Data from: Detecting aquatic invasive species in bait and pond stores with targeted environmental (e) DNA high-throughput sequencing metabarcode assays: angler, retailer, and manager implications
Authors/Creators
- 1. National Oceanic and Atmospheric Administration
- 2. University of Michigan–Ann Arbor
- 3. University of Miami
- 4. University of Toledo
Description
Bait and pond stores comprise potential, yet poorly understood, vectors for aquatic invasive species (AIS). We tested for AIS and illegal native species in 51 bait and 21 pond stores from the central Great Lakes (Lake Erie, Ohio and Lake St. Clair, Michigan) and the adjacent Wabash River (Indiana) using environmental DNA (eDNA) metabarcode assays of water samples and morphological identifications. Retailers were questioned about supply chains, and anglers surveyed about baitfish use and disposal. Assays revealed unadvertised species eDNA in 100% of bait stores, with 61% containing illegal native non-bait (totaling 13 species) and 88% having AIS (11 species). Illegal native non-bait species included juvenile walleye, yellow perch, and white sucker eDNA. AIS eDNA included Eurasian ruffe in seven stores (all states), silver carp in five (including a Lake Erie store in two separate years), and bighead carp in two Lake Erie stores that also had silver carp. Among pond stores, two in Lake St. Clair had bighead carp eDNA, one also contained silver carp, and a Wabash River location showed European ide. Unadvertised invasive snails were discerned in 55% of pond stores. Four contained zebra mussel eDNA and two had invasive bryozoans. Illegal native species and AIS were widespread, but showed little relationship to the retailers' variable and extensive supply chains. Live baitfish releases were reported by 50% of Lake Erie anglers and 35% in Lake St. Clair. Consumer behavior and AIS prevalence in the bait and pond trades thus pose serious risks for introductions and spread.
Notes
MetaTrim.py: See README.md
SeqTabToFasta.pl: script converts SeqTab format files with results from Dada2 (R package) to FASTA files for each sample. Expects an input file named SeqTab.txt in the CWD.
BlastCylce500.pl: script performs BLAST searches for every sequence in files ending with ".fasta" in the CWD. BLAST searches are performed against custom databases for all Actinopterygii on GenBank and only fishes in the Great Lakes. If file name begins with "m" (MiFish), sequences are blasted against 12S databases, otherwise, against Cytochrome b databases.
BlastCycle500Remote.pl: script performs BLAST searches for every sequence in files ending with ".fasta" in the CWD. BLAST is performed remotely against the entirety of GenBank.
SummarizeBlasteDNAEnvironmentSepASVs.pl: script summarizes BLAST results (files ending in "Res.txt" from BlastCycle500.pl"). Species names for hits with >90% query cover and identity are concatenated if the e value is the lowest for all hits. Returns a txt file with summarized hits per sample. Expects an input file named InReads.txt in the CWD. This file is tab delimited. The first value should be the sample name identical to that used as input in the above script, followed by tab, then the number of reads in that sample. This allows calculation of proportion of read represented by the hit.
BOPPSummarize*.py: script removes species hits that do not occur at a portion above the error for a specific marker in a specific sample, unless the occur in multiple markers in that same sample. Hits are then compared against morphological results from bait and pond stores. Several inputs are required and are included in this repository. They include a file showing the error rate calculated from positive controls for each marker on each sequencing run (ErrorCons.txt; if none is supplied, the default value will be 0.001), a shop key file (ShopKeybaitShops.txt), a file indicating the legality of species in each state sampled (SppStatusBait.txt), morphological results from each store at the time of sampling (InMorph.txt), and BLAST results files (summarized by the script above, separated by marker).
Funding provided by: Environmental Protection Agency
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100001589
Funding provided by: National Science Foundation
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000001
Files
ErrorCons.txt
Files
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Additional details
Related works
- Is cited by
- 10.1016/j.biocon.2020.108430 (DOI)