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Barcoding Fauna Bavarica: 78% of the Neuropterida Fauna Barcoded!

Barcoding Fauna Bavarica: 78% of the Neuropterida Fauna Barcoded!

  • Jérome Morinière, 
  • Lars Hendrich, 
  • Axel Hausmann, 
  • Paul Hebert, 
  • Gerhard Haszprunar, 
  • Axel Gruppe
PLOS
x

Abstract

This publication provides the first comprehensive DNA barcode data set for the Neuropterida of Central Europe, including 80 of the 102 species (78%) recorded from Bavaria (Germany) and three other species from nearby regions (Austria, France and the UK). Although the 286 specimens analyzed had a heterogeneous conservation history (60% dried; 30% in 80% EtOH; 10% fresh specimens in 95% EtOH), 237 (83%) generated a DNA barcode. Eleven species (13%) shared a BIN, but three of these taxa could be discriminated through barcodes. Four pairs of closely allied species shared barcodes including Chrysoperla pallida Henry et al., 2002 and C. lucasina Lacroix, 1912; Wesmaelius concinnus (Stephens, 1836) and W. quadrifasciatus (Reuter, 1894); Hemerobius handschini Tjeder, 1957 and H. nitidulus Fabricius, 1777; and H. atrifrons McLachlan, 1868 and H. contumax Tjeder, 1932. Further studies are needed to test the possible synonymy of these species pairs or to determine if other genetic markers permit their discrimination. Our data highlight five cases of potential cryptic diversity within Bavarian Neuropterida: Nineta flava (Scopoli, 1763), Sympherobius pygmaeus (Rambur, 1842), Sisyra nigra (Retzius, 1783), Semidalis aleyrodiformis (Stephens, 1836) and Coniopteryx pygmaea Enderlein, 1906 are each split into two or three BINs. The present DNA barcode library not only allows the identification of adult and larval stages, but also provides valuable information for alpha-taxonomy, and for ecological and evolutionary research.

Introduction

The comparatively small clade of holometabolous Neuropterida contains three insect orders (Rhaphidioptera, Megaloptera, Neuroptera) with about 6.300 described species worldwide [1]. Part of the superorder Endopterygota and closely related to beetles (Coleoptera), they are usually considered an unranked taxon [2]. Well-known members of Neuropterida are the snakeflies, dobsonflies, fishflies, lacewings and antlions. Some neuropterans are economically important, as the larvae of Chrysopidae and Hemerobiidae are used for the biocontrol of pest species on agricultural crops [3], [4]. Saure [5], [6], [7] reported 115 species for Germany and 97 species for Bavaria, but more recent studies have raised the count for Bavaria to 102 species [8]. This study provides COI barcode sequences for 80 of these species, including representatives of all 35 known genera (Fig. 1 and Fig. S1).

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Figure 1. Neighbour joining tree (established in BOLD – Radial tree layout was performed in Figtree).

https://doi.org/10.1371/journal.pone.0109719.g001

In 2006 the Bavarian State Collection of Zoology (ZSM) started a close collaboration with the Biodiversity Institute of Ontario (‘BIO’, Guelph, Canada) to assemble a DNA barcode library for all animals, plants and fungi known to occur in Bavaria in the framework of the International Barcode of Life Initiative (‘iBOL’). Over the past seven years, the ZSM submitted tissue samples from more than 150,000 identified vouchers belonging to more than 40,000 insect species. Sequencing was performed at the Canadian Centre for DNA Barcoding (‘CCDB’, Guelph, Canada). Photographs and geo-referenced label data, barcode sequences and trace files for all vouchers are available on the BOLD database [9], [10]. The present DNA barcode data set was produced as part of the Barcoding Fauna Bavarica (BFB) campaign which is a 10 year project (2009–2018) of the ZSM. The goal of this project is to create a DNA barcode library for all Bavarian species. Bavaria represents the largest of all German states with a landmass of 70,000 km2. It also harbors the highest biodiversity of all German states (with high altitude biomes, foothill areas and forested lowlands), with at least 35,000 animal species reported [11], representing a significant portion of the Central European fauna.

Material and Methods

Ethics statements

Field work permits were issued by the responsible state environmental office of Bavaria [Bayerisches Staatsministerium für Umwelt und Gesundheit, Munich, Germany, project: “Barcoding Fauna Bavarica”, reference number 62e-U8645.8-2008/3-17]. The study sites comprise state forests, public land and protected areas. We confirm that the field studies did not involve any protected species by European or national laws.

Specimens

We selected 286 specimens of Neuropterida from the collection of A.G. (which will later be deposited in the ZSM) as well as from material in the ZSM (Table 1). Additional specimens of Neuropterida collected by Malaise traps in the Bavarian Forest National Park were also included. For 20 species known from Bavaria we used vouchers from outside Bavaria, including three species (Pseudomallada inornata (Navás, 1901), Coniopteryx hoelzeli Aspöck, 1964, C. drammonti Rousset, 1964), which are likely to occur in Bavaria, but have not yet been recorded. Specimens were determined to a species level according to Aspöck et al. [12] following the nomenclature of Aspöck et al. [2]. Photos of all specimens and all sequence records are available on BOLD (public data set DS-NEUBFB; dx.doi.org/10.5883/DS-NEUBFB), while sequence data are also on GenBank (cf. accession numbers in Appendix S1).

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Table 1. Species list including species (BIN) origin, number of specimen (n), as well as Mean and Max intraspecific differences (ISD).

https://doi.org/10.1371/journal.pone.0109719.t001

Laboratory procedures

A single leg was removed from each specimen and sent in 96 well plates to the Canadian Center for DNA Barcoding (CCDB) for standardized, high-throughput DNA extraction, PCR amplification and bidirectional Sanger sequencing (www.dnabarcoding.ca/pa/ge/research/protocols). The amplified target region has a length of 658 bp, starting from the 5′end of the mitochondrial cytochrome oxidase c (COI) gene, which includes the 648 bp barcode region [13].

Data analysis

Sequence divergences (mean and maximum intraspecific variation and minimum genetic distance to the nearest-neighbour species) were calculated using the “Barcode Gap Analysis” tool on BOLD, employing the Kimura-2-Parameter distance metric and MUSCLE for sequence alignment. We only included sequences with a length of more than 500 bp in the analyses. The “BIN Discordance” analysis on BOLD was used to reveal species clusters which shared a BIN, and those which were assigned to two or more BINs. The Barcode Index Number (BIN) is assigned by BOLD and it represents a globally unique identifier for specimens with closely similar COI barcode sequences [14]. In most cases, members of a BIN belong to a single species recognized by traditional taxonomy [10].

Results and Discussion

The successfully sequenced specimens were assigned to 83 species by morphological taxonomy while the barcode data assigned them to 82 BINs (see accumulation curve, Fig. 2). The 83% success rate in DNA barcode recovery was high, considering that 60% of the specimens were dry and three quarters of the other specimens had been stored, suboptimally, in 80% EtOH. Only 10% of the specimens were optimally conserved in 95% EtOH.

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Figure 2. Accumulation curve for the 83 species and 82 BINs with DNA barcodes from Bavarian species.

Accumulation curve (from BOLD database; randomized; 100 iterations) for the 237 barcoded individuals (>500 bp).

https://doi.org/10.1371/journal.pone.0109719.g002

  1. 66 of the 83 species (80%) recognized by traditional taxonomy were represented by a single BIN cluster. Each of these clusters was clearly separated from all neighboring species, meaning that the species in question can be identified unambiguously by DNA barcoding.
  2. Eleven species (13%), including 4 pairs and one triplet, shared a BIN. Three of these species show constant (though small) genetic divergences from other species, meaning that they can be identified. The other eight species (four pairs) cannot be discriminated using the barcode fragment. Additional marker genes or morphological and ecological re-analysis might resolve these taxa or they may be synonyms.
  3. Five species (6%) were assigned to more than one BIN. Four of these cases were assigned to two BINs, while members of the final species were placed into three BINs. Because all of these cases of additional BINs are unique, i.e. none shares its sequence with any other neuropterid species; all species in this category can be unambiguously identified. However, specimens of these species assigned to different BINs should be carefully checked for differences in morphological characters and for divergence in other marker genes to establish if they are cases of cryptic or sibling species.

Raphidioptera (Inocellidae, Raphidiidae)

We obtained barcode sequences for 5 of the 8 species of Raphidiidae and one sequence for the only species of Inocellidae known from Bavaria [5]. All species of Inocellidae and Raphidiidae cluster together in a single clade, but the six species show a high mean interspecific divergence of 15.26%.

Megaloptera (Sialidae)

We obtained barcodes for three of the four species of Sialidae [6]. These species were clearly separated and the mean intraspecific divergence in S. lutaria (Linnaeus, 1758) was low (0.08%).

Coniopterygidae

We analyzed 14 of the 16 species of Coniopterygidae reported from Bavaria [15]. High intraspecific variation (>2%) was found in three species, cases that likely represent instances of overlooked species. Specimens of Coniopteryx pygmaea Enderlein, 1906 (n = 9) were assigned to three BINs (BOLD:AAU4143, BOLD:AAV8087 and BOLD:ACJ9303) with minimum pairwise distances ranging from 13.66–14.83%. Two barcode clusters were detected for both Conwentzia psociformis (Curtis, 1834) (n = 4) (BOLD:ACF6246, BOLD:ACJ9308) with a minimum distance of 13.28% and Semidalis aleyrodiformis (Stephens, 1836) (n = 7) (BOLD:AAU2412, BOLD:AAU2413) with a minimum distances of 3.77%. Two species of Coniopteryx (C. esbenpeterseni Tjeder, 1930, C. lentiae Aspöck & Aspöck, 1964) were assigned to the same BIN (BOLD:AAU4414), but possessed a pairwise distance of 1.16%, allowing their identification.

Chrysopidae

COI barcode sequences were obtained for 25 of the 28 chrysopid species reported from Bavaria [7]. No cases of high intraspecific divergence were detected using barcode gap analysis. Three species (C. lucasina Lacroix, 1912, C. pallida Henry et al., 2002, C. carnea Stephens, 1836) in the Chrysoperla carnea group were assigned to the same BIN (BOLD:AAB0373). The first two species have very similar barcode sequences with only 0.27% of mean distance between them. C. carnea showed a minimum distance of 0.76% from the other two species, allowing its diagnosis. The taxonomy of the C. carnea group has recently been reviewed by Henry et al. [16]. Although more than 20 species can be clearly identified by their duetting behavior, separation based on 4630 bp combined mitochondrial DNA sequences from ND2, COI, COII and ND5 was not possible [17]. Thus, speciation seems to be driven by strong premating isolation within this group [17].

Hemerobiidae

We obtained barcode sequences from 27 of the 36 hemerobiid species reported from Bavaria [7]. Barcode gap analysis on BOLD revealed three pairs of sister species which were assigned to the same BIN: Hemerobius handschini Tjeder, 1957 and H. nitidulus Fabricius, 1777 (BOLD:ABU9615), Wesmaelius concinnus (Stephens, 1836) and W. quadrifasciatus (Reuter, 1894) (BOLD:ABU9030) and Hemerobius atrifrons McLachlan, 1868 and H. contumax Tjeder, 1932 (BOLD:ACF6575). H. handschini and H. nitidulus may be diagnosed by barcodes, but this needs confirmation as the present analysis revealed just a single diagnostic difference (0.15% divergence). These species, together with H. schedlii are closely related and their validity has been questioned by Aspöck et al. [12] considering the high variability of morphological characters. No interspecific divergence was detected for the other two species pairs W. concinnus/W. quadrifasciatus and H. atrifrons/H. contumax. The members of these two species pairs generally show morphological differences [12], but Monserrat [18] noted problems in the discrimination of H.atrifrons and H. contumax. Additional genetic data should be obtained to validate the status of these taxa.

COI data suggest that within the genus Sympherobius Banks, 1904 the subgenera Sympherobius s.str Banks, 1904 (S. pygmaeus (Rambur, 1842), S. elegans (Stephens, 1836)) and Niremberge Navas 1909 (S. fuscescens (Wallengren, 1863), S. pellucidus (Walker, 1853), and S. klapaleki Zeleny, 1963) are not closely related to each other (cf. Neighbor Joining Tree, Fig. S2, but this needs to be corroborated with additional marker genes. S. pygmaeus (n = 3) splits into two BINs (BOLD:ACF9381, BOLD:ACG0292) with a minimum distances of 3.12%, suggesting that it may be a sibling species pair.

Sisyridae, Osmylidae, Myrmeleontidae and Ascalaphidae

We obtained COI sequences for 2 of 3 species of Sisyridae from Bavaria [7]. DNA barcode analysis revealed that Sisyra nigra (Retzius, 1783) (n = 3) includes two BINs (BOLD:AAU3596, BOLD:ACE8429) with a minimum distances of 2.65%. For the remaining families of Neuropterida, the analysis did not recover any case of barcode sharing or potential cryptic diversity. We obtained barcode sequences for the only species of Osmylidae species, for all four species of Myrmelontidae and for one of the two species of Ascalaphidae.

Concluding Remarks

Except for a few cases of BIN sharing and other cases of deep divergence that may reflect cryptic diversity, the present COI barcode data allow unambiguous identification of 75/83 (90%) of the species of Bavarian Neuropterida species which were examined. Furthermore, one or more of the four species pairs that could not be separated may represent cases of unrecognized synonymy. Interestingly, the interspecific distances (to the nearest neighbours) within the Chrysopidae were considerably lower (5–10%) than those in the Coniopterygidae, Hemerobiidae, and Myrmeleontidae (10–20%).

The success rate (83%) in obtaining DNA barcodes was high, especially considering the fact that most specimens were stored under suboptimal conditions. Thus dried specimens of Neuropterida are a suitable source for DNA barcoding as is also the case for Lepidoptera [9], [10], [13], [19], while other groups, such as Coleoptera, are more problematic [20].

Supporting Information

Figure S1.

Taxon ID Tree (established in BOLD) – BIN clusters appear in different colours.

https://doi.org/10.1371/journal.pone.0109719.s001

(PDF)

Figure S2.

Neighbor joining tree of the genus Sympherobius (established in BOLD) – BIN clusters appear in different colours.

https://doi.org/10.1371/journal.pone.0109719.s002

(PDF)

Appendix S1.

List of all specimens used in this study, including BOLD process IDs, BOLD sample IDs and Genbank accession numbers.

https://doi.org/10.1371/journal.pone.0109719.s003

(DOCX)

Acknowledgments

The project was supported by grants from the Bavarian State Government (BFB) and the German Federal Ministry of Education and Research (GBOL2:01LI1101B). We thank our colleagues Dr. Reinhard Müller (Büro für Hydrobiologie, Berlin, Germany), Dieter Doczkal and Dr. Andreas Segerer (both ZSM, Munich, Germany) for providing specimens and Dr. Ernst-Joachim Tröger (Freiburg, Germany) for the identification of some species. We are grateful to the team of Prof. Paul Hebert in Guelph (Ontario, Canada) for their great support and help and particularly to Sujeevan Ratnasingham for developing the BOLD database infrastructure and the BIN management tools. The sequencing work was supported by funding from the Government of Canada to Genome Canada through the Ontario Genomics Institute, while the Ontario Ministry of Research and Innovation and NSERC supported development of the BOLD informatics platform.

Author Contributions

Conceived and designed the experiments: JM LH AH PH GH AG. Performed the experiments: JM LH PH AH. Analyzed the data: JM LH AG. Contributed reagents/materials/analysis tools: AH PH GH. Contributed to the writing of the manuscript: JM LH AH AG PH GH.

References

  1. 1. Aspöck U, Aspöck H (2007) Verbliebene Vielfalt vergangener Blüte. Zur Evolution, Phylogenie und Biodiversität der Neuropterida (Insecta: Endopterygota). Denisia 20, 451–516.
  2. 2. Grimaldi DA, Engel MS (2005) Evolution of the Insects. Cambridge University Press, New York, 2005, 755 p.
  3. 3. Senior LJ, McEwen P (2001) The use of lacewings in biological control. In: McEwen P, New TR & Whittington AE (Eds.): Lacewings in the Crop Environment, 296–302.
  4. 4. Daane KM, Hagen KS (2001) An evalution of lacewing release in North America. In: McEwen P, New TR & Whittington AE (Eds.): Lacewings in the Crop Environment, 398–407.
  5. 5. Saure C (2003a) Verzeichnis der Kamelhalsfliegen (Raphidioptera) Deutschlands. - In: Klausnitzer B (Editor), Entomofauna Germanica 6. Entomologische Nachrichten und Berichte, Beiheft 8: 276–278.
  6. 6. Saure C (2003b) Verzeichnis der Schlammfliegen (Megaloptera) Deutschlands. - In: Klausnitzer B (Editor), Entomofauna Germanica 6. Entomologische Nachrichten und Berichte, Beiheft 8: 279–281.
  7. 7. Saure C (2003c) Verzeichnis der Netzflügler (Neuroptera) Deutschlands. - In: Klausnitzer B (Editor), Entomofauna Germanica 6. Entomologische Nachrichten und Berichte, Beiheft 8: 282–343.
  8. 8. Gruppe A, Hendrich L, Morinière J (2014) Barcoding Fauna Bavarica – Erste Ergebnisse zu den Neuropterida Bayerns. DGaaE-Nachrichten (Accepted).
  9. 9. Hausmann A, Godfray HCJ, Huemer P, Mutanen M, Rougerie R et al.. (2013) Genetic patterns in European geometrid moths revealed by the Barcode Index Number (BIN) system. PLoS ONE 10.1371/journal.pone.0084518.
  10. 10. Hausmann A, Hendrich L, Balke M, Morinière J, Schmidt S et al.. (2013) A major contribution of the ZSM to the genetic library of life: 35.000 insect species barcoded in 7 years. - In: Kroh A, Berning B, Haring E, Harzhauser M, Sattmann H, Walochnik J, Zimmermann D & Zuschin D (Eds.). BioSyst.EU 2013 Global systematics! 18–22 February 2013. Abstract Volume NOBIS Austria, Vienna, 279 pp.
  11. 11. Voith J (2003) Grundlagen und Bilanzen zur Roten Liste gefährdeter Tiere Bayerns. In: Schriftenreihe Bayerisches Landesamt für Umweltschutz 116: 11–24.
  12. 12. Aspöck H, Aspöck U, Hölzel H (1980) Die Neuropteren Europas. Eine zusammenfassende Darstellung der Systematik, Ökologie und Chorologie der Neuropteroidea Megaloptera, Raphidioptera, Planipennia). Europas. 2 volumes, Goecke & Evers, Krefeld. 495 p. & 355 p.
  13. 13. Hebert PDN, Cywinska A, Ball SL, deWaard JR (2003) Biological identifications through DNA barcodes. Proceedings, Biological sciences/The Royal Society, 270(1251), 313–321, DOI:10.1098/rsbp.2002.2218.
  14. 14. Ratnasingham S, Hebert PDN (2013) A DNA-based registry for all animal species: The Barcode Index Number (BIN) System. PLOS ONE 8(8): e66213 Doi:10.1371/journal.pone.0066213.
  15. 15. Gruppe A, Zehetmair T (2011) Nachweise von Staubhaften in Bayern (Insecta: Neuropterida: Coniopterygidae). Beiträge zur Bayerischen Entomofaunistik 11, 39–48.
  16. 16. Henry CS, Brooks SJ, Duelli P, Johnson JB, Wells MLM et al.. (2012) Parallel evolution in courtship songs of North American and European green lacewings (Neuroptera: Chrysopidae). Biological Journal of the Linnaean Society 105, 776–796.
  17. 17. Henry CS, Brooks SJ, Duelli P, Johnson JB, Wells MM et al.. (2013) Obligatory duetting behavior in the Chrysoperla carnea-group of cryptic species (Neuroptera: Chrysopidae): its role in shaping evolutionary history. Biol. Rev., 88, 787–808.
  18. 18. Monserrat VJ (2000) New data on the Brown Lacewings from Asia (Neuroptera: Hemerobiidae). Journal of Neuropterology 3: 61–97.
  19. 19. Hebert PDN, deWaard J & Landry JF (2010) DNA barcodes for 1/1000 of the animal kingdom. Biol Letters 6, 359–362.
  20. 20. Hendrich L, Morinière J, Haszprunar G, Hebert PDN, Hausmann A et al. (submitted) A comprehensive DNA barcode database for Central European beetles: Adding more than 3,500 identified species to BOLD.