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

Chang, J.J.M.; Ip, Y.C.A.; Bauman, A.G.; Huang, D.

Publication

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

Chang, J.J.M.; Ip, Y.C.A.; Bauman, A.G.; Huang, D.

Abstract

Autonomous Reef Monitoring Structure (ARMS) are standardized 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 >2 mm-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. © Copyright © 2020 Chang, Ip, Bauman and Huang.

Keywords

amplicon sequencing, cytochrome c oxidase subunit I (COI), DNA barcoding, metazoa, next-generation sequencing, Oxford Nanopore Technologies, species estimation