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Universal and blocking primer mismatches limit the use of high‐throughput DNA sequencing for the quantitative metabarcoding of arthropods
Abstract
The quantification of the biological diversity in environmental samples using high‐throughput DNA sequencing is hindered by the PCR bias caused by variable primer–template mismatches of the individual species. In some dietary studies, there is the added problem that samples are enriched with predator DNA, so often a predator‐specific blocking oligonucleotide is used to alleviate the problem. However, specific blocking oligonucleotides could coblock nontarget species to some degree. Here, we accurately estimate the extent of the PCR biases induced by universal and blocking primers on a mock community prepared with DNA of twelve species of terrestrial arthropods. We also compare universal and blocking primer biases with those induced by variable annealing temperature and number of PCR cycles. The results show that reads of all species were recovered after PCR enrichment at our control conditions (no blocking oligonucleotide, 45 °C annealing temperature and 40 cycles) and high‐throughput sequencing. They also show that the four factors considered biased the final proportions of the species to some degree. Among these factors, the number of primer–template mismatches of each species had a disproportionate effect (up to five orders of magnitude) on the amplification efficiency. In particular, the number of primer–template mismatches explained most of the variation (~3/4) in the amplification efficiency of the species. The effect of blocking oligonucleotide concentration on nontarget species relative abundance was also significant, but less important (below one order of magnitude). Considering the results reported here, the quantitative potential of the technique is limited, and only qualitative results (the species list) are reliable, at least when targeting the barcoding COI region.
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“the amplification efficiency of the COI gene varies among species, and this might severely bias results [34,39] particularly in view of the variation in biomass.”
In the citing paper
“the amplification efficiency of the COI gene varies among species, and this might severely bias results [34,39] particularly in view of the variation in biomass.”
In the citing paper
“Amplification of diverse multitemplate mixtures using universal primers can lead to highly unequal amplification efficiencies among products [39,49].”
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“Piñol et al. [39] proposed a relationship between biomass and sequence reads, but did not systematically examine this hypothesis.”
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Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
Folmer, O., Black, M., Hoeh, W., Lutz, R., & Vrijenhoek, R. (1994) · PubMed · doi:10.5281/zenodo.15145663 · Cited by 15,546
A Greedy Algorithm for Aligning DNA Sequences
Zhang, Z., Schwartz, S., Wagner, L., & Miller, W. (2000) · Journal of Computational Biology · doi:10.1089/10665270050081478 · Cited by 5,459
Quality control and preprocessing of metagenomic datasets
Schmieder, R., & Edwards, R. A. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr026 · Cited by 5,119
Microbial diversity in the deep sea and the underexplored “rare biosphere”
Sogin, M. L., Morrison, H. G., Huber, J. A., Welch, D. B. M., Huse, S. M., Neal, P. R., Arrieta, J. M., & Herndl, G. J. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605127103 · Cited by 3,803
Determination of microbial diversity in environmental samples: pitfalls of PCR-based rRNA analysis
von Wintzingerode, F., Göbel, U. B., & Stackebrandt, E. S. (1997) · FEMS Microbiology Reviews · doi:10.1111/j.1574-6976.1997.tb00351.x · Cited by 2,085
Quail, M., Smith, M. E., Coupland, P., Otto, T. D., Harris, S. R., Connor, T. R., Bertoni, A., Swerdlow, H. P., & Gu, Y. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-341 · Cited by 2,031
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
Leray, M., Yang, J., Meyer, C., Mills, S. C., Agudelo, N., Ranwez, V., Boehm, J. T., & Machida, R. J. (2013) · Frontiers in Zoology · doi:10.1186/1742-9994-10-34 · Cited by 1,648
Integrative analysis of environmental sequences using MEGAN4Preprint
Huson, D. H., Mitra, S., Ruscheweyh, H., Weber, N., & Schuster, S. C. (2011) · Genome Research · doi:10.1101/gr.120618.111 · Cited by 1,559
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Bista, I., Carvalho, G. R., Tang, M., Walsh, K. A., Zhou, X. Y., Hajibabaei, M., Shokralla, S., Seymour, M., Bradley, D. T. C., Liu, S., et al. (2018) · Molecular Ecology Resources · doi:10.1111/1755-0998.12888 · Cited by 156
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Nascimento, F. J. A., Lallias, D., Bik, H. M., & Creer, S. (2018) · Scientific Reports · doi:10.1038/s41598-018-30179-1 · Cited by 70
Ficetola, G. F., Boyer, F., Valentini, A., Bonin, A., Meyer, A., Déjean, T., Gaboriaud, C., Usseglio‐Polatera, P., & Taberlet, P. (2020) · Molecular Ecology · doi:10.1111/mec.15632 · Cited by 70
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Metadata
- Authors
- Piñol, J., Mir, G., Gomez‐Polo, P., & Agustí, N.
- Affiliations
- Universitat Autònoma de Barcelona (ES)
- CRAG CSIC IRTA UAB UB Cerdanyola del Vallès 08193 Spain
- Institute of Agrifood Research and Technology (ES)
- Corresponding author
- Piñol, J.
- Venue
- Molecular Ecology Resources
- Publisher
- Wiley
- Published
- 2014-12-23
- Volume
- 15
- Issue
- 4
- Pages
- 819-830
- ISSN
- 1755-098X (ISSN-L)
- 1755-0998
- OpenAlex
- W2051331361
- Cited by
- 423
- References
- 48
- Citations by year
- 2026: 37 · 2025: 42 · 2024: 37 · 2023: 34 · 2022: 45 · 2021: 53 · 2020: 40 · 2019: 31 · 2018: 53 · 2017: 22 · 2016: 20 · 2015: 9
- FWCI
- 14.76
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Molecular Ecology Resources (publishedVersion)
- PubMed (publishedVersion)
- DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion)
- Funders
- MINECO (CGL2010-18182, AGL2011-24349)
- 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
- PCR bias, primer-template mismatch, arthropods, COI barcoding, mock communities, amplification efficiency, annealing temperature, dietary assessment, species relative abundance
- MeSH terms
- Animals, Arthropods, Diagnostic Errors, Molecular Sequence Data, Polymerase Chain Reaction, Sequence Analysis, DNA, DNA Primers, Base Pair Mismatch, DNA Barcoding, Taxonomic, High-Throughput Nucleotide Sequencing
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