Comparative Pair-wise Domain-Combinations for Screening the Clade Specific Domain-architectures in Metazoan Genomes

Shuichi Kawashima[1] (
Takeshi Kawashima[2],[3] (
Nicholas H Putnam[2] (
Daniel S Rokhsar[2] (
Hiroshi Wada[4] (
Minoru Kanehisa[1],[5] (

[1]Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan
[2]Department of Molecular and Cell Biology, University of California, Berkeley, LSA Bldg. #3200, Berkeley, CA 94720-3200, USA
[3]Japan Sociery for the Promotion of Science, 8 Ichibancho, Chiyoda-ku, Tokyo 102- 8472, Japan
[4]Graduate School of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki 305-8572, Japan
[5]Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan


In the evolution of the eukaryotic genome, exon or domain shuffling has produced a variety of proteins. On the assumption that each fusion event between two independent protein-domains occurred only once in the evolution of metazoans, we can roughly estimate when the fusion events were happened. For this purpose, we made phylogenetic profiles of pair-wise domain-combinations of metazoans. The phylogenetic profiles can be expected to reflect the protein evolution of metazoan. Interestingly, the phylogenetic tree of metazoans, derived from the profiles, supported the “Ecdysozoa hypothesis” that is one of the major hypotheses for metazoan evolution. Further, the phylogenetic profiles showed the candidates of genes that were required for each clade-specific features in metazoan evolution. We propose that comparative proteome analysis focusing on pair-wise domain-combinations is a useful strategy for researching the metazoan evolution. Additionally, we found that the extant ecdysozoans share only fourteen domain-combinations in our profiles. Such a small number of ecdysozoan-specific domain-combinations is consistent with the extensive gene-losses through the evolution of ecdysozoans.

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Japanese Society for Bioinformatics