@article {Bourret2022.11.17.513905, author = {Audrey Bourret and Claude Noz{\`e}res and Eric Parent and Genevi{\`e}ve J. Parent}, title = {Maximizing the reliability and the number of species assignments in metabarcoding studies}, elocation-id = {2022.11.17.513905}, year = {2022}, doi = {10.1101/2022.11.17.513905}, publisher = {Cold Spring Harbor Laboratory}, abstract = {The use of environmental DNA (eDNA) for biodiversity assessments has increased rapidly over the last decade. However, the reliability of taxonomic assignments in metabarcoding studies is variable, and affected by the reference databases and the assignment methods used. Species level assignments are usually considered as reliable using regional libraries but unreliable using public repositories. In this study, we aimed to test this assumption for metazoan species detected in the Gulf of St. Lawrence, in the Northwest Atlantic. We first created a regional library with COI barcode sequences including a reliability ranking system for species assignments. We then estimated the accuracy of the public repository NCBI-nt for species assignments using sequences from the regional library, and contrasted assigned species and their reliability using NCBI-nt or the regional library with a metabarcoding dataset and popular assignment methods. With NCBI-nt and sequences from the regional library, Blast-LCA was the most accurate method for species assignments but the proportions of accurate species assignments were higher with Blast-TopHit (\>80 \% overall taxa, between 70 and 90 \% amongst taxonomic groups). With the metabarcoding dataset, the reliability of species assignments was greater using the GSL-rl compared to NCBI-nt. However, we also observed that the total number of reliable species assignments could be maximized using both GSL-rl and NCBI-nt, and their optimal assignment methods, which differed. The use of a two-step approach in species assignments, using a regional library and a public repository, could improve the reliability and the number of detected species in metabarcoding studies.Competing Interest StatementThe authors have declared no competing interest.}, URL = {https://www.biorxiv.org/content/early/2022/11/18/2022.11.17.513905}, eprint = {https://www.biorxiv.org/content/early/2022/11/18/2022.11.17.513905.full.pdf}, journal = {bioRxiv} }