Post-bioinformatic methods to identify and reduce the prevalence of artefacts in metabarcoding data

Abstract

Metabarcoding provides a powerful tool for investigating biodiversity and trophic interactions, but the high sensitivity of this methodology makes it vulnerable to errors, resulting in artefacts in the final data. Metabarcoding studies thus often utilise minimum sequence copy thresholds (MSCTs) to remove artefacts that remain in datasets; however, there is no consensus on best practice for the use of MSCTs. To mitigate erroneous reporting of results and inconsistencies, this study discusses and provides guidance for best-practice filtering of metabarcoding data for the ascertainment of conservative and accurate data. The most common MSCTs identified in the literature were applied to example datasets of Eurasian otter (Lutra lutra) and cereal crop spider (Araneae: Linyphiidae and Lycosidae) diets. Changes in both the method and threshold value considerably affected the resultant data. Of the MSCTs tested, it was concluded that the optimal method for the examples given combined a sample-based threshold with removal of maximum taxon contamination, providing stringent filtering of artefacts whilst retaining target data. Choice of threshold value differed between datasets due to variation in artefact abundance and sequencing depth, thus studies should employ controls (mock communities, negative controls with no DNA and unused MID-tag combinations) to select threshold values appropriate for each individual study.

Density‐independent prey choice, taxonomy, life history, and web characteristics determine the diet and biocontrol potential of spiders (Linyphiidae and Lycosidae) in cereal crops

“…Library preparation for Illumina sequencing was carried out on the cleaned libraries via NEXTflex Rapid DNA‐Seq Kit (Bioo Scientific, Austin, USA) and samples were sequenced on an Illumina MiSeq via a V3 chip with 300‐bp paired‐end reads (expected capacity ≤25,000,000 reads). Bioinformatic analysis followed (Drake et al 2021); (Appendix S1).…”

Otterly delicious: Spatiotemporal variation in the diet of a recovering population of Eurasian otters (Lutra lutra) revealed throughDNAmetabarcoding and morphological analysis of prey remains

“…Data are available at dryad under two sources. Metabarcoding data, including raw sequence data and data that has been filtered following application of bioinformatic and post‐bioinformatic thresholds, are available at Drake and Cuff (2021). Morphological data alongside Metabarcoding data filtered for dietary analyses can be found at Drake et al (2023).…”

Using multi-marker DNA metabarcoding to reveal the diet of a scarce woodland bird

“…The Illumina run generated 6,328,388 and 12,307,560 ITS2 and COI reads respectively. All reads were checked for truncation, quality checked, filtered and assigned taxonomic identification following Drake et al, (2021). All read counts less than the maximum in unused-MID tag combinations and negative controls for each respective zero radius OTU (zOTU) were removed prior to statistical analysis.…”