Assessment of BOLD and GenBank – Their accuracy and reliability for the identification of biological materials

Kelly A. Meiklejohn, Natalie Damaso, James Robertson

PLoS ONE · 2019 · 259 citations · 37 references

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Concepts

TL;DR

DNA barcoding identifies biological materials by comparing unknown sequences to reference databases, and accurate taxonomic identification is essential across disciplines, with BOLD and GenBank serving as the primary public repositories. The study assessed the accuracy and reliability of BOLD and GenBank sequences and outlined the utility of BLAST and the BOLD identification engine while highlighting precautions for using public sequence repositories. The authors curated reference materials for plants, macro‑fungi, and insects, generated barcode sequences (rbcL, matK, trnH‑psbA, ITS, COI), and optimized search parameters to match known species in each database. GenBank achieved higher species‑level identification for insects (53% vs 35% for BOLD), while both databases performed similarly for plants and macro‑fungi (~81% vs ~57%), and a multi‑locus barcode approach further improved identification success.

Abstract

Taxonomic identification of biological materials can be achieved through DNA barcoding, where an unknown "barcode" sequence is compared to a reference database. In many disciplines, obtaining accurate taxonomic identifications can be imperative (e.g., evolutionary biology, food regulatory compliance, forensics). The Barcode of Life DataSystems (BOLD) and GenBank are the main public repositories of DNA barcode sequences. In this study, an assessment of the accuracy and reliability of sequences in these databases was performed. To achieve this, 1) curated reference materials for plants, macro-fungi and insects were obtained from national collections, 2) relevant barcode sequences (rbcL, matK, trnH-psbA, ITS and COI) from these reference samples were generated and used for searching against both databases, and 3) optimal search parameters were determined that ensure the best match to the known species in either database. While GenBank outperformed BOLD for species-level identification of insect taxa (53% and 35%, respectively), both databases performed comparably for plants and macro-fungi (~81% and ~57%, respectively). Results illustrated that using a multi-locus barcode approach increased identification success. This study outlines the utility of the BLAST search tool in GenBank and the BOLD identification engine for taxonomic identifications and identifies some precautions needed when using public sequence repositories in applied scientific disciplines.

References

37