A Comprehensive Evaluation of Taxonomic Classifiers in Marine Vertebrate eDNA Studies.

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Autori principali: Bayer, Philipp E, Bennett, Adam, Nester, Georgia, Corrigan, Shannon, Raes, Eric J, Cooper, Madalyn, Ayad, Marcelle E, McVey, Philip, Kardailsky, Anya, Pearce, Jessica, Fraser, Matthew W, Goncalves, Priscila, Burnell, Stephen, Rauschert, Sebastian
Natura: Artículo científico
Lingua:en
Pubblicazione: Molecular ecology resources 2025
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author Bayer, Philipp E
Bennett, Adam
Nester, Georgia
Corrigan, Shannon
Raes, Eric J
Cooper, Madalyn
Ayad, Marcelle E
McVey, Philip
Kardailsky, Anya
Pearce, Jessica
Fraser, Matthew W
Goncalves, Priscila
Burnell, Stephen
Rauschert, Sebastian
author_facet Bayer, Philipp E
Bennett, Adam
Nester, Georgia
Corrigan, Shannon
Raes, Eric J
Cooper, Madalyn
Ayad, Marcelle E
McVey, Philip
Kardailsky, Anya
Pearce, Jessica
Fraser, Matthew W
Goncalves, Priscila
Burnell, Stephen
Rauschert, Sebastian
Bayer, Philipp E
Bennett, Adam
Nester, Georgia
Corrigan, Shannon
Raes, Eric J
Cooper, Madalyn
Ayad, Marcelle E
McVey, Philip
Kardailsky, Anya
Pearce, Jessica
Fraser, Matthew W
Goncalves, Priscila
Burnell, Stephen
Rauschert, Sebastian
collection PubMed - marine biology
contents A Comprehensive Evaluation of Taxonomic Classifiers in Marine Vertebrate eDNA Studies. Bayer, Philipp E Bennett, Adam Nester, Georgia Corrigan, Shannon Raes, Eric J Cooper, Madalyn Ayad, Marcelle E McVey, Philip Kardailsky, Anya Pearce, Jessica Fraser, Matthew W Goncalves, Priscila Burnell, Stephen Rauschert, Sebastian Animals Vertebrates Aquatic Organisms DNA Barcoding, Taxonomic RNA, Ribosomal, 16S DNA, Environmental Computational Biology Australia Metagenomics Biodiversity RNA, Ribosomal Environmental DNA (eDNA) metabarcoding is a widely used tool for surveying marine vertebrate biodiversity. To this end, many computational tools have been released and a plethora of bioinformatic approaches are used for eDNA-based community composition analysis. Simulation studies and careful evaluation of taxonomic classifiers are essential to establish reliable benchmarks to improve the accuracy and reproducibility of eDNA-based findings. Here we present a comprehensive evaluation of nine taxonomic classifiers exploring three widely used mitochondrial markers (12S rDNA, 16S rDNA and COI) in Australian marine vertebrates. Curated reference databases and exclusion database tests were used to simulate diverse species compositions, including three positive control and two negative control datasets. Using these simulated datasets ranging from 36 to 302 marker genes, we were able to identify between 19% and 89% of marine vertebrate species using mitochondrial markers. We show that MMSeqs2 and Metabuli generally outperform BLAST with 10% and 11% higher F1 scores for 12S and 16S rDNA markers, respectively, and that Naive Bayes Classifiers such as Mothur outperform sequence-based classifiers except MMSeqs2 for COI markers by 11%. Database exclusion tests reveal that MMSeqs2 and BLAST are less susceptible to false positives compared to Kraken2 with default parameters. Based on these findings, we recommend that MMSeqs2 is used for taxonomic classification of marine vertebrates given its ability to improve species-level assignments while reducing the number of false positives. Our work contributes to the establishment of best practices in eDNA-based biodiversity analysis to ultimately increase the reliability of this monitoring tool in the context of marine vertebrate conservation.
format Artículo científico
id pubmed_40243260
institution PubMed
language en
publishDate 2025
publisher Molecular ecology resources
record_format pubmed
spellingShingle A Comprehensive Evaluation of Taxonomic Classifiers in Marine Vertebrate eDNA Studies.
Bayer, Philipp E
Bennett, Adam
Nester, Georgia
Corrigan, Shannon
Raes, Eric J
Cooper, Madalyn
Ayad, Marcelle E
McVey, Philip
Kardailsky, Anya
Pearce, Jessica
Fraser, Matthew W
Goncalves, Priscila
Burnell, Stephen
Rauschert, Sebastian
Animals
Vertebrates
Aquatic Organisms
DNA Barcoding, Taxonomic
RNA, Ribosomal, 16S
DNA, Environmental
Computational Biology
Australia
Metagenomics
Biodiversity
RNA, Ribosomal
A Comprehensive Evaluation of Taxonomic Classifiers in Marine Vertebrate eDNA Studies. Bayer, Philipp E Bennett, Adam Nester, Georgia Corrigan, Shannon Raes, Eric J Cooper, Madalyn Ayad, Marcelle E McVey, Philip Kardailsky, Anya Pearce, Jessica Fraser, Matthew W Goncalves, Priscila Burnell, Stephen Rauschert, Sebastian Animals Vertebrates Aquatic Organisms DNA Barcoding, Taxonomic RNA, Ribosomal, 16S DNA, Environmental Computational Biology Australia Metagenomics Biodiversity RNA, Ribosomal Environmental DNA (eDNA) metabarcoding is a widely used tool for surveying marine vertebrate biodiversity. To this end, many computational tools have been released and a plethora of bioinformatic approaches are used for eDNA-based community composition analysis. Simulation studies and careful evaluation of taxonomic classifiers are essential to establish reliable benchmarks to improve the accuracy and reproducibility of eDNA-based findings. Here we present a comprehensive evaluation of nine taxonomic classifiers exploring three widely used mitochondrial markers (12S rDNA, 16S rDNA and COI) in Australian marine vertebrates. Curated reference databases and exclusion database tests were used to simulate diverse species compositions, including three positive control and two negative control datasets. Using these simulated datasets ranging from 36 to 302 marker genes, we were able to identify between 19% and 89% of marine vertebrate species using mitochondrial markers. We show that MMSeqs2 and Metabuli generally outperform BLAST with 10% and 11% higher F1 scores for 12S and 16S rDNA markers, respectively, and that Naive Bayes Classifiers such as Mothur outperform sequence-based classifiers except MMSeqs2 for COI markers by 11%. Database exclusion tests reveal that MMSeqs2 and BLAST are less susceptible to false positives compared to Kraken2 with default parameters. Based on these findings, we recommend that MMSeqs2 is used for taxonomic classification of marine vertebrates given its ability to improve species-level assignments while reducing the number of false positives. Our work contributes to the establishment of best practices in eDNA-based biodiversity analysis to ultimately increase the reliability of this monitoring tool in the context of marine vertebrate conservation.
title A Comprehensive Evaluation of Taxonomic Classifiers in Marine Vertebrate eDNA Studies.
topic Animals
Vertebrates
Aquatic Organisms
DNA Barcoding, Taxonomic
RNA, Ribosomal, 16S
DNA, Environmental
Computational Biology
Australia
Metagenomics
Biodiversity
RNA, Ribosomal
url https://pubmed.ncbi.nlm.nih.gov/40243260/