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Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding

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...

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Detalles Bibliográficos
Autores principales: Krehenwinkel, Henrik, Wolf, Madeline, Lim, Jun Ying, Rominger, Andrew J., Simison, Warren B., Gillespie, Rosemary G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5732254/
https://www.ncbi.nlm.nih.gov/pubmed/29247210
http://dx.doi.org/10.1038/s41598-017-17333-x
Descripción
Sumario: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.