Just over two decades ago, DNA-based dietary analysis promised to advance the resolution, sensitivity, and speed with which we could detect and identify trophic interactions. Since then, these approaches have generated a paradigm shift in our understanding across a wide range of natural systems. Although decreasing sequencing costs and increased access to sequencing technologies have significantly broadened adoption in recent years, advances in the methods used for dietary analysis have arguably slowed. We stand now, however, at the brink of the next advance, as traditionally DNA-based ecological studies increasingly apply RNA-based methods. To date, this has most commonly taken place in the context of environmental monitoring, and the application to dietary analysis is still underrepresented despite immense potential and relatively straightforward implementation. Given the reduced stability of some RNA types, the detection of consumed resources via RNA alongside DNA can mitigate many longstanding methodological pitfalls of DNA-based dietary analyses alone by (i) differentiating between living and dead resources, (ii) identifying potential false positives, and (iii) providing temporal context to detections, facilitating the construction of weighted or multilayer trophic networks. Detection of functional RNA may also present an opportunity to ascribe functional contexts to both consumers and resources, and contextualise interactions or their impact on wider trophic networks. With the increasing accessibility of RNA-based methods, their application to community and network ecology may significantly advance our ability to analyse and understand trophic interactions in complex natural systems. Here, we summarise RNA-based dietary analysis methods with reference to recent literature in trophic ecology and identify areas that would benefit from additional research. By summarising the immediately identifiable advances and constraints that dietary RNA presents, we hope to stimulate widespread adoption of these approaches and advance integration of RNA-based analyses into trophic ecological research.
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