Multi-omic Environmental Monitoring Reveals When Molecular Signals Reflect Living Biology

Authors

Ip, Y. C. A., Guri, G., Brandao-Dias, P. F. P., Allan, E. A., Kelly, R. P.

Abstract

Environmental molecular monitoring has transformed biodiversity detection, yet most methods capture only species presence through amplified DNA fragments, missing the biological information encoded in native nucleic acids. Here we show that a single shotgun Oxford Nanopore sequencing library from water can be read through several independent biological lenses, and that each class of molecule (environmental RNA, CpG methylation, and bulk DNA) differs in its environmental persistence, which sets the window over which signal can be trusted. Sampling Pacific salmon spawning runs, we simultaneously recovered environmental RNA indicating fresh biological input, CpG methylation profiles reflecting age demographics, and pathogen signatures reflecting health. Environmental RNA tracked spawning phenology, qPCR corroborated the timing of fresh biological input over the weeks sampled, and methylation-based age inference held only while fresh DNA dominated, a condition we term the 'Freshness Gate.' Because environmental water is not a tissue sample, we detect functional transcripts as evidence of biological input but do not infer differential gene expression, and we read methylation state but do not infer biological age outside the Freshness Gate. Variance partitioning is consistent with biological freshness, rather than technical factors such as fragment length or sequencing depth, structuring environmental methylation, though these comparisons did not reach significance at nine time points. Comparable dynamics were observed in Chinook salmon, with timing offsets following their distinct spawning season. By defining when environmental molecules faithfully encode living biology and when degradation decouples signal from current state, our framework sets practical and theoretical boundaries for multi-omic environmental monitoring.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 08 Sep 2026.

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