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      Evolutionary history and functional implications of protein domains and their combinations in eukaryotes

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          Abstract

          A rapid emergence of animal-specific domains was observed in animals, contributing to specific domain combinations and functional diversification, but no similar trends were observed in other clades of eukaryotes.

          Abstract

          Background

          In higher multicellular eukaryotes, complex protein domain combinations contribute to various cellular functions such as regulation of intercellular or intracellular signaling and interactions. To elucidate the characteristics and evolutionary mechanisms that underlie such domain combinations, it is essential to examine the different types of domains and their combinations among different groups of eukaryotes.

          Results

          We observed a large number of group-specific domain combinations in animals, especially in vertebrates. Examples include animal-specific combinations in tyrosine phosphorylation systems and vertebrate-specific combinations in complement and coagulation cascades. These systems apparently underwent extensive evolution in the ancestors of these groups. In extant animals, especially in vertebrates, animal-specific domains have greater connectivity than do other domains on average, and contribute to the varying number of combinations in each animal subgroup. In other groups, the connectivities of older domains were greater on average. To observe the global behavior of domain combinations during evolution, we traced the changes in domain combinations among animals and fungi in a network analysis. Our results indicate that there is a correlation between the differences in domain combinations among different phylogenetic groups and different global behaviors.

          Conclusion

          Rapid emergence of animal-specific domains was observed in animals, contributing to specific domain combinations and functional diversification, but no such trends were observed in other clades of eukaryotes. We therefore suggest that the strategy for achieving complex multicellular systems in animals differs from that of other eukaryotes.

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          Most cited references59

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          Emergence of scaling in random networks

          Systems as diverse as genetic networks or the world wide web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites. A model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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            Profile hidden Markov models.

            S. Eddy (1998)
            The recent literature on profile hidden Markov model (profile HMM) methods and software is reviewed. Profile HMMs turn a multiple sequence alignment into a position-specific scoring system suitable for searching databases for remotely homologous sequences. Profile HMM analyses complement standard pairwise comparison methods for large-scale sequence analysis. Several software implementations and two large libraries of profile HMMs of common protein domains are available. HMM methods performed comparably to threading methods in the CASP2 structure prediction exercise.
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              Pfam: clans, web tools and services

              Pfam is a database of protein families that currently contains 7973 entries (release 18.0). A recent development in Pfam has enabled the grouping of related families into clans. Pfam clans are described in detail, together with the new associated web pages. Improvements to the range of Pfam web tools and the first set of Pfam web services that allow programmatic access to the database and associated tools are also presented. Pfam is available on the web in the UK (), the USA (), France () and Sweden ().
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                Author and article information

                Journal
                Genome Biol
                Genome Biology
                BioMed Central
                1465-6906
                1465-6914
                2007
                25 June 2007
                : 8
                : 6
                : R121
                Affiliations
                [1 ]Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan
                Article
                gb-2007-8-6-r121
                10.1186/gb-2007-8-6-r121
                2394772
                17588271
                76b36720-3b52-43e4-90cc-1685a30a7c3e
                Copyright © 2007 Itoh et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 9 February 2007
                : 10 May 2007
                : 25 June 2007
                Categories
                Research

                Genetics
                Genetics

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