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Avoiding quantification bias in metabarcoding: Application of a cell biovolume correction factor in diatom molecular biomonitoring

Abstract : 1. 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 rbcL gene appears to be a suitable barcode for diatoms, providing relevant qualitative data to describe taxonomic composition, improvement of species quantifica-tion is still required. 2. Here, we hypothesized that rbcL copy number is correlated with diatom cell biovol-ume (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 rbcL 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 rbcL barcode. 3. 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 ben-thic biofilms) for which the application of CF allowed differences between molecular and morphological water quality indices to be reduced by 47%. 4. 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. K E Y W O R D S benthic diatom, biovolume correction factor, freshwater ecosystems, gene copy number variation, quantitative metabarcoding
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Submitted on : Monday, August 17, 2020 - 5:16:13 PM
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Valentin Vasselon, Agnès Bouchez, Frédéric Rimet, Stéphan Jacquet, Rosa Trobajo, et al.. Avoiding quantification bias in metabarcoding: Application of a cell biovolume correction factor in diatom molecular biomonitoring. Methods in Ecology and Evolution, Wiley, 2017, 9 (4), pp.1060-1069. ⟨10.1111/2041-210X.12960⟩. ⟨hal-02916343⟩



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