Chang, J. J. M. | Search bioRxiv

bioRxiv2023

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

BackgroundDNA 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. FindingsWe 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. ConclusionsCollectively, 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.

zoology↗

bioRxiv2020

MinION-in-ARMS: Nanopore Sequencing To Expedite Barcoding Of Specimen-Rich Macrofaunal Samples From Autonomous Reef Monitoring Structures

Autonomous Reef Monitoring Structure (ARMS) are standardised devices for sampling biodiversity in complex marine benthic habitats such as coral reefs. When coupled with DNA sequencing, these devices greatly expand our ability to document marine biodiversity. Unfortunately, the existing workflow for processing macrofaunal samples (>2-mm) in the ARMS pipeline—which involves Sanger sequencing—is expensive, laborious, and thus prohibitive for ARMS researchers. Here, we propose a faster, more cost-effective alternative by demonstrating a successful application of the MinION-based barcoding approach on the >2mm-size fraction of ARMS samples. All data were available within 3.5–4 h, and sequencing costs relatively low at approximately US$3 per MinION barcode. We sequenced the 313-bp fragment of the cytochrome c oxidase subunit I (COI) for 725 samples on both MinION and Illumina platforms, and retrieved 507–584 overlapping barcodes. MinION barcodes were highly accurate (~99.9%) when compared with Illumina reference barcodes. Molecular operational taxonomic units inferred between MinION and Illumina barcodes were consistently stable, and match ratios demonstrated highly congruent clustering patterns (≥0.96). Our method would make ARMS more accessible to researchers, and greatly expedite the processing of macrofaunal samples; it can also be easily applied to other small-to-moderate DNA barcoding projects (<10,000 specimens) for rapid species identification and discovery.View Full Text

zoology↗