<p>Environmental DNA (eDNA) discovery has changed aquatic monitoring with non-invasive techniques used to detect species, evaluate biodiversity, and track pathogens. Regardless, typical eDNA-based analyses provide information on presence and abundance of species, but minimal insights into physiological state, stress-response, or adaptation mechanisms elicited in organisms. The study of epigenetics, which examines dynamics in gene expression that do not involve changes in underlying DNA sequence, provides more insight into how organisms engage with their environment. The recent concept of “epigenetics-environmental DNA (epi-eDNA)” posits that epigenetic marks on eDNA fragments can act as effective indicators of the source organisms’ recent physiological status, developmental processes, or environmental exposure. This review consolidates the current knowledge on the mechanisms of epi-eDNA formation, release pathways, and environmental persistence in aquatic systems, outlining analytical strategies for recovering and characterizing epigenetic marks from environmental samples, including bisulfite sequencing, methylation-sensitive restriction assays, and emerging direct-read sequencing platforms. Potential applications of epi-eDNA have been further highlighted, including monitoring and tracking species and populations in aquaculture, disease detection, physiological stress, identification of quality broodstock and feeding responses, documenting interactions between cultivated and natural populations, and evaluating ecosystem health related to environmental change. Although technical challenges persist, such as low quantity of DNA, epigenetic marks deteriorate, challenging interpretations of tissue-specific signals, and absence of standardized workflows within this research field, the potential to combine epi-eDNA with multi-omics, informed machine learning applications, and real-time environmental sensing in future holds promise for predictive and precision aquaculture management, as well as advancing ecological sustainability. </p> Graphical Abstract <p></p>