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      Transcriptomes of three species of Tipuloidea (Diptera, Tipulomorpha) and implications for phylogeny of Tipulomorpha

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          Abstract

          Tipulomorpha has long been a problematic taxon in terms of familial composition, phylogenetic relationships among families and position relative to other ‘lower’ Diptera. Whole-transcriptome shotgun sequencing provides a powerful basis for phylogenetic studies. We performed de novo transcriptome sequencing to produce the first transcriptome datasets representing the families Pediciidae, Limoniidae and Cylindrotomidae using high-throughput sequencing technologies. We assembled cDNA libraries for Pedicia vetusta (Alexander) (Pediciidae), Rhipidia sejuga Zhang, Li and Yang (Limoniidae) and Liogma simplicicornis Alexander (Cylindrotomidae). Using the Illumina RNA-Seq method, we obtained 28,252, 44,152 and 44,281 unigenes, from the three respective species. Based on sequence similarity searches, 12,475 (44.16%), 20,334 (46.05%) and 17,478 (39.47%) genes were identified. Analysis of genes highly conserved at the amino acid sequence level revealed there were 1,709 single-copy orthologs genes across the analyzed species. Phylogenetic trees constructed using maximum likelihood (ML) based on the 1,709 single-copy orthologs genes indicated that the relationship between the four major infraorders of lower Diptera was: Culicomorpha + (Tipulomorpha + (Psychodomorpha + (Bibionomorpha + Brachycera))). Trichoceridae belongs within Tipulomorpha as the sister-group of Tipuloidea. Highly supported relationships within the Tipuloidea are Pediciidae + (Limoniidae + (Cylindrotomidae + Tipulidae)). Four-cluster likelihood mapping was used to study potential incongruent signals supporting other topologies, however, results were congruent with the ML tree.

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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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            NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins

            NCBI's reference sequence (RefSeq) database () is a curated non-redundant collection of sequences representing genomes, transcripts and proteins. The database includes 3774 organisms spanning prokaryotes, eukaryotes and viruses, and has records for 2 879 860 proteins (RefSeq release 19). RefSeq records integrate information from multiple sources, when additional data are available from those sources and therefore represent a current description of the sequence and its features. Annotations include coding regions, conserved domains, tRNAs, sequence tagged sites (STS), variation, references, gene and protein product names, and database cross-references. Sequence is reviewed and features are added using a combined approach of collaboration and other input from the scientific community, prediction, propagation from GenBank and curation by NCBI staff. The format of all RefSeq records is validated, and an increasing number of tests are being applied to evaluate the quality of sequence and annotation, especially in the context of complete genomic sequence.
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              Improved accuracy of multiple ncRNA alignment by incorporating structural information into a MAFFT-based framework

              Background Structural alignment of RNAs is becoming important, since the discovery of functional non-coding RNAs (ncRNAs). Recent studies, mainly based on various approximations of the Sankoff algorithm, have resulted in considerable improvement in the accuracy of pairwise structural alignment. In contrast, for the cases with more than two sequences, the practical merit of structural alignment remains unclear as compared to traditional sequence-based methods, although the importance of multiple structural alignment is widely recognized. Results We took a different approach from a straightforward extension of the Sankoff algorithm to the multiple alignments from the viewpoints of accuracy and time complexity. As a new option of the MAFFT alignment program, we developed a multiple RNA alignment framework, X-INS-i, which builds a multiple alignment with an iterative method incorporating structural information through two components: (1) pairwise structural alignments by an external pairwise alignment method such as SCARNA or LaRA and (2) a new objective function, Four-way Consistency, derived from the base-pairing probability of every sub-aligned group at every multiple alignment stage. Conclusion The BRAliBASE benchmark showed that X-INS-i outperforms other methods currently available in the sum-of-pairs score (SPS) criterion. As a basis for predicting common secondary structure, the accuracy of the present method is comparable to or rather higher than those of the current leading methods such as RNA Sampler. The X-INS-i framework can be used for building a multiple RNA alignment from any combination of algorithms for pairwise RNA alignment and base-pairing probability. The source code is available at the webpage found in the Availability and requirements section.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                6 March 2017
                2017
                : 12
                : 3
                : e0173207
                Affiliations
                [1 ]Department of Entomology, China Agricultural University, Beijing, China
                [2 ]Naturalis Biodiversity Center, Darwinweg, CR Leiden, the Netherlands
                [3 ]Department of Entomology, Purdue University, West Lafayette, Indiana, United States of America
                [4 ]Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China
                Beijing Institute of Genomics Chinese Academy of Sciences, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: ZK XZ DY.

                • Data curation: ZK XZ.

                • Formal analysis: ZK XZ.

                • Funding acquisition: DY.

                • Investigation: ZK XZ.

                • Methodology: ZK XZ.

                • Project administration: DY.

                • Resources: XZ.

                • Software: ZK XZ YW.

                • Supervision: SD CT YW HJ SLC MW.

                • Validation: YW SLC.

                • Visualization: ZK XZ.

                • Writing – original draft: ZK XZ.

                • Writing – review & editing: SD CT YW HJ SLC.

                Article
                PONE-D-16-25377
                10.1371/journal.pone.0173207
                5338816
                28264066
                85e48f8c-e0e9-445b-9ac0-3b3e275902ce
                © 2017 Kang et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 24 June 2016
                : 16 February 2017
                Page count
                Figures: 9, Tables: 3, Pages: 20
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31320103902
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31272354
                Award Recipient :
                This work was supported by the National Natural Science Foundation of China (No. 31320103902 and 31272354). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
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                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
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                Arthropoda
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                Computational Biology
                Genome Analysis
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                Transcriptome Analysis
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                Custom metadata
                All data are available from the Genbank database(accession numbers SRR3452301, SRR3452300, SRR3441821, GEMI00000000, GEMJ00000000 and GEMK00000000).

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