Exhaustive reanalysis of barcode sequences from public repositories highlights ongoing misidentifications and impacts taxa diversity and distribution

Fort, Antoine; McHale, Marcus; Cascella, Kevin; Potin, Philippe; Perrineau, Marie Mathilde; Kerrison, Philip D.; Costa, Elisabete da; Calado, Ricardo; Rosário Domingues, Maria do; Costa Azevedo, Isabel; Sousa-Pinto, Isabel; Gachon, Claire; Werf, Adrie van der; Visser, Willem de; Beniers, Johanna E.; Jansen, Henrice; Guiry, Michael D.; Sulpice, Ronan


Accurate species identification often relies on public repositories to compare the barcode sequences of the investigated individual(s) with taxonomically assigned sequences. However, the accuracy of identifications in public repositories is often questionable, and the names originally given are rarely updated. For instance, species of the Sea Lettuce (Ulva spp.; Ulvophyceae, Ulvales, Ulvaceae) are frequently misidentified in public repositories, including herbaria and gene banks, making species identification based on traditional barcoding unreliable. We DNA barcoded 295 individual distromatic foliose strains of Ulva from the North-East Atlantic for three loci (rbcL, tufA, ITS1). Seven distinct species were found, and we compared our results with all worldwide Ulva spp. sequences present in the NCBI database for the three barcodes rbcL, tufA and the ITS1. Our results demonstrate a large degree of species misidentification, where we estimate that 24%–32% of the entries pertaining to foliose species are misannotated and provide an exhaustive list of NCBI sequences reannotations. An analysis of the global distribution of registered samples from foliose species also indicates possible geographical isolation for some species, and the absence of U. lactuca from Northern Europe. We extended our analytical framework to three other genera, Fucus, Porphyra and Pyropia and also identified erroneously labelled accessions and possibly new synonymies, albeit less than for Ulva spp. Altogether, exhaustive taxonomic clarification by aggregation of a library of barcode sequences highlights misannotations and delivers an improved representation of species diversity and distribution.