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To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography

BACKGROUND: The recent blooming of metabarcoding applications to biodiversity studies comes with some relevant methodological debates. One such issue concerns the treatment of reads by denoising or by clustering methods, which have been wrongly presented as alternatives. It has also been suggested t...

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Autores principales: Antich, Adrià, Palacin, Creu, Wangensteen, Owen S., Turon, Xavier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8020537/
https://www.ncbi.nlm.nih.gov/pubmed/33820526
http://dx.doi.org/10.1186/s12859-021-04115-6
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author Antich, Adrià
Palacin, Creu
Wangensteen, Owen S.
Turon, Xavier
author_facet Antich, Adrià
Palacin, Creu
Wangensteen, Owen S.
Turon, Xavier
author_sort Antich, Adrià
collection PubMed
description BACKGROUND: The recent blooming of metabarcoding applications to biodiversity studies comes with some relevant methodological debates. One such issue concerns the treatment of reads by denoising or by clustering methods, which have been wrongly presented as alternatives. It has also been suggested that denoised sequence variants should replace clusters as the basic unit of metabarcoding analyses, missing the fact that sequence clusters are a proxy for species-level entities, the basic unit in biodiversity studies. We argue here that methods developed and tested for ribosomal markers have been uncritically applied to highly variable markers such as cytochrome oxidase I (COI) without conceptual or operational (e.g., parameter setting) adjustment. COI has a naturally high intraspecies variability that should be assessed and reported, as it is a source of highly valuable information. We contend that denoising and clustering are not alternatives. Rather, they are complementary and both should be used together in COI metabarcoding pipelines. RESULTS: Using a COI dataset from benthic marine communities, we compared two denoising procedures (based on the UNOISE3 and the DADA2 algorithms), set suitable parameters for denoising and clustering, and applied these steps in different orders. Our results indicated that the UNOISE3 algorithm preserved a higher intra-cluster variability. We introduce the program DnoisE to implement the UNOISE3 algorithm taking into account the natural variability (measured as entropy) of each codon position in protein-coding genes.  This correction increased the number of sequences retained by 88%. The order of the steps (denoising and clustering) had little influence on the final outcome. CONCLUSIONS: We highlight the need for combining denoising and clustering, with adequate choice of stringency parameters, in COI metabarcoding. We present a program that uses the coding properties of this marker to improve the denoising step. We recommend researchers to report their results in terms of both denoised sequences (a proxy for haplotypes) and clusters formed (a proxy for species), and to avoid collapsing the sequences of the latter into a single representative. This will allow studies at the cluster (ideally equating species-level diversity) and at the intra-cluster level, and will ease additivity and comparability between studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04115-6.
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spelling pubmed-80205372021-04-07 To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography Antich, Adrià Palacin, Creu Wangensteen, Owen S. Turon, Xavier BMC Bioinformatics Research Article BACKGROUND: The recent blooming of metabarcoding applications to biodiversity studies comes with some relevant methodological debates. One such issue concerns the treatment of reads by denoising or by clustering methods, which have been wrongly presented as alternatives. It has also been suggested that denoised sequence variants should replace clusters as the basic unit of metabarcoding analyses, missing the fact that sequence clusters are a proxy for species-level entities, the basic unit in biodiversity studies. We argue here that methods developed and tested for ribosomal markers have been uncritically applied to highly variable markers such as cytochrome oxidase I (COI) without conceptual or operational (e.g., parameter setting) adjustment. COI has a naturally high intraspecies variability that should be assessed and reported, as it is a source of highly valuable information. We contend that denoising and clustering are not alternatives. Rather, they are complementary and both should be used together in COI metabarcoding pipelines. RESULTS: Using a COI dataset from benthic marine communities, we compared two denoising procedures (based on the UNOISE3 and the DADA2 algorithms), set suitable parameters for denoising and clustering, and applied these steps in different orders. Our results indicated that the UNOISE3 algorithm preserved a higher intra-cluster variability. We introduce the program DnoisE to implement the UNOISE3 algorithm taking into account the natural variability (measured as entropy) of each codon position in protein-coding genes.  This correction increased the number of sequences retained by 88%. The order of the steps (denoising and clustering) had little influence on the final outcome. CONCLUSIONS: We highlight the need for combining denoising and clustering, with adequate choice of stringency parameters, in COI metabarcoding. We present a program that uses the coding properties of this marker to improve the denoising step. We recommend researchers to report their results in terms of both denoised sequences (a proxy for haplotypes) and clusters formed (a proxy for species), and to avoid collapsing the sequences of the latter into a single representative. This will allow studies at the cluster (ideally equating species-level diversity) and at the intra-cluster level, and will ease additivity and comparability between studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04115-6. BioMed Central 2021-04-05 /pmc/articles/PMC8020537/ /pubmed/33820526 http://dx.doi.org/10.1186/s12859-021-04115-6 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, 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. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Antich, Adrià
Palacin, Creu
Wangensteen, Owen S.
Turon, Xavier
To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography
title To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography
title_full To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography
title_fullStr To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography
title_full_unstemmed To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography
title_short To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography
title_sort to denoise or to cluster, that is not the question: optimizing pipelines for coi metabarcoding and metaphylogeography
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8020537/
https://www.ncbi.nlm.nih.gov/pubmed/33820526
http://dx.doi.org/10.1186/s12859-021-04115-6
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