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Finding gene regulatory network candidates using the gene expression knowledge base.

Venkatesan A, Tripathi S, Sanz de Galdeano A, Blondé W, Lægreid A, Mironov V, Kuiper M - BMC Bioinformatics (2014)

Bottom Line: Semantic web technologies provide the means for processing and integrating various heterogeneous information sources.The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression.This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Norwegian University of Science and Technology (NTNU), N-7491, Trondheim, Norway. aravind.venkatesan@ntnu.no.

ABSTRACT

Background: Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis.

Results: We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions.

Conclusions: Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

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Core CCK2R network and novel candidate regulators. The core of the gastrin mediated signal transduction network (CCK2R), and the novel candidate regulators resulting from our queries are shown. The CCK2R DbTFs that were targeted in our queries are colored light green. The network components in grey and the solid lines connecting them are part of the core CCK2R network and documented as regulators of the CCK2R DbTFs and respond to gastrin. The dotted lines represent new relations identified by the queries which could be verified against literature: blue pointed arrows denote ‘activation or positive influence’ and red bar-headed arrows depict ‘repression or negative influence’. CREB1 candidate regulators identified through Q1, Q2 and Q3 are colored yellow. Candidate regulators of NFκB1 identified through Q4 are colored turquoise, and candidate regulators of TCF7L2 identified through Q5 are colored orange. The target genes shared by the CCK2R DbTFs (CREB1 and NFκB1) and the DbTF candidates identified through Q6 are colored light red (JUN and BRCA2) and their connections are shown as solid arrows.
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Fig1: Core CCK2R network and novel candidate regulators. The core of the gastrin mediated signal transduction network (CCK2R), and the novel candidate regulators resulting from our queries are shown. The CCK2R DbTFs that were targeted in our queries are colored light green. The network components in grey and the solid lines connecting them are part of the core CCK2R network and documented as regulators of the CCK2R DbTFs and respond to gastrin. The dotted lines represent new relations identified by the queries which could be verified against literature: blue pointed arrows denote ‘activation or positive influence’ and red bar-headed arrows depict ‘repression or negative influence’. CREB1 candidate regulators identified through Q1, Q2 and Q3 are colored yellow. Candidate regulators of NFκB1 identified through Q4 are colored turquoise, and candidate regulators of TCF7L2 identified through Q5 are colored orange. The target genes shared by the CCK2R DbTFs (CREB1 and NFκB1) and the DbTF candidates identified through Q6 are colored light red (JUN and BRCA2) and their connections are shown as solid arrows.

Mentions: NFκB1 and RELA are members of the NFκB transcription factor family known to be involved in regulating apoptosis, proliferation, and immune responses [22]. Gastrin dependent regulation of these transcription factors reportedly is mediated through PKC and Rho GTPase signaling cascades [23,24] (Figure 1). The activity of NFκB transcription factors is under the control of a family of inhibitors, known as ‘inhibitors of kB’ (IkB), which sequester NFκB in the cytoplasm and thereby keep these transcription factors in their inactive state [25]. Proteasomal degradation of IkB factors results in restoration of the active state of the NFκB and promotes its import to the nucleus. In order to gain detailed mechanistic insights in NFκB regulation, we were interested in retrieving proteins that contribute to NFκB down-regulation, and at the same time have functions related to proteasomal degradation.Figure 1


Finding gene regulatory network candidates using the gene expression knowledge base.

Venkatesan A, Tripathi S, Sanz de Galdeano A, Blondé W, Lægreid A, Mironov V, Kuiper M - BMC Bioinformatics (2014)

Core CCK2R network and novel candidate regulators. The core of the gastrin mediated signal transduction network (CCK2R), and the novel candidate regulators resulting from our queries are shown. The CCK2R DbTFs that were targeted in our queries are colored light green. The network components in grey and the solid lines connecting them are part of the core CCK2R network and documented as regulators of the CCK2R DbTFs and respond to gastrin. The dotted lines represent new relations identified by the queries which could be verified against literature: blue pointed arrows denote ‘activation or positive influence’ and red bar-headed arrows depict ‘repression or negative influence’. CREB1 candidate regulators identified through Q1, Q2 and Q3 are colored yellow. Candidate regulators of NFκB1 identified through Q4 are colored turquoise, and candidate regulators of TCF7L2 identified through Q5 are colored orange. The target genes shared by the CCK2R DbTFs (CREB1 and NFκB1) and the DbTF candidates identified through Q6 are colored light red (JUN and BRCA2) and their connections are shown as solid arrows.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4279962&req=5

Fig1: Core CCK2R network and novel candidate regulators. The core of the gastrin mediated signal transduction network (CCK2R), and the novel candidate regulators resulting from our queries are shown. The CCK2R DbTFs that were targeted in our queries are colored light green. The network components in grey and the solid lines connecting them are part of the core CCK2R network and documented as regulators of the CCK2R DbTFs and respond to gastrin. The dotted lines represent new relations identified by the queries which could be verified against literature: blue pointed arrows denote ‘activation or positive influence’ and red bar-headed arrows depict ‘repression or negative influence’. CREB1 candidate regulators identified through Q1, Q2 and Q3 are colored yellow. Candidate regulators of NFκB1 identified through Q4 are colored turquoise, and candidate regulators of TCF7L2 identified through Q5 are colored orange. The target genes shared by the CCK2R DbTFs (CREB1 and NFκB1) and the DbTF candidates identified through Q6 are colored light red (JUN and BRCA2) and their connections are shown as solid arrows.
Mentions: NFκB1 and RELA are members of the NFκB transcription factor family known to be involved in regulating apoptosis, proliferation, and immune responses [22]. Gastrin dependent regulation of these transcription factors reportedly is mediated through PKC and Rho GTPase signaling cascades [23,24] (Figure 1). The activity of NFκB transcription factors is under the control of a family of inhibitors, known as ‘inhibitors of kB’ (IkB), which sequester NFκB in the cytoplasm and thereby keep these transcription factors in their inactive state [25]. Proteasomal degradation of IkB factors results in restoration of the active state of the NFκB and promotes its import to the nucleus. In order to gain detailed mechanistic insights in NFκB regulation, we were interested in retrieving proteins that contribute to NFκB down-regulation, and at the same time have functions related to proteasomal degradation.Figure 1

Bottom Line: Semantic web technologies provide the means for processing and integrating various heterogeneous information sources.The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression.This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Norwegian University of Science and Technology (NTNU), N-7491, Trondheim, Norway. aravind.venkatesan@ntnu.no.

ABSTRACT

Background: Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis.

Results: We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions.

Conclusions: Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

Show MeSH