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◆ Genome2026-08-14

Filling DNA barcode gaps in Central European Auchenorrhyncha: a new reference library and Oxford Nanopore Technologies-based species identification.

Sandra Schallhart, Jacqueline Grimm, Werner E Holzinger, Elisabeth Huber, Nadine Klar, Gernot Kunz, Sylvia Schäffer, Lydia Schlosser, Bettina Thalinger, Stephan Koblmüller

原始摘要(英文原文)· Original abstract
Terrestrial arthropods are declining in most ecosystems, creating a need for efficient and scalable biodiversity monitoring tools. DNA-barcoding enables high-throughput species identification but is constrained by incomplete reference libraries for many taxa. Here, we expand the DNA barcode database for Austrian Auchenorrhyncha by combining morphological identification with Sanger-sequenced COI barcodes. A total of 1 304 specimens representing 394 species were successfully barcoded, resulting in 384 Barcode Index Numbers (BINs), including 73 newly established BINs. Elevated intraspecific COI divergence and BIN discordance in several taxa reveal species complexes and missing barcode gaps. The expanded reference library was applied to Auchenorrhyncha from Malaise trap samples collected at an agricultural lowland and an alpine site and analyzed using a high-throughput Oxford Nanopore Technologies (ONT) workflow. The improved reference library substantially increased assignment success and taxonomic resolution. Finally, we compared the ONT barcoding results from Malaise trap catches with morphology-based identifications from single-event suction sampling. Both approaches detected similar proportions of species, and differences in species composition likely reflect sampling- and method-specific biases. Overall, this study advances the development of a comprehensive DNA barcode reference library for Central European Auchenorrhyncha and underscores the importance of regionally curated databases and complementary approaches for biodiversity assessments.
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Filling DNA barcode gaps in Central European Auchenorrhyncha: a new reference library and Oxford Nanopore Technologies-based species identification. — 科研速览 Science Skim