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A predicted protein interactome for rice.

ABSTRACT: BACKGROUND:Protein-protein interactions (PPIs) create the steps in signaling and regulatory networks central to most fundamental biological processes. It is possible to predict these interactions by making use of experimentally determined orthologous interactions in other species. RESULTS:In this study, prediction of PPIs in rice was carried out by the interolog method of mapping deduced orthologous genes to protein interactions supported by experimental evidence from reference organisms. We predicted 37112 interactions for 4567 rice proteins, including 1671 predicted self interactions (homo-interactions) and 35441 predicted interactions between different proteins (hetero-interactions). These matched 168 of 675 experimentally-determined interactions in rice. Interacting proteins were significantly more co-expressed than expected by chance, which is typical of experimentally-determined interactomes. The rice interacting proteins were divided topologically into 981 free ends (proteins with single interactions), 499 pipes (proteins with two interactions) and 3087 hubs of different sizes ranging from three to more than 100 interactions. CONCLUSIONS:This predicted rice interactome extends known pathways and improves functional annotation of unknown rice proteins and networks in rice, and is easily explored with software tools presented here.

SUBMITTER: Ho CL

PROVIDER: S-EPMC4883691 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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A predicted protein interactome for rice.

Ho Chai-Ling CL Wu Yingzhou Y Shen Hong-Bin HB Provart Nicholas J NJ Geisler Matt M

Rice (New York, N.Y.) 20120702 1

<h4>Background</h4>Protein-protein interactions (PPIs) create the steps in signaling and regulatory networks central to most fundamental biological processes. It is possible to predict these interactions by making use of experimentally determined orthologous interactions in other species.<h4>Results</h4>In this study, prediction of PPIs in rice was carried out by the interolog method of mapping deduced orthologous genes to protein interactions supported by experimental evidence from reference or ...[more]

PMID: 24279740

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Project description:BackgroundProtein-protein interactions play a fundamental role in elucidating the molecular mechanisms of biomolecular function, signal transductions and metabolic pathways of living organisms. Although high-throughput technologies such as yeast two-hybrid system and affinity purification followed by mass spectrometry are widely used in model organisms, the progress of protein-protein interactions detection in plants is rather slow. With this motivation, our work presents a computational approach to predict protein-protein interactions in Oryza sativa.ResultsTo better understand the interactions of proteins in Oryza sativa, we have developed PRIN, a Predicted Rice Interactome Network. Protein-protein interaction data of PRIN are based on the interologs of six model organisms where large-scale protein-protein interaction experiments have been applied: yeast (Saccharomyces cerevisiae), worm (Caenorhabditis elegans), fruit fly (Drosophila melanogaster), human (Homo sapiens), Escherichia coli K12 and Arabidopsis thaliana. With certain quality controls, altogether we obtained 76,585 non-redundant rice protein interaction pairs among 5,049 rice proteins. Further analysis showed that the topology properties of predicted rice protein interaction network are more similar to yeast than to the other 5 organisms. This may not be surprising as the interologs based on yeast contribute nearly 74% of total interactions. In addition, GO annotation, subcellular localization information and gene expression data are also mapped to our network for validation. Finally, a user-friendly web interface was developed to offer convenient database search and network visualization.ConclusionsPRIN is the first well annotated protein interaction database for the important model plant Oryza sativa. It has greatly extended the current available protein-protein interaction data of rice with a computational approach, which will certainly provide further insights into rice functional genomics and systems biology. PRIN is available online at http://bis.zju.edu.cn/prin/.

Dataset Information

A predicted protein interactome for rice.

Publications

A predicted protein interactome for rice.

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