Back

Targeted hybridization capture enables comprehensive detection of freshwater bioassessment invertebrates from environmental DNA

Craine, J. M.; Darcy, J. L.; Devitt, J.; Leopold, D.; Miller, G. W.; Ralson, M.; Schulte, N.; Fierer, N.

2026-08-19 ecology
10.64898/2026.08.14.744904 bioRxiv
Show abstract

Freshwater bioassessment relies on assessing aquatic assemblages to infer ecological conditions, yet conventional surveys require extensive field sampling, specimen processing, and specialized taxonomic expertise. Existing environmental DNA (eDNA) methods have not yet provided a practical alternative to conventional macroinvertebrate assays in part because current approaches cannot feasibly recover broad taxonomic diversity at sufficient taxonomic resolution. Here, we evaluated targeted hybridization capture of mitochondrial cytochrome oxidase I (COI) target sequences as a unified molecular approach for cross-phylum freshwater bioassessment. Environmental DNA was collected at 18 sites along 63 km of Boulder Creek spanning nearly 1,500 m of elevation from forested headwaters to agricultural plains. COI targets were enriched using custom RNA bait panels designed to target regional freshwater arthropods, annelids, and molluscs. Hybridization capture increased recovery of COI sequences [~]1,760-fold relative to unenriched shotgun libraries, generating Folmer-region COI contigs that averaged [~]400 bp. Across the watershed, we recovered sequences for approximately 450 macroinvertebrate genera across 8 phyla. Detected macroinvertebrate richness averaged 56 genera per site and increased down Boulder Canyon before declining downstream of the city. Macroinvertebrate assemblage composition from hybridization capture paralleled patterns observed with past conventional bioassessment. These results demonstrate that targeted hybridization capture enables robust, cross-phylum detection of species used for freshwater bioassessment from environmental DNA.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.