Observation Bias in Metabarcoding

Details

• Journal Title:
  Molecular Ecology Resources
• Personal Author:
  Shaffer, Megan R. ; Andruszkiewicz Allan, Elizabeth ; Van Cise, Amy M. ; Parsons, Kim M. ; Shelton, Andrew Olaf ; Kelly, Ryan P.
• NOAA Program & Office:
  NMFS (National Marine Fisheries Service) ; NWFSC (Northwest Fisheries Science Center)
• Description:
  DNA metabarcoding is subject to observation bias associated with PCR and sequencing, which can result in observed read proportions differing from actual species proportions in the DNA extract. Here, we amplify and sequence a mock community of known composition containing marine fishes and cetaceans using four different primer sets and a variety of PCR conditions. We first compare metabarcoding observations to two different sets of expected species proportions based on total genomic DNA and on target mitochondrial template DNA. We find that calibrating observed read proportions based on template DNA concentration is most appropriate as it isolates PCR amplification bias; calibration with total genomic DNA results in bias that can be attributed to both PCR amplification bias and differing ratios of template to total genomic DNA. We then model the remaining amplification bias and find that approximately 60% can be explained by inherent species‐specific DNA characteristics. These include primer‐template mismatches, amplicon fragment length, and GC content, which vary somewhat across Taq polymerases. Finally, we investigate how different PCR protocols influence community composition regardless of expected proportions and find that changing protocols most strongly influence the amplification of templates with primer mismatches. Our findings suggest that using primer‐template pairs without mismatches and targeting a narrow taxonomic group can yield more repeatable and accurate estimates of species' true, underlying DNA template proportions. These findings identify key factors that should be considered when designing studies that aim to apply metabarcoding data quantitatively.
• Source:
  Molecular Ecology Resources (2025)
• DOI:
  https://doi.org/10.1111/1755-0998.14119
• ISSN:
  1755-098X ; 1755-0998
• Format:
  PDF
• Publisher:
  Wiley
• Document Type:
  Journal Article
• License:
  https://creativecommons.org/licenses/by/4.0/
• Rights Information:
  CC BY
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:3c6fa39e9ea6ae0338bdfd642f678b3693a32c56dfc4392e5a861577b8314b00cdad66e2e50fbc4c77190360764080be85011cfcc337a35daf9dc2781f50337c
• Download URL:
  https://repository.library.noaa.gov/view/noaa/70556/noaa_70556_DS1.pdf
• File Type:
  [PDF - 1.61 MB ]