Quantitative evaluation of bias in PCR amplification and next-generation sequencing derived from metabarcoding samples
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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.
KeywordsMetabarcoding 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.
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: http://biordf.org:8983/u/mikel-egana-aranguren/p/sources-of-bias-in-applying-barcoding-markers-for-sequence-analysis-of-environmental-samples).
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