TRIDENT (Taxonomic Resolution and IDentification using Environmental dNa Traces): An Optimized Algorithm for Vertebrate Taxonomic Assignments in eDNA Metabarcoding, Integrating Molecular, Taxonomic, and Ecological Criteria
Abstract
Environmental DNA (eDNA) metabarcoding has become a powerful approach for large-scale biodiversity assessment, yet taxonomic assignment remains one of its most critical error-prone steps. Current bioinformatic pipelines rely on molecular similarity searches against reference databases, but assignment accuracy is constrained not only by short marker length and database incompleteness, but also by fundamental limitations, including recent species radiations, incomplete lineage sorting, introgression, NUMTs, and the imperfect correspondence between genetic variation and species boundaries. Here, we present TRIDENT (Taxonomic Resolution and IDentification using Environmental dNa Traces), an automated and simple protocol designed to improve taxonomic assignments in eDNA metabarcoding. Initially developed for marine vertebrates, TRIDENT may be used with any barcode and integrates three complementary sources of evidence: molecular similarity (NCBI/GenBank and BOLD), curated taxonomic information (WoRMS), and ecological plausibility derived from biogeographic occurrence data (GBIF). The workflow sequentially constructs candidate taxon lists based on sequence similarity, expands them through taxonomic hierarchies, and filters them using spatial occurrence constraints. It further identifies possible taxa lacking reference barcodes and evaluates their plausibility through CO1-based similarity if data exist in BOLD. TRIDENT has been implemented as a source-available Python tool and tested using empirical eDNA datasets from marine vertebrates as well as simulated communities. Results demonstrate that the tool produces taxonomic assignments consistent with expert manual curation while substantially reducing processing time and attention errors caused by manual processing of large datasets. By combining molecular, taxonomic, and ecological criteria within a single framework, TRIDENT improves transparency and reproducibility and provides a robust and flexible solution strengthening confidence in taxonomic identifications in eDNA-based biodiversity assessments.
Related
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BibTeX
@misc{haderle2026trident,
title = {{TRIDENT (Taxonomic Resolution and IDentification using Environmental dNa Traces): An Optimized Algorithm for Vertebrate Taxonomic Assignments in eDNA Metabarcoding, Integrating Molecular, Taxonomic, and Ecological Criteria}},
author = {Rachel Haderlé and Gabriel Jung and Manon Riou and Visotheary Ung and Jean-Luc Jung},
howpublished = {HAL},
year = {2026},
month = jun,
doi = {10.64898/2026.06.29.735257},
url = {https://hal.science/hal-05842292v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - TRIDENT (Taxonomic Resolution and IDentification using Environmental dNa Traces): An Optimized Algorithm for Vertebrate Taxonomic Assignments in eDNA Metabarcoding, Integrating Molecular, Taxonomic, and Ecological Criteria
AU - Rachel Haderlé
AU - Gabriel Jung
AU - Manon Riou
AU - Visotheary Ung
AU - Jean-Luc Jung
PY - 2026
DA - 2026/06/30
PB - HAL
DO - 10.64898/2026.06.29.735257
UR - https://hal.science/hal-05842292v1
AB - Environmental DNA (eDNA) metabarcoding has become a powerful approach for large-scale biodiversity assessment, yet taxonomic assignment remains one of its most critical error-prone steps. Current bioinformatic pipelines rely on molecular similarity searches against reference databases, but assignment accuracy is constrained not only by short marker length and database incompleteness, but also by fundamental limitations, including recent species radiations, incomplete lineage sorting, introgression, NUMTs, and the imperfect correspondence between genetic variation and species boundaries. Here, we present TRIDENT (Taxonomic Resolution and IDentification using Environmental dNa Traces), an automated and simple protocol designed to improve taxonomic assignments in eDNA metabarcoding. Initially developed for marine vertebrates, TRIDENT may be used with any barcode and integrates three complementary sources of evidence: molecular similarity (NCBI/GenBank and BOLD), curated taxonomic information (WoRMS), and ecological plausibility derived from biogeographic occurrence data (GBIF). The workflow sequentially constructs candidate taxon lists based on sequence similarity, expands them through taxonomic hierarchies, and filters them using spatial occurrence constraints. It further identifies possible taxa lacking reference barcodes and evaluates their plausibility through CO1-based similarity if data exist in BOLD. TRIDENT has been implemented as a source-available Python tool and tested using empirical eDNA datasets from marine vertebrates as well as simulated communities. Results demonstrate that the tool produces taxonomic assignments consistent with expert manual curation while substantially reducing processing time and attention errors caused by manual processing of large datasets. By combining molecular, taxonomic, and ecological criteria within a single framework, TRIDENT improves transparency and reproducibility and provides a robust and flexible solution strengthening confidence in taxonomic identifications in eDNA-based biodiversity assessments.
ER -