGs only. The network contained 2835 nodes representing proteins encoded by not significantly differentially-expressed genes (Table 1).

Bottom Line: Highly-connected proteins are not necessarily encoded by genes significantly differentially expressed.Furthermore, genes that were not defined as significantly differentially expressed may encode proteins with many interacting partners.We also found that hubs and superhubs display a significant diversity of co-expression patterns in comparison to peripheral nodes.

View Article: PubMed Central - PubMed

Affiliation: School of Computing and Mathematics, University of Ulster at Jordanstown, Newtownabbey, Northern Ireland, United Kingdom.

ABSTRACT

Background: Gene expression profiling and the analysis of protein-protein interaction (PPI) networks may support the identification of disease bio-markers and potential drug targets. Thus, a step forward in the development of systems approaches to medicine is the integrative analysis of these data sources in specific pathological conditions. We report such an integrative bioinformatics analysis in human heart failure (HF). A global PPI network in HF was assembled, which by itself represents a useful compendium of the current status of human HF-relevant interactions. This provided the basis for the analysis of interaction connectivity patterns in relation to a HF gene expression data set.

Results: Relationships between the significance of the differentiation of gene expression and connectivity degrees in the PPI network were established. In addition, relationships between gene co-expression and PPI network connectivity were analysed. Highly-connected proteins are not necessarily encoded by genes significantly differentially expressed. Genes that are not significantly differentially expressed may encode proteins that exhibit diverse network connectivity patterns. Furthermore, genes that were not defined as significantly differentially expressed may encode proteins with many interacting partners. Genes encoding network hubs may exhibit weak co-expression with the genes encoding their interacting protein partners. We also found that hubs and superhubs display a significant diversity of co-expression patterns in comparison to peripheral nodes. Gene Ontology (GO) analysis established that highly-connected proteins are likely to be engaged in higher level GO biological process terms, while low-connectivity proteins tend to be engaged in more specific disease-related processes.

Conclusion: This investigation supports the hypothesis that the integrative analysis of differential gene expression and PPI network analysis may facilitate a better understanding of functional roles and the identification of potential drug targets in human heart failure.

Show MeSH
Related in: MedlinePlus