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Identifying archived insect bulk samples using DNA metabarcoding: A case study using the long-term Rothamsted Insect Survey

Lookup NU author(s): Dr Dimitrios Petsopoulos, Dr Jordan CuffORCiD, Dr James Kitson, Professor Neil Boonham, Professor Darren Evans



This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


© 2024 The Authors. Environmental DNA published by John Wiley & Sons Ltd.Insect populations are declining in many parts of the world, but a lack of long-term monitoring data is impeding our ability to understand and mitigate the causes of insect biodiversity loss. Whilst high-throughput sequencing (HTS) approaches, such as DNA metabarcoding, have the potential to revolutionize insect biomonitoring through rapid scalable identification, it is unclear to what extent HTS can be applied to long-term stored insect samples. Archived insect samples could inform forecasting and provide valuable information regarding past changes to biodiversity. Here, we assess the efficacy of DNA metabarcoding to identify archived samples from the longest passive monitoring scheme in the United Kingdom: the Rothamsted Insect Survey (RIS). With a focus on aphids as the target taxa of a national network of suction-traps, we analyze a 16-year time-series of stored samples (2003–2018) using DNA metabarcoding from one of the RIS suction traps as an exemplar. We achieved this by using a non-destructive DNA extraction protocol, ensuring the integrity of archival samples for further studies. We compared the identities of aphids determined by both metabarcoding (as inferred amplicon sequence variants [ASVs]) and morphological identification and found that metabarcoding detected most genera with varying success (mean > 76%). When comparing the two methods objectively (i.e., including taxa not detected morphologically), however, congruence decreased (51%). We show that minimum sequence copy thresholds can minimize metabarcoding false positives, but at the expense of introducing false negatives, highlighting the need for careful data curation. Detectability of taxa identified morphologically and similarity between the two methods did not significantly vary over time, demonstrating the viability of metabarcoding for screening archival samples. We discuss the advantages and challenges of metabarcoding for insect biomonitoring, particularly from archival samples, including improvements to sample handling, processing, and archiving. We highlight the wider potential of HTS approaches for stored samples from insect monitoring schemes, unlocking the immense potential of global historical time series.

Publication metadata

Author(s): Petsopoulos D, Cuff JP, Bell JR, Kitson JJN, Collins L, Boonham N, Morales-Hojas R, Evans DM

Publication type: Article

Publication status: Published

Journal: Environmental DNA

Year: 2024

Volume: 6

Issue: 3

Print publication date: 01/05/2024

Online publication date: 04/05/2024

Acceptance date: 20/03/2024

Date deposited: 14/05/2024

ISSN (electronic): 2637-4943

Publisher: John Wiley and Sons Inc


DOI: 10.1002/edn3.542


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Funder referenceFunder name
Biotechnology and Biological Sciences Research Council
Institute for Agri-Food Research and Innovation at Newcastle University