mkLTG: a command-line tool for taxonomic assignment of metabarcoding sequences using variable identity thresholds.

Metabarcoding is now a widely used method for biodiversity studies. Taxonomic assignment of environmental sequences is one of the key steps of metabarcoding. Assignments based on lowest common ancestor (LCA) method generally rely on fixed arbitrary thresholds, and this is generally not well adapted for assignment of taxonomically diverse groups with variable coverage in reference databases.

Scientific history, biogeography, and biological traits predict presence of cryptic or overlooked species.

Genetic data show that many nominal species are composed of more than one biological species, and thus contain cryptic species in the broad sense (including overlooked species). When ignored, cryptic species generate confusion which, beyond biodiversity or vulnerability underestimation, blurs our understanding of ecological and evolutionary processes and may impact the soundness of decisions in conservation or medicine. However, very few hypotheses have been tested about factors that predispose a taxon to contain cryptic or overlooked species.

Genetic diversity of the submerged macrophyte depends on habitat hydrology and habitat fragmentation.

The adaptability of plant populations to a changing environment depends on their genetic diversity, which in turn is influenced by the degree of sexual reproduction and gene flow from distant areas. Aquatic macrophytes can reproduce both sexually and asexually, and their reproductive fragments are spread in various ways (e.g.

VTAM: A robust pipeline for validating metabarcoding data using controls.

To obtain accurate estimates for biodiversity and ecological studies, metabarcoding studies should be carefully designed to minimize both false positive (FP) and false negative (FN) occurrences. Internal controls (mock samples and negative controls), replicates, and overlapping markers allow controlling metabarcoding errors but current metabarcoding software packages do not explicitly integrate these additional experimental data to optimize filtering. We have developed the metabarcoding analysis software VTAM, which uses explicitly these elements of the experimental design to find optimal parameter settings that minimize FP and FN occurrences.

COInr and mkCOInr: Building and customizing a nonredundant barcoding reference database from BOLD and NCBI using a semi-automated pipeline.

Reference databases with wide taxonomic coverage are greatly needed in many fields of biology, most particularly for the taxonomic assignment of metabarcoding sequences. Therefore, it is fundamental to be able to access and pool data from different primary databases. The COInr database is a freely available, easy-to-access database of COI reference sequences extracted from the BOLD and NCBI nucleotide databases.