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Avoiding quantification bias in metabarcoding: Application of a cell biovolume correction factor in diatom molecular biomonitoring
Author(s) -
Vasselon Valentin,
Bouchez Agnès,
Rimet Frédéric,
Jacquet Stéphan,
Trobajo Rosa,
Corniquel Méline,
Tapolczai Kálmán,
Domaizon Isabelle
Publication year - 2018
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12960
Subject(s) - diatom , biomonitoring , biology , dna barcoding , taxon , benthic zone , relative species abundance , ecology , abundance (ecology)
In recent years, remarkable progress has been made in developing environmental DNA metabarcoding. However, its ability to quantify species relative abundance remains uncertain, limiting its application for biomonitoring. In diatoms, although the rbc L gene appears to be a suitable barcode for diatoms, providing relevant qualitative data to describe taxonomic composition, improvement of species quantification is still required. Here, we hypothesized that rbc L copy number is correlated with diatom cell biovolume (as previously described for the 18S gene) and that a correction factor ( CF ) based on cell biovolume should be applied to improve taxa quantification. We carried out a laboratory experiment using pure cultures of eight diatom species with contrasted cell biovolumes in order to (1) verify the relationship between rbc L copy numbers (estimated by qPCR ) and diatom cell biovolumes and (2) define a potential CF . In order to evaluate CF efficiency, five mock communities were created by mixing different amounts of DNA from the eight species, and were sequenced using HTS and targeting the same rbc L barcode. As expected, the correction of DNA reads proportions by the CF improved the congruence between morphological and molecular inventories. Final validation of the CF was obtained on environmental samples (metabarcoding data from 80 benthic biofilms) for which the application of CF allowed differences between molecular and morphological water quality indices to be reduced by 47%. Overall, our results highlight the usefulness of applying a CF factor, which is effective in reducing over‐estimation of high biovolume species, correcting quantitative biases in diatom metabarcoding studies and improving final water quality assessment.