RNA metabarcoding helps reveal zooplankton community response to environmental stressors

New prospects of environmental RNA metabarcoding research in biological diversity, ecotoxicological monitoring, and detection of COVID-19: a critical review

Ecosystems are multifaceted and complex systems and understanding their composition is crucial for the implementation of efficient conservation and management. Conventional approaches to biodiversity surveys can have limitations in detecting the complete range of species present. In contrast, the study of environmental RNA (eRNA) offers a non-invasive and comprehensive method for monitoring and evaluating biodiversity across different ecosystems. Similar to eDNA, the examination of genetic material found in environmental samples can identify and measure many species, including ones that pose challenges to traditional methods. However, eRNA is degraded quickly and therefore shows promise in detection of living organisms closer to their actual location than eDNA methods. This method provides a comprehensive perspective on the well-being of ecosystems, facilitating the development of focused conservation approaches to save at-risk species and uphold ecological equilibrium. Furthermore, eRNA has been recognized as a valuable method for the identification of COVID-19 in the environment, besides its established uses in biodiversity protection. The SARS-CoV-2 virus, which is accountable for the worldwide epidemic, releases RNA particles into the surrounding environment via human waste, providing insights into the feasibility of detecting it in wastewater and other samples taken from the environment. In this article, we critically reviewed the recent research activities that use the eRNA method, including its utilization in biodiversity conservation, ecological surveillance, and ecotoxicological monitoring as well as its innovative potential in identifying COVID-19. Through this review, the reader can understand the recent developments, prospects, and challenges of eRNA research in ecosystem management and biodiversity conservation.