ONTbarcoder and MinION barcodes aid biodiversity discovery and identification by everyone, for everyone

Abstract

Background DNA barcodes are a useful tool for discovering, understanding, and monitoring biodiversity which are critical tasks at a time of rapid biodiversity loss. However, widespread adoption of barcodes requires cost-effective and simple barcoding methods. We here present a workflow that satisfies these conditions. It was developed via “innovation through subtraction” and thus requires minimal lab equipment, can be learned within days, reduces the barcode sequencing cost to < 10 cents, and allows fast turnaround from specimen to sequence by using the portable MinION sequencer. Results We describe how tagged amplicons can be obtained and sequenced with the real-time MinION sequencer in many settings (field stations, biodiversity labs, citizen science labs, schools). We also provide amplicon coverage recommendations that are based on several runs of the latest generation of MinION flow cells (“R10.3”) which suggest that each run can generate barcodes for > 10,000 specimens. Next, we present a novel software, ONTbarcoder, which overcomes the bioinformatics challenges posed by MinION reads. The software is compatible with Windows 10, Macintosh, and Linux, has a graphical user interface (GUI), and can generate thousands of barcodes on a standard laptop within hours based on only two input files (FASTQ, demultiplexing file). We document that MinION barcodes are virtually identical to Sanger and Illumina barcodes for the same specimens (> 99.99%) and provide evidence that MinION flow cells and reads have improved rapidly since 2018. Conclusions We propose that barcoding with MinION is the way forward for government agencies, universities, museums, and schools because it combines low consumable and capital cost with scalability. Small projects can use the flow cell dongle (“Flongle”) while large projects can rely on MinION flow cells that can be stopped and re-used after collecting sufficient data for a given project.

Hitchhiking into the future on a fly: Toward a better understanding of phoresy and avian louse evolution (Phthiraptera) by screening bird carcasses for phoretic lice on hippoboscid flies (Diptera)

“…For the lice and flies, we use NGS barcoding (Srivathsan et al, 2021; Srivathsan, Hartop, et al, 2019; Srivathsan, Nagarajan, & Meier, 2019; Wong et al, 2017; Yeo et al, 2018) to address the taxonomic impediments that interfere with so much natural history research. The specimens were sorted into putative species based on NGS barcodes which can now be obtained at low cost for thousands of specimens within days (Srivathsan et al, 2018, 2021; Srivathsan, Hartop, et al, 2019; Srivathsan, Nagarajan, & Meier, 2019; Wang et al, 2018; Yeo et al, 2018). This yielded two new cases of phoresy which are here added to the species interaction networks identified based on literature data.…”

DiversityScanner: Robotic handling of small invertebrates with machine learning methods

“…The data and images would be an important scientific and educational resource. Of course, the newly discovered species would still need description and we would still know very little about the ecological roles that these species play, but molecular approaches to species interaction research, diet analysis and life history stage matching can help fill these gaps (e.g., Reeves et al, 2018;Six, 2013;Srivathsan et al, 2019b;Yeo et al, 2018).…”

“…The first is cost-effective methods for obtaining and sequencing specimen-specific barcode amplicons with second-and third-generation sequencing technologies (Hebert et al, 2018;Srivathsan et al, 2019aSrivathsan et al, , 2021Wang et al, 2018). Indeed, today's consumable cost for barcoding a sample with 1000 specimens is <100 USD (Srivathsan et al, 2021) and portable sequencers produced by Oxford Nanopore Technologies are democratizing access to DNA sequences (Buchner et al, 2021;Pomerantz et al, 2018;Srivathsan et al, 2021;Watsa et al, 2020). Unfortunately, automation and data processing with neural networks, which present the other two developments, remain underutilized.…”

Amplicon_sorter: A tool for reference‐free amplicon sorting based on sequence similarity and for building consensus sequences

“…IsoCon and ToFu are reference‐free long‐read consensus algorithms for transcriptome data that have been described but aim for a different application (Gordon et al, 2015 ; Sahlin et al, 2018 ). The recent programs ONTrack (Maestri et al, 2019 ), NGSpeciesID (Sahlin et al, 2021 ), and ONTbarcoder (Srivathsan et al, 2021a ) perform reference‐free clustering of amplicons and create a high‐quality consensus sequence and are designed for specific amplicon sequencing applications. ONTrack needs demultiplexed files, processes only the reads in the most abundant cluster, and needs the large fast5 files to polish the consensus sequence.…”