Data from: Testing genome skimming for species discrimination in the large and taxonomically difficult genus Rhododendron

Standard plant DNA barcodes based on 2-3 plastid regions, and nrDNA ITS show variable levels of resolution, and fail to discriminate among species in many plant groups. Genome skimming to recover complete plastid genome sequences and nrDNA arrays has been proposed as a solution to address these resolution limitations. However, few studies have empirically tested what gains are achieved in practice. Of particular interest is whether adding substantially more plastid and nrDNA characters will lead to an increase in discriminatory power, or whether the resolution limitations of standard plants barcodes are fundamentally due to plastid genomes and nrDNA not tracking species boundaries. To address this, we used genome skimming to recover near-complete plastid genomes and nuclear ribosomal DNA from Rhododendron species and compared discrimination success with standard plant barcodes. We sampled 218 individuals representing 145 species of this species-rich and taxonomically difficult genus, focusing on the global biodiversity hotspots of the Himalaya-Hengduan Mountains. Only 33% of species were distinguished using ITS+matK+rbcL+trnH-psbA. In contrast, 55% of species were distinguished using plastid genome and nrDNA sequences. The vast majority of this increase is due to the additional plastid characters. Thus, despite previous studies showing an asymptote in discrimination success beyond 3-4 plastid regions, these results show that a demonstrable increase in discriminatory power is possible with extensive plastid genome data. However, despite these gains, many species remain unresolved, and these results also reinforce the need to access multiple unlinked nuclear loci to obtain transformative gains in species discrimination in plants.Sequence alignments and all trees. See README.txt file. Funding provided by: The Large-scale Scientific Facilities of the Chinese Academy of Sciences*Crossref Funder Registry ID: Award Number: 2017-LSFGBOWS-02Funding provided by: The Strategic Priority Research Program of Chinese Academy of Sciences*Crossref Funder Registry ID: Award Number: XDB31000000Funding provided by: National Natural Science Foundation of ChinaCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100001809Award Number: 91631101, 31670213Funding provided by: The Program of Science and Technology Talents Training of Yunnan Province, China*Crossref Funder Registry ID: Award Number: 2017HA014Funding provided by: The Large-scale Scientific Facilities of the Chinese Academy of SciencesCrossref Funder Registry ID: Award Number: 2017-LSFGBOWS-02Funding provided by: The Strategic Priority Research Program of Chinese Academy of SciencesCrossref Funder Registry ID: Award Number: XDB3100000