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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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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
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author Krehenwinkel, Henrik
Wolf, Madeline
Lim, Jun Ying
Rominger, Andrew J.
Simison, Warren B.
Gillespie, Rosemary G.
author_facet Krehenwinkel, Henrik
Wolf, Madeline
Lim, Jun Ying
Rominger, Andrew J.
Simison, Warren B.
Gillespie, Rosemary G.
author_sort Krehenwinkel, Henrik
collection PubMed
description 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.
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spelling pubmed-57322542017-12-21 Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding Krehenwinkel, Henrik Wolf, Madeline Lim, Jun Ying Rominger, Andrew J. Simison, Warren B. Gillespie, Rosemary G. Sci Rep Article 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. Nature Publishing Group UK 2017-12-15 /pmc/articles/PMC5732254/ /pubmed/29247210 http://dx.doi.org/10.1038/s41598-017-17333-x Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Krehenwinkel, Henrik
Wolf, Madeline
Lim, Jun Ying
Rominger, Andrew J.
Simison, Warren B.
Gillespie, Rosemary G.
Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding
title Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding
title_full Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding
title_fullStr Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding
title_full_unstemmed Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding
title_short Estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding
title_sort estimating and mitigating amplification bias in qualitative and quantitative arthropod metabarcoding
topic Article
url 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
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