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      Transcriptome sequences spanning key developmental states as a resource for the study of the cestode Schistocephalus solidus, a threespine stickleback parasite

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          Abstract

          Background

          Schistocephalus solidus is a well-established model organism for studying the complex life cycle of cestodes and the mechanisms underlying host-parasite interactions. However, very few large-scale genetic resources for this species are available. We have sequenced and de novo-assembled the transcriptome of S. solidus using tissues from whole worms at three key developmental states - non-infective plerocercoid, infective plerocercoid and adult plerocercoid - to provide a resource for studying the evolution of complex life cycles and, more specifically, how parasites modulate their interactions with their hosts during development.

          Findings

          The de novo transcriptome assembly reconstructed the coding sequence of 10,285 high-confidence unigenes from which 24,765 non-redundant transcripts were derived. 7,920 (77 %) of these unigenes were annotated with a protein name and 7,323 (71 %) were assigned at least one Gene Ontology term. Our raw transcriptome assembly (unfiltered transcripts) covers 92 % of the predicted transcriptome derived from the S. solidus draft genome assembly currently available on WormBase. It also provides new ecological information and orthology relationships to further annotate the current WormBase transcriptome and genome.

          Conclusion

          This large-scale transcriptomic dataset provides a foundation for studies on how parasitic species with complex life cycles modulate their response to changes in biotic and abiotic conditions experienced inside their various hosts, which is a fundamental objective of parasitology. Furthermore, this resource will help in the validation of the S solidus gene features that have been predicted based on genomic sequence.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13742-016-0128-3) contains supplementary material, which is available to authorized users.

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          Most cited references40

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Profile hidden Markov models.

            S. Eddy (1998)
            The recent literature on profile hidden Markov model (profile HMM) methods and software is reviewed. Profile HMMs turn a multiple sequence alignment into a position-specific scoring system suitable for searching databases for remotely homologous sequences. Profile HMM analyses complement standard pairwise comparison methods for large-scale sequence analysis. Several software implementations and two large libraries of profile HMMs of common protein domains are available. HMM methods performed comparably to threading methods in the CASP2 structure prediction exercise.
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              eggNOG v3.0: orthologous groups covering 1133 organisms at 41 different taxonomic ranges

              Orthologous relationships form the basis of most comparative genomic and metagenomic studies and are essential for proper phylogenetic and functional analyses. The third version of the eggNOG database (http://eggnog.embl.de) contains non-supervised orthologous groups constructed from 1133 organisms, doubling the number of genes with orthology assignment compared to eggNOG v2. The new release is the result of a number of improvements and expansions: (i) the underlying homology searches are now based on the SIMAP database; (ii) the orthologous groups have been extended to 41 levels of selected taxonomic ranges enabling much more fine-grained orthology assignments; and (iii) the newly designed web page is considerably faster with more functionality. In total, eggNOG v3 contains 721 801 orthologous groups, encompassing a total of 4 396 591 genes. Additionally, we updated 4873 and 4850 original COGs and KOGs, respectively, to include all 1133 organisms. At the universal level, covering all three domains of life, 101 208 orthologous groups are available, while the others are applicable at 40 more limited taxonomic ranges. Each group is amended by multiple sequence alignments and maximum-likelihood trees and broad functional descriptions are provided for 450 904 orthologous groups (62.5%).
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                Author and article information

                Contributors
                1-418-656-2131 , 1-418-656-7176 , francois-olivier.gagnon-hebert.1@ulaval.ca
                Journal
                Gigascience
                Gigascience
                GigaScience
                BioMed Central (London )
                2047-217X
                2 June 2016
                2 June 2016
                2016
                : 5
                : 24
                Affiliations
                [ ]Institut de Biologie Intégrative et des Systèmes (IBIS), Département de Biologie, Université Laval, Pavillon Charles-Eugène-Marchand, Québec, G1V 0A6, Canada
                [ ]Department of Neuroscience, Psychology and Behaviour, Adrian Building, University of Leicester, University Road, Leicester, LE1 7RH, UK
                Article
                128
                10.1186/s13742-016-0128-3
                4891850
                27259971
                a6b84744-9049-4459-9989-45b1984717fd
                © Hébert et al. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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
                : 16 December 2015
                : 11 May 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000038, Natural Sciences and Engineering Research Council of Canada (CA);
                Award ID: Vanier Scholarship
                Funded by: FundRef http://dx.doi.org/10.13039/501100003151, Fonds de Recherche du Québec - Nature et Technologies;
                Award ID: Projet de Recherche en Équipe
                Award ID: Projets de Recherche en Équipe
                Award Recipient :
                Categories
                Data Note
                Custom metadata
                © The Author(s) 2016

                transcriptome,rna-seq,de novo assembly,schistocephalus solidus,parasite,cestode,flatworm,threespine stickleback,gasterosteus aculeatus

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