Towards reproducible metabarcoding data: Lessons from an international cross‐laboratory experiment

Abstract

Advances in high-throughput sequencing (HTS) are revolutionizing monitoring in ma-rine environments by enabling rapid, accurate and holistic detection of species withincomplex biological samples. Research institutions worldwide increasingly employHTS methods for biodiversity assessments. However, variance in laboratory proce-dures, analytical workflows and bioinformatic pipelines impede the transferabilityand comparability of results across research groups. An international experiment wasconducted to assess the consistency of metabarcoding results derived from identicalsamples and primer sets using varying laboratory procedures. Homogenized biofoul-ing samples collected from four coastal locations (Australia, Canada, New Zealand andthe USA) were distributed to 12 independent laboratories. Participants were asked to follow one of two HTS library preparation workflows. While DNA extraction, prim-ers and bioinformatic analyses were purposefully standardized to allow comparison,many other technical variables were allowed to vary among laboratories (amplifica-tion protocols, type of instrument used, etc.). Despite substantial variation observedin raw results, the primary signal in the data was consistent, with the samples group -ing strongly by geographical origin for all data sets. Simple post hoc data clean-up byremoving low-quality samples gave the best improvement in sample classification fornuclear 18S rRNA gene data, with an overall 92.81% correct group attribution. For mi-tochondrial COI gene data, the best classification result (95.58%) was achieved aftercorrection for contamination errors. The identified critical methodological factorsthat introduced the greatest variability (preservation buffer, sample defrosting, tem-plate concentration, DNA polymerase, PCR enhancer) should be of great assistance instandardizing future biodiversity studies using metabarcoding.