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Mock community experiments can inform on the reliability of eDNA metabarcoding data: a case study on marine phytoplankton

Articolo
Data di Pubblicazione:
2023
Abstract:
: Environmental DNA metabarcoding is increasingly implemented in biodiversity monitoring, including phytoplankton studies. Using 21 mock communities composed of seven unicellular diatom and dinoflagellate algae, assembled with different composition and abundance by controlling the number of cells, we tested the accuracy of an eDNA metabarcoding protocol in reconstructing patterns of alpha and beta diversity. This approach allowed us to directly evaluate both qualitative and quantitative metabarcoding estimates. Our results showed non-negligible rates (17-25%) of false negatives (i.e., failure to detect a taxon in a community where it was included), for three taxa. This led to a statistically significant underestimation of metabarcoding-derived alpha diversity (Wilcoxon p = 0.02), with the detected species richness being lower than expected (based on cell numbers) in 8/21 mock communities. Considering beta diversity, the correlation between metabarcoding-derived and expected community dissimilarities was significant but not strong (R2 = 0.41), indicating suboptimal accuracy of metabarcoding results. Average biovolume and rDNA gene copy number were estimated for the seven taxa, highlighting a potential, though not exhaustive, role of the latter in explaining the recorded biases. Our findings highlight the importance of mock communities for assessing the reliability of phytoplankton eDNA metabarcoding studies and identifying their limitations.
Tipologia CRIS:
01.01 - Articolo in rivista
Elenco autori:
Marinchel, N; Marchesini, A; Nardi, D; Girardi, M; Casabianca, S; Vernesi, C; Penna, A
Autori di Ateneo:
NARDI DAVIDE
Link alla scheda completa:
https://www.research.unipd.it/handle/11577/3504464
Link al Full Text:
https://www.research.unipd.it//retrieve/handle/11577/3504464/925746/unpaywall-bitstream-196076911.pdf
Pubblicato in:
SCIENTIFIC REPORTS
Journal
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