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Monitoring the ecological status of rivers with diatom eDNA metabarcoding: A comparison of taxonomic markers and analytical approaches for the inference of a molecular diatom index
Author(s) -
ApothélozPerretGentil Laure,
Bouchez Agnès,
Cordier Tristan,
Cordonier Arielle,
Guéguen Julie,
Rimet Frederic,
Vasselon Valentin,
Pawlowski Jan
Publication year - 2021
Publication title -
molecular ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.619
H-Index - 225
eISSN - 1365-294X
pISSN - 0962-1083
DOI - 10.1111/mec.15646
Subject(s) - diatom , biology , inference , benchmark (surveying) , ecology , taxonomy (biology) , index (typography) , computational biology , artificial intelligence , computer science , cartography , world wide web , geography
Recently, several studies demonstrated the usefulness of diatom eDNA metabarcoding as an alternative to assess the ecological quality of rivers and streams. However, the choice of the taxonomic marker as well as the methodology for data analysis differ between these studies, hampering the comparison of their results and effectiveness. The aim of this study was to compare two taxonomic markers commonly used in diatom metabarcoding and three distinct analytical approaches to infer a molecular diatom index. We used the values of classical morphological diatom index as a benchmark for this comparison. We amplified and sequenced both a fragment of the rbc L gene and the V4 region of the 18S rRNA gene for 112 epilithic samples from Swiss and French rivers. We inferred index values using three analytical approaches: by computing it directly from taxonomically assigned sequences, by calibrating de novo the ecovalues of all metabarcodes, and by using a supervised machine learning algorithm to train predictive models. In general, the values of index obtained using the two “taxonomy‐free” approaches, encompassing molecular assignment and machine learning, were closer correlated to the values of the morphological index than the values based on taxonomically assigned sequences. The correlations of the three analytical approaches were higher in the case of rbc L compared to the 18S marker, highlighting the importance of the reference database which is more complete for the rbc L marker. Our study confirms the effectiveness of diatom metabarcoding as an operational tool for rivers ecological quality assessment and shows that the analytical approaches by‐passing the taxonomic assignments are particularly efficient when reference databases are incomplete.