22
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Excluding spatial sampling bias does not eliminate oversplitting in DNA‐based species delimitation analyses

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          DNA barcoding and DNA‐based species delimitation are major tools in DNA taxonomy. Sampling has been a central debate in this context, because the geographical composition of samples affects the accuracy and performance of DNA barcoding. Performance of complex DNA‐based species delimitation is to be tested under simpler conditions in absence of geographic sampling bias. Here, we present an empirical dataset sampled from a single locality in a Southeast‐Asian biodiversity hotspot (Laos: Phou Pan mountain). We investigate the performance of various species delimitation approaches on a megadiverse assemblage of herbivorous chafer beetles (Coleoptera: Scarabaeidae) to infer whether species delimitation suffers in the same way from exaggerate infraspecific variation despite the lack of geographic genetic variation that led to inconsistencies between entities from DNA‐based and morphology‐based species inference in previous studies. For this purpose, a 658 bp fragment of the mitochondrial cytochrome c oxidase subunit 1 ( cox1) was analyzed for a total of 186 individuals of 56 morphospecies. Tree‐based and distance‐based species delimitation methods were used. All approaches showed a rather limited match ratio (max. 77%) with morphospecies. Poisson tree process (PTP) and statistical parsimony network analysis (TCS) prevailingly over‐splitted morphospecies, while 3% clustering and Automatic Barcode Gap Discovery (ABGD) also lumped several species into one entity. ABGD revealed the highest congruence between molecular operational taxonomic units (MOTUs) and morphospecies. Disagreements between morphospecies and MOTUs have to be explained by historically acquired geographic genetic differentiation, incomplete lineage sorting, and hybridization. The study once again highlights how important morphology still is in order to correctly interpret the results of molecular species delimitation.

          Abstract

          Performance of complex DNA‐based species delimitation is to be tested under simpler conditions in the absence of geographic sampling bias. Here, we present an empirical data set sampled from a single locality in a Southeast‐Asian biodiversity hotspot in Laos and investigate the performance of species delimitation approaches on a megadiverse assemblage of herbivore chafer beetles (Coleoptera: Scarabaeidae) to infer whether species delimitation suffers in the same way from exaggerate infraspecific variation despite the lack of geographic genetic variation that led to inconsistencies between entities from DNA‐based and morphology‐based species inference in previous studies.

          Related collections

          Most cited references93

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

          Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

              Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.
                Bookmark

                Author and article information

                Contributors
                d.ahrens@leibniz-zfmk.de , ahrens.dirk_col@gmx.de
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                02 July 2021
                August 2021
                : 11
                : 15 ( doiID: 10.1002/ece3.v11.15 )
                : 10327-10337
                Affiliations
                [ 1 ] Zoologisches Forschungsmuseum Alexander Koenig Zentrum für Taxonomie und Evolutionsforschung Bonn Germany
                [ 2 ] Zoologische Evolutionsbiologie Paris‐Lodron‐Universität Salzburg Austria
                [ 3 ] Villach Austria
                Author notes
                [*] [* ] Correspondence

                Dirk Ahrens, Zoologisches Forschungsmuseum Alexander Koenig, Zentrum für Taxonomie und Evolutionsforschung, Adenauerallee 160, 53113 Bonn, Germany.

                Emails: d.ahrens@ 123456leibniz-zfmk.de ; ahrens.dirk_col@ 123456gmx.de

                Author information
                https://orcid.org/0000-0003-3524-7153
                Article
                ECE37836
                10.1002/ece3.7836
                8328443
                34367578
                ac5e8ce7-4808-455f-8269-bcc7d772457c
                © 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 05 June 2021
                : 21 April 2021
                : 07 June 2021
                Page count
                Figures: 5, Tables: 2, Pages: 11, Words: 8332
                Funding
                Funded by: Zoologisches Forschungsmuseum A. Koenig Bonn
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                August 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.4 mode:remove_FC converted:02.08.2021

                Evolutionary Biology
                barcoding,cox1,geographic sampling bias,laos,species delimitation
                Evolutionary Biology
                barcoding, cox1, geographic sampling bias, laos, species delimitation

                Comments

                Comment on this article