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This Déjà Vu Feeling—Analysis of Multidomain Protein Evolution in Eukaryotic Genomes

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PLoS Computational Biology

Public Library of Science

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      Abstract

      Evolutionary innovation in eukaryotes and especially animals is at least partially driven by genome rearrangements and the resulting emergence of proteins with new domain combinations, and thus potentially novel functionality. Given the random nature of such rearrangements, one could expect that proteins with particularly useful multidomain combinations may have been rediscovered multiple times by parallel evolution. However, existing reports suggest a minimal role of this phenomenon in the overall evolution of eukaryotic proteomes. We assembled a collection of 172 complete eukaryotic genomes that is not only the largest, but also the most phylogenetically complete set of genomes analyzed so far. By employing a maximum parsimony approach to compare repertoires of Pfam domains and their combinations, we show that independent evolution of domain combinations is significantly more prevalent than previously thought. Our results indicate that about 25% of all currently observed domain combinations have evolved multiple times. Interestingly, this percentage is even higher for sets of domain combinations in individual species, with, for instance, 70% of the domain combinations found in the human genome having evolved independently at least once in other species. We also show that previous, much lower estimates of this rate are most likely due to the small number and biased phylogenetic distribution of the genomes analyzed. The process of independent emergence of identical domain combination is widespread, not limited to domains with specific functional categories. Besides data from large-scale analyses, we also present individual examples of independent domain combination evolution. The surprisingly large contribution of parallel evolution to the development of the domain combination repertoire in extant genomes has profound consequences for our understanding of the evolution of pathways and cellular processes in eukaryotes and for comparative functional genomics.

      Author Summary

      Most proteins in eukaryotes are composed of two or more domains, evolutionary independent units with (often) their own individual functions. The specific repertoire of multidomain proteins in a given species defines the topology of pathways and networks that carry out its metabolic and regulatory processes. When proteins with new domain combinations emerge by gene fusion and fission, it directly affects topology of cellular networks in this organism. To better understand the evolution of such networks we analyzed a large set of eukaryotic genomes for the evolutionary history of known domain combinations. Our analysis shows that 70% of all domain combinations present in the human genome independently appeared in at least one other eukaryotic genome. Overall, over 25% of all known multidomain architectures emerged independently several times in the history of life. The difference between a global and species specific picture can be explained by the existence of a core set of domain combinations that keeps reemerging in different species, which are accompanied by a smaller number of unique domain combinations that do not appear anywhere else.

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      Most cited references 47

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      The Pfam protein families database

      Pfam is a widely used database of protein families and domains. This article describes a set of major updates that we have implemented in the latest release (version 24.0). The most important change is that we now use HMMER3, the latest version of the popular profile hidden Markov model package. This software is ∼100 times faster than HMMER2 and is more sensitive due to the routine use of the forward algorithm. The move to HMMER3 has necessitated numerous changes to Pfam that are described in detail. Pfam release 24.0 contains 11 912 families, of which a large number have been significantly updated during the past two years. Pfam is available via servers in the UK (http://pfam.sanger.ac.uk/), the USA (http://pfam.janelia.org/) and Sweden (http://pfam.sbc.su.se/).
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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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          Reconstructing the early evolution of Fungi using a six-gene phylogeny.

          The ancestors of fungi are believed to be simple aquatic forms with flagellated spores, similar to members of the extant phylum Chytridiomycota (chytrids). Current classifications assume that chytrids form an early-diverging clade within the kingdom Fungi and imply a single loss of the spore flagellum, leading to the diversification of terrestrial fungi. Here we develop phylogenetic hypotheses for Fungi using data from six gene regions and nearly 200 species. Our results indicate that there may have been at least four independent losses of the flagellum in the kingdom Fungi. These losses of swimming spores coincided with the evolution of new mechanisms of spore dispersal, such as aerial dispersal in mycelial groups and polar tube eversion in the microsporidia (unicellular forms that lack mitochondria). The enigmatic microsporidia seem to be derived from an endoparasitic chytrid ancestor similar to Rozella allomycis, on the earliest diverging branch of the fungal phylogenetic tree.
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            Author and article information

            Affiliations
            Program in Bioinformatics and Systems Biology, Sanford-Burnham Medical Research Institute, La Jolla, California, United States of America
            University College London, United Kingdom
            Author notes

            The authors have declared that no competing interests exist.

            Conceived and designed the experiments: CMZ AG. Performed the experiments: CMZ. Analyzed the data: CMZ AG. Contributed reagents/materials/analysis tools: CMZ AG. Wrote the paper: CMZ AG.

            Contributors
            Role: Editor
            Journal
            PLoS Comput Biol
            PLoS Comput. Biol
            plos
            ploscomp
            PLoS Computational Biology
            Public Library of Science (San Francisco, USA )
            1553-734X
            1553-7358
            November 2012
            November 2012
            15 November 2012
            : 8
            : 11
            23166479
            3499355
            PCOMPBIOL-D-12-00320
            10.1371/journal.pcbi.1002701
            (Editor)

            This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

            Counts
            Pages: 16
            Funding
            The research described in this article was supported in part by the NIH grants GM087218 and GM101457. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
            Categories
            Research Article
            Biology
            Computational Biology
            Evolutionary Biology

            Quantitative & Systems biology

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