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Disentangling bias for non-destructive insect metabarcoding

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 metabarco...

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Detalles Bibliográficos
Autores principales: Martoni, Francesco, Piper, Alexander M., Rodoni, Brendan C., Blacket, Mark J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8881911/
https://www.ncbi.nlm.nih.gov/pubmed/35228909
http://dx.doi.org/10.7717/peerj.12981
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author Martoni, Francesco
Piper, Alexander M.
Rodoni, Brendan C.
Blacket, Mark J.
author_facet Martoni, Francesco
Piper, Alexander M.
Rodoni, Brendan C.
Blacket, Mark J.
author_sort Martoni, Francesco
collection PubMed
description 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.
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spelling pubmed-88819112022-02-27 Disentangling bias for non-destructive insect metabarcoding Martoni, Francesco Piper, Alexander M. Rodoni, Brendan C. Blacket, Mark J. PeerJ Bioinformatics 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. PeerJ Inc. 2022-02-23 /pmc/articles/PMC8881911/ /pubmed/35228909 http://dx.doi.org/10.7717/peerj.12981 Text en © 2022 Martoni et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Martoni, Francesco
Piper, Alexander M.
Rodoni, Brendan C.
Blacket, Mark J.
Disentangling bias for non-destructive insect metabarcoding
title Disentangling bias for non-destructive insect metabarcoding
title_full Disentangling bias for non-destructive insect metabarcoding
title_fullStr Disentangling bias for non-destructive insect metabarcoding
title_full_unstemmed Disentangling bias for non-destructive insect metabarcoding
title_short Disentangling bias for non-destructive insect metabarcoding
title_sort disentangling bias for non-destructive insect metabarcoding
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8881911/
https://www.ncbi.nlm.nih.gov/pubmed/35228909
http://dx.doi.org/10.7717/peerj.12981
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