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      Endogenous florendoviruses are major components of plant genomes and hallmarks of virus evolution

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          Abstract

          The extent and importance of endogenous viral elements have been extensively described in animals but are much less well understood in plants. Here we describe a new genus of Caulimoviridae called ‘Florendovirus’, members of which have colonized the genomes of a large diversity of flowering plants, sometimes at very high copy numbers (>0.5% total genome content). The genome invasion of Oryza is dated to over 1.8 million years ago (MYA) but phylogeographic evidence points to an even older age of 20–34 MYA for this virus group. Some appear to have had a bipartite genome organization, a unique characteristic among viral retroelements. In Vitis vinifera, 9% of the endogenous florendovirus loci are located within introns and therefore may influence host gene expression. The frequent colocation of endogenous florendovirus loci with TA simple sequence repeats, which are associated with chromosome fragility, suggests sequence capture during repair of double-stranded DNA breaks.

          Abstract

          Endogenous viral elements have been extensively described in animals but their significance in plants is less well understood. Here, Geering et al. describe a new group of endogenous pararetroviruses, called florendoviruses, which have colonized the genomes of many important crop species.

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          Most cited references 69

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          MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods.

          Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.
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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data

              Massively-parallel cDNA sequencing has opened the way to deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here, we present the Trinity methodology for de novo full-length transcriptome reconstruction, and evaluate it on samples from fission yeast, mouse, and whitefly – an insect whose genome has not yet been sequenced. Trinity fully reconstructs a large fraction of the transcripts present in the data, also reporting alternative splice isoforms and transcripts from recently duplicated genes. In all cases, Trinity performs better than other available de novo transcriptome assembly programs, and its sensitivity is comparable to methods relying on genome alignments. Our approach provides a unified and general solution for transcriptome reconstruction in any sample, especially in the complete absence of a reference genome.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Pub. Group
                2041-1723
                10 November 2014
                : 5
                Affiliations
                [1 ]Queensland Alliance for Agriculture and Food Innovation, The University of Queensland , GPO Box 267, Brisbane, Queensland 4001, Australia
                [2 ]INRA, UR1164 URGI, INRA de Versailles-Grignon, Route de Saint-Cyr , Versailles 78026, France
                [3 ]Arizona Genomics Institute, School of Plant Sciences, BIO5 Institute, University of Arizona , Tucson, Arizona 85721, USA
                [4 ]International Rice Research Institute, Genetic Resource Center , Los Baños, Laguna, The Philippines
                [5 ]Department of Ecology and Evolutionary Biology, University of Arizona , Tucson, Arizona 85721, USA
                [6 ]Istituto di Genomica Applicata, Parco Scientifico e Tecnologico di Udine Luigi Danieli , Via J Linussio 51, 33100 Udine, Italy
                [7 ]Research and Innovation Centre, Fondazione Edmund Mach , Via E. Mach 1, 38010 San Michele all’Adige (TN), Italy
                [8 ]CIRAD UMR AGAP, Station de Neufchâteau, Sainte-Marie , 97130 Capesterre Belle-Eau, Guadeloupe, France
                Author notes
                [*]

                These authors contributed equally to this work

                Article
                ncomms6269
                10.1038/ncomms6269
                4241990
                25381880
                Copyright © 2014, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                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/

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