Environmental metabarcodes for insects: in silicoPCR reveals potential for taxonomic bias
Open accessAbstract
Studies of insect assemblages are suited to the simultaneous DNA‐based identification of multiple taxa known as metabarcoding. To obtain accurate estimates of diversity, metabarcoding markers ideally possess appropriate taxonomic coverage to avoid PCR‐amplification bias, as well as sufficient sequence divergence to resolve species. We used in silico PCR to compare the taxonomic coverage and resolution of newly designed insect metabarcodes (targeting 16 S) with that of existing markers [16 S and cytochrome oxidase c subunit I (COI)] and then compared their efficiency in vitro. Existing metabarcoding primers amplified in silico <75% of insect species with complete mitochondrial genomes available, whereas new primers targeting 16 S provided >90% coverage. Furthermore, metabarcodes targeting COI appeared to introduce taxonomic PCR‐amplification bias, typically amplifying a greater percentage of L epidoptera and D iptera species, while failing to amplify certain orders in silico. To test whether bias predicted in silico was observed in vitro, we created an artificial DNA blend containing equal amounts of DNA from 14 species, representing 11 insect orders and one arachnid. We PCR‐amplified the blend using five primer sets, targeting either COI or 16 S, with high‐throughput amplicon sequencing yielding more than 6 million reads. In vitro results typically corresponded to in silico PCR predictions, with newly designed 16 S primers detecting 11 insect taxa present, thus providing equivalent or better taxonomic coverage than COI metabarcodes. Our results demonstrate that in silico PCR is a useful tool for predicting taxonomic bias in mixed template PCR and that researchers should be wary of potential bias when selecting metabarcoding markers.
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While the conserved ribosomal mitochondrial gene approach could have comparable taxonomic resolution as the COI barcode, it is currently limited by the lack of reference databases.
“However, while this approach could have comparable taxonomic resolution as the COI barcode, it is currently limited by the lack of reference databases [55].”
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- Authors
- Clarke, L. J., Soubrier, J., Weyrich, L. S., & Cooper, A.
- Affiliations
- The University of Adelaide (AU)
- Corresponding author
- Clarke, Laurence J.
- Venue
- Molecular Ecology Resources
- Publisher
- Wiley
- Published
- 2014-05-14
- Volume
- 14
- Issue
- 6
- Pages
- 1160-1170
- ISSN
- 1755-098X (ISSN-L)
- 1755-0998
- OpenAlex
- W2051569068
- Cited by
- 351
- References
- 46
- Citations by year
- 2026: 14 · 2025: 31 · 2024: 26 · 2023: 20 · 2022: 31 · 2021: 51 · 2020: 47 · 2019: 30 · 2018: 31 · 2017: 26 · 2016: 24 · 2015: 13 · 2014: 6
- FWCI
- 19.92
- Type
- journal article
- Language
- en
- Open access
- green
- figshare.com
- Locations
- Molecular Ecology Resources (publishedVersion)
- PubMed (publishedVersion)
- eCite Digital Repository (University of Tasmania) (submittedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Funders
- Australian Research Council (LP0991985)
- Topics
- Physical Sciences › Environmental Science › Ecology › Environmental DNA in Biodiversity Studies
- Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Invertebrate Taxonomy and Ecology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- 16S rRNA, mitochondrial COI, PCR bias, taxonomic coverage, primer design, in silico PCR, mitochondrial DNA markers, Lepidoptera, Diptera, insect diversity
- MeSH terms
- Animals, Electron Transport Complex IV, DNA, Ribosomal, Insecta, RNA, Ribosomal, 16S, Polymerase Chain Reaction, Computational Biology, DNA Barcoding, Taxonomic, High-Throughput Nucleotide Sequencing, Genotyping Techniques
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