READS WITH RELEVANCE: QUANTIFYING DNA METABARCODING FOR IMPROVED UNDERSTANDING OF PROTISTAN COMMUNITIES

DNA metabarcoding is a powerful and popular technique for investigating the composition of protistan communities, revealing the presence of cryptic and hard-to-visualize taxa. Despite its many advantages, metabarcoding results can be difficult to interpret because the commonly-used 18S rRNA gene can vary by orders of magnitude among individuals. Furthermore, DNA metabarcoding yields compositional data, giving relative rather than absolute abundances. Together, these characteristics impede translation of metabarcoding data into ecologically useful metrics. Here, we conducted metabarcoding of mock and in situ communities using multiple primer sets and both DNA and cDNA as PCR templates. Mock communities were constructed from uni-algal cultures of taxonomically diverse phytoplankton and in situ samples were collected weekly over one month from the Narragansett Bay Long-Term Plankton Time Series. These communities were used to identify correlation coefficients of metabarcoding results and ecologically useful metrics such as cell number and biomass. As expected, our results highlight that relative read number is poorly correlated with relative cell number at the V4 region of the 18S rRNA gene. On-going analyses will yield quantitative correlations of metabarcoding data with other gene regions and nucleic acids yielding important insights into how metabarcoding can and cannot be used to interpret the composition and quantity of natural communities.

Presentation Preference: Oral

Primary Presenter: Fran Webber, University of Rhode Island (fwebber@uri.edu)

Authors:

Fran Webber, University of Rhode Island, Graduate School of Oceanography  (fwebber@uri.edu)

Samantha Setta, University of Washington, CICOES; National Oceanic Atmospheric Association, PMEL  (samantha.setta@noaa.gov)

Tatiana Rynearson, University of Rhode Island, Graduate School of Oceanography  (rynearson@uri.edu)