Primed and ready: Nanopore metabarcoding can now recover highly accurate consensus barcodes that are generally indel-free

Background DNA metabarcoding applies high-throughput sequencing approaches to generate numerous DNA barcodes from mixed sample pools for mass species identification and community characterisation. To date, however, most metabarcoding studies employ second-generation sequencing platforms like Illumina, which are limited by short read lengths and longer turnaround times. While third-generation platforms such as the MinION (Oxford Nanopore Technologies) can sequence longer reads and even in real-time, application of these platforms for metabarcoding has remained scarce due to the relatively high read error rate as well as the paucity of specialised software for processing such reads. Findings We show that this is no longer the case by performing nanopore-based metabarcoding on 34 zooplankton bulk samples with amplicon_sorter, benchmarking the results against conventional Illumina MiSeq sequencing. The R10.3 sequencing chemistry and super accurate (SUP) basecalling model reduced raw read error rates to ∼4%, and consensus calling with amplicon_sorter (without further error correction) generated metabarcodes that were ≤1% erroneous. Although Illumina recovered a higher number of molecular operational taxonomic units (MOTUs) than nanopore sequencing (589 vs. 471), we found no significant differences in the zooplankton communities inferred between the sequencing platforms. Indeed, the same ecological conclusions were obtained regardless of the sequencing platform used. Moreover, 406 of 444 (91.4%) shared MOTUs between Illumina and nanopore were found to be indel-free. Conclusions Collectively, our results illustrate the viability of nanopore metabarcoding for characterising communities, and paves the way for greater utilisation of nanopore sequencing in various metabarcoding applications.