Compilation, Revision, and Annotation of DNA Barcodes of Marine Invertebrate Non-Indigenous Species (NIS) Occurring in European Coastal Regions

Abstract

The introduction of non-indigenous species (NIS) is one of the major threats to the integrity of European coastal ecosystems. DNA-based assessments have been increasingly adopted for monitoring NIS. However, the accuracy of DNA-based taxonomic assignments is largely dependent on the completion and reliability of DNA barcode reference libraries. As such, we aimed to compile and audit a DNA barcode reference library for marine invertebrate NIS occurring in Europe. To do so, we compiled a list of NIS using three databases: the European Alien Species Information Network (EASIN), the Information System on Aquatic Non-indigenous and Cryptogenic Species (AquaNIS), and the World Register of Introduced Marine Species (WRiMS). For each species, we retrieved the available cytochrome c oxidase subunit I (COI) mitochondrial gene sequences from the Barcode of Life Data System (BOLD) and used the Barcode, Audit & Grade System (BAGS) to check congruence between morphospecies names and Barcode Index Numbers (BINs). From the 1249 species compiled, approximately 42% had records on BOLD, among which 56% were discordant. We further analyzed these cases to determine the causes of the discordances and attributed additional annotation tags. Of the 622 discordant BINs, after revision, 35% were successfully solved, which increased the number of NIS detected in metabarcoding datasets from 12 to 16. However, a fair number of BINs remained discordant. Reliability of reference barcode records is particularly critical in the case of NIS, where erroneous identification may trigger action or inaction when not required.

DNA metabarcoding-based detection of non-indigenous invertebrates in recreational marinas: influence of sample type and seasonal variation

“…This is due to the limitations of DNA metabarcoding identifications that include the incompleteness of reference libraries; operational limitations (false positives and negatives, primer bias and contamination) and the lack of standardization (Ruppert et al 2019; Duarte et al 2021), as well as the inability to generate absolute abundance data and population status. Other complications may arise due to the inaccuracy or ambiguity of the reference sequences available in publicly-accessible databases (Fontes et al 2021; Radulovici et al 2021; Lavrador et al 2023), which made us to exclude some NIS records from this study that had uncertain species identifications. For example, Watersipora subtorquata , a well-known and highly invasive NIS, was only detected (using the COI marker) in BINs assigned to more than one species, that could not be solved by our curation method.…”

“…The remaining reads were clustered into Operational Taxonomic Units (OTUs) using a distance threshold of 3%. Taxonomic assignment at the species level using a 97% similarity threshold was performed for the resulting OTUs by comparing them against the BOLD database, as well as against several public datasets specific for marine invertebrates of the Northeast Atlantic previously published: DS-GAIMARIN (Leite et al, 2020), DS-BIBLIO (Lobo et al, 2017), DS-PTGB (Lobo et al 2016), DS-3150 (Lobo et al 2017b), DS-PMACA (Vieira et al 2022) and DS-NISEUREF (Lavrador et al 2023). The Barcode Index Number (BIN) system englobe a cluster of COI nucleotide sequences to produce operational taxonomic units that usually represent a species molecularly, using well established algorithms in BOLD (Ratnasingham and Hebert 2013).…”

“…For the identification of NIS, final species lists were matched to Portuguese invertebrate updated NIS lists (gently shared with us by Paula Chainho, which is the Portuguese contact point for the Working Group on Introductions and Transfers of Marine Organisms (WGITMO) of the ICES) as well as to an updated European NIS list. The European NIS list was obtained from three public databases: the European Alien Species Information Network (EASIN) (https://easin.jrc.ec.europa.eu/easin, accessed on 22nd March 2023) (Katsanevakis et al 2012), the Information System on Aquatic Non-indigenous and Cryptogenic Species (AquaNIS) (http://www.corpi.ku.lt/databases/index.php/aquanis/, accessed on 17th March 2023) (Olenin et al 2014) and the World Register of Introduced Marine Species (WRiMS) (https://www.marinespecies.org/introduced, accessed on 22nd March 2023) (Rius et al 2022) (as described in Lavrador et al, 2023).…”

“…In mBrave, HTS data is matched to these BINs whenever possible, to obtain a taxonomic identification of the sequences to species level, but for some cases a further audition and curation is needed. These matches were audited with the following methodology: 1) matches with BINs attributed to more than one species were identified and flagged; 2) those matches were audited using the protocol detailed in Lavrador et al, 2023. Briefly, matches with BINs attributed to 3 or more morphospecies were automatically discarded.…”

“…After these initial steps of quality control, identical reads were identified (dereplication), the unique reads were clustered (OTUs) on a per sample basis, and then the reference read of each OTU was taxonomically assigned. Lavrador et al, 2023).…”