A reference library for Canadian invertebrates with 1.5 million barcodes, voucher specimens, and DNA samples

The synthesis of this dataset was enabled by funding from the Canada Foundation for Innovation, from Genome Canada through Ontario Genomics, from NSERC, and from the Ontario Ministry of Research, Innovation and Science in support of the International Barcode of Life project. It was also enabled by philanthropic support from the Gordon and Betty Moore Foundation and from Ann McCain Evans and Chris Evans. The release of the data on GGBN was supported by a GGBN – Global Genome Initiative Award and we thank G. Droege, L. Loo, K. Barker, and J. Coddington for their support. Our work depended heavily on the analytical capabilities of the Barcode of Life Data Systems (BOLD, www.boldsystems.org). We also thank colleagues at the CBG for their support, including S. Adamowicz, S. Bateson, E. Berzitis, V. Breton, V. Campbell, A. Castillo, C. Christopoulos, J. Cossey, C. Gallant, J. Gleason, R. Gwiazdowski, M. Hajibabaei, R. Hanner, K. Hough, P. Janetta, A. Pawlowski, S. Pedersen, J. Robertson, D. Roes, K. Seidle, M. A. Smith, B. St. Jacques, A. Stoneham, J. Stahlhut, R. Tabone, J.Topan, S. Walker, and C. Wei. For bioblitz-related assistance, we are grateful to D. Ireland, D. Metsger, A. Guidotti, J. Quinn and other members of Bioblitz Canada and Ontario Bioblitz. For our work in Canada’s national parks, we thank S. Woodley and J. Waithaka for their lead role in organizing permits and for the many Parks Canada staff who facilitated specimen collections, including M. Allen, D. Amirault-Langlais, J. Bastick, C. Belanger, C. Bergman, J.-F. Bisaillon, S. Boyle, J. Bridgland, S. Butland, L. Cabrera, R. Chapman, J. Chisholm, B. Chruszcz, D. Crossland, H. Dempsey, N. Denommee, T. Dobbie, C. Drake, J. Feltham, A. Forshner, K. Forster, S. Frey, L. Gardiner, P. Giroux, T. Golumbia, D. Guedo, N. Guujaaw, S. Hairsine, E. Hansen, C. Harpur, S. Hayes, J. Hofman, S. Irwin, B. Johnston, V. Kafa, N. Kang, P. Langan, P. Lawn, M. Mahy, D. Masse, D. Mazerolle, C. McCarthy, I. McDonald, J. McIntosh, C. McKillop, V. Minelga, C. Ouimet, S. Parker, N. Perry, J. Piccin, A. Promaine, P. Roy, M. Savoie, D. Sigouin, P. Sinkins, R. Sissons, C. Smith, R. Smith, H. Stewart, G. Sundbo, D. Tate, R. Tompson, E. Tremblay, Y. Troutet, K. Tulk, J. Van Wieren, C. Vance, G. Walker, D. Whitaker, C. White, R. Wissink, C. Wong, and Y. Zharikov. For our work near Canada’s ports in Vancouver, Toronto, Montreal, and Halifax, we thank R. Worcester, A. Chreston, M. Larrivee, and T. Zemlak, respectively. Many other organizations improved coverage in the reference library by providing access to specimens – they included the Canadian National Collection of Insects, Arachnids and Nematodes, Smithsonian Institution’s National Museum of Natural History, the Canadian Museum of Nature, the University of Guelph Insect Collection, the Royal British Columbia Museum, the Royal Ontario Museum, the Pacifc Forestry Centre, the Northern Forestry Centre, the Lyman Entomological Museum, the Churchill Northern Studies Centre, and rare Charitable Research Reserve. We also thank the many taxonomic specialists who identifed specimens, including A. Borkent, B. Brown, M. Buck, C. Carr, T. Ekrem, J. Fernandez Triana, C. Guppy, K. Heller, J. Huber, L. Jacobus, J. Kjaerandsen, J. Klimaszewski, D. Lafontaine, J-F. Landry, G. Martin, A. Nicolai, D. Porco, H. Proctor, D. Quicke, J. Savage, B. C. Schmidt, M. Sharkey, A. Smith, E. Stur, A. Tomas, J. Webb, N. Woodley, and X. Zhou. We also thank K. Kerr and T. Mason for facilitating collections at Toronto Zoo and D. Iles for servicing the trap at Wapusk National Park. This paper contributes to the University of Guelph’s Food from Thought research program supported by the Canada First Research Excellence Fund. The Barcode of Life Data System (BOLD; www.boldsystems.org)8 was used as the primary workbench for creating, storing, analyzing, and validating the specimen and sequence records and the associated data resources48. The BOLD platform has a private, password-protected workbench for the steps from specimen data entry to data validation (see details in Data Records), and a public data portal for the release of data in various formats. The latter is accessible through an API (http://www.boldsystems.org/index.php/resources/api?type=webservices) that can also be controlled through R75 with the package ‘bold’76.Peer reviewedPublisher PD

A molecular-based identification resource for the arthropods of Finland

Publisher Copyright: © 2021 The Authors. Molecular Ecology Resources published by John Wiley & Sons Ltd.To associate specimens identified by molecular characters to other biological knowledge, we need reference sequences annotated by Linnaean taxonomy. In this study, we (1) report the creation of a comprehensive reference library of DNA barcodes for the arthropods of an entire country (Finland), (2) publish this library, and (3) deliver a new identification tool for insects and spiders, as based on this resource. The reference library contains mtDNA COI barcodes for 11,275 (43%) of 26,437 arthropod species known from Finland, including 10,811 (45%) of 23,956 insect species. To quantify the improvement in identification accuracy enabled by the current reference library, we ran 1000 Finnish insect and spider species through the Barcode of Life Data system (BOLD) identification engine. Of these, 91% were correctly assigned to a unique species when compared to the new reference library alone, 85% were correctly identified when compared to BOLD with the new material included, and 75% with the new material excluded. To capitalize on this resource, we used the new reference material to train a probabilistic taxonomic assignment tool, FinPROTAX, scoring high success. For the full-length barcode region, the accuracy of taxonomic assignments at the level of classes, orders, families, subfamilies, tribes, genera, and species reached 99.9%, 99.9%, 99.8%, 99.7%, 99.4%, 96.8%, and 88.5%, respectively. The FinBOL arthropod reference library and FinPROTAX are available through the Finnish Biodiversity Information Facility (www.laji.fi) at https://laji.fi/en/theme/protax. Overall, the FinBOL investment represents a massive capacity-transfer from the taxonomic community of Finland to all sectors of society.Peer reviewe

Revision of Nearctic Paramyia Williston (Diptera: Milichiidae)

Levesque-Beaudin, Valerie, Mlynarek, Julia J. (2020): Revision of Nearctic Paramyia Williston (Diptera: Milichiidae). Zootaxa 4732 (1): 1-56, DOI: https://doi.org/10.11646/zootaxa.4732.1.

Unravelling bird nest arthropod community structure using metabarcoding

Bird nests are fascinating microcosms harboring a wide range of arthropods parasitizing the nesting birds or feeding on prey remains, feces, and the nest material. Studies of these communities have been entirely based on emergence traps which collect live organisms out of the nests. The analysis of nest contents and environmental DNA (eDNA) via metabarcoding could expand our knowledge and identify prey, exuviae, and other animal remains in bird nests. Here, we investigated the potential of arthropod remains, nest dust, and feathers to better describe arthropod diversity accumulated in 20 bird nests collected in Guelph (Canada). We used subsampling strategies and tested two extraction approaches to investigate the distribution of DNA in nests, account for low-quality DNA, and the presence of inhibitory substances. In total, 103 taxa were detected via metabarcoding. Arthropod remains delivered the highest number of taxa (n = 67), followed by nest dust (n = 29). Extractions with the PowerSoil kit outperformed DNeasy extractions coupled with PowerClean Pro inhibitor removal. Per nest, on average 5.5% taxonomic overlap between arthropod remains of different size classes was detected and subsamples of nest dust extracted with the PowerSoil kit showed 47.3% taxonomic overlap indicating a heterogeneous eDNA distribution in nests. Most detected species were either feeding in the nest, i.e., herbivorous / predatory, or bird food. We also detected molecular traces of 25 bird species, whose feathers were likely used as nest material. Consequently, the metabarcoding of bird nest materials provides a more complete picture of nest communities, which can enable future studies on functional diversity and better comparisons between nesting species

Description of Cabamofa vietnamensis sp. nov., the second species of Cabamofa in mainland southeast Asia (Diptera: Bibionomorpha: Sciaroidea incertae sedis)

Jaschhof, Mathias, Levesque-Beaudin, Valerie, Broadley, Adam, Heller, Kai, Lien, Vu Van, Schmidt, Stefan (2022): Description of Cabamofa vietnamensis sp. nov., the second species of Cabamofa in mainland southeast Asia (Diptera: Bibionomorpha: Sciaroidea incertae sedis). Zootaxa 5182 (3): 297-300, DOI: https://doi.org/10.11646/zootaxa.5182.3.

A DNA Barcoding Survey of an Arctic Arthropod Community: Implications for Future Monitoring

Accurate and cost-effective methods for tracking changes in arthropod communities are needed to develop integrative environmental monitoring programs in the Arctic. To date, even baseline data on their species composition at established ecological monitoring sites are severely lacking. We present the results of a pilot assessment of non-marine arthropod diversity in a middle arctic tundra area near Ikaluktutiak (Cambridge Bay), Victoria Island, Nunavut, undertaken in 2018 using DNA barcodes. A total of 1264 Barcode Index Number (BIN) clusters, used as a proxy for species, were recorded. The efficacy of widely used sampling methods was assessed. Yellow pan traps captured 62% of the entire BIN diversity at the study sites. When complemented with soil and leaf litter sifting, the coverage rose up to 74.6%. Combining community-based data collection with high-throughput DNA barcoding has the potential to overcome many of the logistic, financial, and taxonomic obstacles for large-scale monitoring of the Arctic arthropod fauna

A workflow for expanding DNA barcode reference libraries through ‘museum harvesting’ of natural history collections

Natural history collections are the physical repositories of our knowledge on species, the entities of biodiversity. Making this knowledge accessible to society – through, for example, digitisation or the construction of a validated, global DNA barcode library – is of crucial importance. To this end, we developed and streamlined a workflow for ‘museum harvesting’ of authoritatively identified Diptera specimens from the Smithsonian Institution’s National Museum of Natural History. Our detailed workflow includes both on-site and off-site processing through specimen selection, labelling, imaging, tissue sampling, databasing and DNA barcoding. This approach was tested by harvesting and DNA barcoding 941 voucher specimens, representing 32 families, 819 genera and 695 identified species collected from 100 countries. We recovered 867 sequences (> 0 base pairs) with a sequencing success of 88.8% (727 of 819 sequenced genera gained a barcode > 300 base pairs). While Sanger-based methods were more effective for recently-collected specimens, the methods employing next-generation sequencing recovered barcodes for specimens over a century old. The utility of the newly-generated reference barcodes is demonstrated by the subsequent taxonomic assignment of nearly 5000 specimen records in the Barcode of Life Data Systems

A workflow for expanding DNA barcode reference libraries through ‘museum harvesting’ of natural history collections

Developing an efficient and effective protocol for capturing biological data held in natural history collections is critically important for many emergent projects in biodiversity, such as the construction of a validated, global DNA barcode reference library. To this end, we developed and streamlined a workflow for ‘museum harvesting’ of authoritatively identified Diptera specimens from the Smithsonian National Museum of Natural History (USNM). Our detailed workflow includes both on-site and off-site processing through specimen selection, labeling, imaging, tissue sampling, databasing and DNA barcoding. This approach was tested by harvesting and DNA barcoding 941 voucher specimens, representing 32 families, 819 genera, and 695 identified species collected from 100 countries. We recovered 867 sequences (> 0 base pairs) with a sequencing success of 88.8% (727 of 819 sequenced genera gained a barcode > 300 base pairs). While Sanger-based methods were more effective for recently-collected specimens, the methods employing next-generation sequencing recovered barcodes for specimens over a century old. The utility of the newly generated reference barcodes is demonstrated by the subsequent taxonomic assignment of nearly 5000 specimen records in the Barcode of Life Data System