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      ANISEED 2019: 4D exploration of genetic data for an extended range of tunicates

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          Abstract

          ANISEED ( https://www.aniseed.cnrs.fr) is the main model organism database for the worldwide community of scientists working on tunicates, the vertebrate sister-group. Information provided for each species includes functionally-annotated gene and transcript models with orthology relationships within tunicates, and with echinoderms, cephalochordates and vertebrates. Beyond genes the system describes other genetic elements, including repeated elements and cis-regulatory modules. Gene expression profiles for several thousand genes are formalized in both wild-type and experimentally-manipulated conditions, using formal anatomical ontologies. These data can be explored through three complementary types of browsers, each offering a different view-point. A developmental browser summarizes the information in a gene- or territory-centric manner. Advanced genomic browsers integrate the genetic features surrounding genes or gene sets within a species. A Genomicus synteny browser explores the conservation of local gene order across deuterostome. This new release covers an extended taxonomic range of 14 species, including for the first time a non-ascidian species, the appendicularian Oikopleura dioica. Functional annotations, provided for each species, were enhanced through a combination of manual curation of gene models and the development of an improved orthology detection pipeline. Finally, gene expression profiles and anatomical territories can be explored in 4D online through the newly developed Morphonet morphogenetic browser.

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          Tunicates and not cephalochordates are the closest living relatives of vertebrates.

          Tunicates or urochordates (appendicularians, salps and sea squirts), cephalochordates (lancelets) and vertebrates (including lamprey and hagfish) constitute the three extant groups of chordate animals. Traditionally, cephalochordates are considered as the closest living relatives of vertebrates, with tunicates representing the earliest chordate lineage. This view is mainly justified by overall morphological similarities and an apparently increased complexity in cephalochordates and vertebrates relative to tunicates. Despite their critical importance for understanding the origins of vertebrates, phylogenetic studies of chordate relationships have provided equivocal results. Taking advantage of the genome sequencing of the appendicularian Oikopleura dioica, we assembled a phylogenomic data set of 146 nuclear genes (33,800 unambiguously aligned amino acids) from 14 deuterostomes and 24 other slowly evolving species as an outgroup. Here we show that phylogenetic analyses of this data set provide compelling evidence that tunicates, and not cephalochordates, represent the closest living relatives of vertebrates. Chordate monophyly remains uncertain because cephalochordates, albeit with a non-significant statistical support, surprisingly grouped with echinoderms, a hypothesis that needs to be tested with additional data. This new phylogenetic scheme prompts a reappraisal of both morphological and palaeontological data and has important implications for the interpretation of developmental and genomic studies in which tunicates and cephalochordates are used as model animals.
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            Ultra-fast sequence clustering from similarity networks with SiLiX

            Background The number of gene sequences that are available for comparative genomics approaches is increasing extremely quickly. A current challenge is to be able to handle this huge amount of sequences in order to build families of homologous sequences in a reasonable time. Results We present the software package SiLiX that implements a novel method which reconsiders single linkage clustering with a graph theoretical approach. A parallel version of the algorithms is also presented. As a demonstration of the ability of our software, we clustered more than 3 millions sequences from about 2 billion BLAST hits in 7 minutes, with a high clustering quality, both in terms of sensitivity and specificity. Conclusions Comparing state-of-the-art software, SiLiX presents the best up-to-date capabilities to face the problem of clustering large collections of sequences. SiLiX is freely available at http://lbbe.univ-lyon1.fr/SiLiX.
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              Exploring long-range genome interactions using the WashU Epigenome Browser.

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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                08 January 2020
                04 November 2019
                04 November 2019
                : 48
                : D1
                : D668-D675
                Affiliations
                [1 ] CRBM, Université de Montpellier, CNRS , Montpellier, France
                [2 ] Bioself Communication; 28 rue de la Bibliothèque , F-13001 Marseille, France
                [3 ] ISEM, Université de Montpellier, CNRS, IRD, EPHE , Montpellier, France
                [4 ] Laboratoire d’Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Université de Montpellier, CNRS , Montpellier, France
                [5 ] Department of Biological Sciences, Graduate School of Science, Osaka University , 1-1 Machikaneyama-cho, Toyonaka, Osaka 560-0043, Japan
                [6 ] Whitney Laboratory for Marine Bioscience , 9505 Ocean Shore Boulevard, St. Augustine, FL 32080, USA
                [7 ] Department of Biology, University of Florida , 220 Bartram Hall, Gainesville, FL 32611, USA
                [8 ] DYOGEN, IBENS, Département de Biologie, Ecole Normale Supérieure, CNRS, Inserm, PSL Research University , F-75005 Paris, France
                [9 ] IBDM, Université Aix-Marseille, CNRS , Marseille, France
                [10 ] Institut de Génomique Fonctionnelle de Lyon, Université de Lyon, Ecole Normale Supérieure de Lyon , Université Claude Bernard Lyon 1, CNRS; 46 allée d’Italie, F-69364 Lyon, France
                [11 ] Laboratoire de Biologie du Développement de Villefranche-sur-mer (LBDV), Sorbonne Universités, Université Pierre-et-Marie-Curie, CNRS; Quai de la Darse , F-06234 Villefranche-sur-Mer Cedex, France
                [12 ] Division of Biology, Kansas State University , Manhattan, KS 66506, USA
                [13 ] State Key Laboratory of Cell Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, University of Chinese Academy of Sciences , 320 Yueyang Road, Shanghai 200031, China
                [14 ] Université de Montpellier , Montpellier, France
                [15 ] Department of Chemistry and Biotechnology, Faculty of Science and Technology, Kochi University , Kochi-shi, Kochi, Japan
                [16 ] Department of Biology, Swarthmore College , Swarthmore, PA 19081, USA
                Author notes
                To whom correspondence should be addressed. Tel: +33 4 34 35 94 00; Email: patrick.lemaire@ 123456crbm.cnrs.fr
                Correspondence may also be addressed to Christelle Dantec. Tel: +33 4 34 35 94 00; Email: christelle.dantec@ 123456crbm.cnrs.fr

                The authors wish it to be known that, in their opinion, the last two authors should be regarded as Joint Last Authors.

                Author information
                http://orcid.org/0000-0003-3152-1194
                http://orcid.org/0000-0002-6667-3297
                http://orcid.org/0000-0003-2787-0885
                http://orcid.org/0000-0002-9739-6333
                http://orcid.org/0000-0003-0404-7212
                http://orcid.org/0000-0001-7032-5650
                http://orcid.org/0000-0003-3151-0962
                http://orcid.org/0000-0002-6821-2427
                http://orcid.org/0000-0001-9464-180X
                http://orcid.org/0000-0002-8444-0630
                http://orcid.org/0000-0002-0752-6537
                http://orcid.org/0000-0003-3406-892X
                http://orcid.org/0000-0002-8209-173X
                http://orcid.org/0000-0001-5286-647X
                http://orcid.org/0000-0001-5478-0522
                http://orcid.org/0000-0002-7249-1668
                http://orcid.org/0000-0001-7247-6460
                http://orcid.org/0000-0003-4925-2009
                Article
                gkz955
                10.1093/nar/gkz955
                7145539
                31680137
                7aa1420b-999f-4f5f-9790-b9a66b14d75c
                © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 October 2019
                : 08 October 2019
                : 16 September 2019
                Page count
                Pages: 8
                Funding
                Funded by: CNRS 10.13039/501100004794
                Funded by: Agence Nationale de la Recherche 10.13039/501100001665
                Award ID: ANR-13-BSV2-0011-01
                Award ID: ANR-10-BINF-01-03
                Award ID: ANR-10-LABX-54
                Award ID: ANR-10-IDEX-0001-02
                Award ID: ANR-16-CE92-0019
                Funded by: Institut Français de Bioinformatique
                Funded by: National Science Foundation 10.13039/100000001
                Funded by: MEXT 10.13039/501100001700
                Award ID: 221S0002
                Funded by: JSPS 10.13039/501100001691
                Award ID: 24870019
                Award ID: 26840079
                Award ID: 18K06256
                Award ID: 26650079
                Award ID: 15H04377
                Award ID: 16K14735
                Award ID: 17KT0023
                Award ID: 19H03234
                Funded by: Inamori Foundation 10.13039/501100003844
                Funded by: Kato Memorial Research Foundation
                Funded by: Sumitomo Foundation 10.13039/100008608
                Funded by: Japan Foundation for Applied Enzymology 10.13039/100008695
                Categories
                Database Issue

                Genetics
                Genetics

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