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      A phylogenomic profile of globins

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          Abstract

          Background

          Globins occur in all three kingdoms of life: they can be classified into single-domain globins and chimeric globins. The latter comprise the flavohemoglobins with a C-terminal FAD-binding domain and the gene-regulating globin coupled sensors, with variable C-terminal domains. The single-domain globins encompass sequences related to chimeric globins and «truncated» hemoglobins with a 2-over-2 instead of the canonical 3-over-3 α-helical fold.

          Results

          A census of globins in 26 archaeal, 245 bacterial and 49 eukaryote genomes was carried out. Only ~25% of archaea have globins, including globin coupled sensors, related single domain globins and 2-over-2 globins. From one to seven globins per genome were found in ~65% of the bacterial genomes: the presence and number of globins are positively correlated with genome size. Globins appear to be mostly absent in Bacteroidetes/Chlorobi, Chlamydia, Lactobacillales, Mollicutes, Rickettsiales, Pastorellales and Spirochaetes. Single domain globins occur in metazoans and flavohemoglobins are found in fungi, diplomonads and mycetozoans. Although red algae have single domain globins, including 2-over-2 globins, the green algae and ciliates have only 2-over-2 globins. Plants have symbiotic and nonsymbiotic single domain hemoglobins and 2-over-2 hemoglobins. Over 90% of eukaryotes have globins: the nematode Caenorhabditis has the most putative globins, ~33. No globins occur in the parasitic, unicellular eukaryotes such as Encephalitozoon, Entamoeba, Plasmodium and Trypanosoma.

          Conclusion

          Although Bacteria have all three types of globins, Archaeado not have flavohemoglobins and Eukaryotes lack globin coupled sensors. Since the hemoglobins in organisms other than animals are enzymes or sensors, it is likely that the evolution of an oxygen transport function accompanied the emergence of multicellular animals.

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          Most cited references126

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          Sequencing and comparison of yeast species to identify genes and regulatory elements.

          Identifying the functional elements encoded in a genome is one of the principal challenges in modern biology. Comparative genomics should offer a powerful, general approach. Here, we present a comparative analysis of the yeast Saccharomyces cerevisiae based on high-quality draft sequences of three related species (S. paradoxus, S. mikatae and S. bayanus). We first aligned the genomes and characterized their evolution, defining the regions and mechanisms of change. We then developed methods for direct identification of genes and regulatory motifs. The gene analysis yielded a major revision to the yeast gene catalogue, affecting approximately 15% of all genes and reducing the total count by about 500 genes. The motif analysis automatically identified 72 genome-wide elements, including most known regulatory motifs and numerous new motifs. We inferred a putative function for most of these motifs, and provided insights into their combinatorial interactions. The results have implications for genome analysis of diverse organisms, including the human.
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            Comparative genomics of the eukaryotes.

            A comparative analysis of the genomes of Drosophila melanogaster, Caenorhabditis elegans, and Saccharomyces cerevisiae-and the proteins they are predicted to encode-was undertaken in the context of cellular, developmental, and evolutionary processes. The nonredundant protein sets of flies and worms are similar in size and are only twice that of yeast, but different gene families are expanded in each genome, and the multidomain proteins and signaling pathways of the fly and worm are far more complex than those of yeast. The fly has orthologs to 177 of the 289 human disease genes examined and provides the foundation for rapid analysis of some of the basic processes involved in human disease.
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              FUGUE: sequence-structure homology recognition using environment-specific substitution tables and structure-dependent gap penalties.

              FUGUE, a program for recognizing distant homologues by sequence-structure comparison (http://www-cryst.bioc.cam.ac.uk/fugue/), has three key features. (1) Improved environment-specific substitution tables. Substitutions of an amino acid in a protein structure are constrained by its local structural environment, which can be defined in terms of secondary structure, solvent accessibility, and hydrogen bonding status. The environment-specific substitution tables have been derived from structural alignments in the HOMSTRAD database (http://www-cryst.bioc. cam.ac.uk/homstrad/). (2) Automatic selection of alignment algorithm with detailed structure-dependent gap penalties. FUGUE uses the global-local algorithm to align a sequence-structure pair when they greatly differ in length and uses the global algorithm in other cases. The gap penalty at each position of the structure is determined according to its solvent accessibility, its position relative to the secondary structure elements (SSEs) and the conservation of the SSEs. (3) Combined information from both multiple sequences and multiple structures. FUGUE is designed to align multiple sequences against multiple structures to enrich the conservation/variation information. We demonstrate that the combination of these three key features implemented in FUGUE improves both homology recognition performance and alignment accuracy. Copyright 2001 Academic Press.
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                Author and article information

                Journal
                BMC Evol Biol
                BMC Evolutionary Biology
                BioMed Central (London )
                1471-2148
                2006
                7 April 2006
                : 6
                : 31
                Affiliations
                [1 ]Department of Biochemistry and Molecular Biology, Wayne State University School of Medicine, Detroit, MI 48201, USA
                [2 ]Department of Biology, Ghent University, B-9000 Ghent, Belgium
                [3 ]Station Biologique de Roscoff, 29680 Roscoff, France
                [4 ]Laboratorio de Biofísica y Biología Molecular, Facultad de Ciencias, Universidad Autónoma del Estado de Morelos, 62210 Cuernavaca, Morelos, México
                [5 ]RIKEN Genomic Sciences Centre, Yokohama 230-0045, Japan
                [6 ]Department of Biomedical Sciences, University of Antwerp, 2610 Antwerp, Belgium
                Article
                1471-2148-6-31
                10.1186/1471-2148-6-31
                1457004
                16600051
                f4071a42-75c9-4956-a517-07d60875d3a5
                Copyright © 2006 Vinogradov 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
                : 15 December 2005
                : 7 April 2006
                Categories
                Research Article

                Evolutionary Biology
                Evolutionary Biology

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