Data from: Development and validation of targeted environmental DNA (eDNA) metabarcoding for early detection of 69 invasive fishes and aquatic invertebrates

Invasive species are of concern due to their impacts on ecosystems and
economies, but they pose significant control challenges. Environmental DNA
(eDNA) is a powerful tool in the detection of aquatic organisms at low
densities due to high sensitivity and ease of collection. Aquatic eDNA
analyses have increased worldwide and are generally either applied to a
few target species (quantitative PCR) or for broad taxonomic applications
(metabarcoding).  Here we describe the development and testing of
a hybrid approach that utilized high sensitivity PCR primer sets and
high-throughput sequencing (HTS), referred to as targeted metabarcoding,
to detect 69 fishes and invertebrates. We identified target species based
on reports of globally important invasive species and developed two
independent PCR primers for each species (CO1 and a second mtDNA region).
We assessed sensitivity and eDNA interference for all 138 primers (2 per
species, 69 species) using standard end-point PCR and tested them on 10
eDNA samples spiked with various amounts of one or more of the target
species' DNA.  The sensitivity of the 138 primer sets ranged
between 1.5×10-5 and 2.64 ng template DNA (mean = 0.069 ng). Primers were
also tested for interference effects using plankton eDNA to simulate field
conditions. The inclusion of interfering plankton DNA reduced the
sensitivity for most primer sets by one or more orders of magnitude (range
0 to 3). Overall, our targeted metabarcoding resulted in the detection of
~ 98% of species in the DNA spiked samples, and, perhaps more importantly,
the HTS read count was positively related to the quantity of spiked DNA (P
< 0.002).  We envision this technique being particularly
useful for the early detection of species at low population densities;
however, there are diverse applications of targeted metabarcoding for
monitoring aquatic community composition and quantifying ecosystem change
and health.