DNA barcodes combined with multi-locus data of representative taxa can generate reliable higher-level phylogenies

Taxa are frequently labeled incertae sedis when their placement is debated
at ranks above the species level, such as their subgeneric, generic, or
subtribal placement. This is a pervasive problem in groups with complex
systematics due to difficulties in identifying suitable synapomorphies. In
this study, we propose combining DNA barcodes with a multilocus backbone
phylogeny in order to assign taxa to genus or other higher-level
categories. This sampling strategy generates molecular matrices containing
large amounts of missing data that are not distributed randomly: barcodes
are sampled for all representatives, and additional markers are sampled
only for a small percentage. We investigate the effects of the degree and
randomness of missing data on phylogenetic accuracy using simulations for
up to 100 markers in 1000-tips trees, as well as a real case: the subtribe
Polyommatina (Lepidoptera: Lycaenidae), a large group including numerous
species with unresolved taxonomy. Our simulation tests show that when a
strategic and representative selection of species for higher-level
categories has been made for multigene sequencing (approximately one per
simulated genus), the addition of this multigene backbone DNA data for as
few as 5–10% of the specimens in the total data set can produce
high-quality phylogenies, comparable to those resulting from 100%
multigene sampling. In contrast, trees based exclusively on barcodes
performed poorly. This approach was applied to a 1365-specimen data set of
Polyommatina (including ca. 80% of described species), with nearly 8% of
representative species included in the multigene backbone and the
remaining 92% included only by mitochondrial COI barcodes, a phylogeny was
generated that highlighted potential misplacements, unrecognized major
clades, and placement for incertae sedis taxa. We use this information to
make systematic rearrangements within Polyommatina, and to describe two
new genera. Finally, we propose a systematic workflow to assess
higher-level taxonomy in hyperdiverse groups. This research identifies an
additional, enhanced value of DNA barcodes for improvements in
higher-level systematics using large data sets.