While the need for biodiversity research is growing, paradoxically, global taxonomical expertise is decreasing as a result of the neglected funding for young academics in taxonomy. Non-destructive approaches for DNA barcoding are necessary for a more efficient use of this dwindling expertise to fill gaps, and identify incorrect entries in sequence databases like BOLD or GenBank. They are efficient because morphological re-examination of species vouchers is still possible post-DNA barcoding. Non-destructive approaches for Diptera with a comprehensive species representation or the consideration of diagnostic fragile morphological characters are missing. Additionally, most non-destructive approaches combine a time intensive and non-destructive digestion step with common DNA extraction methods, such as commercial kits or CTAB DNA isolation. We circumvented those approaches and combined a modified non-destructive TE buffer high-speed DNA extraction, with a PCR inhibitor-resistant PCR reaction system, to a non-destructive DNA barcoding procedure for fresh and frozen samples of the Schizophora (Diptera). This method avoids morphological impairment and the application of harmful chemicals, is cost and time effective, restricts the need for laboratory equipment to a minimum, and prevents cross-contamination risk during DNA isolation. Moreover, the study indicates that the presented non-destructive DNA barcoding procedure is transferable to other soft-bodied insects. We suggest that PCR inhibitor-resistant master mixes enable the development of new—and the modification of existing—non-destructive approaches with the avoidance of further DNA template cleaning.

The increasing number of Barcode of Life Database (BOLD) records per species and genus leads to contradictory species assignments within Barcode Index Numbers (BINs), serving as identifiers for the BOLD ID engine. To examine these issues, we analyzed a dataset comprising original and curated BOLD records for the genus Tachina (Insecta: Tachinidae), based on a previous publication. This dataset included both published and private records. We were able to assess the performance of the BOLD engine’s species determination algorithm, Refined Single Linkage (RESL), and compare it to Assemble Species by Automatic Partitioning (ASAP). Additionally, we investigated the usage of BINs by the BOLD v4 ID engine. Our analysis confirmed that BOLD queries primarily rely on BINs for species identification, although some cases deviated from this pattern, resulting in species matches inconsistent with the assigned BIN species. ASAP was found to be superior to RESL due to RESL’s adherence to the concept of the DNA barcoding gap. Moreover, we found that taxonomic misassignments, inconsistencies in BIN formation, and missing metadata also contribute significantly to unreliable identifications. These problems appear to stem from both algorithmic limitations and deficiencies in submission and post-submission processes. Moreover, we noted that the default mode of the BOLD v4 ID engine integrates both private and published data, leading to public records based solely on COI-based identifications. However, this issue may now be mitigated, as the BOLD v5 ID engine default mode exclusively employs published data. To enhance BOLD’s reliability, we propose improvements to submission and post-submission processes. Without such amendments, the accumulation of contradictory species assignments within BINs will continue to rise and the reliability of specimen identification by BOLD will decrease.

DNA barcoding is a popular tool for species identification of insect samples, with important applications for plant protection. However, Barcode of Life Database queries related to tachinid samples can produce ambiguous results due to contradictory species assignments. Therefore, we applied Bayesian phylogenetic inference to 811 Tachina Meigen, 1803 COI-5P sequences containing all contradictory species assignments of Tachina Barcode Index Numbers. Based on phylogenetic assignment, the assemble species by automatic partitioning (ASAP) analysis, the MonoPhy test and analyses of genetic divergence, we identified 805 sequences representing species of the Tachina genus, whereas six sequences were incorrectly assigned to Tachina. The dataset contained 21 described species and at least seven unidentified species. Additionally, we found that the described species Tachina marklini Zetterstedt, 1838, includes two cryptic species based on ASAP partitioning of sequences, phylogenetic inference and geographical metadata. Furthermore, we harmonized conflicting subgeneric classifications of the Palearctic and Nearctic by employing different subgenera assignments from both partitions. We aimed at monophyletic subgenera partitions. We largely confirmed the validity of the Palearctic Tachina subgenera and Nowickia as a subgenus of Tachina. However, Palearctic Nowickia species formerly allocated to the outdated genus Fabriciella appeared to constitute one monophyletic group with the subgenus Rhachogaster. We conclude that this set of bioinformatics tools is suitable for curating COI-5P-based DNA barcode libraries. Although, curation is limited due to possible species introgression, horizontal gene transfer, incomplete lineage sorting and human errors the resulting dataset enabled the revision of subgenera concepts and the unambiguous cryptic species detection.