Analytical and Bioanalytical Chemistry

, Volume 407, Issue 7, pp 1841–1848 | Cite as

Quantitative evaluation of bias in PCR amplification and next-generation sequencing derived from metabarcoding samples

  • Marta Pawluczyk
  • Julia Weiss
  • Matthew G. Links
  • Mikel Egaña Aranguren
  • Mark D. Wilkinson
  • Marcos Egea-CortinesEmail author
Research Paper


Unbiased identification of organisms by PCR reactions using universal primers followed by DNA sequencing assumes positive amplification. We used six universal loci spanning 48 plant species and quantified the bias at each step of the identification process from end point PCR to next-generation sequencing. End point amplification was significantly different for single loci and between species. Quantitative PCR revealed that Cq threshold for various loci, even within a single DNA extraction, showed 2,000-fold differences in DNA quantity after amplification. Next-generation sequencing (NGS) experiments in nine species showed significant biases towards species and specific loci using adaptor-specific primers. NGS sequencing bias may be predicted to some extent by the Cq values of qPCR amplification.


Metabarcoding Next-generation sequencing Ion torrent Cq value PCR efficiency 



This work was performed as partial fulfillment of the PhD of Marta Pawluczyk. This work was funded by the Comunidad Autónoma de la Región de Murcia Project “Molecular markers in conservation and management of the flora of Murcia Region” (“Marcadores moleculares en conservación y gestión de la flora murciana”). Part of the work was performed under the Proyecto Vitalis Campus Mare Nostrum “Espacio Mediterráneo de Investigación en Red en Alimentos y Salud” - CEI10-2-0002.

Data availability

Raw and processed data will be made publicly available via entries in Data Dryad, and a formal Data Descriptor will be published detailing the methodologies and workflows used, as well as rich descriptions of the data elements themselves. The analytical workflow for sequence processing and mapping is already publicly available as a Galaxy workflow, as described in the manuscript, and can be freely re-run at any time. The analysis can be reproduced, with the same parameters and data, at the following Galaxy installation (page:


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Marta Pawluczyk
    • 1
  • Julia Weiss
    • 1
  • Matthew G. Links
    • 2
  • Mikel Egaña Aranguren
    • 3
    • 4
  • Mark D. Wilkinson
    • 3
  • Marcos Egea-Cortines
    • 1
    Email author
  1. 1.Genetics, Instituto de Biotecnología VegetalUniversidad Politécnica de CartagenaCartagenaSpain
  2. 2.Department of Computer ScienceUniversity of Saskatchewan, Saskatoon Research CentreSaskatoonCanada
  3. 3.Centro de Biotecnología y Genómica de Plantas UPM-INIA (CBGP)Pozuelo de Alarcón MadridSpain
  4. 4.Genomic Resources, Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Science and TechnologyUniversity of Basque Country (UPV/EHU)Leioa-BilboSpain

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