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      The planetary biology of cytochrome P450 aromatases

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          Abstract

          Background

          Joining a model for the molecular evolution of a protein family to the paleontological and geological records (geobiology), and then to the chemical structures of substrates, products, and protein folds, is emerging as a broad strategy for generating hypotheses concerning function in a post-genomic world. This strategy expands systems biology to a planetary context, necessary for a notion of fitness to underlie (as it must) any discussion of function within a biomolecular system.

          Results

          Here, we report an example of such an expansion, where tools from planetary biology were used to analyze three genes from the pig Sus scrofa that encode cytochrome P450 aromatases–enzymes that convert androgens into estrogens. The evolutionary history of the vertebrate aromatase gene family was reconstructed. Transition redundant exchange silent substitution metrics were used to interpolate dates for the divergence of family members, the paleontological record was consulted to identify changes in physiology that correlated in time with the change in molecular behavior, and new aromatase sequences from peccary were obtained. Metrics that detect changing function in proteins were then applied, including K A/K S values and those that exploit structural biology. These identified specific amino acid replacements that were associated with changing substrate and product specificity during the time of presumed adaptive change. The combined analysis suggests that aromatase paralogs arose in pigs as a result of selection for Suoidea with larger litters than their ancestors, and permitted the Suoidea to survive the global climatic trauma that began in the Eocene.

          Conclusions

          This combination of bioinformatics analysis, molecular evolution, paleontology, cladistics, global climatology, structural biology, and organic chemistry serves as a paradigm in planetary biology. As the geological, paleontological, and genomic records improve, this approach should become widely useful to make systems biology statements about high-level function for biomolecular systems.

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          Most cited references93

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          Statistical methods for detecting molecular adaptation.

          The past few years have seen the development of powerful statistical methods for detecting adaptive molecular evolution. These methods compare synonymous and nonsynonymous substitution rates in protein-coding genes, and regard a nonsynonymous rate elevated above the synonymous rate as evidence for darwinian selection. Numerous cases of molecular adaptation are being identified in various systems from viruses to humans. Although previous analyses averaging rates over sites and time have little power, recent methods designed to detect positive selection at individual sites and lineages have been successful. Here, we summarize recent statistical methods for detecting molecular adaptation, and discuss their limitations and possible improvements.
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            Resolution of the early placental mammal radiation using Bayesian phylogenetics.

            Molecular phylogenetic studies have resolved placental mammals into four major groups, but have not established the full hierarchy of interordinal relationships, including the position of the root. The latter is critical for understanding the early biogeographic history of placentals. We investigated placental phylogeny using Bayesian and maximum-likelihood methods and a 16.4-kilobase molecular data set. Interordinal relationships are almost entirely resolved. The basal split is between Afrotheria and other placentals, at about 103 million years, and may be accounted for by the separation of South America and Africa in the Cretaceous. Crown-group Eutheria may have their most recent common ancestry in the Southern Hemisphere (Gondwana).
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              A new method for estimating synonymous and nonsynonymous rates of nucleotide substitution considering the relative likelihood of nucleotide and codon changes.

              W Li, C. Wu, C Luo (1985)
              A new method is proposed for estimating the number of synonymous and nonsynonymous nucleotide substitutions between homologous genes. In this method, a nucleotide site is classified as nondegenerate, twofold degenerate, or fourfold degenerate, depending on how often nucleotide substitutions will result in amino acid replacement; nucleotide changes are classified as either transitional or transversional, and changes between codons are assumed to occur with different probabilities, which are determined by their relative frequencies among more than 3,000 changes in mammalian genes. The method is applied to a large number of mammalian genes. The rate of nonsynonymous substitution is extremely variable among genes; it ranges from 0.004 X 10(-9) (histone H4) to 2.80 X 10(-9) (interferon gamma), with a mean of 0.88 X 10(-9) substitutions per nonsynonymous site per year. The rate of synonymous substitution is also variable among genes; the highest rate is three to four times higher than the lowest one, with a mean of 4.7 X 10(-9) substitutions per synonymous site per year. The rate of nucleotide substitution is lowest at nondegenerate sites (the average being 0.94 X 10(-9), intermediate at twofold degenerate sites (2.26 X 10(-9)). and highest at fourfold degenerate sites (4.2 X 10(-9)). The implication of our results for the mechanisms of DNA evolution and that of the relative likelihood of codon interchanges in parsimonious phylogenetic reconstruction are discussed.
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                Author and article information

                Journal
                BMC Biol
                BMC Biology
                BioMed Central (London )
                1741-7007
                2004
                17 August 2004
                : 2
                : 19
                Affiliations
                [1 ]Foundation for Applied Molecular Evolution, 1115 NW 4th Street, Gainesville FL 32601-4256, USA
                [2 ]Department of Psychiatry, Duke University Medical Center, Durham, NC 27708, USA
                [3 ]Department of Physiology & Biophysics, Medical Sciences & Children's Nutrition Center, University of Arkansas, 1120 Marshall Street, Little Rock AR, 72202, USA
                [4 ]Computational Biology Unit, Bergen Center for Computational Science, University of Bergen, 5020 Bergen, Norway
                [5 ]Ecology and Evolutionary Biology, Brown University, Providence RI 02912, USA
                [6 ]Department of Chemistry, University of Florida, Gainesville FL 32611-7200, USA
                Article
                1741-7007-2-19
                10.1186/1741-7007-2-19
                515309
                15315709
                4ab7c616-5c49-4e0d-8e62-0f9494b3fd88
                Copyright © 2004 Gaucher 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
                : 12 February 2004
                : 17 August 2004
                Categories
                Research Article

                Life sciences
                Life sciences

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