Minimizing polymerase biases in metabarcoding

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.

Quantitative and qualitative assessment of pollen DNA metabarcoding using constructed species mixtures

“…Sources of bias, particularly isolation and amplification biases have been examined in detail for microbiological studies (Brooks et al., ), but not for studies on pollen, and very few for any other complex eukaryotes (Nichols et al. ). While most of these biases will be the same regardless of the sample type, for DNA isolation efficiency and marker copy number, the properties of pollen will differ from other organisms, or even other tissue types within plants.…”

Metabarcoding a diverse arthropod mock community

“…BIN accumulation curves indicated that the read depth employed in this study allowed all four treatments to meet a slope of < 0.01. However, the Single Leg treatment reached this value with much lower read depth than the bulk samples due to its relative protection from the impacts of PCR bias (Nichols et al ; Pan et al, , Dabney & Meyer, ; Elbrecht & Leese, ). Interestingly, the other three treatments showed similar BIN accumulation curves on all three sequencers, suggesting shared factors constrain BIN recovery.…”

“…The Miseq produced the highest quality reads, suggesting that the higher incidence of unmatched reads on the Ion Torrent platforms reflect, in part, sequencing errors, especially the PGM which has a steep decline in quality towards the 3’ end (Supporting Information Figure S1). PCR errors introduced by the DNA polymerase can be exacerbated by sequencing errors (Dabney & Meyer, ; Nichols et al, ; Pan et al, ). Because long amplicons improve taxonomic resolution, their use should be standard for metabarcoding studies unless template DNA is degraded.…”

“…First, DNA templates derived from the species in a mixed sample are often differentially amplified (Elbrecht & Leese, ; Piñol, Mir, Gomez‐Polo, & Agustí, ; Tedersoo et al, ). Such bias can arise from either the DNA polymerase (Dabney & Meyer, ; Nichols et al, ; Pan et al, ) or the PCR primers (Clarke, Soubrier, Weyrich, & Cooper, ). Polymerase bias involves the differential amplification of templates as a result of variation in their sequence motifs, GC content or length (Dabney & Meyer, ; Nichols et al, ; Pan et al, ).…”

“…Such bias can arise from either the DNA polymerase (Dabney & Meyer, ; Nichols et al, ; Pan et al, ) or the PCR primers (Clarke, Soubrier, Weyrich, & Cooper, ). Polymerase bias involves the differential amplification of templates as a result of variation in their sequence motifs, GC content or length (Dabney & Meyer, ; Nichols et al, ; Pan et al, ). Primer bias arises due to either varying levels of primer mismatch or template degradation (Clarke et al, ; Elbrecht & Leese, ).…”