title: A DNA-based registry for all animal species: the barcode index number (BIN) system.
abstract: 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.
authors.affiliation: Biodiversity Institute of Ontario, University of Guelph, Guelph, Ontario, Canada. sratnasi@uoguelph.ca
authors.forename: Sujeevan
authors.initials: S
authors.lastname: Ratnasingham
authors.forename: Paul D N
authors.initials: PD
authors.lastname: Hebert
mesh_terms: D000465:Algorithms; D000818:Animals; D016000:Cluster Analysis; D058893:DNA Barcoding, Taxonomic / Q000379:methods*; D019992:Databases as Topic; D007915:Lepidoptera / Q000145:classification; D009656:North America; D012042:Registries; D013045:Species Specificity; D013997:Time Factors