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      Miiuy Croaker Transferrin Gene and Evidence for Positive Selection Events Reveal Different Evolutionary Patterns

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          Abstract

          Transferrin (TF) is a protein that plays a central role in iron metabolism. This protein is associated with the innate immune system, which is responsible for disease defense responses after bacterial infection. The clear link between TF and the immune defense mechanism has led researchers to consider TF as a candidate gene for disease resistance. In this study, the Miichthys miiuy (miiuy croaker) TF gene (MIMI-TF) was cloned and characterized. The gene structure consisted of a coding region of 2070 nucleotides divided into 17 exons, as well as a non-coding region that included 16 introns and spans 6757 nucleotides. The deduced MIMI-TF protein consisted of 689 amino acids that comprised a signal peptide and two lobes (N- and C-lobes). MIMI-TF expression was significantly up-regulated after infection with Vibrio anguillarum. A series of model tests implemented in the CODEML program showed that TF underwent a complex evolutionary process. Branch-site models revealed that vertebrate TF was vastly different from that of invertebrates, and that the TF of the ancestors of aquatic and terrestrial organisms underwent different selection pressures. The site models detected 10 positively selected sites in extant TF genes. One site was located in the cleft between the N1 and N2 domains and was expected to affect the capability of TF to bind to or release iron indirectly. In addition, eight sites were found near the TF exterior. Two of these sites, which could have evolved from the competition for iron between pathogenic bacteria and TF, were located in potential pathogen-binding domains. Our results could be used to further investigate the function of TF and the selective mechanisms involved.

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          MRBAYES: Bayesian inference of phylogenetic trees.

          The program MRBAYES performs Bayesian inference of phylogeny using a variant of Markov chain Monte Carlo. MRBAYES, including the source code, documentation, sample data files, and an executable, is available at http://brahms.biology.rochester.edu/software.html.
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            TreeView: an application to display phylogenetic trees on personal computers.

            R D Page (1996)
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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

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                5 September 2012
                : 7
                : 9
                : e43936
                Affiliations
                [1]Laboratory for Marine Living Resources and Molecular Engineering, College of Marine Science, Zhejiang Ocean University, Zhoushan, China
                Auburn University, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: Yueyan Sun TX. Performed the experiments: Yueyan Sun ZZ RW Yuena Sun. Analyzed the data: Yueyan Sun ZZ TX. Contributed reagents/materials/analysis tools: Yuena Sun TX. Wrote the paper: Yueyan Sun TX.

                Article
                PONE-D-12-14186
                10.1371/journal.pone.0043936
                3434209
                22957037
                db46ab73-ebbf-4e95-942c-1a489b249faf
                Copyright @ 2012

                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.

                History
                : 20 May 2012
                : 26 July 2012
                Page count
                Pages: 9
                Funding
                This study was supported by Nation Nature Science Foundation of China (31001120) and Zhejiang Provincial Natural Science Foundation of China (Y3100013, Y12C030014). 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
                Molecular Genetics
                Gene Identification and Analysis
                Evolutionary Biology
                Evolutionary Processes
                Evolutionary Selection
                Evolutionary Genetics
                Genetics
                Gene Expression
                DNA transcription
                Molecular Genetics
                Gene Identification and Analysis
                Animal Genetics
                Gene Function
                Human Genetics
                Immunology
                Genetics of the Immune System

                Uncategorized
                Uncategorized

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