A workflow for accurate metabarcoding using nanopore MinION sequencing
Abstract
1. 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™, 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%. 2. To test whether the MinION™ 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™ 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. 3. 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. 4. Our study demonstrates that Nanopore sequencing can be used for metabarcoding, but exploration of other isothermal amplification procedures to improve consensus accuracy is recommended.
Additional Information
© 2021 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Issue Online: 04 May 2021; Version of Record online: 18 February 2021; Accepted manuscript online: 28 January 2021; Manuscript accepted: 07 January 2021; Manuscript received: 26 May 2020. We thank all staff at the Centre for Biodiversity Genomics who helped to collect the samples employed to assemble the mock community. We also would like to thank Florian Leese, Arne Beermann, Cristina Hartmann‐Fatu, and Marie Gutgesell for collecting and providing specimens. This study was supported by funding through the Canada First Research Excellence Fund. The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript. This work represents a contribution to the University of Guelph Food From Thought research program. Authors' Contributions: B.B., V.E., T.B. and D.S. designed the experiments; B.B. and S.M. assembled the mock community; B.B. did the laboratory work; V.E. did the MiSeq experiment; B.B. and Z.C. analysed the data and built the bioinformatics pipeline; B.B. and D.S. wrote the manuscript, all authors contributed to the manuscript. Peer Review: The peer review history for this article is available at https://publons.com/publon/10.1111/2041‐210X.13561. Data Availability Statement: Software ASHURE is deposited at Zenodo https://doi.org/10.5281/zenodo.4450611 (Baloğlu & Chen, 2021) and is available at Github under https://github.com/BBaloglu/ASHURE. Raw read data are available at the SRA under PRJNA627498 (ONT: Protocols A and B) and SRR9207930 (Illumina MiSeq).Attached Files
Published - 2041-210X.13561.pdf
Submitted - 2020.05.21.108852v1.full.pdf
Supplemental Material - mee313561-sup-0001-tables1.xlsx
Supplemental Material - mee313561-sup-0002-tables3.xlsx
Supplemental Material - mee313561-sup-0003-supinfo.pdf
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Additional details
- Eprint ID
- 103450
- Resolver ID
- CaltechAUTHORS:20200526-120017153
- Canada First Research Excellence Fund
- Created
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2020-05-26Created from EPrint's datestamp field
- Updated
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2021-05-07Created from EPrint's last_modified field