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      Gypsy moth genome provides insights into flight capability and virus–host interactions

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          Abstract

          Since its accidental introduction to Massachusetts in the late 1800s, the European gypsy moth (EGM; Lymantria dispar dispar) has become a major defoliator in North American forests. However, in part because females are flightless, the spread of the EGM across the United States and Canada has been relatively slow over the past 150 years. In contrast, females of the Asian gypsy moth (AGM; Lymantria dispar asiatica) subspecies have fully developed wings and can fly, thereby posing a serious economic threat if populations are established in North America. To explore the genetic determinants of these phenotypic differences, we sequenced and annotated a draft genome of L. dispar and used it to identify genetic variation between EGM and AGM populations. The 865-Mb gypsy moth genome is the largest Lepidoptera genome sequenced to date and encodes ∼13,300 proteins. Gene ontology analyses of EGM and AGM samples revealed divergence between these populations in genes enriched for several gene ontology categories related to muscle adaptation, chemosensory communication, detoxification of food plant foliage, and immunity. These genetic differences likely contribute to variations in flight ability, chemical sensing, and pathogen interactions among EGM and AGM populations. Finally, we use our new genomic and transcriptomic tools to provide insights into genome-wide gene-expression changes of the gypsy moth after viral infection. Characterizing the immunological response of gypsy moths to virus infection may aid in the improvement of virus-based bioinsecticides currently used to control larval populations.

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          Most cited references60

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          Identification of novel transcripts in annotated genomes using RNA-Seq.

          We describe a new 'reference annotation based transcript assembly' problem for RNA-Seq data that involves assembling novel transcripts in the context of an existing annotation. This problem arises in the analysis of expression in model organisms, where it is desirable to leverage existing annotations for discovering novel transcripts. We present an algorithm for reference annotation-based transcript assembly and show how it can be used to rapidly investigate novel transcripts revealed by RNA-Seq in comparison with a reference annotation. The methods described in this article are implemented in the Cufflinks suite of software for RNA-Seq, freely available from http://bio.math.berkeley.edu/cufflinks. The software is released under the BOOST license. cole@broadinstitute.org; lpachter@math.berkeley.edu Supplementary data are available at Bioinformatics online.
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            GenBank

            Abstract GenBank® (www.ncbi.nlm.nih.gov/genbank/) is a comprehensive database that contains publicly available nucleotide sequences for 400 000 formally described species. These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole genome shotgun and environmental sampling projects. Most submissions are made using BankIt, the National Center for Biotechnology Information (NCBI) Submission Portal, or the tool tbl2asn. GenBank staff assign accession numbers upon data receipt. Daily data exchange with the European Nucleotide Archive and the DNA Data Bank of Japan ensures worldwide coverage. GenBank is accessible through the NCBI Nucleotide database, which links to related information such as taxonomy, genomes, protein sequences and structures, and biomedical journal literature in PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. Recent updates include changes to sequence identifiers, submission wizards for 16S and Influenza sequences, and an Identical Protein Groups resource.
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              Autophagy is an essential component of Drosophila immunity against vesicular stomatitis virus.

              Intrinsic innate immune mechanisms are the first line of defense against pathogens and exist to control infection autonomously in infected cells. Here, we showed that autophagy, an intrinsic mechanism that can degrade cytoplasmic components, played a direct antiviral role against the mammalian viral pathogen vesicular stomatitis virus (VSV) in the model organism Drosophila. We found that the surface glycoprotein, VSV-G, was likely the pathogen-associated molecular pattern (PAMP) that initiated this cell-autonomous response. Once activated, autophagy decreased viral replication, and repression of autophagy led to increased viral replication and pathogenesis in cells and animals. Lastly, we showed that the antiviral response was controlled by the phosphatidylinositol 3-kinase (PI3K)-Akt-signaling pathway, which normally regulates autophagy in response to nutrient availability. Altogether, these data uncover an intrinsic antiviral program that links viral recognition to the evolutionarily conserved nutrient-signaling and autophagy pathways.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proc Natl Acad Sci USA
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                January 14 2019
                : 201818283
                Article
                10.1073/pnas.1818283116
                6358702
                30642971
                926dfa59-cabb-4ed5-8635-3525caffd163
                © 2019

                Free to read

                http://www.pnas.org/site/misc/userlicense.xhtml

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