A DNA-Based Registry for All Animal Species: The Barcode Index Number (BIN) System

By Sujeevan Ratnasingham, Paul D. N. Hebert. PLoS ONE, 2013

2,182 citations recorded by the source corpus.

Because many animal species are undescribed, and because the identification of known species is often difficult, interim taxonomic nomenclature has often been used in biodiversity analysis. By assigning individuals to presumptive species, called operational taxonomic units (OTUs), these systems speed investigations into the patterning of biodiversity and enable studies that would otherwise be impossible. Although OTUs have conventionally been separated through their morphological divergence, DNA-based delineations are not only feasible, but have important advantages. OTU designation can be automated, data can be readily archived, and results can be easily compared among investigations. This study exploits these attributes to develop a persistent, species-level taxonomic registry for the animal kingdom based on the analysis of patterns of nucleotide variation in the barcode region of the cytochrome c oxidase I (COI) gene. It begins by examining the correspondence between groups of specimens identified to a species through prior taxonomic work and those inferred from the analysis of COI sequence variation using one new (RESL) and four established (ABGD, CROP, GMYC, jMOTU) algorithms. It subsequently describes the implementation, and structural attributes of the Barcode Index Number (BIN) system. Aside from a pragmatic role in biodiversity assessments, BINs will aid revisionary taxonomy by flagging possible cases of synonymy, and by collating geographical information, descriptive metadata, and images for specimens that are likely to belong to the same species, even if it is undescribed. More than 274,000 BIN web pages are now available, creating a biodiversity resource that is positioned for rapid growth.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/300bf50905509a4b8cf8604af1435c72272475b1

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Citations in the corpus

A DNA barcoding framework for taxonomic verification in the Darwin Tree of Life Project (2024, methodology): “Use of the Barcode Index Number (BIN) system (Ratnasingham & Hebert, 2013).”
DNA barcoding Madagascar's amphibian fauna (2014, methodology): “Despite being a relatively new diagnostic method, DNA barcoding has evolved into an important technique for sorting individual organisms into clusters on the basis of genetic information (Ratnasingham and Hebert, 2013) and consequently for accurately identifying species of fauna and flora (Fouquet e”
Validating taxonomic identifications in entomological research (2018, background): “First, the identity of ‘easily identified’ species could be verified through sending vouchers to an acknowledged taxonomic expert on the group or through DNA barcoding (Ratnasingham & Hebert, 2013; Frewin, 2015).”
The biodiversity of species and their rates of extinction, distribution, and protection (2014, background): “It raises the controversial idea that many species may become known by a number derived from barcoding and not—or not only—from conventional descriptions (123).”
Multi-rate Poisson tree processes for single-locus species delimitation under maximum likelihood and Markov chain Monte Carlo (2016, background): “This and previous studies (Monaghan et al., 2009; Esselstyn et al., 2012; Ratnasingham and Hebert, 2013; Tang et al., 2014) suggest that single-locus barcoding methods provide meaningful clusters, close to taxonomically acknowledged species.”
DNA Barcoding, species delineation and taxonomy: a historical perspective (2015, neutral): “In order to facilitate the assembly of DNA barcodes reference libraries, Barcode Index Number (BIN) have been recently created in order to facilitate the checking of mismatch between nominal species and DNA barcodes clusters and ease their discrimination through standard procedures [61].”
Benchmarking DNA Metabarcoding for Biodiversity-Based Monitoring and Assessment (2016, background): “The COI gene is by far the most commonly used marker for metazoan metabarcoding (Ratnasingham and Hebert, 2013), for which thousands of reference sequences are available in public databases [the Barcode of Life Database (BOLD) contains >1,000,000 COI sequences belonging to animal species] and…”
Assessing strengths and weaknesses of DNA metabarcoding‐based macroinvertebrate identification for routine stream monitoring (2017, background): “Additionally, the accuracy of identification of larvae and adult invertebrates varies depending on expert experience, and even databases like BOLD, specifically built for DNA barcoding, contain misidentified taxa or conflicting taxonomic assignments for the same BIN (Barcode Index Number, Ratnasingh”
ASAP: assemble species by automatic partitioning (2020, methodology): “The relative performances of these three exploratory methods, GMYC, PTP and ABGD, sometimes together with less used methods (Flot et al., 2010; Ratnasingham & Hebert, 2013) have been compared in various taxa: mammals (Derouiche et al., 2017), amphibians (Vacher et al., 2017), squamates (Blair &…”
NCBI Taxonomy: a comprehensive update on curation, resources and tools (2020, background): “Typically, users submit data sets to GenBank from their accounts in the BOLD system (47, 77) before the associated articles are published.”
Clumpak: a program for identifying clustering modes and packaging population structure inferences across K (2015, background): “…identifying clusters, and it has previously been adapted for diverse biological problems, including orthology assignments (Enright et al. 2002), detection of operational taxonomic units (Ratnasingham & Hebert 2013), and identiﬁcation of co-occurring associations among microbes (Faust et al. 2012).”