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      Construction of a Species-Level Tree of Life for the Insects and Utility in Taxonomic Profiling

      Systematic Biology
      Oxford University Press
      Data integration, data mining, insects, phylogenomics, phyloinformatics, tree of life

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          Although comprehensive phylogenies have proven an invaluable tool in ecology and evolution, their construction is made increasingly challenging both by the scale and structure of publically available sequences. The distinct partition between gene-rich (genomic) and species-rich (DNA barcode) data is a feature of data that has been largely overlooked, yet presents a key obstacle to scaling supermatrix analysis. I present a phyloinformatics framework for draft construction of a species-level phylogeny of insects (Class Insecta). Matrix-building requires separately optimized pipelines for nuclear transcriptomic, mitochondrial genomic, and species-rich markers, whereas tree-building requires hierarchical inference in order to capture species-breadth while retaining deep-level resolution. The phylogeny of insects contains 49,358 species, 13,865 genera, 760 families. Deep-level splits largely reflected previous findings for sections of the tree that are data rich or unambiguous, such as inter-ordinal Endopterygota and Dictyoptera, the recently evolved and relatively homogeneous Lepidoptera, Hymenoptera, Brachycera (Diptera), and Cucujiformia (Coleoptera). However, analysis of bias, matrix construction and gene-tree variation suggests confidence in some relationships (such as in Polyneoptera) is less than has been indicated by the matrix bootstrap method. To assess the utility of the insect tree as a tool in query profiling several tree-based taxonomic assignment methods are compared. Using test data sets with existing taxonomic annotations, a tendency is observed for greater accuracy of species-level assignments where using a fixed comprehensive tree of life in contrast to methods generating smaller de novo reference trees. Described herein is a solution to the discrepancy in the way data are fit into supermatrices. The resulting tree facilitates wider studies of insect diversification and application of advanced descriptions of diversity in community studies, among other presumed applications.

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          Author and article information

          Syst Biol
          Syst. Biol
          Systematic Biology
          Oxford University Press
          May 2017
          25 January 2017
          01 May 2018
          : 66
          : 3
          : 426-439
          Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
          Author notes
          * Correspondence to be sent to: Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; E-mail: dchesters@ 123456ioz.ac.cn

          Associate Editor: Vincent Savolainen

          PMC5837528 PMC5837528 5837528 syw099
          © The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com
          : 20 September 2015
          : 3 November 2015
          : 18 October 2016
          Page count
          Pages: 14
          Funded by: Wellcome Trust 10.13039/100004440
          Regular Articles

          tree of life,phyloinformatics,phylogenomics,insects,data mining,Data integration


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