Title |
Express barcoding with NextGenPCR and MinION for species‐level sorting of ecological samples
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Published in |
Molecular Ecology Resources, January 2024
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DOI | 10.1111/1755-0998.13922 |
Pubmed ID | |
Authors |
Cristina Vasilita, Vivian Feng, Aslak Kappel Hansen, Emily Hartop, Amrita Srivathsan, Robin Struijk, Rudolf Meier |
Abstract |
The use of DNA barcoding is well established for specimen identification and large-scale biodiversity discovery, but remains underutilized for time-sensitive applications such as rapid species discovery in field stations, identifying pests, citizen science projects, and authenticating food. The main reason is that existing express barcoding workflows are either too expensive or can only be used in very well-equipped laboratories by highly-trained staff. We here show an alternative workflow combining rapid DNA extraction with HotSHOT, amplicon production with NextGenPCR thermocyclers, and sequencing with low-cost MinION sequencers. We demonstrate the power of the approach by generating 250 barcodes for 285 specimens within 6 h including specimen identification through BLAST. The workflow required only the following major equipment that easily fits onto a lab bench: Thermocycler, NextGenPCR, microplate sealer, Qubit, and MinION. Based on our results, we argue that simplified barcoding workflows for species-level sorting are now faster, more accurate, and sufficiently cost-effective to replace traditional morpho-species sorting in many projects. |
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Geographical breakdown
Country | Count | As % |
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Germany | 4 | 4% |
United Kingdom | 2 | 2% |
France | 2 | 2% |
Australia | 1 | <1% |
Poland | 1 | <1% |
India | 1 | <1% |
Finland | 1 | <1% |
Bolivia, Plurinational State of | 1 | <1% |
Unknown | 89 | 87% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 50 | 49% |
Members of the public | 48 | 47% |
Science communicators (journalists, bloggers, editors) | 4 | 4% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 25 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 6 | 24% |
Student > Ph. D. Student | 4 | 16% |
Student > Bachelor | 2 | 8% |
Student > Master | 2 | 8% |
Professor | 1 | 4% |
Other | 1 | 4% |
Unknown | 9 | 36% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 10 | 40% |
Biochemistry, Genetics and Molecular Biology | 3 | 12% |
Earth and Planetary Sciences | 2 | 8% |
Environmental Science | 1 | 4% |
Engineering | 1 | 4% |
Other | 0 | 0% |
Unknown | 8 | 32% |