Environmental Monitoring: Inferring the Diatom Index from Next-Generation Sequencing Data
Abstract
Diatoms are widely used as bioindicators for the assessment of water quality in rivers and streams. Classically, the diatom biotic indices are based on the relative abundance of morphologically identified species weighted by their autoecological value. Obtaining such indices is time-consuming, costly, and requires excellent taxonomic expertise, which is not always available. Here we tested the possibility to overcome these limitations using a next-generation sequencing (NGS) approach to identify and quantify diatoms found in environmental DNA and RNA samples. We analyzed 27 river sites in the Geneva area (Switzerland), in order to compare the values of the Swiss Diatom Index (DI-CH) computed either by microscopic quantification of diatom species or directly from NGS data. Despite gaps in the reference database and variations in relative abundance of analyzed species, the diatom index shows a significant correlation between morphological and molecular data indicating similar biological quality status for the majority of sites. This proof-of-concept study demonstrates the potential of the NGS approach for identification and quantification of diatoms in environmental samples, opening new avenues toward the routine application of genetic tools for bioassessment and biomonitoring of aquatic ecosystems.