Please use this identifier to cite or link to this item: https://doi.org/10.1038/s41598-017-17333-x
Title: Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding
Authors: Krehenwinkel, Henrik
Wolf, Madeline
Lim, Jun Ying 
Rominger, Andrew J
Simison, Warren B
Gillespie, Rosemary G
Keywords: Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
MITOCHONDRIAL-DNA
BIODIVERSITY ASSESSMENT
EVOLUTION
MARKER
NUMBER
TARGET
Issue Date: 15-Dec-2017
Publisher: NATURE PORTFOLIO
Citation: Krehenwinkel, Henrik, Wolf, Madeline, Lim, Jun Ying, Rominger, Andrew J, Simison, Warren B, Gillespie, Rosemary G (2017-12-15). Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding. SCIENTIFIC REPORTS 7 (1). ScholarBank@NUS Repository. https://doi.org/10.1038/s41598-017-17333-x
Abstract: Amplicon based metabarcoding promises rapid and cost-efficient analyses of species composition. However, it is disputed whether abundance estimates can be derived from metabarcoding due to taxon specific PCR amplification biases. PCR-free approaches have been suggested to mitigate this problem, but come with considerable increases in workload and cost. Here, we analyze multilocus datasets of diverse arthropod communities, to evaluate whether amplification bias can be countered by (1) targeting loci with highly degenerate primers or conserved priming sites, (2) increasing PCR template concentration, (3) reducing PCR cycle number or (4) avoiding locus specific amplification by directly sequencing genomic DNA. Amplification bias is reduced considerably by degenerate primers or targeting amplicons with conserved priming sites. Surprisingly, a reduction of PCR cycles did not have a strong effect on amplification bias. The association of taxon abundance and read count was actually less predictable with fewer cycles. Even a complete exclusion of locus specific amplification did not exclude bias. Copy number variation of the target loci may be another explanation for read abundance differences between taxa, which would affect amplicon based and PCR free methods alike. As read abundance biases are taxon specific and predictable, the application of correction factors allows abundance estimates.
Source Title: SCIENTIFIC REPORTS
URI: https://scholarbank.nus.edu.sg/handle/10635/227723
ISSN: 20452322
DOI: 10.1038/s41598-017-17333-x
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