| Literature DB >> 34398515 |
Anastasija Zaiko1,2, Paul Greenfield3,4, Cathryn Abbott5, Ulla von Ammon1, Jaret Bilewitch6, Michael Bunce7, Melania E Cristescu8, Anthony Chariton4, Eddy Dowle9, Jonathan Geller10, Alba Ardura Gutierrez11, Mehrdad Hajibabaei12, Emmet Haggard10, Graeme J Inglis13, Shane D Lavery2,14, Aurelija Samuiloviene15, Tiffany Simpson16, Michael Stat17, Sarah Stephenson3, Judy Sutherland6, Vibha Thakur14, Kristen Westfall5, Susanna A Wood1, Michael Wright12, Guang Zhang8, Xavier Pochon1,2.
Abstract
Advances in high-throughput sequencing (HTS) are revolutionizing monitoring in marine environments by enabling rapid, accurate and holistic detection of species within complex biological samples. Research institutions worldwide increasingly employ HTS methods for biodiversity assessments. However, variance in laboratory procedures, analytical workflows and bioinformatic pipelines impede the transferability and comparability of results across research groups. An international experiment was conducted to assess the consistency of metabarcoding results derived from identical samples and primer sets using varying laboratory procedures. Homogenized biofouling samples collected from four coastal locations (Australia, Canada, New Zealand and the USA) were distributed to 12 independent laboratories. Participants were asked to follow one of two HTS library preparation workflows. While DNA extraction, primers and bioinformatic analyses were purposefully standardized to allow comparison, many other technical variables were allowed to vary among laboratories (amplification protocols, type of instrument used, etc.). Despite substantial variation observed in raw results, the primary signal in the data was consistent, with the samples grouping strongly by geographical origin for all data sets. Simple post hoc data clean-up by removing low-quality samples gave the best improvement in sample classification for nuclear 18S rRNA gene data, with an overall 92.81% correct group attribution. For mitochondrial COI gene data, the best classification result (95.58%) was achieved after correction for contamination errors. The identified critical methodological factors that introduced the greatest variability (preservation buffer, sample defrosting, template concentration, DNA polymerase, PCR enhancer) should be of great assistance in standardizing future biodiversity studies using metabarcoding.Entities:
Keywords: 18S ribosomal rRNA (18S rRNA); high-throughput sequencing; metabarcoding; mitochondrial cytochrome c oxidase subunit 1 (COI); reproducibility; standardization
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Year: 2021 PMID: 34398515 DOI: 10.1111/1755-0998.13485
Source DB: PubMed Journal: Mol Ecol Resour ISSN: 1755-098X Impact factor: 7.090