A workflow for accurate metabarcoding using nanopore MinION sequencing

Metabarcoding has become a common approach to the rapid identification of the species composition in a mixed sample. The majority of studies use established short‐read high‐throughput sequencing platforms. The Oxford Nanopore MinION TM , a portable sequencing platform, represents a low‐cost alternative allowing researchers to generate sequence data in the field. However, a major drawback is the high raw read error rate that can range from 10% to 22%. To test whether the MinION TM represents a viable alternative to other sequencing platforms, we used rolling circle amplification (RCA) to generate full‐length consensus DNA barcodes for a bulk mock sample of 50 aquatic invertebrate species with at least 15% genetic distance to each other. By applying two different laboratory protocols, we generated two MinION TM runs that were used to build error‐corrected consensus sequences. A newly developed Python pipeline, ASHURE, was used for data processing, consensus building, clustering and taxonomic assignment of the resulting reads. Our pipeline achieved median accuracies of up to 99.3% for long concatemeric reads (>45 barcodes) and successfully identified all 50 species in the mock community. The use of RCA was integral for increasing consensus accuracy but was also the most time‐consuming step of the laboratory workflow. Most concatemeric reads were skewed towards a shorter read length range with a median read length of up to 1,262 bp. Our study demonstrates that Nanopore sequencing can be used for metabarcoding, but exploration of other isothermal amplification procedures to improve consensus accuracy is recommended.