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      Phylogenomics of the benzoxazinoid biosynthetic pathway of Poaceae: gene duplications and origin of the Bx cluster

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          Abstract

          Background

          The benzoxazinoids 2,4-dihydroxy-1,4-benzoxazin-3-one (DIBOA) and 2,4-dihydroxy-7- methoxy-1,4-benzoxazin-3-one (DIMBOA), are key defense compounds present in major agricultural crops such as maize and wheat. Their biosynthesis involves nine enzymes thought to form a linear pathway leading to the storage of DI(M)BOA as glucoside conjugates. Seven of the genes ( Bx1-Bx6 and Bx8) form a cluster at the tip of the short arm of maize chromosome 4 that includes four P450 genes ( Bx2-5) belonging to the same CYP71C subfamily. The origin of this cluster is unknown.

          Results

          We show that the pathway appeared following several duplications of the TSA gene (α- subunit of tryptophan synthase) and of a Bx2-like ancestral CYP71C gene and the recruitment of Bx8 before the radiation of Poaceae. The origins of Bx6 and Bx7 remain unclear. We demonstrate that the Bx2-like CYP71C ancestor was not committed to the benzoxazinoid pathway and that after duplications the Bx2-Bx5 genes were under positive selection on a few sites and underwent functional divergence, leading to the current specific biochemical properties of the enzymes. The absence of synteny between available Poaceae genomes involving the Bx gene regions is in contrast with the conserved synteny in the TSA gene region.

          Conclusions

          These results demonstrate that rearrangements following duplications of an IGL/TSA gene and of a CYP71C gene probably resulted in the clustering of the new copies ( Bx1 and Bx2) at the tip of a chromosome in an ancestor of grasses. Clustering favored cosegregation and tip chromosomal location favored gene rearrangements that allowed the further recruitment of genes to the pathway. These events, a founding event and elongation events, may have been the key to the subsequent evolution of the benzoxazinoid biosynthetic cluster.

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          Most cited references62

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          ProtTest: selection of best-fit models of protein evolution.

          Using an appropriate model of amino acid replacement is very important for the study of protein evolution and phylogenetic inference. We have built a tool for the selection of the best-fit model of evolution, among a set of candidate models, for a given protein sequence alignment. ProtTest is available under the GNU license from http://darwin.uvigo.es
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            A codon-based model of nucleotide substitution for protein-coding DNA sequences.

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            A codon-based model for the evolution of protein-coding DNA sequences is presented for use in phylogenetic estimation. A Markov process is used to describe substitutions between codons. Transition/transversion rate bias and codon usage bias are allowed in the model, and selective restraints at the protein level are accommodated using physicochemical distances between the amino acids coded for by the codons. Analyses of two data sets suggest that the new codon-based model can provide a better fit to data than can nucleotide-based models and can produce more reliable estimates of certain biologically important measures such as the transition/transversion rate ratio and the synonymous/nonsynonymous substitution rate ratio.
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              Codon-substitution models for heterogeneous selection pressure at amino acid sites.

              Comparison of relative fixation rates of synonymous (silent) and nonsynonymous (amino acid-altering) mutations provides a means for understanding the mechanisms of molecular sequence evolution. The nonsynonymous/synonymous rate ratio (omega = d(N)d(S)) is an important indicator of selective pressure at the protein level, with omega = 1 meaning neutral mutations, omega 1 diversifying positive selection. Amino acid sites in a protein are expected to be under different selective pressures and have different underlying omega ratios. We develop models that account for heterogeneous omega ratios among amino acid sites and apply them to phylogenetic analyses of protein-coding DNA sequences. These models are useful for testing for adaptive molecular evolution and identifying amino acid sites under diversifying selection. Ten data sets of genes from nuclear, mitochondrial, and viral genomes are analyzed to estimate the distributions of omega among sites. In all data sets analyzed, the selective pressure indicated by the omega ratio is found to be highly heterogeneous among sites. Previously unsuspected Darwinian selection is detected in several genes in which the average omega ratio across sites is 1. Genes undergoing positive selection include the beta-globin gene from vertebrates, mitochondrial protein-coding genes from hominoids, the hemagglutinin (HA) gene from human influenza virus A, and HIV-1 env, vif, and pol genes. Tests for the presence of positively selected sites and their subsequent identification appear quite robust to the specific distributional form assumed for omega and can be achieved using any of several models we implement. However, we encountered difficulties in estimating the precise distribution of omega among sites from real data sets.
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                Author and article information

                Journal
                BMC Evol Biol
                BMC Evol. Biol
                BMC Evolutionary Biology
                BioMed Central
                1471-2148
                2012
                11 May 2012
                : 12
                : 64
                Affiliations
                [1 ]Institut National de la Recherche Agronomique, UMR 1355 Institut Sophia Agrobiotech, Centre National de la Recherche Scientifique, UMR 7254, Université de Nice Sophia Antipolis, Sophia-Antipolis, France
                Article
                1471-2148-12-64
                10.1186/1471-2148-12-64
                3449204
                22577841
                e2d5c41b-d724-48bd-8a31-01e73ecbea6d
                Copyright ©2012 Dutartre 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 August 2011
                : 17 April 2012
                Categories
                Research Article

                Evolutionary Biology
                p450,plants,secondary metabolism,gene cluster,gene duplication,neofunctionalization

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