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      Functional Annotation and Comparative Analysis of a Zygopteran Transcriptome

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          In this paper we present a de novo assembly of the transcriptome of the damselfly ( Enallagma hageni) through the use of 454 pyrosequencing. E. hageni is a member of the suborder Zygoptera, in the order Odonata, and Odonata organisms form the basal lineage of the winged insects (Pterygota). To date, sequence data used in phylogenetic analysis of Enallagma species have been derived from either mitochondrial DNA or ribosomal nuclear DNA. This Enallagma transcriptome contained 31,661 contigs that were assembled and translated into 14,813 individual open reading frames. Using these data, we constructed an extensive dataset of 634 orthologous nuclear protein-encoding genes across 11 species of Arthropoda and used Bayesian techniques to elucidate the position of Enallagma in the arthropod phylogenetic tree. Additionally, we demonstrated that the Enallagma transcriptome contains 169 genes that are evolving at rates that differ relative to those of the rest of the transcriptome (29 accelerated and 140 decreased), and, through multiple Gene Ontology searches and clustering methods, we present the first functional annotation of any palaeopteran’s transcriptome in the literature.

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          Most cited references 42

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          Clustal W and Clustal X version 2.0.

          The Clustal W and Clustal X multiple sequence alignment programs have been completely rewritten in C++. This will facilitate the further development of the alignment algorithms in the future and has allowed proper porting of the programs to the latest versions of Linux, Macintosh and Windows operating systems. The programs can be run on-line from the EBI web server: The source code and executables for Windows, Linux and Macintosh computers are available from the EBI ftp site
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            MrBayes 3: Bayesian phylogenetic inference under mixed models.

            MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models. This allows the user to analyze heterogeneous data sets consisting of different data types-e.g. morphological, nucleotide, and protein-and to explore a wide variety of structured models mixing partition-unique and shared parameters. The program employs MPI to parallelize Metropolis coupling on Macintosh or UNIX clusters.
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              Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research.

              We present here Blast2GO (B2G), a research tool designed with the main purpose of enabling Gene Ontology (GO) based data mining on sequence data for which no GO annotation is yet available. B2G joints in one application GO annotation based on similarity searches with statistical analysis and highlighted visualization on directed acyclic graphs. This tool offers a suitable platform for functional genomics research in non-model species. B2G is an intuitive and interactive desktop application that allows monitoring and comprehension of the whole annotation and analysis process. Blast2GO is freely available via Java Web Start at -> Evaluation.

                Author and article information

                G3 (Bethesda)
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes|Genomes|Genetics
                Genetics Society of America
                1 April 2013
                April 2013
                : 3
                : 4
                : 763-770
                [* ]Rutgers, The State University of New Jersey, Department of Genetics, Piscataway, New Jersey 08854-8082
                []Department of Biological Science, Dartmouth College, New Hampshire 03755
                Author notes

                Supporting information is available online at

                Sequence and transcriptome data from this article have been deposited in the National Center for Biotechnology Information (NCBI) database under Enallagma hageni BioProject no. PRJNA185185 ID:185185, which contains links and access to insect sampling data under BioSample SAMN01881995 and raw sequencing under Sequence Read Archive (SRA) SRR649536 and transcriptome SUB156504 data.

                [1 ]Corresponding author: Rutgers, The State University of New Jersey, Department of Genetics, Nelson Bio Labs-B416, 604 Allison Road, Piscataway, NJ 08854-8082. E-mail: alexander.shanku@
                Copyright © 2013 Shanku et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution Unported License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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                Pages: 8
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