title: DODO: an efficient orthologous genes assignment tool based on domain architectures. Domain based ortholog detection.
abstract: BACKGROUND
  Orthologs are genes derived from the same ancestor gene loci after speciation events. Orthologous proteins usually have similar sequences and perform comparable biological functions. Therefore, ortholog identification is useful in annotations of newly sequenced genomes. With rapidly increasing number of sequenced genomes, constructing or updating ortholog relationship between all genomes requires lots of effort and computation time. In addition, elucidating ortholog relationships between distantly related genomes is challenging because of the lower sequence similarity. Therefore, an efficient ortholog detection method that can deal with large number of distantly related genomes is desired.
  
  
  RESULTS
  An efficient ortholog detection pipeline DODO (DOmain based Detection of Orthologs) is created on the basis of domain architectures in this study. Supported by domain composition, which usually directly related with protein function, DODO could facilitate orthologs detection across distantly related genomes. DODO works in two main steps. Starting from domain information, it first assigns protein groups according to their domain architectures and further identifies orthologs within those groups with much reduced complexity. Here DODO is shown to detect orthologs between two genomes in considerably shorter period of time than traditional methods of reciprocal best hits and it is more significant when analyzed a large number of genomes. The output results of DODO are highly comparable with other known ortholog databases.
  
  
  CONCLUSIONS
  DODO provides a new efficient pipeline for detection of orthologs in a large number of genomes. In addition, a database established with DODO is also easier to maintain and could be updated relatively effortlessly. The pipeline of DODO could be downloaded from http://140.109.42.19:16080/dodo_web/home.htm.
authors.affiliation: Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan.
authors.forename: Ting-wen
authors.initials: TW
authors.lastname: Chen
authors.forename: Timothy H
authors.initials: TH
authors.lastname: Wu
authors.forename: Wailap V
authors.initials: WV
authors.lastname: Ng
authors.forename: Wen-chang
authors.initials: WC
authors.lastname: Lin
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D016678:Genome / Q000235:genetics*; D006801:Humans; D051379:Mice; D058977:Molecular Sequence Annotation / Q000379:methods; D008969:Molecular Sequence Data; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry* / Q000235:genetics*; D016415:Sequence Alignment
chemical_list: D011506:Proteins