Refining the snapshot using environmental RNA

One concern with eDNA approaches is that the eDNA signal may persist in the environment for a long period of time, and can derive from decaying dead organisms or organisms that are no longer present in the environment (Marshall et al. 2021). This leads to false positive detections (at least in the temporal sense as the organism was indeed present at one time) and may constrain assessments of rapid changes in communities.

Environmental RNA (eRNA) has received increasing attention over the past few years to assess local and living communities. Indeed, eRNA reflects metabolically active assemblages and thus has potentially a higher turnover than eDNA (Cristescu 2019; Yates et al. 2021). eRNA is less stable than eDNA and thus degrades faster (Kagzi et al. 2022), but can still be filtered from water and metabarcoded to reliably provide species composition information (Littlefair et al. 2022). Its potential goes beyond species detections (see Hechler and Cristescu, 2024). RNA plays a crucial role in gene expression, so it offers the possibility to assess the health of ecosystems by analysing the transcriptional profiles of environmental samples (metatranscriptomics) (Yates et al. 2021), and can even be used to distinguish life stages when target genes are exclusively expressed in one life stage (Parsley and Goldberg 2023).

The genomic origin (mitochondrial vs nuclear) and marker characteristics (e.g. ribosomal vs protein-coding gene) are important factors to consider in eRNA work (Marshall et al. 2021; Kagzi et al. 2023). Mitochondrial genome copies (e.g. COI) are more numerous than nuclear copies (e.g. except for repetitive nuclear ribosomal markers such as 18S), but mRNA is single-stranded so less stable than rRNA (transcribed rRNA make stable ribosome complex with ribosomal proteins). Finally, eRNA studies are still limited by higher cost and labour than eDNA based studies because eRNA must be processed with extra-care and an expensive additional step (reverse transcription from RNA to cDNA) (Macher 2023).