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      Comparative genome sequencing reveals genomic signature of extreme desiccation tolerance in the anhydrobiotic midge

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          Abstract

          Anhydrobiosis represents an extreme example of tolerance adaptation to water loss, where an organism can survive in an ametabolic state until water returns. Here we report the first comparative analysis examining the genomic background of extreme desiccation tolerance, which is exclusively found in larvae of the only anhydrobiotic insect, Polypedilum vanderplanki. We compare the genomes of P. vanderplanki and a congeneric desiccation-sensitive midge P. nubifer. We determine that the genome of the anhydrobiotic species specifically contains clusters of multi-copy genes with products that act as molecular shields. In addition, the genome possesses several groups of genes with high similarity to known protective proteins. However, these genes are located in distinct paralogous clusters in the genome apart from the classical orthologues of the corresponding genes shared by both chironomids and other insects. The transcripts of these clustered paralogues contribute to a large majority of the mRNA pool in the desiccating larvae and most likely define successful anhydrobiosis. Comparison of expression patterns of orthologues between two chironomid species provides evidence for the existence of desiccation-specific gene expression systems in P. vanderplanki.

          Abstract

          The African chironomid midge, Polypedilum vanderplanki, is able to withstand extreme desiccation. Here the authors sequence the genomes of a desiccation-tolerant and desiccation-sensitive species of chironomid midge and pinpoint genes that may have a role in conferring resistance to desiccation.

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          Most cited references43

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          Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources

          Background In order to improve gene prediction, extrinsic evidence on the gene structure can be collected from various sources of information such as genome-genome comparisons and EST and protein alignments. However, such evidence is often incomplete and usually uncertain. The extrinsic evidence is usually not sufficient to recover the complete gene structure of all genes completely and the available evidence is often unreliable. Therefore extrinsic evidence is most valuable when it is balanced with sequence-intrinsic evidence. Results We present a fairly general method for integration of external information. Our method is based on the evaluation of hints to potentially protein-coding regions by means of a Generalized Hidden Markov Model (GHMM) that takes both intrinsic and extrinsic information into account. We used this method to extend the ab initio gene prediction program AUGUSTUS to a versatile tool that we call AUGUSTUS+. In this study, we focus on hints derived from matches to an EST or protein database, but our approach can be used to include arbitrary user-defined hints. Our method is only moderately effected by the length of a database match. Further, it exploits the information that can be derived from the absence of such matches. As a special case, AUGUSTUS+ can predict genes under user-defined constraints, e.g. if the positions of certain exons are known. With hints from EST and protein databases, our new approach was able to predict 89% of the exons in human chromosome 22 correctly. Conclusion Sensitive probabilistic modeling of extrinsic evidence such as sequence database matches can increase gene prediction accuracy. When a match of a sequence interval to an EST or protein sequence is used it should be treated as compound information rather than as information about individual positions.
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            The generic genome browser: a building block for a model organism system database.

            The Generic Model Organism System Database Project (GMOD) seeks to develop reusable software components for model organism system databases. In this paper we describe the Generic Genome Browser (GBrowse), a Web-based application for displaying genomic annotations and other features. For the end user, features of the browser include the ability to scroll and zoom through arbitrary regions of a genome, to enter a region of the genome by searching for a landmark or performing a full text search of all features, and the ability to enable and disable tracks and change their relative order and appearance. The user can upload private annotations to view them in the context of the public ones, and publish those annotations to the community. For the data provider, features of the browser software include reliance on readily available open source components, simple installation, flexible configuration, and easy integration with other components of a model organism system Web site. GBrowse is freely available under an open source license. The software, its documentation, and support are available at http://www.gmod.org.
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              Sequencing and de novo analysis of a coral larval transcriptome using 454 GSFlx

              Background New methods are needed for genomic-scale analysis of emerging model organisms that exemplify important biological questions but lack fully sequenced genomes. For example, there is an urgent need to understand the potential for corals to adapt to climate change, but few molecular resources are available for studying these processes in reef-building corals. To facilitate genomics studies in corals and other non-model systems, we describe methods for transcriptome sequencing using 454, as well as strategies for assembling a useful catalog of genes from the output. We have applied these methods to sequence the transcriptome of planulae larvae from the coral Acropora millepora. Results More than 600,000 reads produced in a single 454 sequencing run were assembled into ~40,000 contigs with five-fold average sequencing coverage. Based on sequence similarity with known proteins, these analyses identified ~11,000 different genes expressed in a range of conditions including thermal stress and settlement induction. Assembled sequences were annotated with gene names, conserved domains, and Gene Ontology terms. Targeted searches using these annotations identified the majority of genes associated with essential metabolic pathways and conserved signaling pathways, as well as novel candidate genes for stress-related processes. Comparisons with the genome of the anemone Nematostella vectensis revealed ~8,500 pairs of orthologs and ~100 candidate coral-specific genes. More than 30,000 SNPs were detected in the coral sequences, and a subset of these validated by re-sequencing. Conclusion The methods described here for deep sequencing of the transcriptome should be widely applicable to generate catalogs of genes and genetic markers in emerging model organisms. Our data provide the most comprehensive sequence resource currently available for reef-building corals, and include an extensive collection of potential genetic markers for association and population connectivity studies. The characterization of the larval transcriptome for this widely-studied coral will enable research into the biological processes underlying stress responses in corals and evolutionary adaptation to global climate change.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Pub. Group
                2041-1723
                12 September 2014
                : 5
                : 4784
                Affiliations
                [1 ]National Institute of Agrobiological Sciences (NIAS) , Tsukuba 305-8602, Japan
                [2 ]Institute of Fundamental Biology and Medicine, Kazan Federal University , Kazan 420008, Russia
                [3 ]ISS Science Project Office, Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA) , Tsukuba 305-8505, Japan
                [4 ]Okinawa Institute of Science and Technology Graduate University (OIST) , Onna, Okinawa 904-0495, Japan
                [5 ]Department of Bioengineering and Bioinformatics, Lomonosov Moscow State University , Moscow 119991, Russia
                [6 ]A. N. Belozersky Research Institute of Physico-Chemical Biology, Lomonosov Moscow State University , Moscow 119991, Russia
                [7 ]Institute for Information Transmission Problems of the Russian Academy of Sciences , Moscow 127994, Russia
                [8 ]Life Sciences Institute and Department of Ecology and Evolutionary Biology, University of Michigan , Ann Arbor, Michigan 48109, USA
                [9 ]Department of Genetics, Faculty of Biology, Lomonosov Moscow State University , Moscow 119991, Russia
                [10 ]Scientific Research Institute of Physico-Chemical Medicine, Federal Bio-Medical Agency of Russia , Moscow 119828, Russia
                [11 ]Department of Biological Sciences, Vanderbilt University , Nashville, Tennessee 37235, USA
                [12 ]Advanced Science Research Center, Kanazawa University , Kanazawa 920-0934, Japan
                [13 ]National Institute for Basic Biology (NIBB) , Okazaki 444-8585, Japan
                [14 ]Department of Basic Biology, School of Life Science, Graduate University for Advanced Studies , Okazaki 444-8585, Japan
                [15 ]Institute of Cytology and Genetics of the Russian Academy of Sciences , Novosibirsk 630090, Russia
                Author notes
                [*]

                These authors contributed equally to this work

                Article
                ncomms5784
                10.1038/ncomms5784
                4175575
                25216354
                d7251adb-09e1-4ea8-809b-e93817ed8ab5
                Copyright © 2014, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 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-nc-sa/4.0/

                History
                : 11 April 2014
                : 23 July 2014
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