2021-03-192021-03-192016-07-211932-6203http://hdl.handle.net/2133/20243Valid fish species identification is essential for biodiversity conservation and fisheries management. Here, we provide a sequence reference library based on mitochondrial cytochrome c oxidase subunit I for a valid identification of 79 freshwater fish species from the Lower Paraná River. Neighbour-joining analysis based on K2P genetic distances formed non-overlapping clusters for almost all species with a 99% bootstrap support each. Identification was successful for 97.8% of species as the minimum genetic distance to the nearest neighbour exceeded the maximum intraspecific distance in all these cases. A barcoding gap of 2.5% was apparent for the whole data set with the exception of four cases. Within species distances ranged from 0.00% to 7.59%, while interspecific distances varied between 4.06% and 19.98%, without considering Odontesthes species with a minimum genetic distance of 0%. Sequence library validation was performed by applying BOLDs BIN analysis tool, Poisson Tree Processes model and Automatic Barcode Gap Discovery, along with a reliable taxonomic assignment by experts. Exhaustive revision of vouchers was performed when a conflicting assignment was detected after sequence analysis and BIN discordance evaluation. Thus, the sequence library presented here can be confidently used as a benchmark for identification of half of the fish species recorded for the Lower Paraná River.Para citar este articulo: Díaz J, Villanova GV, Brancolini F, del Pazo F, Posner VM, Grimberg A, et al. (2016) First DNA Barcode Reference Library for the Identification of South American Freshwater Fish from the Lower Paraná River. PLoS ONE 11(7): e0157419. doi:10.1371/journal.pone.0157419application/pdf1-20engopenAccessDNA BarcodingElectron Transport Complex IParaná RiverFishesFirst DNA barcode reference library for the identification of South American freshwater fish from the lower Paraná RiverarticleUniversidad Nacional de RosarioDíaz, JuanVillanova, Gabriela VaninaBrancolini, FlorenciaDel Pazo, FelipePosner, Victoria MaríaGrimberg, AlexisArranz, Silvia EdaAttribution 4.0 International (CC BY 4.0)