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      Molecular Evolution of GDP-D-Mannose Epimerase ( GME), a Key Gene in Plant Ascorbic Acid Biosynthesis

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          Abstract

          The widespread ascorbic acid (AsA) plays a vital role in plant development and abiotic stress tolerance, but AsA concentration varies greatly among different plants. GDP-D-mannose epimerase (GME), which catalyzes GDP-D-mannose to GDP- L-galactose or GDP- L-gulose, is a key enzyme in plant AsA biosynthesis pathway. Functions and expression patterns of GME have been well studied in previous works, however, little information is known about the evolutionary patterns of the gene. In this study, GME gene structure, corresponding conserved protein motifs and evolutionary relationships were systematically analyzed. A total of 111 GME gene sequences were retrieved from 59 plant genomes, which representing almost all the major lineages of Viridiplantae: dicotyledons, monocotyledons, gymnosperms, pteridophytes, bryophytes, and chlorophytes. Results showed that homologs of GME were widely present in Viridiplantae. GME gene structures were conservative in higher plants, while varied greatly in the basal subgroups of the phylogeny including lycophytes, bryophytes, and chlorophytes, suggesting GME gene structure might have undergone severe differentiation at lower plant and then gradually fixed as plant evolution. The basic motifs of GME were strongly conserved throughout Viridiplantae, suggesting the conserved function of the protein. Molecular evolution analysis showed that strong purifying selection was the predominant force in the evolution of GME. A few branches and sites under episodic diversifying selection were identified and most of the branches located in the subgroup of chlorphytes, indicating episodic diversifying selection at a few branches and sites may play a role in the evolution of GME and diversifying selection may have occurred at the early stage of Viridiplantae. Our results provide novel insights into functional conservation and the evolution of GME.

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          Datamonkey 2010: a suite of phylogenetic analysis tools for evolutionary biology.

          Datamonkey is a popular web-based suite of phylogenetic analysis tools for use in evolutionary biology. Since the original release in 2005, we have expanded the analysis options to include recently developed algorithmic methods for recombination detection, evolutionary fingerprinting of genes, codon model selection, co-evolution between sites, identification of sites, which rapidly escape host-immune pressure and HIV-1 subtype assignment. The traditional selection tools have also been augmented to include recent developments in the field. Here, we summarize the analyses options currently available on Datamonkey, and provide guidelines for their use in evolutionary biology. Availability and documentation: http://www.datamonkey.org.
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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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              HMMER web server: 2015 update

              The HMMER website, available at http://www.ebi.ac.uk/Tools/hmmer/, provides access to the protein homology search algorithms found in the HMMER software suite. Since the first release of the website in 2011, the search repertoire has been expanded to include the iterative search algorithm, jackhmmer. The continued growth of the target sequence databases means that traditional tabular representations of significant sequence hits can be overwhelming to the user. Consequently, additional ways of presenting homology search results have been developed, allowing them to be summarised according to taxonomic distribution or domain architecture. The taxonomy and domain architecture representations can be used in combination to filter the results according to the needs of a user. Searches can also be restricted prior to submission using a new taxonomic filter, which not only ensures that the results are specific to the requested taxonomic group, but also improves search performance. The repertoire of profile hidden Markov model libraries, which are used for annotation of query sequences with protein families and domains, has been expanded to include the libraries from CATH-Gene3D, PIRSF, Superfamily and TIGRFAMs. Finally, we discuss the relocation of the HMMER webserver to the European Bioinformatics Institute and the potential impact that this will have.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                04 September 2018
                2018
                : 9
                : 1293
                Affiliations
                [1] 1College of Agronomy, Jiangxi Agricultural University , Nanchang, China
                [2] 2Institute of Kiwifruit, Jiangxi Agricultural University , Nanchang, China
                Author notes

                Edited by: Juan Caballero, Universidad Autónoma de Querétaro, Mexico

                Reviewed by: Cheong Xin Chan, The University of Queensland, Australia; Hao Wang, University of Georgia, United States

                *Correspondence: Xiaobiao Xu, xiaobiaoxu@ 123456hotmail.com

                This article was submitted to Bioinformatics and Computational Biology, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2018.01293
                6132023
                29410674
                92213bb8-36d0-4ba5-a6ee-37ec503e39ef
                Copyright © 2018 Tao, Wu, Li, Huang and Xu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 16 April 2018
                : 17 August 2018
                Page count
                Figures: 3, Tables: 0, Equations: 0, References: 62, Pages: 10, Words: 0
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                ascorbic acid,gme,molecular evolution,l-galactose pathway,viridiplantae
                Plant science & Botany
                ascorbic acid, gme, molecular evolution, l-galactose pathway, viridiplantae

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