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      Genome analysis of a major urban malaria vector mosquito, Anopheles stephensi

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          Abstract

          Background

          Anopheles stephensi is the key vector of malaria throughout the Indian subcontinent and Middle East and an emerging model for molecular and genetic studies of mosquito-parasite interactions. The type form of the species is responsible for the majority of urban malaria transmission across its range.

          Results

          Here, we report the genome sequence and annotation of the Indian strain of the type form of An. stephensi. The 221 Mb genome assembly represents more than 92% of the entire genome and was produced using a combination of 454, Illumina, and PacBio sequencing. Physical mapping assigned 62% of the genome onto chromosomes, enabling chromosome-based analysis. Comparisons between An. stephensi and An. gambiae reveal that the rate of gene order reshuffling on the X chromosome was three times higher than that on the autosomes. An. stephensi has more heterochromatin in pericentric regions but less repetitive DNA in chromosome arms than An. gambiae. We also identify a number of Y-chromosome contigs and BACs. Interspersed repeats constitute 7.1% of the assembled genome while LTR retrotransposons alone comprise more than 49% of the Y contigs. RNA-seq analyses provide new insights into mosquito innate immunity, development, and sexual dimorphism.

          Conclusions

          The genome analysis described in this manuscript provides a resource and platform for fundamental and translational research into a major urban malaria vector. Chromosome-based investigations provide unique perspectives on Anopheles chromosome evolution. RNA-seq analysis and studies of immunity genes offer new insights into mosquito biology and mosquito-parasite interactions.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13059-014-0459-2) contains supplementary material, which is available to authorized users.

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          Most cited references68

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            tRNAscan-SE: A Program for Improved Detection of Transfer RNA Genes in Genomic Sequence

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              Rfam: an RNA family database.

              Rfam is a collection of multiple sequence alignments and covariance models representing non-coding RNA families. Rfam is available on the web in the UK at http://www.sanger.ac.uk/Software/Rfam/ and in the US at http://rfam.wustl.edu/. These websites allow the user to search a query sequence against a library of covariance models, and view multiple sequence alignments and family annotation. The database can also be downloaded in flatfile form and searched locally using the INFERNAL package (http://infernal.wustl.edu/). The first release of Rfam (1.0) contains 25 families, which annotate over 50 000 non-coding RNA genes in the taxonomic divisions of the EMBL nucleotide database.
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                Author and article information

                Contributors
                jiangx@vt.edu
                peerya2@vt.edu
                brant@vt.edu
                atashi04@vt.edu
                xgchen2001@hotmail.com
                robert.waterhouse@gmail.com
                ad3002@gmail.com
                mriehle@umn.edu
                yogesh@nccs.res.in
                msharakh@vt.edu
                lawson@ebi.ac.uk
                npakpour@ucdavis.edu
                arensburger@gmail.com
                victorea@ksu.edu
                kei@pasteur.fr
                semrich@nd.edu
                phippl3@vt.edu
                Ryan.C.Kennedy@alumni.nd.edu
                smane@vbi.vt.edu
                gmaslen@ebi.ac.uk
                chyoma12@yahoo.com
                yuqi@vt.edu
                rsettlage@vbi.vt.edu
                marta.tojo@gmail.com
                jmctubio@gmail.com
                munger1@nd.edu
                bwangucd@gmail.com
                kenneth.vernick@pasteur.fr
                jribeiro@niaid.nih.gov
                aajames@uci.edu
                kmichel@ksu.edu
                mriehle@ag.arizona.edu
                sluckhart@ucdavis.edu
                igor@vt.edu
                jaketu@vt.edu
                Journal
                Genome Biol
                Genome Biology
                BioMed Central (London )
                1465-6906
                1465-6914
                23 September 2014
                23 September 2014
                2014
                : 15
                : 9
                : 459
                Affiliations
                [ ]Program of Genetics, Bioinformatics, and Computational Biology, Virginia Tech, Blacksburg, VA USA
                [ ]Department of Biochemistry, Virginia Tech, Blacksburg, VA USA
                [ ]Department of Entomology, Virginia Tech, Blacksburg, VA USA
                [ ]Department of Pathogen Biology, Southern Medical University, Guangzhou, Guangdong China
                [ ]Department of Genetic Medicine and Development, University of Geneva Medical School, rue Michel-Servet 1, 1211 Geneva, Switzerland
                [ ]Swiss Institute of Bioinformatics, rue Michel-Servet 1, 1211 Geneva, Switzerland
                [ ]Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 32 Vassar Street, Cambridge, MA USA
                [ ]The Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA USA
                [ ]Theodosius Dobzhansky Center for Genome Bioinformatics, St. Petersburg State University, St. Petersburg, Russia
                [ ]Institute of Cytology Russian Academy of Sciences, St. Petersburg, Russia
                [ ]Department of Microbiology, University of Minnesota, Minneapolis, MN USA
                [ ]National Center for Cell Science, Pune University Campus, Ganeshkhind, Pune India
                [ ]European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD UK
                [ ]Department of Medical Microbiology and Immunology, University of California, Davis, CA USA
                [ ]Biological Sciences Department, California State Polytechnic University, Pomona, CA USA
                [ ]Division of Biology, Kansas State University, Manhattan, KS USA
                [ ]Department of Parasitology and Mycology, Unit of Insect Vector Genetics and Genomics, Institut Pasteur, Paris, France
                [ ]CNRS Unit of Hosts, Vectors and Pathogens (URA3012), Paris, France
                [ ]Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN USA
                [ ]Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA USA
                [ ]Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA USA
                [ ]Department of Entomology, University of Arizona, Tucson, AZ USA
                [ ]Department of Physiology, School of Medicine – CIMUS, Instituto de Investigaciones Sanitarias, University of Santiago de Compostela, Santiago de Compostela, Spain
                [ ]Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire UK
                [ ]Department of Biological Sciences, University of Notre Dame, Notre Dame, IN USA
                [ ]Section of Vector Biology, Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, Rockville, MD USA
                [ ]Departments of Microbiology & Molecular Genetics and Molecular Biology & Biochemistry, University of California, Irvine, CA USA
                Article
                459
                10.1186/s13059-014-0459-2
                4195908
                25244985
                7d63344f-c678-4269-bfd1-671a5968d608
                © Jiang et al.; licensee BioMed Central Ltd. 2014

                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 use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 27 April 2014
                : 3 September 2014
                Categories
                Research
                Custom metadata
                © The Author(s) 2014

                Genetics
                Genetics

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