Protein interaction maps for complete genomes based on gene fusion events

Anton J. Enright, Ioannis Iliopoulos, Nikos C. Kyrpides and Christos A. Ouzounis ()
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Anton J. Enright: Computational Genomics Group, Research Programme, The European Bioinformatics Institute, EMBL Cambridge Outstation
Ioannis Iliopoulos: Computational Genomics Group, Research Programme, The European Bioinformatics Institute, EMBL Cambridge Outstation
Nikos C. Kyrpides: Computational Genomics Group, Research Programme, The European Bioinformatics Institute, EMBL Cambridge Outstation
Christos A. Ouzounis: Computational Genomics Group, Research Programme, The European Bioinformatics Institute, EMBL Cambridge Outstation

Nature, 1999, vol. 402, issue 6757, 86-90

Abstract: Abstract A large-scale effort to measure, detect and analyse protein–protein interactions using experimental methods is under way1,2. These include biochemistry such as co-immunoprecipitation or crosslinking, molecular biology such as the two-hybrid system or phage display, and genetics such as unlinked noncomplementing mutant detection3. Using the two-hybrid system4, an international effort to analyse the complete yeast genome is in progress5. Evidently, all these approaches are tedious, labour intensive and inaccurate6. From a computational perspective, the question is how can we predict that two proteins interact from structure or sequence alone. Here we present a method that identifies gene-fusion events in complete genomes, solely based on sequence comparison. Because there must be selective pressure for certain genes to be fused over the course of evolution, we are able to predict functional associations of proteins. We show that 215 genes or proteins in the complete genomes of Escherichia coli, Haemophilus influenzae and Methanococcus jannaschii are involved in 64 unique fusion events. The approach is general, and can be applied even to genes of unknown function.

Date: 1999
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DOI: 10.1038/47056

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