Maximizing the reliability and the number of species assignments in metabarcoding studies using a curated regional library and a public repository

Biodiversity assessments relying on DNA have 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 (GSL-rl) by data mining COI barcode sequences from BOLD, and included a reliability ranking system for species assignments. We then estimated 1) the accuracy and precision of the public repository NCBI-nt for species assignments using sequences from the regional library and 2) compared the detection and reliability of species assignments of a metabarcoding dataset using either NCBI-nt or the regional library and popular assignment methods. With NCBI-nt and sequences from the regional library, the BLAST-LCA (least common ancestor) method was the most precise method for species assignments, but the accuracy was higher with the BLAST-TopHit method (>80% over all taxa, between 70% and 90% amongst taxonomic groups). With the metabarcoding dataset, the reliability of species assignments was greater using 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 with different optimized assignment methods. The use of a two-step approach for species assignments, i.e., using a regional library and a public repository, could improve the reliability and the number of detected species in metabarcoding studies