A fast and reliable method for obtaining a species-level identification is a fundamental requirement for a wide range of activities, from plant protection and invasive species management to biodiversity assessments and ecological studies. For insects, novel molecular techniques such as DNA metabarcoding have emerged as a rapid alternative to traditional morphological identification, reducing the dependence on limited taxonomic experts. Until recently, molecular techniques have required a destructive DNA extraction, precluding the possibility of preserving voucher specimens for future studies, or species descriptions. Here we paired insect metabarcoding with two recent non-destructive DNA extraction protocols, to obtain a rapid and high-throughput taxonomic identification of diverse insect taxa while retaining a physical voucher specimen. The aim of this work was to explore how non-destructive extraction protocols impact the semi-quantitative nature of metabarcoding, which alongside species presence/absence also provides a quantitative, but biased, representation of their relative abundances. By using a series of mock communities representing each stage of a typical metabarcoding workflow we were able to determine how different morphological (i.e., insect biomass and exoskeleton hardness) and molecular traits (i.e., primer mismatch and amplicon GC%), interact with different protocol steps to introduce quantitative bias into non-destructive metabarcoding results. We discuss the relevance of taxonomic bias to metabarcoding identification of insects and potential approaches to account for it.
Funding
This work was supported by the iMapPESTS project, supported by Horticulture Innovation Australia (ST16010) through funding from the Australian Government Department of Agriculture as part of its Rural R&D for Profit program and Grains Research and Development Corporation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
History
Publication Date
2022-02-23
Journal
PeerJ
Volume
10
Article Number
e12981
Pagination
23p.
Publisher
PeerJ
ISSN
2167-8359
Rights Statement
Copyright 2022 Martoni et al. Distributed under a Creative Commons CC-BY 4.0 license (https://creativecommons.org/licenses/by/4.0/) which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.