The nuclear ribosomal DNA Internal Transcribed Spacer (ITS) region is used as a universal fungal barcode marker, but often lacks a significant DNA barcoding gap between sister taxa. Here we tested the reliability of protein coding low-copy genes as alternative barcode markers. Mock communities of three unrelated agaric genera (Dermoloma, Hodophilus, and Russula) representing lineages of closely related species were sequenced by the Illumina platform targeting the ITS1, ITS2, the second largest subunit of RNA polymerase II gene (rpb2) and the transcription elongation factor 1-alpha gene (ef1-α) regions. Species representation and their relative abundances were similar across all tested barcode regions, despite a lower copy number in protein coding markers. ITS1 and ITS2 required more sophisticated sequence filtering because they produced a high number of chimeric sequences requiring reference-based chimera removal and had a higher number of sequence variants per species. Although clustering of filtered ITS sequences resulted in an average higher number of correctly clustered units at optimal similarity thresholds, these thresholds varied substantially among genera. Best-fitted thresholds of low-copy markers were more consistent across genera but frequently lacked species resolution due to low intraspecific variability. At some thresholds, we observed multiple species lumped together, and at the same time, species split into multiple partial clusters, which should be taken into consideration when assessing the best clustering thresholds and taxonomic identity of clusters. To achieve the best taxonomic resolution and improve species detection, we recommend combining different markers and applying additional reference-based sorting of clusters. The current availability of rpb2 and ef1-α reference sequences in public databases is far from being complete for all fungal groups, but a combined marker approach can be used for group-specific studies that can build reference data for their own purposes.

• Klíčová slova
• amplicon abundance, chimera, sympatric species, threshold,
• Publikační typ
• časopisecké články MeSH

DNA metabarcoding provides a scalable alternative to traditional botanical surveys, which are often time-consuming and reliant on taxonomic expertise. Here, we compare DNA metabarcoding with quadrat-based botanical surveys to assess plant species composition in experimental grassland plots under four defoliation regimes (continuous grazing, rotational grazing, frequent cutting and conservation cutting). Botanical surveys identified 16 taxa, while metabarcoding detected 25 taxa, including the dominant species Holcus lanatus and Lolium perenne. Despite detecting more taxa, there were some discrepancies in identification, with the sequence data only able to resolve some taxa at the genus level (e.g., Agrostis spp. instead of Agrostis capillaris) and potential species misidentifications (e.g., Cardaminopsis helleri vs. Cardamine flexuosa). However, both methods provided comparable results and revealed statistically significant differences in species composition between treatments, with higher diversity in cut versus grazed plots. The semi-quantitative nature of metabarcoding limits its capacity to accurately reflect species abundance, posing challenges for ecological interpretations where precise quantification is required. However, it provides a broader view of biodiversity and can complement traditional methods, offering new opportunities for efficient biodiversity monitoring. The findings support the integration of DNA metabarcoding into biodiversity assessments, particularly when used alongside traditional techniques. Further refinement of bioinformatics tools and reference databases will enhance their accuracy and reliability, enabling more effective monitoring of grassland biodiversity and sustainable management practices. This study highlights DNA metabarcoding as a valuable tool for understanding plant community responses to management interventions.

• Klíčová slova
• DNA metabarcoding, botanical survey, ecological monitoring, grassland biodiversity, species composition,
• Publikační typ
• časopisecké články MeSH