eRNA metabarcoding for biodiversity surveys
Environmental DNA (eDNA) metabarcoding has emerged as a promising approach to assess biodiversity and derive ecological status classes from water samples. However, limitation of eDNA surveys is that detected DNA molecules may come from other places or even dead organisms, distorting local biodiversity assessments. Environmental RNA (eRNA) metabarcoding was recently proposed as a complementary tool for more localized assessments of the biological community. In this study, we compared the richness and community patterns inferred by eDNA and eRNA metabarcoding targeting vertebrates (12S) and invertebrates (COI) from water samples collected in a Central European lowland river. Overall, we detected 31 fish, 16 mammal, 10 bird, and 1 lamprey species in the vertebrate dataset. Alpha diversity was higher for the eRNA dataset than for the eDNA dataset. Additionally, we detected a positive correlation between the locality of genetic signals and species distribution patterns based on traditional fish monitoring data. In the invertebrate dataset, we detected 109 arthropod, 22 annelid, 12 rotiferan, 8 molluscan, and 4 cnidarian species. In contrast to the pattern of vertebrate diversity, invertebrate alpha diversity was higher in the eDNA dataset than in the eRNA dataset. Overall, while eRNA-based monitoring is an efficient method to assess stream-associated vertebrates, the assessment of invertebrates remains difficult. These results provide insight into the advantages, limitations and scope of applications of eRNA metabarcoding for biodiversity monitoring and research. Keywords: biomonitoring, environmental RNA, environmental DNA, COI, 12S.