Maximizing Identification Precision of Hymenoptera and Brachycera (Diptera) With a Non-Destructive DNA Metabarcoding Approach.

ABSTRACT: In recent years, DNA metabarcoding has been used for a more efficient assessment of bulk samples. However, there remains a paucity of studies examining potential disparities in species identification methodologies. Here, we explore the outcomes of diverse clustering and filtering techniques on data from a non-destructive metabarcoding approach, compared to species-level morphological identification of Brachycera (Diptera) and Hymenoptera of two bulk samples collected with Malaise traps. The study evaluated four distinct approaches, namely clustering to Amplicon Sequence Variants (ASVs) or ASVs clustered to Operational Taxonomic Units (OTUs) coupled with subsequent filtering using the LULU algorithm at 84% and 96% minimum match. In total, 114 species of Brachycera (35 families) and 85 speci

SUBMITTER: Kilian IC 

PROVIDER: S-EPMC11756930 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature