Optimizing a metabarcoding primer portfolio for species-level detection
of taxa in complex mixtures of diverse fishes
Abstract
DNA metabarcoding is used to enumerate and identify taxa in both
environmental samples and tissue mixtures. The composition and
resolution of metabarcoding data depend on the primer(s) used. Markers
that amplify different genes can mitigate biases in primer affinity,
amplification efficiency, and reference database resolution, but few
empirical studies have evaluated markers for complementary performance.
Here, we assess the individual and joint performance of 22 markers for
detecting species in a DNA pool of >100 species of
primarily marine and freshwater fishes, but also including
representatives of elasmobranchs, cephalopods, and crustaceans. Marker
performance includes the integrated effect of primer specificity and
reference availability. We find that a portfolio of four markers
targeting 12S, 16S, and multiple regions of COI identifies 100% of
reference taxa to family and nearly 60% to species. We then use the
four markers in this portfolio to evaluate metabarcoding of
heterogeneous tissue mixtures, using experimental fishmeal to test: 1)
the tissue input threshold to ensure detection; 2) how read depth scales
with tissue abundance; and 3) the effect of non-target material in the
mixture on recovery of target taxa. We consistently detect taxa that
make up >1% of fishmeal mixtures and can detect taxa at
the lowest input level of 0.01%, but rare taxa (<1%) were
detected inconsistently across markers and replicates. Read counts
showed weak correlation with tissue input, suggesting they are not a
valid proxy for relative abundance. Despite this limitation, our results
demonstrate the value of a primer portfolio approach—tailored to the
taxa of interest—for detecting and identifying both rare and abundant
species in heterogeneous tissue mixtures.