Metabarcoding by Combining Environmental DNA with Environmental RNA to Monitor Fish Species in the Han River, Korea

Abstract

Fishes are ecologically important organisms that have long lifespans, high mobilities, and diverse trophic levels. Due to their importance, fishes are used as bioindicators for monitoring aquatic environments. One method for monitoring fishes is based on environmental DNA (eDNA), which are the deoxynucleic acids released by organisms into the environment. However, there has been a problem with false positives because eDNA is relatively stable in the environment and could even likely represent dead or non-inhabiting organisms. To address this weakness, environmental RNA (eRNA), which degrades more rapidly than eDNA in the environment, can be utilized to complement eDNA. But, to date, few studies have used eRNA for freshwater fish monitoring. In this study, to determine the relative usefulness of eDNA and eRNA metabarcoding in freshwater fishes, we performed eDNA and eRNA metabarcoding on 12S rRNA targeting fish using water samples that were collected from three locations in the Han River. We then calculated the sensitivity and positive predictivity of this approach by comparing our data to the previous specimen capture survey (PSCS) data from the last six years. The results showed that 42 species were detected by eDNA and 19 by eRNA at the three locations. At all locations, compared to the PSCS data, the average sensitivity was higher for eDNA (46.1%) than for eRNA (34.6%), and the average positive predictivity was higher for eRNA (31.7%) than for eDNA (20.7%). This confirmed that eDNA metabarcoding has the advantage of broadly determining species presence or absence (including those that are no longer present or dead), but it also generates false positives; meanwhile, eRNA metabarcoding reports living fish species, but detects fewer species than eDNA. Combining eDNA and eRNA therefore emphasizes their advantages and compensates for their disadvantages, and conducting this may therefore be useful for identifying false positives and monitoring the fish species that are actually present in the environment. This metabarcoding technique can be used in the future to provide insights into the aquatic environment and the monitoring of fisheries.