Format

Send to

Choose Destination
Mol Ecol Resour. 2018 May 24. doi: 10.1111/1755-0998.12895. [Epub ahead of print]

Minimizing polymerase biases in metabarcoding.

Author information

1
Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, California.
2
Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California.
3
Department of Social Sciences, Flagler College, St. Augustine, Florida.
4
Department of Geography, University of Wisconsin-Madison, Madison, Wisconsin.
5
Tromsø University Museum, UiT - The Arctic University of Norway, Tromsø, Norway.

Abstract

DNA metabarcoding is an increasingly popular method to characterize and quantify biodiversity in environmental samples. Metabarcoding approaches simultaneously amplify a short, variable genomic region, or "barcode," from a broad taxonomic group via the polymerase chain reaction (PCR), using universal primers that anneal to flanking conserved regions. Results of these experiments are reported as occurrence data, which provide a list of taxa amplified from the sample, or relative abundance data, which measure the relative contribution of each taxon to the overall composition of amplified product. The accuracy of both occurrence and relative abundance estimates can be affected by a variety of biological and technical biases. For example, taxa with larger biomass may be better represented in environmental samples than those with smaller biomass. Here, we explore how polymerase choice, a potential source of technical bias, might influence results in metabarcoding experiments. We compared potential biases of six commercially available polymerases using a combination of mixtures of amplifiable synthetic sequences and real sedimentary DNA extracts. We find that polymerase choice can affect both occurrence and relative abundance estimates and that the main source of this bias appears to be polymerase preference for sequences with specific GC contents. We further recommend an experimental approach for metabarcoding based on results of our synthetic experiments.

KEYWORDS:

bias; eDNA; environmental DNA; metabarcoding; soil; trnL P6 loop

PMID:
29797549
DOI:
10.1111/1755-0998.12895

Supplemental Content

Full text links

Icon for Wiley
Loading ...
Support Center