title: Functional associations of proteins in entire genomes by means of exhaustive detection of gene fusions.
abstract: BACKGROUND
  It has recently been shown that the detection of gene fusion events across genomes can be used for predicting functional associations of proteins, including physical interaction or complex formation. To obtain such predictions we have made an exhaustive search for gene fusion events within 24 available completely sequenced genomes.
  
  
  RESULTS
  Each genome was used as a query against the remaining 23 complete genomes to detect gene fusion events. Using an improved, fully automatic protocol, a total of 7,224 single-domain proteins that are components of gene fusions in other genomes were detected, many of which were identified for the first time. The total number of predicted pairwise functional associations is 39,730 for all genomes. Component pairs were identified by virtue of their similarity to 2,365 multidomain composite proteins. We also show for the first time that gene fusion is a complex evolutionary process with a number of contributory factors, including paralogy, genome size and phylogenetic distance. On average, 9% of genes in a given genome appear to code for single-domain, component proteins predicted to be functionally associated. These proteins are detected by an additional 4% of genes that code for fused, composite proteins.
  
  
  CONCLUSIONS
  These results provide an exhaustive set of functionally associated genes and also delineate the power of fusion analysis for the prediction of protein interactions.
authors.affiliation: Computational Genomics Group, European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK.
authors.forename: A J
authors.initials: AJ
authors.lastname: Enright
authors.forename: C A
authors.initials: CA
authors.lastname: Ouzounis
mesh_terms: D000465:Algorithms; D000818:Animals; D019677:Artificial Gene Fusion; D001426:Bacterial Proteins / Q000235:genetics / Q000378:metabolism; D029742:Caenorhabditis elegans Proteins / Q000235:genetics / Q000378:metabolism; D019295:Computational Biology / Q000379:methods; D029721:Drosophila Proteins / Q000235:genetics / Q000378:metabolism; D019143:Evolution, Molecular; D005656:Fungal Proteins / Q000235:genetics / Q000378:metabolism; D020869:Gene Expression Profiling; D016678:Genome; D005810:Multigene Family / Q000235:genetics; D010802:Phylogeny; D011485:Protein Binding; D011506:Proteins / Q000235:genetics* / Q000378:metabolism*; D011993:Recombinant Fusion Proteins / Q000235:genetics; D011994:Recombinant Proteins / Q000235:genetics; D011995:Recombination, Genetic / Q000235:genetics*; D015203:Reproducibility of Results; D020798:Two-Hybrid System Techniques
chemical_list: D001426:Bacterial Proteins; D029742:Caenorhabditis elegans Proteins; D029721:Drosophila Proteins; D005656:Fungal Proteins; D011506:Proteins; D011993:Recombinant Fusion Proteins; D011994:Recombinant Proteins