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Dynamics of genomic innovation in the unicellular ancestry of animals

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      Abstract

      Which genomic innovations underpinned the origin of multicellular animals is still an open debate. Here, we investigate this question by reconstructing the genome architecture and gene family diversity of ancestral premetazoans, aiming to date the emergence of animal-like traits. Our comparative analysis involves genomes from animals and their closest unicellular relatives (the Holozoa), including four new genomes: three Ichthyosporea and Corallochytrium limacisporum. Here, we show that the earliest animals were shaped by dynamic changes in genome architecture before the emergence of multicellularity: an early burst of gene diversity in the ancestor of Holozoa, enriched in transcription factors and cell adhesion machinery, was followed by multiple and differently-timed episodes of synteny disruption, intron gain and genome expansions. Thus, the foundations of animal genome architecture were laid before the origin of complex multicellularity – highlighting the necessity of a unicellular perspective to understand early animal evolution.

      DOI: http://dx.doi.org/10.7554/eLife.26036.001

      eLife digest

      Hundreds of millions of years ago, some single-celled organisms gained the ability to work together and form multicellular organisms. This transition was a major step in evolution and took place at separate times in several parts of the tree of life, including in animals, plants, fungi and algae.

      Animals are some of the most complex organisms on Earth. Their single-celled ancestors were also quite genetically complex themselves and their genomes (the complete set of the organism’s DNA) already contained many genes that now coordinate the activity of the cells in a multicellular organism.

      The genome of an animal typically has certain features: it is large, diverse and contains many segments (called introns) that are not genes. By seeing if the single-celled relatives of animals share these traits, it is possible to learn more about when specific genetic features first evolved, and whether they are linked to the origin of animals.

      Now, Grau-Bové et al. have studied the genomes of several of the animal kingdom’s closest single-celled relatives using a technique called whole genome sequencing. This revealed that there was a period of rapid genetic change in the single-celled ancestors of animals during which their genes became much more diverse. Another ‘explosion’ of diversity happened after animals had evolved. Furthermore, the overall amount of the genomic content inside cells and the number of introns found in the genome rapidly increased in separate, independent events in both animals and their single-celled ancestors.

      Future research is needed to investigate whether other multicellular life forms – such as plants, fungi and algae – originated in the same way as animal life. Understanding how the genetic material of animals evolved also helps us to understand the genetic structures that affect our health. For example, genes that coordinate the behavior of cells (and so are important for multicellular organisms) also play a role in cancer, where cells break free of this regulation to divide uncontrollably.

      DOI: http://dx.doi.org/10.7554/eLife.26036.002

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      Trimmomatic: a flexible trimmer for Illumina sequence data

      Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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        MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

        We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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          RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

          Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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            Author and article information

            Affiliations
            [1 ]Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra) , Barcelona, Catalonia, Spain
            [2 ]deptDepartament de Genètica, Microbiologia i Estadística , Universitat de Barelona , Barcelona, Catalonia, Spain
            [3 ]deptUnité d'Ecologie, Systématique et Evolution , Université Paris-Sud/Paris-Saclay, AgroParisTech , Orsay, France
            [4 ]deptDepartment of Microbiology , University of Hawai'i at Mānoa , Honolulu, United States
            [5 ]deptAdvanced Studies in Genomics, Proteomics and Bioinformatics , University of Hawai'i at Mānoa , Honolulu, United States
            [6 ]deptFaculty of Life and Environmental Sciences , Prefectural University of Hiroshima , Hiroshima, Japan
            [7 ]deptDepartment of Biosciences , University of Exeter , Exeter, United Kingdom
            [8 ]ICREA, Passeig Lluís Companys , Barcelona, Catalonia, Spain
            Max-Planck Institute for Evolutionary Biology , Germany
            Max-Planck Institute for Evolutionary Biology , Germany
            Author notes
            Contributors
            Role: Reviewing editor,
            Max-Planck Institute for Evolutionary Biology , Germany
            Journal
            eLife
            Elife
            eLife
            eLife
            eLife
            eLife Sciences Publications, Ltd
            2050-084X
            20 July 2017
            2017
            : 6
            28726632 5560861 26036 10.7554/eLife.26036
            © 2017, Grau-Bové et al

            This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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            Funding
            Funded by: FundRef http://dx.doi.org/10.13039/501100003329, Ministerio de Economía y Competitividad;
            Award ID: BFU2014-57779-P
            Award Recipient :
            Funded by: FundRef http://dx.doi.org/10.13039/501100000780, European Commission;
            Award ID: ERC-2012-Co -616960
            Award Recipient :
            Funded by: FundRef http://dx.doi.org/10.13039/501100003329, Ministerio de Economía y Competitividad;
            Award ID: BFU-2011-23434
            Award Recipient :
            Funded by: FundRef http://dx.doi.org/10.13039/501100002809, Generalitat de Catalunya;
            Award ID: 2014 SGR 619
            Award Recipient :
            The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
            Categories
            Research Article
            Genes and Chromosomes
            Genomics and Evolutionary Biology
            Custom metadata
            2.5
            The foundations of genomic complexity in multicellular animals have deep roots in their unicellular prehistory, both in terms of innovations in gene content, as well as the evolutionary dynamics of genome architecture.
            2.5

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