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      Rearrangement of mitochondrial tRNA genes in flat bugs (Hemiptera: Aradidae)

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          Abstract

          The typical insect mitochondrial (mt) genome organization, which contains a single chromosome with 37 genes, was found in the infraorder Pentatomomorpha (suborder Heteroptera). The arrangement of mt genes in these true bugs is usually the same as the ancestral mt gene arrangement of insects. Rearrangement of transfer RNA (tRNA) genes, however, has been found in two subfamilies of flat bugs (Mezirinae and Calisiinae, family Aradidae). In this study, we sequenced the complete mt genomes of four species from three other subfamilies (Aradinae, Carventinae and Aneurinae). We found tRNA gene rearrangement in all of these four species. All of the rearranged tRNA genes are located between the mitochondrial control region and cox1, indicating this region as a hotspot for gene rearrangement in flat bugs; the rearrangement is likely caused by events of tandem duplication and random deletion of genes. Furthermore, our phylogenetic and dating analyses indicated that the swap of positions between trnQ and trnI occurred ~162 million years ago (MYA) in the most recent common ancestor of the five subfamilies of flat bugs investigated to date, whereas the swap of positions between trnC and trnW occurred later in the lineage leading to Calisiinae, and the translocation of trnC and trnY occurred later than 134 MYA in the lineage leading to Aradinae.

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          TranslatorX: multiple alignment of nucleotide sequences guided by amino acid translations

          We present TranslatorX, a web server designed to align protein-coding nucleotide sequences based on their corresponding amino acid translations. Many comparisons between biological sequences (nucleic acids and proteins) involve the construction of multiple alignments. Alignments represent a statement regarding the homology between individual nucleotides or amino acids within homologous genes. As protein-coding DNA sequences evolve as triplets of nucleotides (codons) and it is known that sequence similarity degrades more rapidly at the DNA than at the amino acid level, alignments are generally more accurate when based on amino acids than on their corresponding nucleotides. TranslatorX novelties include: (i) use of all documented genetic codes and the possibility of assigning different genetic codes for each sequence; (ii) a battery of different multiple alignment programs; (iii) translation of ambiguous codons when possible; (iv) an innovative criterion to clean nucleotide alignments with GBlocks based on protein information; and (v) a rich output, including Jalview-powered graphical visualization of the alignments, codon-based alignments coloured according to the corresponding amino acids, measures of compositional bias and first, second and third codon position specific alignments. The TranslatorX server is freely available at http://translatorx.co.uk.
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            Paleontological evidence to date the tree of life.

            The role of fossils in dating the tree of life has been misunderstood. Fossils can provide good "minimum" age estimates for branches in the tree, but "maximum" constraints on those ages are poorer. Current debates about which are the "best" fossil dates for calibration move to consideration of the most appropriate constraints on the ages of tree nodes. Because fossil-based dates are constraints, and because molecular evolution is not perfectly clock-like, analysts should use more rather than fewer dates, but there has to be a balance between many genes and few dates versus many dates and few genes. We provide "hard" minimum and "soft" maximum age constraints for 30 divergences among key genome model organisms; these should contribute to better understanding of the dating of the animal tree of life.
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              Bayesian estimation of species divergence times under a molecular clock using multiple fossil calibrations with soft bounds.

              We implement a Bayesian Markov chain Monte Carlo algorithm for estimating species divergence times that uses heterogeneous data from multiple gene loci and accommodates multiple fossil calibration nodes. A birth-death process with species sampling is used to specify a prior for divergence times, which allows easy assessment of the effects of that prior on posterior time estimates. We propose a new approach for specifying calibration points on the phylogeny, which allows the use of arbitrary and flexible statistical distributions to describe uncertainties in fossil dates. In particular, we use soft bounds, so that the probability that the true divergence time is outside the bounds is small but nonzero. A strict molecular clock is assumed in the current implementation, although this assumption may be relaxed. We apply our new algorithm to two data sets concerning divergences of several primate species, to examine the effects of the substitution model and of the prior for divergence times on Bayesian time estimation. We also conduct computer simulation to examine the differences between soft and hard bounds. We demonstrate that divergence time estimation is intrinsically hampered by uncertainties in fossil calibrations, and the error in Bayesian time estimates will not go to zero with increased amounts of sequence data. Our analyses of both real and simulated data demonstrate potentially large differences between divergence time estimates obtained using soft versus hard bounds and a general superiority of soft bounds. Our main findings are as follows. (1) When the fossils are consistent with each other and with the molecular data, and the posterior time estimates are well within the prior bounds, soft and hard bounds produce similar results. (2) When the fossils are in conflict with each other or with the molecules, soft and hard bounds behave very differently; soft bounds allow sequence data to correct poor calibrations, while poor hard bounds are impossible to overcome by any amount of data. (3) Soft bounds eliminate the need for "safe" but unrealistically high upper bounds, which may bias posterior time estimates. (4) Soft bounds allow more reliable assessment of estimation errors, while hard bounds generate misleadingly high precisions when fossils and molecules are in conflict.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                16 May 2016
                2016
                : 6
                : 25725
                Affiliations
                [1 ]Department of Entomology, China Agricultural University , Beijing 100193, China
                [2 ]GeneCology Research Centre, Faculty of Science, Health, Education and Engineering, University of the Sunshine Coast , Maroochydore, Queensland 4556, Australia
                [3 ]College of Life Sciences and Technology, Inner Mongolia Normal University , Hohhot 010022, China
                [4 ]Department of Plant Pathology and Crop Protection, Georg-August-University Göttingen , Göttingen 37077, Germany
                [5 ]Tiroler Landesmuseum, Josef-Schraffl-Strassbe 2a , A-6020 Innsbruck, Austria
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                srep25725
                10.1038/srep25725
                4867608
                27180804
                d5acf0ce-c6da-454d-a979-83935faa94fc
                Copyright © 2016, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 18 November 2015
                : 21 April 2016
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