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Predicting protein-protein interactions in Arabidopsis thaliana through integration of orthology, gene ontology and co-expression.

De Bodt S, Proost S, Vandepoele K, Rouzé P, Van de Peer Y - BMC Genomics (2009)

Bottom Line: We conclude that the integration of orthology with functional association data is adequate to predict protein-protein interactions.Through this approach, a high number of novel protein-protein interactions with diverse biological roles is discovered.Overall, we have predicted a reliable set of protein-protein interactions suitable for further computational as well as experimental analyses.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, B-9052 Gent, Belgium. stefanie.debodt@psb.vib-ugent.be

ABSTRACT

Background: Large-scale identification of the interrelationships between different components of the cell, such as the interactions between proteins, has recently gained great interest. However, unraveling large-scale protein-protein interaction maps is laborious and expensive. Moreover, assessing the reliability of the interactions can be cumbersome.

Results: In this study, we have developed a computational method that exploits the existing knowledge on protein-protein interactions in diverse species through orthologous relations on the one hand, and functional association data on the other hand to predict and filter protein-protein interactions in Arabidopsis thaliana. A highly reliable set of protein-protein interactions is predicted through this integrative approach making use of existing protein-protein interaction data from yeast, human, C. elegans and D. melanogaster. Localization, biological process, and co-expression data are used as powerful indicators for protein-protein interactions. The functional repertoire of the identified interactome reveals interactions between proteins functioning in well-conserved as well as plant-specific biological processes. We observe that although common mechanisms (e.g. actin polymerization) and components (e.g. ARPs, actin-related proteins) exist between different lineages, they are active in specific processes such as growth, cancer metastasis and trichome development in yeast, human and Arabidopsis, respectively.

Conclusion: We conclude that the integration of orthology with functional association data is adequate to predict protein-protein interactions. Through this approach, a high number of novel protein-protein interactions with diverse biological roles is discovered. Overall, we have predicted a reliable set of protein-protein interactions suitable for further computational as well as experimental analyses.

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Interolog detection and filtering. Proteins in similar color belong to the same orthologous group as identified by OrthoMCL. Connecting lines indicate predicted interactions between proteins. First, all possible combinations between proteins in the two orthologous groups are predicted. Second, some connections between proteins do not hold true when considering the genomic features e.g. GO cellular component. The result is the filtered interactome (solid lines), which extended to the predicted interactome using the interactions that did not pass the filters (dashed lines).
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Figure 1: Interolog detection and filtering. Proteins in similar color belong to the same orthologous group as identified by OrthoMCL. Connecting lines indicate predicted interactions between proteins. First, all possible combinations between proteins in the two orthologous groups are predicted. Second, some connections between proteins do not hold true when considering the genomic features e.g. GO cellular component. The result is the filtered interactome (solid lines), which extended to the predicted interactome using the interactions that did not pass the filters (dashed lines).

Mentions: The basis of the prediction of protein-protein interactions in Arabidopsis thaliana performed in this study resides in the detection of interologs. Interologs are defined as protein-protein interactions that are conserved between two species and that can be detected through the identification of the orthologs in the target organism of the proteins known to interact in the source organism (see Fig. 1). Applying this approach, we assume that protein-protein interactions occurring in yeast, C. elegans, Drosophila and/or human, are conserved and consequently occur in Arabidopsis as well.


Predicting protein-protein interactions in Arabidopsis thaliana through integration of orthology, gene ontology and co-expression.

De Bodt S, Proost S, Vandepoele K, Rouzé P, Van de Peer Y - BMC Genomics (2009)

Interolog detection and filtering. Proteins in similar color belong to the same orthologous group as identified by OrthoMCL. Connecting lines indicate predicted interactions between proteins. First, all possible combinations between proteins in the two orthologous groups are predicted. Second, some connections between proteins do not hold true when considering the genomic features e.g. GO cellular component. The result is the filtered interactome (solid lines), which extended to the predicted interactome using the interactions that did not pass the filters (dashed lines).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2719670&req=5

Figure 1: Interolog detection and filtering. Proteins in similar color belong to the same orthologous group as identified by OrthoMCL. Connecting lines indicate predicted interactions between proteins. First, all possible combinations between proteins in the two orthologous groups are predicted. Second, some connections between proteins do not hold true when considering the genomic features e.g. GO cellular component. The result is the filtered interactome (solid lines), which extended to the predicted interactome using the interactions that did not pass the filters (dashed lines).
Mentions: The basis of the prediction of protein-protein interactions in Arabidopsis thaliana performed in this study resides in the detection of interologs. Interologs are defined as protein-protein interactions that are conserved between two species and that can be detected through the identification of the orthologs in the target organism of the proteins known to interact in the source organism (see Fig. 1). Applying this approach, we assume that protein-protein interactions occurring in yeast, C. elegans, Drosophila and/or human, are conserved and consequently occur in Arabidopsis as well.

Bottom Line: We conclude that the integration of orthology with functional association data is adequate to predict protein-protein interactions.Through this approach, a high number of novel protein-protein interactions with diverse biological roles is discovered.Overall, we have predicted a reliable set of protein-protein interactions suitable for further computational as well as experimental analyses.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, B-9052 Gent, Belgium. stefanie.debodt@psb.vib-ugent.be

ABSTRACT

Background: Large-scale identification of the interrelationships between different components of the cell, such as the interactions between proteins, has recently gained great interest. However, unraveling large-scale protein-protein interaction maps is laborious and expensive. Moreover, assessing the reliability of the interactions can be cumbersome.

Results: In this study, we have developed a computational method that exploits the existing knowledge on protein-protein interactions in diverse species through orthologous relations on the one hand, and functional association data on the other hand to predict and filter protein-protein interactions in Arabidopsis thaliana. A highly reliable set of protein-protein interactions is predicted through this integrative approach making use of existing protein-protein interaction data from yeast, human, C. elegans and D. melanogaster. Localization, biological process, and co-expression data are used as powerful indicators for protein-protein interactions. The functional repertoire of the identified interactome reveals interactions between proteins functioning in well-conserved as well as plant-specific biological processes. We observe that although common mechanisms (e.g. actin polymerization) and components (e.g. ARPs, actin-related proteins) exist between different lineages, they are active in specific processes such as growth, cancer metastasis and trichome development in yeast, human and Arabidopsis, respectively.

Conclusion: We conclude that the integration of orthology with functional association data is adequate to predict protein-protein interactions. Through this approach, a high number of novel protein-protein interactions with diverse biological roles is discovered. Overall, we have predicted a reliable set of protein-protein interactions suitable for further computational as well as experimental analyses.

Show MeSH
Related in: MedlinePlus