ABSTRACT
DNA metabarcoding was utilized for a large-scale, multiyear assessment of biodiversity in Malaise trap collections from the Bavarian Forest National Park (Germany, Bavaria). Principal component analysis of read count-based biodiversities revealed clustering in concordance with whether collection sites were located inside or outside of the National Park. Jaccard distance matrices of the presences of barcode index numbers (BINs) at collection sites in the two survey years (2016 and 2018) were significantly correlated. Overall similar patterns in the presence of total arthropod BINs, as well as BINs belonging to four major arthropod orders across the study area, were observed in both survey years, and are also comparable with results of a previous study based on DNA barcoding of Sanger-sequenced specimens. A custom reference sequence library was assembled from publicly available data to screen for pest or invasive arthropods among the specimens or from the preservative ethanol. A single 98.6% match to the invasive bark beetle Ips duplicatus was detected in an ethanol sample. This species has not previously been detected in the National Park.
Subject(s)
Arthropods , Biodiversity , DNA Barcoding, Taxonomic , Animals , Arthropods/classification , Germany , Parks, RecreationalABSTRACT
This study summarizes results of a DNA barcoding campaign on German Diptera, involving analysis of 45,040 specimens. The resultant DNA barcode library includes records for 2,453 named species comprising a total of 5,200 barcode index numbers (BINs), including 2,700 COI haplotype clusters without species-level assignment, so called "dark taxa." Overall, 88 out of 117 families (75%) recorded from Germany were covered, representing more than 50% of the 9,544 known species of German Diptera. Until now, most of these families, especially the most diverse, have been taxonomically inaccessible. By contrast, within a few years this study provided an intermediate taxonomic system for half of the German Dipteran fauna, which will provide a useful foundation for subsequent detailed, integrative taxonomic studies. Using DNA extracts derived from bulk collections made by Malaise traps, we further demonstrate that species delineation using BINs and operational taxonomic units (OTUs) constitutes an effective method for biodiversity studies using DNA metabarcoding. As the reference libraries continue to grow, and gaps in the species catalogue are filled, BIN lists assembled by metabarcoding will provide greater taxonomic resolution. The present study has three main goals: (a) to provide a DNA barcode library for 5,200 BINs of Diptera; (b) to demonstrate, based on the example of bulk extractions from a Malaise trap experiment, that DNA barcode clusters, labelled with globally unique identifiers (such as OTUs and/or BINs), provide a pragmatic, accurate solution to the "taxonomic impediment"; and (c) to demonstrate that interim names based on BINs and OTUs obtained through metabarcoding provide an effective method for studies on species-rich groups that are usually neglected in biodiversity research projects because of their unresolved taxonomy.
Subject(s)
Ceratopogonidae/classification , Ceratopogonidae/genetics , Chironomidae/classification , Chironomidae/genetics , DNA Barcoding, Taxonomic , Diptera/classification , Diptera/genetics , Animals , Ecological Parameter Monitoring/methods , GermanyABSTRACT
Throughout the years, DNA barcoding has gained in importance in forensic entomology as it leads to fast and reliable species determination. High-quality results, however, can only be achieved with a comprehensive DNA barcode reference database at hand. In collaboration with the Bavarian State Criminal Police Office, we have initiated at the Bavarian State Collection of Zoology the establishment of a reference library containing arthropods of potential forensic relevance to be used for DNA barcoding applications. CO1-5P' DNA barcode sequences of hundreds of arthropods were obtained via DNA extraction, PCR and Sanger Sequencing, leading to the establishment of a database containing 502 high-quality sequences which provide coverage for 88 arthropod species. Furthermore, we demonstrate an application example of this library using it as a backbone to a high throughput sequencing analysis of arthropod bulk samples collected from human corpses, which enabled the identification of 31 different arthropod Barcode Index Numbers.