14
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Phylogeography and DNA-based species delimitation provide insight into the taxonomy of the polymorphic rose chafer Protaetia ( Potosia) cuprea species complex (Coleoptera: Scarabaeidae: Cetoniinae) in the Western Palearctic

      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

          The development of modern methods of species delimitation, unified under the “integrated taxonomy” approach, allows a critical examination and re-evaluation of complex taxonomic groups. The rose chafer Protaetia ( Potosia) cuprea is a highly polymorphic species group with a large distribution range. Despite its overall commonness, its taxonomy is unclear and subject to conflicting hypotheses, most of which largely fail to account for its evolutionary history. Based on the sequences of two mitochondrial markers from 65 individuals collected across the species range, and a detailed analysis of morphological characters including a geometric morphometry approach, we infer the evolutionary history and phylogeography of the P. cuprea species complex. Our results demonstrate the existence of three separate lineages in the Western Palearctic region, presumably with a species status. However, these lineages are in conflict with current taxonomic concepts. None of the 29 analyzed morphological characters commonly used in the taxonomy of this group proved to be unambiguously species- or subspecies- specific. The geometric morphometry analysis reveals a large overlap in the shape of the analyzed structures (pronotum, meso-metaventral projection, elytra and aedeagus), failing to identify either the genetically detected clades or the classical species entities. Our results question the monophyly of P. cuprea in regard to P. cuprina, as well as the species status of P. metallica. On the other hand, we found support for the species status of the Sicilian P. hypocrita. Collectively, our findings provide a new and original insight into the taxonomy and phylogeny of the P. cuprea species complex. At the same time, the results represent the first attempt to elucidate the phylogeography of these polymorphic beetles.

          Related collections

          Most cited references57

          • Record: found
          • Abstract: found
          • Article: not found

          Revisiting the insect mitochondrial molecular clock: the mid-Aegean trench calibration.

          Phylogenetic trees in insects are frequently dated by applying a "standard" mitochondrial DNA (mtDNA) clock estimated at 2.3% My(-1), but despite its wide use reliable calibration points have been lacking. Here, we used a well-established biogeographic barrier, the mid-Aegean trench separating the western and eastern Aegean archipelago, to estimate substitution rates in tenebrionid beetles. Cytochrome oxidase I (cox1) for six codistributed genera across 28 islands (444 individuals) on both sides of the mid-Aegean trench revealed 60 independently coalescing entities delimited with a mixed Yule-coalescent model. One representative per entity was used for phylogenetic analysis of mitochondrial (cox1, 16S rRNA) and nuclear (Mp20, 28S rRNA) genes. Six nodes marked geographically congruent east-west splits whose separation was largely contemporaneous and likely to reflect the formation of the mid-Aegean trench at 9-12 Mya. Based on these "known" dates, a divergence rate of 3.54% My(-1) for the cox1 gene (2.69% when combined with the 16S rRNA gene) was obtained under the preferred partitioning scheme and substitution model selected using Bayes factors. An extensive survey suggests that discrepancies in mtDNA substitution rates in the entomological literature can be attributed to the use of different substitution models, the use of different mitochondrial gene regions, mixing of intraspecific with interspecific data, and not accounting for variance in coalescent times or postseparation gene flow. Different treatments of these factors in the literature confound estimates of mtDNA substitution rates in opposing directions and obscure lineage-specific differences in rates when comparing data from various sources.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            The perils of DNA barcoding and the need for integrative taxonomy.

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              DNA Barcoding: Promise and Pitfalls

              In this issue of PLoS Biology, Hebert et al. (2004) have set out to test the resolution and performance of “DNA barcoding,” using a single mtDNA gene, cytochrome c oxidase I (COI), for a sample of North American birds. Before turning to details of this study, it is useful as context to consider the following questions: What is DNA barcoding, and what does it promise? What is new about it? Why is it controversial? What are the potential pitfalls? Put simply, the intent of DNA barcoding is to use large-scale screening of one or a few reference genes in order to (i) assign unknown individuals to species, and (ii) enhance discovery of new species (Hebert et al. 2003; Stoeckle 2003). Proponents envisage development of a comprehensive database of sequences, preferably associated with voucher specimens representing described species, against which sequences from sampled individuals can be compared. Given the long history of use of molecular markers (e.g., allozymes, rDNA, and mtDNA) for these purposes (Avise 2004), there is nothing fundamentally new in the DNA barcoding concept, except increased scale and proposed standardization. The former is inevitable. Standardization, i.e., the selection of one or more reference genes, is of proven value in the microbial community and in stimulating large-scale phylogenetic analyses, but whether “one gene fits all” is open to debate. Why, then, all the fuss? Initial reactions to the DNA barcoding concept have ranged from unbridled enthusiasm, especially from ecologists (Janzen 2004), to outright condemnation, largely from taxonomists (e.g., see the February 2003 issue of Trends in Ecology and Evolution). The former view reflects a real need to connect different life history stages and to increase the precision and efficiency of field studies involving diverse and difficult-to-identify taxa. The criticisms are mainly in response to the view that single-gene sequences should be the primary identifier for species (“DNA taxonomy”; Tautz et al. 2002; see also Blaxter 2004). At least for the macrobiota, the DNA barcoding community has moved away from this to emphasize the importance of embedding any large-scale sequence database within the existing framework and practice of systematics, including the importance of voucher specimens and of integrating molecular with morphological characters. Another point of contention—that DNA barcodes have limited phylogenetic resolution—arises from confusion about the scope of inference. At best, single-gene assays can hope to identify an individual to species or reveal inconsistencies between molecular variation and current perceptions of species boundaries. DNA barcoding should not be confused with efforts to resolve the “tree of life.” It should connect with and benefit from such projects, but resolving phylogeny at scales from species to major eukaryotic clades requires a very different strategy for selecting genes. Indeed, the very characteristic that makes the COI gene a candidate for high-throughput DNA barcoding—highly constrained amino acid sequence and thus broad applicability of primers (Hebert et al. 2003)—also limits its information content at deeper phylogenetic levels (e.g., Russo et al. 1996; Zardoya and Meyer 1996; Naylor and Brown 1997). Finally, while superficially appealing, the very term DNA barcoding is unfortunate, as it implies that each species has a fixed and invariant characteristic—like a barcode on a supermarket product. As evolutionary biologists, we should question this analogy. In evaluating the promise and pitfalls of DNA barcoding, we need to separate the two areas of application: molecular diagnostics of individuals relative to described taxa, and DNA-led discovery of new species. Both are inherently phylogenetic and rely on a solid taxonomic foundation, including adequate sampling of variation within species and inclusion of all previously described extant species within a given genus. Accurate diagnosis depends on low intraspecific variation compared with that between species, such that a short DNA sequence will allow precise allocation of an individual to a described taxon. The extensive literature on mtDNA phylogeography (Avise 2000) indicates that this condition often holds, although there are exceptions. Furthermore, within many species there is sufficient structure that it will be possible to allocate an individual to a particular geographic population. Such identifications should be accompanied by a statement of confidence—e.g., node support in a phylogenetic analysis and caveats in relation to the breath of sampling in the reference database (e.g., whale forensics; Palumbi and Cipriano 1998). DNA-led species discovery is more contentious, but again is not new. In animals, inclusion of mtDNA evidence in biogeographic and systematic analyses often reveals unexpected diversity or discordance with morphology, which then prompts re-evaluation of morphological and ecological characteristics and, if warranted, taxonomic revision. But, despite recent proposals (Wiens and Penkrot 2002; Hebert et al. 2004), it does not follow that mtDNA divergence should be a primary criterion for recognizing species boundaries (see also Sites and Marshall 2003). Potential limitations of using mtDNA to infer species boundaries include retention of ancestral polymorphism, male-biased gene flow, selection on any mtDNA nucleotide (as the whole genome is one linkage group), introgression following hybridization, and paralogy resulting from transfer of mtDNA gene copies to the nucleus. These are acknowledged by Hebert et al. (2004) and well documented in the literature (Bensasson et al. 2001; Ballard and Whitlock 2004), including that on birds (Degnan 1993; Quinn and White 1987; Lovette and Bermingham 2001; Weckstein et al. 2001). More specifically, using some level of mtDNA divergence as a yardstick for species boundaries ignores the low precision with which coalescence of mtDNA predicts phylogenetic divergence at nuclear genes (Hudson and Turelli 2003). An additional problem with focusing on mtDNA (or any other molecular) divergence as a primary criterion for recognizing species is that it will lead us to overlook new or rapidly diverged species, such as might arise through divergent selection or polyploidy, and thus to conclude that speciation requires long-term isolation. For example, a recent mtDNA analysis of North American birds (Johnson and Cicero 2004) showed that numerous avian species have low divergences and that speciation can occur relatively rapidly under certain circumstances. We contend, therefore, that whereas divergent or discordant mtDNA sequences might stimulate taxonomic reassessment based on nuclear genes as well as morphology, ecology, or behavior, mtDNA divergence is neither necessary nor sufficient as a criterion for delineating species. This view accords with existing practice: taxonomic splits in North American birds typically are based on multiple lines of biological evidence, e.g., morphological and vocal differences as well as genetic data (American Ornithologists' Union 1998). We turn now to the core of Hebert et al.'s paper—COI sequencing of a substantial sample of North American birds (260 of 667 species) and its validity as a test of the barcoding concept. Their aim is to test “the correspondence between species boundaries signaled by COI barcodes and those established by prior taxonomic research.” North American birds are an interesting choice because their species-level taxonomy is relatively well resolved and there has been extensive previous analysis of levels of mtDNA sequence divergence within and among described species (Klicka and Zink 1997; Avise and Walker 1998; Johnson and Cicero 2004). Herbert et al. (2004) found differences in COI sequences “between closely related species” that were 19–24 times greater in magnitude than the differences within species (7.05%–7.93% versus 0.27%–0.43%, respectively). From these data, they conclude that most North American bird species can be discriminated via molecular diagnosis of individuals and propose a “standard sequence threshold” of ten times the mean intraspecific variation (yielding a 2.7% threshold in birds) to flag genetically divergent taxa as “provisional species.” Thus, their analysis seeks to address both potential applications of DNA barcoding. Although Herbert et al. sampled a large number of species, a true test of the precision of mtDNA barcodes to assign individuals to species would include comparisons with sister species—the most closely related extant relatives. This would require that all members of a genus be examined, rather than a random sample of imprecisely defined close relatives, and that taxa be included from more than one geographic region. Johnson and Cicero (2004) showed the importance of comparing sister species when examining genetic divergence values in North American birds, with results that contrast strongly with those of Hebert et al. as well as previous studies (e.g., Klicka and Zink 1997). For 39 pairs of avian sister species, mtDNA sequence divergences ranged from 0.0% to 8.2%, with an average of 1.9% (cf. 7% to 8% among closely related species in Hebert et al.). Of these, 29 pairs (74%) are at or below the 2.7% threshold proposed by Herbert et al. and thus would not be recognized as species despite biological differences. Moreover, although only a few of these 39 pairs (see Table 1 in Johnson and Cicero [2004]) had sufficient sampling to assess intraspecific variation in mtDNA sequences, these typically showed paraphyly in mtDNA haplotypes. Therefore, there are still too few cases with adequate sampling of intraspecific diversity for sister species pairs to know how common paraphyly is, although a recent meta-analysis found that 17% of bird species deviated from mtDNA monophyly (Funk and Omland 2003). Collectively, these observations cast doubt on the precision of DNA barcoding for allocating individuals to previously described avian species. Empidonax flycatchers, which are renowned for their morphological similarity and could thereby benefit from DNA-based identification tools, provide an example of the importance of a more detailed analysis. A complete molecular phylogeny for this group (Johnson and Cicero 2002) yielded distances between four pairs of sister species that ranged from 0.7% (E. difficilis versus E. occidentalis) to 4.6% (E. traillii versus E. alnorum); notably, the genetic distance between mainland and island populations of E. difficilis (E. d. difficilis and E. d. insulicola, 0.9%) was greater than that between sister species (Johnson and Cicero 2002). Herbert et al.'s analysis included only two species of Empidonax (E. traillii and E. virescens), which are not sisters but members of divergent clades. Because E. virescens is genetically distant from all other species of Empidonax (10.3% to 12.5% uncorrected distance; Johnson and Cicero 2002), its comparison with E. trailli therefore inflates estimates of interspecific distances within the genus. Another key point of Hebert et al.'s analysis was to estimate levels of intraspecific diversity. For 130 species of the 260 examined, more than two individuals were sequenced (n = 2 to 12 individuals per species, mean = 2.4), and pooled pairwise genetic distances were found to be uncorrelated with geographic distances, leading Hebert et al. to conclude that “high levels of intraspecific divergence in COI in North American birds appear uncommon.” However, this makes the assumption that there is a common underlying pattern of phylogeographic structure, which is unlikely for North American birds (Zink 1996, Zink et al. 2001). If there is significant variation, assessment of intraspecific diversity can be based on a small sample of individuals only if individuals are sampled across existing population subdivisions for which geography and phenotypic variation are reasonable initial surrogates. The analyses presented by Hebert et al. will certainly stimulate further debate (a reply by Hebert et al. to the present letter is posted at http://www.barcodinglife.com), but, for the reasons outlined here, they are not yet a definitive test of the utility of DNA barcoding for either diagnosis of individuals or discovery of species. We also question whether the results for North American birds can be extrapolated to the tropics, where DNA barcoding could have maximum value. In general, among-population sequence divergence increases with decreasing latitude, even excluding previously glaciated regions (Martin and MacKay 2004), and studies of intraspecific genetic diversity in Neotropical birds have revealed a higher level of phylogeographic subdivision compared to temperate species (Remsen 1997, Lovette and Bermingham 2001). Thus, the general utility of mtDNA barcoding across different biogeographic regions—and between resident versus migratory taxa—requires further scrutiny. There is little doubt that large-scale and standardized sequencing, when integrated with existing taxonomic practice, can contribute significantly to the challenges of identifying individuals and increasing the rate of discovering biological diversity. But to determine when and where this approach is applicable, we now need to discover the boundary conditions. The real challenge lies with tropical taxa and those with limited dispersal and thus substantial phylogeographic structure. Such analyses need to be taxonomically broad and need to extend beyond the focal geographic region to ensure that potential sister taxa are evaluated and can be discriminated. There is also the need to examine groups with frequent (possibly cryptic) hybridization, recent radiations, and high rates of gene transfer from mtDNA to the nucleus. Only then will the skeptics be satisfied.
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Investigation
                Role: Formal analysisRole: MethodologyRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                20 February 2018
                2018
                : 13
                : 2
                : e0192349
                Affiliations
                [1 ] Department of Zoology, Faculty of Science, Charles University, Prague, Czech Republic
                [2 ] Department of Arthropoda, Zoologisches Forschungsmuseum Alexander Koenig, Bonn, Germany
                Sichuan University, CHINA
                Author notes

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

                ‡ These authors also contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-3699-9245
                Article
                PONE-D-17-39367
                10.1371/journal.pone.0192349
                5819786
                29462164
                aa6c5ca1-fefa-4659-81ca-a2b060879595
                © 2018 Vondráček 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
                : 6 November 2017
                : 20 January 2018
                Page count
                Figures: 7, Tables: 2, Pages: 26
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100007397, Univerzita Karlova v Praze;
                Award ID: SVV 260 434/2017
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100007397, Univerzita Karlova v Praze;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100007397, Univerzita Karlova v Praze;
                Award Recipient :
                Funded by: Charles University Research Centre program
                Award ID: No. 204069
                Award Recipient :
                DV was supported by Charles University grant (SVV 260 434/2017), while PS has been supported by Charles University Research Centre program No. 204069. PS and DK were supported by the institutional resource of Faculty of Science, Charles University as well.
                Categories
                Research Article
                Biology and Life Sciences
                Taxonomy
                Computer and Information Sciences
                Data Management
                Taxonomy
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Biology and Life Sciences
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Computer and Information Sciences
                Data Management
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Biology and Life Sciences
                Biogeography
                Phylogeography
                Ecology and Environmental Sciences
                Biogeography
                Phylogeography
                Earth Sciences
                Geography
                Biogeography
                Phylogeography
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Phylogeography
                Biology and Life Sciences
                Genetics
                Population Genetics
                Phylogeography
                Biology and Life Sciences
                Population Biology
                Population Genetics
                Phylogeography
                People and Places
                Geographical Locations
                Europe
                Biology and Life Sciences
                Genetics
                Heredity
                Genetic Mapping
                Haplotypes
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Arthropoda
                Insects
                Beetles
                Research and Analysis Methods
                Imaging Techniques
                Morphometry
                Biology and Life Sciences
                Population Biology
                Population Dynamics
                Geographic Distribution
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article