The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Quantitative DNA metabarcoding: improved estimates of species proportional biomass using correction factors derived from control material
Open accessAbstract
DNA metabarcoding is a powerful new tool allowing characterization of species assemblages using high‐throughput amplicon sequencing. The utility of DNA metabarcoding for quantifying relative species abundances is currently limited by both biological and technical biases which influence sequence read counts. We tested the idea of sequencing 50/50 mixtures of target species and a control species in order to generate relative correction factors (RCF s) that account for multiple sources of bias and are applicable to field studies. RCF s will be most effective if they are not affected by input mass ratio or co‐occurring species. In a model experiment involving three target fish species and a fixed control, we found RCF s did vary with input ratio but in a consistent fashion, and that 50/50 RCF s applied to DNA sequence counts from various mixtures of the target species still greatly improved relative abundance estimates (e.g. average per species error of 19 ± 8% for uncorrected vs. 3 ± 1% for corrected estimates). To demonstrate the use of correction factors in a field setting, we calculated 50/50 RCF s for 18 harbour seal (Phoca vitulina) prey species (RCF s ranging from 0.68 to 3.68). Applying these corrections to field‐collected seal scats affected species percentages from individual samples (Δ 6.7 ± 6.6%) more than population‐level species estimates (Δ 1.7 ± 1.2%). Our results indicate that the 50/50 RCF approach is an effective tool for evaluating and correcting biases in DNA metabarcoding studies. The decision to apply correction factors will be influenced by the feasibility of creating tissue mixtures for the target species, and the level of accuracy needed to meet research objectives.
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Cites
Towards next-generation biodiversity assessment using DNA metabarcoding
TABERLET, P., COISSAC, E., POMPANON, F., BROCHMANN, C., & WILLERSLEV, E. (2012) · Molecular Ecology · doi:10.1111/j.1365-294x.2012.05470.x · Cited by 1,907
Elbrecht, V., & Leese, F. (2015) · PLOS ONE · doi:10.1371/journal.pone.0130324 · Cited by 765 · cited 1×
“In those circumstances, it is likely unrealistic to expect accurate estimates of species proportion based on DNA sequence read abundances (e.g. Clarke et al. 2014; Elbrecht & Leese 2015), and correction factors are likely not worth pursuing in that stage of methodological development.”
BackgroundPiñol, J., Mir, G., Gomez‐Polo, P., & Agustí, N. (2015) · Molecular Ecology Resources · doi:10.1111/1755-0998.12355 · Cited by 423
Cited by
Consistent and correctable bias in metagenomic sequencing experiments
McLaren, M. R., Willis, A. D., & Callahan, B. J. (2019) · eLife · doi:10.7554/elife.46923 · Cited by 429
Elbrecht, V., Vamos, E. E., Meissner, K., Aroviita, J., & Leese, F. (2017) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.12789 · Cited by 385
Biases in bulk: DNA metabarcoding of marine communities and the methodology involved
van der Loos, L. M., & Nijland, R. (2021) · Molecular Ecology · doi:10.1111/mec.15592 · Cited by 268
Disentangling bias for non-destructive insect metabarcoding
Martoni, F., Piper, A. M., Rodoni, B. C., & Blacket, M. J. (2022) · PeerJ · doi:10.7717/peerj.12981 · Cited by 36
Dietary DNA Metabarcoding From Animal Fecal Samples
McConnell, R. D., Jarrett, C., Ferreira, D. F., Powell, L. L., Quiñones, A. L. S., Dominoni, D. M., & Welch, A. J. (2026) · Current Protocols · doi:10.1002/cpz1.70226 · Cited by 2
Metadata
- Authors
- Thomas, A. C., Deagle, B. E., Eveson, J. P., Harsch, C. H., & Trites, A. W.
- Venue
- Molecular Ecology Resources
- Publisher
- Wiley
- Published
- 2015-12-18
- Volume
- 16
- Issue
- 3
- Pages
- 714-726
- ISSN
- 1755-098X (ISSN-L)
- 1755-0998
- OpenAlex
- W2175688155
- Cited by
- 249
- References
- 3
- FWCI
- 24.77
- Type
- journal article
- Language
- en
- Open access
- green
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