Yan Zhang , Yu Qiu , Kai Liu , Wenjun Zhong , Jianghua Yang , Florian Altermatt , Xiaowei Zhang
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引用次数: 0
Abstract
The monitoring and management of aquatic ecosystems depend on precise estimates of biodiversity. Metabarcoding analyses of environmental nucleic acids (eNAs), including environmental DNA (eDNA) and environmental RNA (eRNA), have garnered attention for their cost-effective and non-invasive biomonitoring capabilities. However, the accuracy of biodiversity estimates obtained through eNAs can vary among different organismal groups. Here we evaluate the performance of eDNA and eRNA metabarcoding across nine organismal groups, ranging from bacteria to terrestrial vertebrates, in three cross-sections of the Yangtze River, China. We observe robust complementarity between eDNA and eRNA data. The relative detectability of eNAs was notably influenced by major taxonomic groups and organismal sizes, with eDNA providing more robust signals for larger organisms. Both eDNA and eRNA exhibited similar cross-sectional and longitudinal patterns. However, the detectability of larger organisms declined in eRNA metabarcoding, possibly due to differential RNA release and decay among different organismal groups or sizes. While underscoring the potential of eDNA and eRNA in large river biomonitoring, we emphasize the need for differential interpretation of eDNA versus eRNA data. This highlights the importance of careful method selection and interpretation in biomonitoring studies.
期刊介绍:
Environmental Science & Ecotechnology (ESE) is an international, open-access journal publishing original research in environmental science, engineering, ecotechnology, and related fields. Authors publishing in ESE can immediately, permanently, and freely share their work. They have license options and retain copyright. Published by Elsevier, ESE is co-organized by the Chinese Society for Environmental Sciences, Harbin Institute of Technology, and the Chinese Research Academy of Environmental Sciences, under the supervision of the China Association for Science and Technology.